Readmission_DT_RF.html

<!DOCTYPE html>
<html>
<head><meta charset="utf-8" />
<title>Readmission_DT_RF</title><script src="https://cdnjs.cloudflare.com/ajax/libs/require.js/2.1.10/require.min.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.0.3/jquery.min.js"></script>

<style type="text/css">
    /*!
*
* Twitter Bootstrap
*
*/
/*!
 * Bootstrap v3.3.7 (http://getbootstrap.com)
 * Copyright 2011-2016 Twitter, Inc.
 * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
 */
/*! normalize.css v3.0.3 | MIT License | github.com/necolas/normalize.css */
html {
  font-family: sans-serif;
  -ms-text-size-adjust: 100%;
  -webkit-text-size-adjust: 100%;
}
body {
  margin: 0;
}
article,
aside,
details,
figcaption,
figure,
footer,
header,
hgroup,
main,
menu,
nav,
section,
summary {
  display: block;
}
audio,
canvas,
progress,
video {
  display: inline-block;
  vertical-align: baseline;
}
audio:not([controls]) {
  display: none;
  height: 0;
}
[hidden],
template {
  display: none;
}
a {
  background-color: transparent;
}
a:active,
a:hover {
  outline: 0;
}
abbr[title] {
  border-bottom: 1px dotted;
}
b,
strong {
  font-weight: bold;
}
dfn {
  font-style: italic;
}
h1 {
  font-size: 2em;
  margin: 0.67em 0;
}
mark {
  background: #ff0;
  color: #000;
}
small {
  font-size: 80%;
}
sub,
sup {
  font-size: 75%;
  line-height: 0;
  position: relative;
  vertical-align: baseline;
}
sup {
  top: -0.5em;
}
sub {
  bottom: -0.25em;
}
img {
  border: 0;
}
svg:not(:root) {
  overflow: hidden;
}
figure {
  margin: 1em 40px;
}
hr {
  box-sizing: content-box;
  height: 0;
}
pre {
  overflow: auto;
}
code,
kbd,
pre,
samp {
  font-family: monospace, monospace;
  font-size: 1em;
}
button,
input,
optgroup,
select,
textarea {
  color: inherit;
  font: inherit;
  margin: 0;
}
button {
  overflow: visible;
}
button,
select {
  text-transform: none;
}
button,
html input[type="button"],
input[type="reset"],
input[type="submit"] {
  -webkit-appearance: button;
  cursor: pointer;
}
button[disabled],
html input[disabled] {
  cursor: default;
}
button::-moz-focus-inner,
input::-moz-focus-inner {
  border: 0;
  padding: 0;
}
input {
  line-height: normal;
}
input[type="checkbox"],
input[type="radio"] {
  box-sizing: border-box;
  padding: 0;
}
input[type="number"]::-webkit-inner-spin-button,
input[type="number"]::-webkit-outer-spin-button {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: textfield;
  box-sizing: content-box;
}
input[type="search"]::-webkit-search-cancel-button,
input[type="search"]::-webkit-search-decoration {
  -webkit-appearance: none;
}
fieldset {
  border: 1px solid #c0c0c0;
  margin: 0 2px;
  padding: 0.35em 0.625em 0.75em;
}
legend {
  border: 0;
  padding: 0;
}
textarea {
  overflow: auto;
}
optgroup {
  font-weight: bold;
}
table {
  border-collapse: collapse;
  border-spacing: 0;
}
td,
th {
  padding: 0;
}
/*! Source: https://github.com/h5bp/html5-boilerplate/blob/master/src/css/main.css */
@media print {
  *,
  *:before,
  *:after {
    background: transparent !important;
    color: #000 !important;
    box-shadow: none !important;
    text-shadow: none !important;
  }
  a,
  a:visited {
    text-decoration: underline;
  }
  a[href]:after {
    content: " (" attr(href) ")";
  }
  abbr[title]:after {
    content: " (" attr(title) ")";
  }
  a[href^="#"]:after,
  a[href^="javascript:"]:after {
    content: "";
  }
  pre,
  blockquote {
    border: 1px solid #999;
    page-break-inside: avoid;
  }
  thead {
    display: table-header-group;
  }
  tr,
  img {
    page-break-inside: avoid;
  }
  img {
    max-width: 100% !important;
  }
  p,
  h2,
  h3 {
    orphans: 3;
    widows: 3;
  }
  h2,
  h3 {
    page-break-after: avoid;
  }
  .navbar {
    display: none;
  }
  .btn > .caret,
  .dropup > .btn > .caret {
    border-top-color: #000 !important;
  }
  .label {
    border: 1px solid #000;
  }
  .table {
    border-collapse: collapse !important;
  }
  .table td,
  .table th {
    background-color: #fff !important;
  }
  .table-bordered th,
  .table-bordered td {
    border: 1px solid #ddd !important;
  }
}
@font-face {
  font-family: 'Glyphicons Halflings';
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot');
  src: url('../components/bootstrap/fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff2') format('woff2'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.woff') format('woff'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../components/bootstrap/fonts/glyphicons-halflings-regular.svg#glyphicons_halflingsregular') format('svg');
}
.glyphicon {
  position: relative;
  top: 1px;
  display: inline-block;
  font-family: 'Glyphicons Halflings';
  font-style: normal;
  font-weight: normal;
  line-height: 1;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
.glyphicon-asterisk:before {
  content: "\002a";
}
.glyphicon-plus:before {
  content: "\002b";
}
.glyphicon-euro:before,
.glyphicon-eur:before {
  content: "\20ac";
}
.glyphicon-minus:before {
  content: "\2212";
}
.glyphicon-cloud:before {
  content: "\2601";
}
.glyphicon-envelope:before {
  content: "\2709";
}
.glyphicon-pencil:before {
  content: "\270f";
}
.glyphicon-glass:before {
  content: "\e001";
}
.glyphicon-music:before {
  content: "\e002";
}
.glyphicon-search:before {
  content: "\e003";
}
.glyphicon-heart:before {
  content: "\e005";
}
.glyphicon-star:before {
  content: "\e006";
}
.glyphicon-star-empty:before {
  content: "\e007";
}
.glyphicon-user:before {
  content: "\e008";
}
.glyphicon-film:before {
  content: "\e009";
}
.glyphicon-th-large:before {
  content: "\e010";
}
.glyphicon-th:before {
  content: "\e011";
}
.glyphicon-th-list:before {
  content: "\e012";
}
.glyphicon-ok:before {
  content: "\e013";
}
.glyphicon-remove:before {
  content: "\e014";
}
.glyphicon-zoom-in:before {
  content: "\e015";
}
.glyphicon-zoom-out:before {
  content: "\e016";
}
.glyphicon-off:before {
  content: "\e017";
}
.glyphicon-signal:before {
  content: "\e018";
}
.glyphicon-cog:before {
  content: "\e019";
}
.glyphicon-trash:before {
  content: "\e020";
}
.glyphicon-home:before {
  content: "\e021";
}
.glyphicon-file:before {
  content: "\e022";
}
.glyphicon-time:before {
  content: "\e023";
}
.glyphicon-road:before {
  content: "\e024";
}
.glyphicon-download-alt:before {
  content: "\e025";
}
.glyphicon-download:before {
  content: "\e026";
}
.glyphicon-upload:before {
  content: "\e027";
}
.glyphicon-inbox:before {
  content: "\e028";
}
.glyphicon-play-circle:before {
  content: "\e029";
}
.glyphicon-repeat:before {
  content: "\e030";
}
.glyphicon-refresh:before {
  content: "\e031";
}
.glyphicon-list-alt:before {
  content: "\e032";
}
.glyphicon-lock:before {
  content: "\e033";
}
.glyphicon-flag:before {
  content: "\e034";
}
.glyphicon-headphones:before {
  content: "\e035";
}
.glyphicon-volume-off:before {
  content: "\e036";
}
.glyphicon-volume-down:before {
  content: "\e037";
}
.glyphicon-volume-up:before {
  content: "\e038";
}
.glyphicon-qrcode:before {
  content: "\e039";
}
.glyphicon-barcode:before {
  content: "\e040";
}
.glyphicon-tag:before {
  content: "\e041";
}
.glyphicon-tags:before {
  content: "\e042";
}
.glyphicon-book:before {
  content: "\e043";
}
.glyphicon-bookmark:before {
  content: "\e044";
}
.glyphicon-print:before {
  content: "\e045";
}
.glyphicon-camera:before {
  content: "\e046";
}
.glyphicon-font:before {
  content: "\e047";
}
.glyphicon-bold:before {
  content: "\e048";
}
.glyphicon-italic:before {
  content: "\e049";
}
.glyphicon-text-height:before {
  content: "\e050";
}
.glyphicon-text-width:before {
  content: "\e051";
}
.glyphicon-align-left:before {
  content: "\e052";
}
.glyphicon-align-center:before {
  content: "\e053";
}
.glyphicon-align-right:before {
  content: "\e054";
}
.glyphicon-align-justify:before {
  content: "\e055";
}
.glyphicon-list:before {
  content: "\e056";
}
.glyphicon-indent-left:before {
  content: "\e057";
}
.glyphicon-indent-right:before {
  content: "\e058";
}
.glyphicon-facetime-video:before {
  content: "\e059";
}
.glyphicon-picture:before {
  content: "\e060";
}
.glyphicon-map-marker:before {
  content: "\e062";
}
.glyphicon-adjust:before {
  content: "\e063";
}
.glyphicon-tint:before {
  content: "\e064";
}
.glyphicon-edit:before {
  content: "\e065";
}
.glyphicon-share:before {
  content: "\e066";
}
.glyphicon-check:before {
  content: "\e067";
}
.glyphicon-move:before {
  content: "\e068";
}
.glyphicon-step-backward:before {
  content: "\e069";
}
.glyphicon-fast-backward:before {
  content: "\e070";
}
.glyphicon-backward:before {
  content: "\e071";
}
.glyphicon-play:before {
  content: "\e072";
}
.glyphicon-pause:before {
  content: "\e073";
}
.glyphicon-stop:before {
  content: "\e074";
}
.glyphicon-forward:before {
  content: "\e075";
}
.glyphicon-fast-forward:before {
  content: "\e076";
}
.glyphicon-step-forward:before {
  content: "\e077";
}
.glyphicon-eject:before {
  content: "\e078";
}
.glyphicon-chevron-left:before {
  content: "\e079";
}
.glyphicon-chevron-right:before {
  content: "\e080";
}
.glyphicon-plus-sign:before {
  content: "\e081";
}
.glyphicon-minus-sign:before {
  content: "\e082";
}
.glyphicon-remove-sign:before {
  content: "\e083";
}
.glyphicon-ok-sign:before {
  content: "\e084";
}
.glyphicon-question-sign:before {
  content: "\e085";
}
.glyphicon-info-sign:before {
  content: "\e086";
}
.glyphicon-screenshot:before {
  content: "\e087";
}
.glyphicon-remove-circle:before {
  content: "\e088";
}
.glyphicon-ok-circle:before {
  content: "\e089";
}
.glyphicon-ban-circle:before {
  content: "\e090";
}
.glyphicon-arrow-left:before {
  content: "\e091";
}
.glyphicon-arrow-right:before {
  content: "\e092";
}
.glyphicon-arrow-up:before {
  content: "\e093";
}
.glyphicon-arrow-down:before {
  content: "\e094";
}
.glyphicon-share-alt:before {
  content: "\e095";
}
.glyphicon-resize-full:before {
  content: "\e096";
}
.glyphicon-resize-small:before {
  content: "\e097";
}
.glyphicon-exclamation-sign:before {
  content: "\e101";
}
.glyphicon-gift:before {
  content: "\e102";
}
.glyphicon-leaf:before {
  content: "\e103";
}
.glyphicon-fire:before {
  content: "\e104";
}
.glyphicon-eye-open:before {
  content: "\e105";
}
.glyphicon-eye-close:before {
  content: "\e106";
}
.glyphicon-warning-sign:before {
  content: "\e107";
}
.glyphicon-plane:before {
  content: "\e108";
}
.glyphicon-calendar:before {
  content: "\e109";
}
.glyphicon-random:before {
  content: "\e110";
}
.glyphicon-comment:before {
  content: "\e111";
}
.glyphicon-magnet:before {
  content: "\e112";
}
.glyphicon-chevron-up:before {
  content: "\e113";
}
.glyphicon-chevron-down:before {
  content: "\e114";
}
.glyphicon-retweet:before {
  content: "\e115";
}
.glyphicon-shopping-cart:before {
  content: "\e116";
}
.glyphicon-folder-close:before {
  content: "\e117";
}
.glyphicon-folder-open:before {
  content: "\e118";
}
.glyphicon-resize-vertical:before {
  content: "\e119";
}
.glyphicon-resize-horizontal:before {
  content: "\e120";
}
.glyphicon-hdd:before {
  content: "\e121";
}
.glyphicon-bullhorn:before {
  content: "\e122";
}
.glyphicon-bell:before {
  content: "\e123";
}
.glyphicon-certificate:before {
  content: "\e124";
}
.glyphicon-thumbs-up:before {
  content: "\e125";
}
.glyphicon-thumbs-down:before {
  content: "\e126";
}
.glyphicon-hand-right:before {
  content: "\e127";
}
.glyphicon-hand-left:before {
  content: "\e128";
}
.glyphicon-hand-up:before {
  content: "\e129";
}
.glyphicon-hand-down:before {
  content: "\e130";
}
.glyphicon-circle-arrow-right:before {
  content: "\e131";
}
.glyphicon-circle-arrow-left:before {
  content: "\e132";
}
.glyphicon-circle-arrow-up:before {
  content: "\e133";
}
.glyphicon-circle-arrow-down:before {
  content: "\e134";
}
.glyphicon-globe:before {
  content: "\e135";
}
.glyphicon-wrench:before {
  content: "\e136";
}
.glyphicon-tasks:before {
  content: "\e137";
}
.glyphicon-filter:before {
  content: "\e138";
}
.glyphicon-briefcase:before {
  content: "\e139";
}
.glyphicon-fullscreen:before {
  content: "\e140";
}
.glyphicon-dashboard:before {
  content: "\e141";
}
.glyphicon-paperclip:before {
  content: "\e142";
}
.glyphicon-heart-empty:before {
  content: "\e143";
}
.glyphicon-link:before {
  content: "\e144";
}
.glyphicon-phone:before {
  content: "\e145";
}
.glyphicon-pushpin:before {
  content: "\e146";
}
.glyphicon-usd:before {
  content: "\e148";
}
.glyphicon-gbp:before {
  content: "\e149";
}
.glyphicon-sort:before {
  content: "\e150";
}
.glyphicon-sort-by-alphabet:before {
  content: "\e151";
}
.glyphicon-sort-by-alphabet-alt:before {
  content: "\e152";
}
.glyphicon-sort-by-order:before {
  content: "\e153";
}
.glyphicon-sort-by-order-alt:before {
  content: "\e154";
}
.glyphicon-sort-by-attributes:before {
  content: "\e155";
}
.glyphicon-sort-by-attributes-alt:before {
  content: "\e156";
}
.glyphicon-unchecked:before {
  content: "\e157";
}
.glyphicon-expand:before {
  content: "\e158";
}
.glyphicon-collapse-down:before {
  content: "\e159";
}
.glyphicon-collapse-up:before {
  content: "\e160";
}
.glyphicon-log-in:before {
  content: "\e161";
}
.glyphicon-flash:before {
  content: "\e162";
}
.glyphicon-log-out:before {
  content: "\e163";
}
.glyphicon-new-window:before {
  content: "\e164";
}
.glyphicon-record:before {
  content: "\e165";
}
.glyphicon-save:before {
  content: "\e166";
}
.glyphicon-open:before {
  content: "\e167";
}
.glyphicon-saved:before {
  content: "\e168";
}
.glyphicon-import:before {
  content: "\e169";
}
.glyphicon-export:before {
  content: "\e170";
}
.glyphicon-send:before {
  content: "\e171";
}
.glyphicon-floppy-disk:before {
  content: "\e172";
}
.glyphicon-floppy-saved:before {
  content: "\e173";
}
.glyphicon-floppy-remove:before {
  content: "\e174";
}
.glyphicon-floppy-save:before {
  content: "\e175";
}
.glyphicon-floppy-open:before {
  content: "\e176";
}
.glyphicon-credit-card:before {
  content: "\e177";
}
.glyphicon-transfer:before {
  content: "\e178";
}
.glyphicon-cutlery:before {
  content: "\e179";
}
.glyphicon-header:before {
  content: "\e180";
}
.glyphicon-compressed:before {
  content: "\e181";
}
.glyphicon-earphone:before {
  content: "\e182";
}
.glyphicon-phone-alt:before {
  content: "\e183";
}
.glyphicon-tower:before {
  content: "\e184";
}
.glyphicon-stats:before {
  content: "\e185";
}
.glyphicon-sd-video:before {
  content: "\e186";
}
.glyphicon-hd-video:before {
  content: "\e187";
}
.glyphicon-subtitles:before {
  content: "\e188";
}
.glyphicon-sound-stereo:before {
  content: "\e189";
}
.glyphicon-sound-dolby:before {
  content: "\e190";
}
.glyphicon-sound-5-1:before {
  content: "\e191";
}
.glyphicon-sound-6-1:before {
  content: "\e192";
}
.glyphicon-sound-7-1:before {
  content: "\e193";
}
.glyphicon-copyright-mark:before {
  content: "\e194";
}
.glyphicon-registration-mark:before {
  content: "\e195";
}
.glyphicon-cloud-download:before {
  content: "\e197";
}
.glyphicon-cloud-upload:before {
  content: "\e198";
}
.glyphicon-tree-conifer:before {
  content: "\e199";
}
.glyphicon-tree-deciduous:before {
  content: "\e200";
}
.glyphicon-cd:before {
  content: "\e201";
}
.glyphicon-save-file:before {
  content: "\e202";
}
.glyphicon-open-file:before {
  content: "\e203";
}
.glyphicon-level-up:before {
  content: "\e204";
}
.glyphicon-copy:before {
  content: "\e205";
}
.glyphicon-paste:before {
  content: "\e206";
}
.glyphicon-alert:before {
  content: "\e209";
}
.glyphicon-equalizer:before {
  content: "\e210";
}
.glyphicon-king:before {
  content: "\e211";
}
.glyphicon-queen:before {
  content: "\e212";
}
.glyphicon-pawn:before {
  content: "\e213";
}
.glyphicon-bishop:before {
  content: "\e214";
}
.glyphicon-knight:before {
  content: "\e215";
}
.glyphicon-baby-formula:before {
  content: "\e216";
}
.glyphicon-tent:before {
  content: "\26fa";
}
.glyphicon-blackboard:before {
  content: "\e218";
}
.glyphicon-bed:before {
  content: "\e219";
}
.glyphicon-apple:before {
  content: "\f8ff";
}
.glyphicon-erase:before {
  content: "\e221";
}
.glyphicon-hourglass:before {
  content: "\231b";
}
.glyphicon-lamp:before {
  content: "\e223";
}
.glyphicon-duplicate:before {
  content: "\e224";
}
.glyphicon-piggy-bank:before {
  content: "\e225";
}
.glyphicon-scissors:before {
  content: "\e226";
}
.glyphicon-bitcoin:before {
  content: "\e227";
}
.glyphicon-btc:before {
  content: "\e227";
}
.glyphicon-xbt:before {
  content: "\e227";
}
.glyphicon-yen:before {
  content: "\00a5";
}
.glyphicon-jpy:before {
  content: "\00a5";
}
.glyphicon-ruble:before {
  content: "\20bd";
}
.glyphicon-rub:before {
  content: "\20bd";
}
.glyphicon-scale:before {
  content: "\e230";
}
.glyphicon-ice-lolly:before {
  content: "\e231";
}
.glyphicon-ice-lolly-tasted:before {
  content: "\e232";
}
.glyphicon-education:before {
  content: "\e233";
}
.glyphicon-option-horizontal:before {
  content: "\e234";
}
.glyphicon-option-vertical:before {
  content: "\e235";
}
.glyphicon-menu-hamburger:before {
  content: "\e236";
}
.glyphicon-modal-window:before {
  content: "\e237";
}
.glyphicon-oil:before {
  content: "\e238";
}
.glyphicon-grain:before {
  content: "\e239";
}
.glyphicon-sunglasses:before {
  content: "\e240";
}
.glyphicon-text-size:before {
  content: "\e241";
}
.glyphicon-text-color:before {
  content: "\e242";
}
.glyphicon-text-background:before {
  content: "\e243";
}
.glyphicon-object-align-top:before {
  content: "\e244";
}
.glyphicon-object-align-bottom:before {
  content: "\e245";
}
.glyphicon-object-align-horizontal:before {
  content: "\e246";
}
.glyphicon-object-align-left:before {
  content: "\e247";
}
.glyphicon-object-align-vertical:before {
  content: "\e248";
}
.glyphicon-object-align-right:before {
  content: "\e249";
}
.glyphicon-triangle-right:before {
  content: "\e250";
}
.glyphicon-triangle-left:before {
  content: "\e251";
}
.glyphicon-triangle-bottom:before {
  content: "\e252";
}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#login_widget {
  float: right;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: baseline;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  padding: 0.4em;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
  padding-top: 11px;
  padding-bottom: 3px;
}
#maintoolbar .navbar-text {
  float: none;
  vertical-align: middle;
  text-align: right;
  margin-left: 5px;
  margin-right: 0px;
  margin-top: 0px;
}
.select-xs {
  height: 24px;
}
.pulse,
.dropdown-menu > li > a.pulse,
li.pulse > a.dropdown-toggle,
li.pulse.open > a.dropdown-toggle {
  background-color: #F37626;
  color: white;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
/** WARNING IF YOU ARE EDITTING THIS FILE, if this is a .css file, It has a lot
 * of chance of beeing generated from the ../less/[samename].less file, you can
 * try to get back the less file by reverting somme commit in history
 **/
/*
 * We'll try to get something pretty, so we
 * have some strange css to have the scroll bar on
 * the left with fix button on the top right of the tooltip
 */
@-moz-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-webkit-keyframes fadeOut {
  from {
    opacity: 1;
  }
  to {
    opacity: 0;
  }
}
@-moz-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
@-webkit-keyframes fadeIn {
  from {
    opacity: 0;
  }
  to {
    opacity: 1;
  }
}
/*properties of tooltip after "expand"*/
.bigtooltip {
  overflow: auto;
  height: 200px;
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
}
/*properties of tooltip before "expand"*/
.smalltooltip {
  -webkit-transition-property: height;
  -webkit-transition-duration: 500ms;
  -moz-transition-property: height;
  -moz-transition-duration: 500ms;
  transition-property: height;
  transition-duration: 500ms;
  text-overflow: ellipsis;
  overflow: hidden;
  height: 80px;
}
.tooltipbuttons {
  position: absolute;
  padding-right: 15px;
  top: 0px;
  right: 0px;
}
.tooltiptext {
  /*avoid the button to overlap on some docstring*/
  padding-right: 30px;
}
.ipython_tooltip {
  max-width: 700px;
  /*fade-in animation when inserted*/
  -webkit-animation: fadeOut 400ms;
  -moz-animation: fadeOut 400ms;
  animation: fadeOut 400ms;
  -webkit-animation: fadeIn 400ms;
  -moz-animation: fadeIn 400ms;
  animation: fadeIn 400ms;
  vertical-align: middle;
  background-color: #f7f7f7;
  overflow: visible;
  border: #ababab 1px solid;
  outline: none;
  padding: 3px;
  margin: 0px;
  padding-left: 7px;
  font-family: monospace;
  min-height: 50px;
  -moz-box-shadow: 0px 6px 10px -1px #adadad;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  border-radius: 2px;
  position: absolute;
  z-index: 1000;
}
.ipython_tooltip a {
  float: right;
}
.ipython_tooltip .tooltiptext pre {
  border: 0;
  border-radius: 0;
  font-size: 100%;
  background-color: #f7f7f7;
}
.pretooltiparrow {
  left: 0px;
  margin: 0px;
  top: -16px;
  width: 40px;
  height: 16px;
  overflow: hidden;
  position: absolute;
}
.pretooltiparrow:before {
  background-color: #f7f7f7;
  border: 1px #ababab solid;
  z-index: 11;
  content: "";
  position: absolute;
  left: 15px;
  top: 10px;
  width: 25px;
  height: 25px;
  -webkit-transform: rotate(45deg);
  -moz-transform: rotate(45deg);
  -ms-transform: rotate(45deg);
  -o-transform: rotate(45deg);
}
ul.typeahead-list i {
  margin-left: -10px;
  width: 18px;
}
ul.typeahead-list {
  max-height: 80vh;
  overflow: auto;
}
ul.typeahead-list > li > a {
  /** Firefox bug **/
  /* see https://github.com/jupyter/notebook/issues/559 */
  white-space: normal;
}
.cmd-palette .modal-body {
  padding: 7px;
}
.cmd-palette form {
  background: white;
}
.cmd-palette input {
  outline: none;
}
.no-shortcut {
  display: none;
}
.command-shortcut:before {
  content: "(command)";
  padding-right: 3px;
  color: #777777;
}
.edit-shortcut:before {
  content: "(edit)";
  padding-right: 3px;
  color: #777777;
}
#find-and-replace #replace-preview .match,
#find-and-replace #replace-preview .insert {
  background-color: #BBDEFB;
  border-color: #90CAF9;
  border-style: solid;
  border-width: 1px;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .match {
  background-color: #FFCDD2;
  border-color: #EF9A9A;
  border-radius: 0px;
}
#find-and-replace #replace-preview .replace .insert {
  background-color: #C8E6C9;
  border-color: #A5D6A7;
  border-radius: 0px;
}
#find-and-replace #replace-preview {
  max-height: 60vh;
  overflow: auto;
}
#find-and-replace #replace-preview pre {
  padding: 5px 10px;
}
.terminal-app {
  background: #EEE;
}
.terminal-app #header {
  background: #fff;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.terminal-app .terminal {
  width: 100%;
  float: left;
  font-family: monospace;
  color: white;
  background: black;
  padding: 0.4em;
  border-radius: 2px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.4);
}
.terminal-app .terminal,
.terminal-app .terminal dummy-screen {
  line-height: 1em;
  font-size: 14px;
}
.terminal-app .terminal .xterm-rows {
  padding: 10px;
}
.terminal-app .terminal-cursor {
  color: black;
  background: white;
}
.terminal-app #terminado-container {
  margin-top: 20px;
}
/*# sourceMappingURL=style.min.css.map */
    </style>
<style type="text/css">
    .highlight .hll { background-color: #ffffcc }
.highlight  { background: #f8f8f8; }
.highlight .c { color: #408080; font-style: italic } /* Comment */
.highlight .err { border: 1px solid #FF0000 } /* Error */
.highlight .k { color: #008000; font-weight: bold } /* Keyword */
.highlight .o { color: #666666 } /* Operator */
.highlight .ch { color: #408080; font-style: italic } /* Comment.Hashbang */
.highlight .cm { color: #408080; font-style: italic } /* Comment.Multiline */
.highlight .cp { color: #BC7A00 } /* Comment.Preproc */
.highlight .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */
.highlight .c1 { color: #408080; font-style: italic } /* Comment.Single */
.highlight .cs { color: #408080; font-style: italic } /* Comment.Special */
.highlight .gd { color: #A00000 } /* Generic.Deleted */
.highlight .ge { font-style: italic } /* Generic.Emph */
.highlight .gr { color: #FF0000 } /* Generic.Error */
.highlight .gh { color: #000080; font-weight: bold } /* Generic.Heading */
.highlight .gi { color: #00A000 } /* Generic.Inserted */
.highlight .go { color: #888888 } /* Generic.Output */
.highlight .gp { color: #000080; font-weight: bold } /* Generic.Prompt */
.highlight .gs { font-weight: bold } /* Generic.Strong */
.highlight .gu { color: #800080; font-weight: bold } /* Generic.Subheading */
.highlight .gt { color: #0044DD } /* Generic.Traceback */
.highlight .kc { color: #008000; font-weight: bold } /* Keyword.Constant */
.highlight .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */
.highlight .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */
.highlight .kp { color: #008000 } /* Keyword.Pseudo */
.highlight .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */
.highlight .kt { color: #B00040 } /* Keyword.Type */
.highlight .m { color: #666666 } /* Literal.Number */
.highlight .s { color: #BA2121 } /* Literal.String */
.highlight .na { color: #7D9029 } /* Name.Attribute */
.highlight .nb { color: #008000 } /* Name.Builtin */
.highlight .nc { color: #0000FF; font-weight: bold } /* Name.Class */
.highlight .no { color: #880000 } /* Name.Constant */
.highlight .nd { color: #AA22FF } /* Name.Decorator */
.highlight .ni { color: #999999; font-weight: bold } /* Name.Entity */
.highlight .ne { color: #D2413A; font-weight: bold } /* Name.Exception */
.highlight .nf { color: #0000FF } /* Name.Function */
.highlight .nl { color: #A0A000 } /* Name.Label */
.highlight .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */
.highlight .nt { color: #008000; font-weight: bold } /* Name.Tag */
.highlight .nv { color: #19177C } /* Name.Variable */
.highlight .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */
.highlight .w { color: #bbbbbb } /* Text.Whitespace */
.highlight .mb { color: #666666 } /* Literal.Number.Bin */
.highlight .mf { color: #666666 } /* Literal.Number.Float */
.highlight .mh { color: #666666 } /* Literal.Number.Hex */
.highlight .mi { color: #666666 } /* Literal.Number.Integer */
.highlight .mo { color: #666666 } /* Literal.Number.Oct */
.highlight .sa { color: #BA2121 } /* Literal.String.Affix */
.highlight .sb { color: #BA2121 } /* Literal.String.Backtick */
.highlight .sc { color: #BA2121 } /* Literal.String.Char */
.highlight .dl { color: #BA2121 } /* Literal.String.Delimiter */
.highlight .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */
.highlight .s2 { color: #BA2121 } /* Literal.String.Double */
.highlight .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */
.highlight .sh { color: #BA2121 } /* Literal.String.Heredoc */
.highlight .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */
.highlight .sx { color: #008000 } /* Literal.String.Other */
.highlight .sr { color: #BB6688 } /* Literal.String.Regex */
.highlight .s1 { color: #BA2121 } /* Literal.String.Single */
.highlight .ss { color: #19177C } /* Literal.String.Symbol */
.highlight .bp { color: #008000 } /* Name.Builtin.Pseudo */
.highlight .fm { color: #0000FF } /* Name.Function.Magic */
.highlight .vc { color: #19177C } /* Name.Variable.Class */
.highlight .vg { color: #19177C } /* Name.Variable.Global */
.highlight .vi { color: #19177C } /* Name.Variable.Instance */
.highlight .vm { color: #19177C } /* Name.Variable.Magic */
.highlight .il { color: #666666 } /* Literal.Number.Integer.Long */
    </style>
<style type="text/css">
    
/* Temporary definitions which will become obsolete with Notebook release 5.0 */
.ansi-black-fg { color: #3E424D; }
.ansi-black-bg { background-color: #3E424D; }
.ansi-black-intense-fg { color: #282C36; }
.ansi-black-intense-bg { background-color: #282C36; }
.ansi-red-fg { color: #E75C58; }
.ansi-red-bg { background-color: #E75C58; }
.ansi-red-intense-fg { color: #B22B31; }
.ansi-red-intense-bg { background-color: #B22B31; }
.ansi-green-fg { color: #00A250; }
.ansi-green-bg { background-color: #00A250; }
.ansi-green-intense-fg { color: #007427; }
.ansi-green-intense-bg { background-color: #007427; }
.ansi-yellow-fg { color: #DDB62B; }
.ansi-yellow-bg { background-color: #DDB62B; }
.ansi-yellow-intense-fg { color: #B27D12; }
.ansi-yellow-intense-bg { background-color: #B27D12; }
.ansi-blue-fg { color: #208FFB; }
.ansi-blue-bg { background-color: #208FFB; }
.ansi-blue-intense-fg { color: #0065CA; }
.ansi-blue-intense-bg { background-color: #0065CA; }
.ansi-magenta-fg { color: #D160C4; }
.ansi-magenta-bg { background-color: #D160C4; }
.ansi-magenta-intense-fg { color: #A03196; }
.ansi-magenta-intense-bg { background-color: #A03196; }
.ansi-cyan-fg { color: #60C6C8; }
.ansi-cyan-bg { background-color: #60C6C8; }
.ansi-cyan-intense-fg { color: #258F8F; }
.ansi-cyan-intense-bg { background-color: #258F8F; }
.ansi-white-fg { color: #C5C1B4; }
.ansi-white-bg { background-color: #C5C1B4; }
.ansi-white-intense-fg { color: #A1A6B2; }
.ansi-white-intense-bg { background-color: #A1A6B2; }

.ansi-bold { font-weight: bold; }

    </style>


<style type="text/css">
/* Overrides of notebook CSS for static HTML export */
body {
  overflow: visible;
  padding: 8px;
}

div#notebook {
  overflow: visible;
  border-top: none;
}@media print {
  div.cell {
    display: block;
    page-break-inside: avoid;
  } 
  div.output_wrapper { 
    display: block;
    page-break-inside: avoid; 
  }
  div.output { 
    display: block;
    page-break-inside: avoid; 
  }
}
</style>

<!-- Custom stylesheet, it must be in the same directory as the html file -->
<link rel="stylesheet" href="custom.css">

<!-- Loading mathjax macro -->
<!-- Load mathjax -->
    <script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS_HTML"></script>
    <!-- MathJax configuration -->
    <script type="text/x-mathjax-config">
    MathJax.Hub.Config({
        tex2jax: {
            inlineMath: [ ['$','$'], ["\\(","\\)"] ],
            displayMath: [ ['$$','$$'], ["\\[","\\]"] ],
            processEscapes: true,
            processEnvironments: true
        },
        // Center justify equations in code and markdown cells. Elsewhere
        // we use CSS to left justify single line equations in code cells.
        displayAlign: 'center',
        "HTML-CSS": {
            styles: {'.MathJax_Display': {"margin": 0}},
            linebreaks: { automatic: true }
        }
    });
    </script>
    <!-- End of mathjax configuration --></head>
<body>
  <div tabindex="-1" id="notebook" class="border-box-sizing">
    <div class="container" id="notebook-container">

<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="Hospital-Re-admission-rate">Hospital Re-admission rate<a class="anchor-link" href="#Hospital-Re-admission-rate">&#182;</a></h1>
</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>This data set is downloaded from UC-irvine Machine learning repository <a href="https://archive.ics.uci.edu/ml/datasets/diabetes">https://archive.ics.uci.edu/ml/datasets/diabetes</a>
The dataset contains encounter information regarding patient demographic, vital(s) and re admitted coulmn indicating whether the patient is readmitted in 30 days</p>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Import necessary libraries and load the data</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[1]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">itertools</span>
<span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">StandardScaler</span>
<span class="kn">from</span> <span class="nn">imblearn.combine</span> <span class="k">import</span> <span class="n">SMOTEENN</span>
<span class="kn">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">Counter</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">confusion_matrix</span><span class="p">,</span> <span class="n">roc_curve</span><span class="p">,</span> <span class="n">auc</span><span class="p">,</span> <span class="n">accuracy_score</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">train_test_split</span>
<span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">GridSearchCV</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="o">%</span><span class="k">matplotlib</span> inline

<span class="n">df</span><span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;diabetic_data.csv&#39;</span><span class="p">,</span> <span class="n">header</span> <span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">asdf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;AdmissionSource.csv&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">atdf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;AdmissionType.csv&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">dddf</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;DischargeDisposition.csv&#39;</span><span class="p">,</span> <span class="n">header</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">df</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[1]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style>
    .dataframe thead tr:only-child th {
        text-align: right;
    }

    .dataframe thead th {
        text-align: left;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>encounter_id</th>
      <th>patient_nbr</th>
      <th>race</th>
      <th>gender</th>
      <th>age</th>
      <th>weight</th>
      <th>admission_type_id</th>
      <th>discharge_disposition_id</th>
      <th>admission_source_id</th>
      <th>time_in_hospital</th>
      <th>...</th>
      <th>citoglipton</th>
      <th>insulin</th>
      <th>glyburide-metformin</th>
      <th>glipizide-metformin</th>
      <th>glimepiride-pioglitazone</th>
      <th>metformin-rosiglitazone</th>
      <th>metformin-pioglitazone</th>
      <th>change</th>
      <th>diabetesMed</th>
      <th>readmitted</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2278392</td>
      <td>8222157</td>
      <td>Caucasian</td>
      <td>Female</td>
      <td>[0-10)</td>
      <td>?</td>
      <td>6</td>
      <td>25</td>
      <td>1</td>
      <td>1</td>
      <td>...</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>NO</td>
    </tr>
    <tr>
      <th>1</th>
      <td>149190</td>
      <td>55629189</td>
      <td>Caucasian</td>
      <td>Female</td>
      <td>[10-20)</td>
      <td>?</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>3</td>
      <td>...</td>
      <td>No</td>
      <td>Up</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>Ch</td>
      <td>Yes</td>
      <td>&gt;30</td>
    </tr>
    <tr>
      <th>2</th>
      <td>64410</td>
      <td>86047875</td>
      <td>AfricanAmerican</td>
      <td>Female</td>
      <td>[20-30)</td>
      <td>?</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>2</td>
      <td>...</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>Yes</td>
      <td>NO</td>
    </tr>
    <tr>
      <th>3</th>
      <td>500364</td>
      <td>82442376</td>
      <td>Caucasian</td>
      <td>Male</td>
      <td>[30-40)</td>
      <td>?</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>2</td>
      <td>...</td>
      <td>No</td>
      <td>Up</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>Ch</td>
      <td>Yes</td>
      <td>NO</td>
    </tr>
    <tr>
      <th>4</th>
      <td>16680</td>
      <td>42519267</td>
      <td>Caucasian</td>
      <td>Male</td>
      <td>[40-50)</td>
      <td>?</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>1</td>
      <td>...</td>
      <td>No</td>
      <td>Steady</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>No</td>
      <td>Ch</td>
      <td>Yes</td>
      <td>NO</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 50 columns</p>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Explore-Data">Explore Data<a class="anchor-link" href="#Explore-Data">&#182;</a></h3>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[2]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># utility functions copied from </span>
<span class="c1"># http://scikit-learn.org/stable/auto_examples/model_selection/plot_confusion_matrix.html</span>

<span class="k">def</span> <span class="nf">plot_confusion_matrix</span><span class="p">(</span><span class="n">cm</span><span class="p">,</span> <span class="n">classes</span><span class="p">,</span>
                          <span class="n">normalize</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
                          <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Confusion matrix&#39;</span><span class="p">,</span>
                          <span class="n">cmap</span><span class="o">=</span><span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">Blues</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    This function prints and plots the confusion matrix.</span>
<span class="sd">    Normalization can be applied by setting `normalize=True`.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">if</span> <span class="n">normalize</span><span class="p">:</span>
        <span class="n">cm</span> <span class="o">=</span> <span class="n">cm</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;float&#39;</span><span class="p">)</span> <span class="o">/</span> <span class="n">cm</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)[:,</span> <span class="n">np</span><span class="o">.</span><span class="n">newaxis</span><span class="p">]</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Normalized confusion matrix&quot;</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Confusion matrix, without normalization&#39;</span><span class="p">)</span>

    <span class="c1"># print(cm)</span>

    <span class="n">im</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">cm</span><span class="p">,</span> <span class="n">interpolation</span><span class="o">=</span><span class="s1">&#39;nearest&#39;</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">cmap</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="n">title</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">im</span><span class="p">,</span> <span class="n">fraction</span><span class="o">=</span><span class="mf">0.046</span><span class="p">,</span> <span class="n">pad</span><span class="o">=</span><span class="mf">0.04</span><span class="p">)</span>
    <span class="n">tick_marks</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">classes</span><span class="p">))</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">(</span><span class="n">tick_marks</span><span class="p">,</span> <span class="n">classes</span><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="mi">45</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">yticks</span><span class="p">(</span><span class="n">tick_marks</span><span class="p">,</span> <span class="n">classes</span><span class="p">)</span>

    <span class="n">fmt</span> <span class="o">=</span> <span class="s1">&#39;.2f&#39;</span> <span class="k">if</span> <span class="n">normalize</span> <span class="k">else</span> <span class="s1">&#39;d&#39;</span>
    <span class="n">thresh</span> <span class="o">=</span> <span class="n">cm</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="o">/</span> <span class="mf">2.</span>
    <span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="n">j</span> <span class="ow">in</span> <span class="n">itertools</span><span class="o">.</span><span class="n">product</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="n">cm</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="nb">range</span><span class="p">(</span><span class="n">cm</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])):</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">j</span><span class="p">,</span> <span class="n">i</span><span class="p">,</span> <span class="nb">format</span><span class="p">(</span><span class="n">cm</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">],</span> <span class="n">fmt</span><span class="p">),</span>
                 <span class="n">horizontalalignment</span><span class="o">=</span><span class="s2">&quot;center&quot;</span><span class="p">,</span>
                 <span class="n">color</span><span class="o">=</span><span class="s2">&quot;white&quot;</span> <span class="k">if</span> <span class="n">cm</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">j</span><span class="p">]</span> <span class="o">&gt;</span> <span class="n">thresh</span> <span class="k">else</span> <span class="s2">&quot;black&quot;</span><span class="p">)</span>

    <span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;True label&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Predicted label&#39;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[3]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># utility function to plot a roc curve</span>

<span class="k">def</span> <span class="nf">plot_roc_curve</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_pred</span><span class="p">):</span>
    <span class="n">fpr</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">thresholds</span> <span class="o">=</span> <span class="n">roc_curve</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span><span class="n">y_pred</span><span class="p">)</span>
    <span class="n">roc_auc</span> <span class="o">=</span> <span class="n">auc</span><span class="p">(</span><span class="n">fpr</span><span class="p">,</span> <span class="n">tpr</span><span class="p">)</span>
    
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Receiver Operating Characteristic&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">fpr</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="s1">&#39;b&#39;</span><span class="p">,</span> <span class="n">label</span> <span class="o">=</span> <span class="s1">&#39;AUC = </span><span class="si">%0.2f</span><span class="s1">&#39;</span><span class="o">%</span> <span class="n">roc_auc</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="s1">&#39;lower right&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">],[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="s1">&#39;r--&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">([</span><span class="o">-</span><span class="mf">0.1</span><span class="p">,</span><span class="mf">1.2</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">([</span><span class="o">-</span><span class="mf">0.1</span><span class="p">,</span><span class="mf">1.2</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;True Positive Rate&#39;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;False Positive Rate&#39;</span><span class="p">)</span>
    
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[4]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># plot with various axes scales</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">15</span><span class="p">))</span>

<span class="c1"># weight</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">321</span><span class="p">)</span>
<span class="n">count_weight</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;weight&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="n">count_weight</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Weight&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Occurrence&quot;</span><span class="p">)</span>

<span class="c1">#Payer code</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">322</span><span class="p">)</span>
<span class="n">count_pc</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;payer_code&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="n">count_pc</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Payer code&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Occurence&quot;</span><span class="p">)</span>

<span class="c1">#Race</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">323</span><span class="p">)</span>
<span class="n">count_race</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;race&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="n">count_race</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Race&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Occurence&quot;</span><span class="p">)</span>

<span class="c1">#Medical specialty</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">324</span><span class="p">)</span>
<span class="n">count_ms</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;medical_specialty&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="n">count_ms</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Medical specialty&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Occurence&quot;</span><span class="p">)</span>


<span class="c1"># Diagnosis 1</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">325</span><span class="p">)</span>
<span class="n">count_ms</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_1&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
<span class="n">count_ms</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;ICD 9 Primary Diagnosis&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Occurence&quot;</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplots_adjust</span><span class="p">(</span><span class="n">top</span><span class="o">=</span><span class="mf">0.92</span><span class="p">,</span> <span class="n">bottom</span><span class="o">=</span><span class="mf">0.08</span><span class="p">,</span> <span class="n">left</span><span class="o">=</span><span class="mf">0.10</span><span class="p">,</span> <span class="n">right</span><span class="o">=</span><span class="mf">0.95</span><span class="p">,</span> <span class="n">hspace</span><span class="o">=</span><span class="mf">0.25</span><span class="p">,</span><span class="n">wspace</span><span class="o">=</span><span class="mf">0.35</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAyoAAAPFCAYAAACK2xyQAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Few features has missing data, represented with '?'. those need to be either imputed with some value or drop the feature <br><br>
Let's observe few vital(s) on patient data, in the data-frame there are around 25 vital's that are collected, for brevity purpose let's observe few vitals</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[5]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">citoglipton_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;citoglipton&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">metformin_pioglitazone_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin-pioglitazone&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">examide_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;examide&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">metformin_rosiglitazone_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin-rosiglitazone&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">glimepiride_pioglitazone_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;glimepiride-pioglitazone&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">max_glu_serum_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;max_glu_serum&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">A1Cresult_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;A1Cresult&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">metformin_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">repaglinide_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;repaglinide&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">nateglinide_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;nateglinide&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>
<span class="n">chlorpropamide_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;chlorpropamide&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">))</span>

<span class="n">vitals_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">citoglipton_df</span><span class="p">,</span><span class="n">metformin_pioglitazone_df</span><span class="p">,</span><span class="n">examide_df</span><span class="p">,</span><span class="n">metformin_rosiglitazone_df</span><span class="p">,</span>
                       <span class="n">glimepiride_pioglitazone_df</span><span class="p">,</span><span class="n">metformin_df</span><span class="p">,</span>
                      <span class="n">repaglinide_df</span><span class="p">,</span><span class="n">nateglinide_df</span><span class="p">,</span><span class="n">chlorpropamide_df</span><span class="p">],</span> <span class="n">join</span><span class="o">=</span><span class="s1">&#39;outer&#39;</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>

<span class="nb">print</span><span class="p">(</span><span class="n">vitals_df</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>        citoglipton  metformin-pioglitazone   examide  \
Down            NaN                     NaN       NaN   
No         101766.0                101765.0  101766.0   
Steady          NaN                     1.0       NaN   
Up              NaN                     NaN       NaN   

        metformin-rosiglitazone  glimepiride-pioglitazone  metformin  \
Down                        NaN                       NaN        575   
No                     101764.0                  101765.0      81778   
Steady                      2.0                       1.0      18346   
Up                          NaN                       NaN       1067   

        repaglinide  nateglinide  chlorpropamide  
Down             45           11               1  
No           100227       101063          101680  
Steady         1384          668              79  
Up              110           24               6  
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>The following vitals are completely skewed and can be dropped from the data frame</p>
<ul>
<li>citoglipton</li>
<li>metformin-pioglitazone</li>
<li>examide</li>
<li>metformin-rosiglitazone</li>
<li>glimepiride-pioglitazone</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Replace the '?' value with None value, and observe how many records are populated</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[6]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;weight&#39;</span><span class="p">]</span> <span class="o">==</span><span class="s1">&#39;?&#39;</span><span class="p">,</span> <span class="s1">&#39;weight&#39;</span><span class="p">]</span><span class="o">=</span><span class="kc">None</span>
<span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;payer_code&#39;</span><span class="p">]</span> <span class="o">==</span><span class="s1">&#39;?&#39;</span><span class="p">,</span> <span class="s1">&#39;payer_code&#39;</span><span class="p">]</span><span class="o">=</span><span class="kc">None</span>
<span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;medical_specialty&#39;</span><span class="p">]</span> <span class="o">==</span><span class="s1">&#39;?&#39;</span><span class="p">,</span> <span class="s1">&#39;medical_specialty&#39;</span><span class="p">]</span><span class="o">=</span><span class="kc">None</span>
<span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_2&#39;</span><span class="p">]</span> <span class="o">==</span><span class="s1">&#39;?&#39;</span><span class="p">,</span> <span class="s1">&#39;diag_2&#39;</span><span class="p">]</span><span class="o">=</span><span class="kc">None</span>
<span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_3&#39;</span><span class="p">]</span> <span class="o">==</span><span class="s1">&#39;?&#39;</span><span class="p">,</span> <span class="s1">&#39;diag_3&#39;</span><span class="p">]</span><span class="o">=</span><span class="kc">None</span>
<span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;race&#39;</span><span class="p">]</span> <span class="o">==</span><span class="s1">&#39;?&#39;</span><span class="p">,</span> <span class="s1">&#39;race&#39;</span><span class="p">]</span><span class="o">=</span><span class="s1">&#39;Other&#39;</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[7]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 101766 entries, 0 to 101765
Data columns (total 50 columns):
encounter_id                101766 non-null int64
patient_nbr                 101766 non-null int64
race                        101766 non-null object
gender                      101766 non-null object
age                         101766 non-null object
weight                      3197 non-null object
admission_type_id           101766 non-null int64
discharge_disposition_id    101766 non-null int64
admission_source_id         101766 non-null int64
time_in_hospital            101766 non-null int64
payer_code                  61510 non-null object
medical_specialty           51817 non-null object
num_lab_procedures          101766 non-null int64
num_procedures              101766 non-null int64
num_medications             101766 non-null int64
number_outpatient           101766 non-null int64
number_emergency            101766 non-null int64
number_inpatient            101766 non-null int64
diag_1                      101766 non-null object
diag_2                      101408 non-null object
diag_3                      100343 non-null object
number_diagnoses            101766 non-null int64
max_glu_serum               101766 non-null object
A1Cresult                   101766 non-null object
metformin                   101766 non-null object
repaglinide                 101766 non-null object
nateglinide                 101766 non-null object
chlorpropamide              101766 non-null object
glimepiride                 101766 non-null object
acetohexamide               101766 non-null object
glipizide                   101766 non-null object
glyburide                   101766 non-null object
tolbutamide                 101766 non-null object
pioglitazone                101766 non-null object
rosiglitazone               101766 non-null object
acarbose                    101766 non-null object
miglitol                    101766 non-null object
troglitazone                101766 non-null object
tolazamide                  101766 non-null object
examide                     101766 non-null object
citoglipton                 101766 non-null object
insulin                     101766 non-null object
glyburide-metformin         101766 non-null object
glipizide-metformin         101766 non-null object
glimepiride-pioglitazone    101766 non-null object
metformin-rosiglitazone     101766 non-null object
metformin-pioglitazone      101766 non-null object
change                      101766 non-null object
diabetesMed                 101766 non-null object
readmitted                  101766 non-null object
dtypes: int64(13), object(37)
memory usage: 38.8+ MB
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Only 3197 records had the weight populated, cannot use Imputer to fill the missing values, as weight varies by age of the individual. The other two features that doesn't have values are payer_code and medical_specialty. Let's plot the Payer code and medical_specialty to see what those values are</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[8]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">221</span><span class="p">)</span>
<span class="n">count_pc</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;payer_code&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="n">count_pc</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Payer code histogram&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Payer code&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Frequency&quot;</span><span class="p">)</span>
<span class="c1">#plt.grid(True)</span>

<span class="c1"># medical_specialty</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">222</span><span class="p">)</span>
<span class="n">count_ms</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;medical_specialty&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">nlargest</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>
<span class="n">count_ms</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Medical specialty histogram&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Medical specialty&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Frequency&quot;</span><span class="p">)</span>
<span class="c1">#plt.grid(True)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAA4sAAAHYCAYAAADkln0TAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Let's observe how skewed the data set is for the target feature 're-admitted'</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[9]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;readmitted&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[9]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>NO     54864
&gt;30    35545
&lt;30    11357
Name: readmitted, dtype: int64</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Functions that transform feature on the dataframe</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[10]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">convert_age</span><span class="p">(</span><span class="n">row</span><span class="p">):</span>
    <span class="n">val</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span>
    <span class="k">if</span><span class="p">(</span><span class="n">val</span>  <span class="o">==</span><span class="s1">&#39;[0-10)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[10-20&#39;</span><span class="p">)</span> <span class="p">:</span> 
      <span class="k">return</span> <span class="s1">&#39;young&#39;</span><span class="p">;</span>
    <span class="k">if</span><span class="p">(</span><span class="n">val</span>  <span class="o">==</span><span class="s1">&#39;[20-30)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[30-40)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[40-50)&#39;</span><span class="p">)</span> <span class="p">:</span>
      <span class="k">return</span> <span class="s1">&#39;adult&#39;</span>
    <span class="k">if</span><span class="p">(</span><span class="n">val</span>  <span class="o">==</span><span class="s1">&#39;[50-60)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[60-70)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[70-80)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[80-90)&#39;</span><span class="p">)</span> <span class="ow">or</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;[90-100)&#39;</span><span class="p">):</span>
      <span class="k">return</span> <span class="s1">&#39;old&#39;</span><span class="p">;</span>
    <span class="k">return</span> <span class="s1">&#39;old&#39;</span><span class="p">;</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[11]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">convert_admission</span><span class="p">(</span><span class="n">row</span><span class="p">):</span>
    <span class="n">val</span> <span class="o">=</span> <span class="n">row</span><span class="p">[</span><span class="s1">&#39;readmitted&#39;</span><span class="p">]</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;&lt;30&#39;</span><span class="p">):</span>
        <span class="k">return</span> <span class="mi">1</span><span class="p">;</span>
    <span class="k">if</span> <span class="p">(</span><span class="n">val</span> <span class="o">==</span> <span class="s1">&#39;&gt;30&#39;</span><span class="p">)</span> <span class="p">:</span>
        <span class="k">return</span> <span class="mi">0</span><span class="p">;</span>
    <span class="k">return</span> <span class="mi">0</span><span class="p">;</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Convert the age and readmitted column values of the dataframe</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[12]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">row</span><span class="p">:</span> <span class="n">convert_age</span><span class="p">(</span><span class="n">row</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;readmitted&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">row</span><span class="p">:</span> <span class="n">convert_admission</span><span class="p">(</span><span class="n">row</span><span class="p">),</span> <span class="n">axis</span> <span class="o">=</span><span class="mi">1</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Drop the columns from the dataframe that has insufficient values and in siginificant values <br>
encounter_id is the index of the dataframe and patient_nbr is random number assigned to a patient.</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[13]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;encounter_id&#39;</span><span class="p">,</span><span class="s1">&#39;patient_nbr&#39;</span><span class="p">,</span><span class="s1">&#39;payer_code&#39;</span><span class="p">,</span><span class="s1">&#39;weight&#39;</span><span class="p">,</span><span class="s1">&#39;medical_specialty&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[14]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;examide&#39;</span><span class="p">,</span> <span class="s1">&#39;citoglipton&#39;</span><span class="p">,</span><span class="s1">&#39;metformin-pioglitazone&#39;</span><span class="p">,</span><span class="s1">&#39;metformin-rosiglitazone&#39;</span><span class="p">,</span><span class="s1">&#39;glimepiride-pioglitazone&#39;</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Applying Label Encoder for the categorical columns, we will have another notebook using one hot encoder and PCA on the same data set</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[15]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;race&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;race&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_2&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_2&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_3&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_3&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;max_glu_serum&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;max_glu_serum&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;A1Cresult&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;A1Cresult&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;repaglinide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;repaglinide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;nateglinide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;nateglinide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;chlorpropamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;chlorpropamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glimepiride&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glimepiride&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;acetohexamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;acetohexamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolbutamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolbutamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;pioglitazone&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;pioglitazone&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;rosiglitazone&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;rosiglitazone&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;acarbose&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;acarbose&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;miglitol&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;miglitol&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;troglitazone&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;troglitazone&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolazamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolazamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="c1"># df[&#39;examide&#39;] = df[&#39;examide&#39;].astype(&#39;category&#39;)</span>
<span class="c1"># df[&#39;citoglipton&#39;] = df[&#39;citoglipton&#39;].astype(&#39;category&#39;)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;insulin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;insulin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide-metformin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide-metformin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide-metformin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide-metformin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="c1"># df[&#39;glimepiride-pioglitazone&#39;] = df[&#39;glimepiride-pioglitazone&#39;].astype(&#39;category&#39;)</span>
<span class="c1"># df[&#39;metformin-rosiglitazone&#39;] = df[&#39;metformin-rosiglitazone&#39;].astype(&#39;category&#39;)</span>
<span class="c1"># df[&#39;metformin-pioglitazone&#39;] = df[&#39;metformin-pioglitazone&#39;].astype(&#39;category&#39;)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;change&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;change&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diabetesMed&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diabetesMed&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">astype</span><span class="p">(</span><span class="s1">&#39;category&#39;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[16]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;race&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;race&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;gender&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;age&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_1&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_1&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_2&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_2&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_3&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diag_3&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;max_glu_serum&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;max_glu_serum&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;A1Cresult&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;A1Cresult&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;metformin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;repaglinide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;repaglinide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;nateglinide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;nateglinide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;chlorpropamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;chlorpropamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glimepiride&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glimepiride&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;acetohexamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;acetohexamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolbutamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolbutamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;pioglitazone&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;pioglitazone&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;rosiglitazone&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;rosiglitazone&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;acarbose&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;acarbose&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;miglitol&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;miglitol&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;troglitazone&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;troglitazone&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolazamide&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;tolazamide&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="c1"># df[&#39;examide&#39;] = df[&#39;examide&#39;].cat.codes</span>
<span class="c1"># df[&#39;citoglipton&#39;] = df[&#39;citoglipton&#39;].cat.codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;insulin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;insulin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide-metformin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glyburide-metformin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide-metformin&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;glipizide-metformin&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="c1"># df[&#39;glimepiride-pioglitazone&#39;] = df[&#39;glimepiride-pioglitazone&#39;].cat.codes</span>
<span class="c1"># df[&#39;metformin-rosiglitazone&#39;] = df[&#39;metformin-rosiglitazone&#39;].cat.codes</span>
<span class="c1"># df[&#39;metformin-pioglitazone&#39;] = df[&#39;metformin-pioglitazone&#39;].cat.codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;change&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;change&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;diabetesMed&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;diabetesMed&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">cat</span><span class="o">.</span><span class="n">codes</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Observe the data type of features, they got converted from  object to either int8/int64</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[17]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 101766 entries, 0 to 101765
Data columns (total 40 columns):
race                        101766 non-null int8
gender                      101766 non-null int8
age                         101766 non-null int8
admission_type_id           101766 non-null int64
discharge_disposition_id    101766 non-null int64
admission_source_id         101766 non-null int64
time_in_hospital            101766 non-null int64
num_lab_procedures          101766 non-null int64
num_procedures              101766 non-null int64
num_medications             101766 non-null int64
number_outpatient           101766 non-null int64
number_emergency            101766 non-null int64
number_inpatient            101766 non-null int64
diag_1                      101766 non-null int16
diag_2                      101766 non-null int16
diag_3                      101766 non-null int16
number_diagnoses            101766 non-null int64
max_glu_serum               101766 non-null int8
A1Cresult                   101766 non-null int8
metformin                   101766 non-null int8
repaglinide                 101766 non-null int8
nateglinide                 101766 non-null int8
chlorpropamide              101766 non-null int8
glimepiride                 101766 non-null int8
acetohexamide               101766 non-null int8
glipizide                   101766 non-null int8
glyburide                   101766 non-null int8
tolbutamide                 101766 non-null int8
pioglitazone                101766 non-null int8
rosiglitazone               101766 non-null int8
acarbose                    101766 non-null int8
miglitol                    101766 non-null int8
troglitazone                101766 non-null int8
tolazamide                  101766 non-null int8
insulin                     101766 non-null int8
glyburide-metformin         101766 non-null int8
glipizide-metformin         101766 non-null int8
change                      101766 non-null int8
diabetesMed                 101766 non-null int8
readmitted                  101766 non-null int64
dtypes: int16(3), int64(12), int8(25)
memory usage: 12.3 MB
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[18]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[18]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style>
    .dataframe thead tr:only-child th {
        text-align: right;
    }

    .dataframe thead th {
        text-align: left;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>race</th>
      <th>gender</th>
      <th>age</th>
      <th>admission_type_id</th>
      <th>discharge_disposition_id</th>
      <th>admission_source_id</th>
      <th>time_in_hospital</th>
      <th>num_lab_procedures</th>
      <th>num_procedures</th>
      <th>num_medications</th>
      <th>...</th>
      <th>acarbose</th>
      <th>miglitol</th>
      <th>troglitazone</th>
      <th>tolazamide</th>
      <th>insulin</th>
      <th>glyburide-metformin</th>
      <th>glipizide-metformin</th>
      <th>change</th>
      <th>diabetesMed</th>
      <th>readmitted</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>2</td>
      <td>0</td>
      <td>2</td>
      <td>6</td>
      <td>25</td>
      <td>1</td>
      <td>1</td>
      <td>41</td>
      <td>0</td>
      <td>1</td>
      <td>...</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>2</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>3</td>
      <td>59</td>
      <td>0</td>
      <td>18</td>
      <td>...</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>3</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>1</td>
      <td>0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>2</td>
      <td>11</td>
      <td>5</td>
      <td>13</td>
      <td>...</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>2</td>
      <td>1</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>2</td>
      <td>44</td>
      <td>1</td>
      <td>16</td>
      <td>...</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>3</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>1</td>
      <td>0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>2</td>
      <td>1</td>
      <td>0</td>
      <td>1</td>
      <td>1</td>
      <td>7</td>
      <td>1</td>
      <td>51</td>
      <td>0</td>
      <td>8</td>
      <td>...</td>
      <td>1</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>2</td>
      <td>1</td>
      <td>0</td>
      <td>0</td>
      <td>1</td>
      <td>0</td>
    </tr>
  </tbody>
</table>
<p>5 rows × 40 columns</p>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Let's observe how skewed the data set is</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[19]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
<span class="n">count_pc</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">value_counts</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;readmitted&#39;</span><span class="p">],</span> <span class="n">sort</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="n">count_pc</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;bar&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Readmitted histogram&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Readmitted&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Count&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAgQAAAF/CAYAAAA2D9EJAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[20]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y</span><span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;readmitted&#39;</span><span class="p">]</span>
<span class="n">X</span><span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;readmitted&#39;</span><span class="p">],</span> <span class="n">axis</span> <span class="o">=</span><span class="mi">1</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[21]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_us_train</span><span class="p">,</span> <span class="n">X_us_test</span><span class="p">,</span> <span class="n">y_us_train</span><span class="p">,</span> <span class="n">y_us_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X</span><span class="p">,</span><span class="n">y</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=.</span><span class="mi">30</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">criterion</span><span class="o">=</span><span class="s1">&#39;entropy&#39;</span><span class="p">,</span> <span class="n">max_depth</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_us_train</span><span class="p">,</span> <span class="n">y_us_train</span><span class="p">)</span>
<span class="n">y_us_predict</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_us_test</span><span class="p">)</span>
<span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_us_test</span><span class="p">,</span> <span class="n">y_us_predict</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[21]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.88221421552571244</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[22]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cnf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_us_test</span><span class="p">,</span> <span class="n">y_us_predict</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[23]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">121</span><span class="p">)</span>
<span class="n">plot_roc_curve</span><span class="p">(</span><span class="n">y_us_test</span><span class="p">,</span> <span class="n">y_us_predict</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">122</span><span class="p">)</span>
<span class="n">plot_confusion_matrix</span><span class="p">(</span><span class="n">cnf_matrix</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Non-Readmitted&#39;</span><span class="p">,</span><span class="s1">&#39;Readmitted&#39;</span><span class="p">],</span>
                      <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Confusion matrix, without normalization&#39;</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Confusion matrix, without normalization
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABDAAAAI5CAYAAABXS8rkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>Because of the data is unbalanced, use the SMOTEENN method to under/over sample the data to have both classes represents significantly on the training data set</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[24]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">smote_enn</span> <span class="o">=</span> <span class="n">SMOTEENN</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">X_rs</span><span class="p">,</span><span class="n">y_rs</span> <span class="o">=</span> <span class="n">smote_enn</span><span class="o">.</span><span class="n">fit_sample</span><span class="p">(</span><span class="n">X</span><span class="p">,</span><span class="n">y</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>After re-sampling, count of non-readmitted and re-admitted observations are as below</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[25]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">collections</span> <span class="k">import</span> <span class="n">Counter</span>
<span class="nb">print</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="n">Counter</span><span class="p">(</span><span class="n">y_rs</span><span class="p">)</span><span class="o">.</span><span class="n">items</span><span class="p">()))</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>[(0, 49682), (1, 82927)]
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h1 id="tune-for-parameters-of-decision-tree:-criterion,-max_depth">tune for parameters of decision tree: criterion, max_depth<a class="anchor-link" href="#tune-for-parameters-of-decision-tree:-criterion,-max_depth">&#182;</a></h1>
</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[26]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dt_params</span> <span class="o">=</span><span class="p">{</span><span class="s1">&#39;criterion&#39;</span><span class="p">:[</span><span class="s1">&#39;gini&#39;</span><span class="p">,</span><span class="s1">&#39;entropy&#39;</span><span class="p">],</span> <span class="s1">&#39;max_depth&#39;</span><span class="p">:[</span><span class="mi">10</span><span class="p">,</span><span class="mi">12</span><span class="p">,</span><span class="mi">14</span><span class="p">]}</span>
<span class="n">dt</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">DecisionTreeClassifier</span><span class="p">()</span>
<span class="n">dt_gscv</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">dt</span><span class="p">,</span><span class="n">param_grid</span> <span class="o">=</span> <span class="n">dt_params</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
<span class="n">dt_gscv</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_rs</span><span class="p">,</span><span class="n">y_rs</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[26]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>GridSearchCV(cv=None, error_score=&#39;raise&#39;,
       estimator=DecisionTreeClassifier(class_weight=None, criterion=&#39;gini&#39;, max_depth=None,
            max_features=None, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=1, min_samples_split=2,
            min_weight_fraction_leaf=0.0, presort=False, random_state=None,
            splitter=&#39;best&#39;),
       fit_params=None, iid=True, n_jobs=1,
       param_grid={&#39;criterion&#39;: [&#39;gini&#39;, &#39;entropy&#39;], &#39;max_depth&#39;: [10, 12, 14]},
       pre_dispatch=&#39;2*n_jobs&#39;, refit=True, return_train_score=&#39;warn&#39;,
       scoring=&#39;accuracy&#39;, verbose=0)</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[27]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dt_gscv</span><span class="o">.</span><span class="n">best_params_</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[27]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;criterion&#39;: &#39;entropy&#39;, &#39;max_depth&#39;: 12}</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[28]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">dt_gscv</span><span class="o">.</span><span class="n">cv_results_</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stderr output_text">
<pre>C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;mean_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split0_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split1_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split2_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;std_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt output_prompt">Out[28]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;mean_fit_time&#39;: array([ 0.7711134 ,  0.81757752,  0.70919689,  0.80738576,  0.98968728,
         0.91156348]),
 &#39;mean_score_time&#39;: array([ 0.01038424,  0.01285823,  0.01041857,  0.01041857,  0.01562754,
         0.0052096 ]),
 &#39;mean_test_score&#39;: array([ 0.86173638,  0.86519769,  0.86739211,  0.84899969,  0.87170554,
         0.86898325]),
 &#39;mean_train_score&#39;: array([ 0.89369166,  0.91041373,  0.92595561,  0.8908525 ,  0.90824573,
         0.92204944]),
 &#39;param_criterion&#39;: masked_array(data = [&#39;gini&#39; &#39;gini&#39; &#39;gini&#39; &#39;entropy&#39; &#39;entropy&#39; &#39;entropy&#39;],
              mask = [False False False False False False],
        fill_value = ?),
 &#39;param_max_depth&#39;: masked_array(data = [10 12 14 10 12 14],
              mask = [False False False False False False],
        fill_value = ?),
 &#39;params&#39;: [{&#39;criterion&#39;: &#39;gini&#39;, &#39;max_depth&#39;: 10},
  {&#39;criterion&#39;: &#39;gini&#39;, &#39;max_depth&#39;: 12},
  {&#39;criterion&#39;: &#39;gini&#39;, &#39;max_depth&#39;: 14},
  {&#39;criterion&#39;: &#39;entropy&#39;, &#39;max_depth&#39;: 10},
  {&#39;criterion&#39;: &#39;entropy&#39;, &#39;max_depth&#39;: 12},
  {&#39;criterion&#39;: &#39;entropy&#39;, &#39;max_depth&#39;: 14}],
 &#39;rank_test_score&#39;: array([5, 4, 3, 6, 1, 2]),
 &#39;split0_test_score&#39;: array([ 0.74196905,  0.73966157,  0.7395937 ,  0.7363587 ,  0.7430323 ,
         0.74233101]),
 &#39;split0_train_score&#39;: array([ 0.96729823,  0.98090606,  0.99018155,  0.96797692,  0.98347379,
         0.99295289]),
 &#39;split1_test_score&#39;: array([ 0.93808113,  0.94676832,  0.93642965,  0.92984639,  0.94421193,
         0.93719883]),
 &#39;split1_train_score&#39;: array([ 0.86101622,  0.87722553,  0.89338959,  0.85412755,  0.87274619,
         0.88740583]),
 &#39;split2_test_score&#39;: array([ 0.90516266,  0.90916701,  0.92615719,  0.88079725,  0.92787657,
         0.9274241 ]),
 &#39;split2_train_score&#39;: array([ 0.85276053,  0.8731096 ,  0.8942957 ,  0.85045302,  0.8685172 ,
         0.88578959]),
 &#39;std_fit_time&#39;: array([ 0.0406291 ,  0.09133044,  0.01532135,  0.02654321,  0.06029924,
         0.01948659]),
 &#39;std_score_time&#39;: array([  4.80476689e-04,   3.02278618e-03,   7.36704434e-03,
          7.36704434e-03,   5.94720425e-07,   7.36749390e-03]),
 &#39;std_test_score&#39;: array([ 0.08574936,  0.09008644,  0.09046591,  0.08212903,  0.09123133,
         0.08964704]),
 &#39;std_train_score&#39;: array([ 0.05215672,  0.04987392,  0.0454161 ,  0.05455583,  0.05322228,
         0.05014065])}</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[29]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># tuning for optimal parameter is not done, will do it a new version of notebook</span>
<span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">X_rs</span><span class="p">,</span><span class="n">y_rs</span><span class="p">,</span> <span class="n">test_size</span><span class="o">=.</span><span class="mi">30</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">model</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">DecisionTreeClassifier</span><span class="p">(</span><span class="n">criterion</span><span class="o">=</span><span class="s1">&#39;entropy&#39;</span><span class="p">,</span> <span class="n">max_depth</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[30]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[30]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>DecisionTreeClassifier(class_weight=None, criterion=&#39;entropy&#39;, max_depth=12,
            max_features=None, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=1, min_samples_split=2,
            min_weight_fraction_leaf=0.0, presort=False, random_state=None,
            splitter=&#39;best&#39;)</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[31]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y_predict</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_predict</span><span class="p">)</span>
<span class="n">cnf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_predict</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[32]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">121</span><span class="p">)</span>
<span class="n">plot_roc_curve</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_predict</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">122</span><span class="p">)</span>
<span class="n">plot_confusion_matrix</span><span class="p">(</span><span class="n">cnf_matrix</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Non-Readmitted&#39;</span><span class="p">,</span><span class="s1">&#39;Readmitted&#39;</span><span class="p">],</span>
                      <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Confusion matrix, without normalization&#39;</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Confusion matrix, without normalization
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABDAAAAI5CAYAAABXS8rkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[33]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#generate the tree png file - Run this cell if the machine has graphviz installed, other wise ignore this cell</span>

<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="s2">&quot;readmission.dot&quot;</span><span class="p">,</span><span class="s2">&quot;w&quot;</span><span class="p">)</span> <span class="k">as</span> <span class="n">f</span><span class="p">:</span>
    <span class="n">f</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">export_graphviz</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">out_file</span> <span class="o">=</span> <span class="n">f</span><span class="p">)</span>
    
<span class="kn">import</span> <span class="nn">pydot</span>

<span class="p">(</span><span class="n">graph</span><span class="p">,)</span> <span class="o">=</span> <span class="n">pydot</span><span class="o">.</span><span class="n">graph_from_dot_file</span><span class="p">(</span><span class="s1">&#39;readmission.dot&#39;</span><span class="p">)</span>
<span class="n">graph</span><span class="o">.</span><span class="n">write_png</span><span class="p">(</span><span class="s1">&#39;readmission.png&#39;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[33]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>True</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Bagging">Bagging<a class="anchor-link" href="#Bagging">&#182;</a></h3><p>Let's ensemble the decision trees to form a Random forest</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[34]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
<span class="n">random_forest</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">200</span><span class="p">,</span> <span class="n">max_depth</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">random_forest</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>

<span class="n">y_predict</span> <span class="o">=</span> <span class="n">random_forest</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_predict</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[34]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>0.91312872332403283</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[35]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cnf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_predict</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[36]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">121</span><span class="p">)</span>
<span class="n">plot_roc_curve</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_predict</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">122</span><span class="p">)</span>
<span class="n">plot_confusion_matrix</span><span class="p">(</span><span class="n">cnf_matrix</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Non-Readmitted&#39;</span><span class="p">,</span><span class="s1">&#39;Readmitted&#39;</span><span class="p">],</span>
                      <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Confusion matrix, without normalization&#39;</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Confusion matrix, without normalization
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABDAAAAI5CAYAAABXS8rkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[37]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">set_printoptions</span><span class="p">(</span><span class="n">precision</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>

<span class="c1"># Plot non-normalized confusion matrix</span>
<span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">121</span><span class="p">)</span>
<span class="n">plot_confusion_matrix</span><span class="p">(</span><span class="n">cnf_matrix</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Non-Readmitted&#39;</span><span class="p">,</span><span class="s1">&#39;Readmitted&#39;</span><span class="p">],</span>
                      <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Confusion matrix, without normalization&#39;</span><span class="p">)</span>

<span class="c1"># Plot normalized confusion matrix</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">122</span><span class="p">)</span>
<span class="n">plot_confusion_matrix</span><span class="p">(</span><span class="n">cnf_matrix</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Non-Readmitted&#39;</span><span class="p">,</span><span class="s1">&#39;Readmitted&#39;</span><span class="p">],</span> <span class="n">normalize</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span>
                      <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Normalized confusion matrix&#39;</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Confusion matrix, without normalization
Normalized confusion matrix
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAsgAAAE6CAYAAAALGaT5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>the following matrix gives the significance of each feature in classifying the observation</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[38]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">np</span><span class="o">.</span><span class="n">set_printoptions</span><span class="p">(</span><span class="n">precision</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">suppress</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[39]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">random_forest</span><span class="o">.</span><span class="n">feature_importances_</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[39]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>array([ 0.03 ,  0.081,  0.016,  0.022,  0.095,  0.029,  0.034,  0.008,
        0.02 ,  0.011,  0.017,  0.031,  0.194,  0.01 ,  0.008,  0.007,
        0.026,  0.002,  0.005,  0.058,  0.   ,  0.   ,  0.   ,  0.003,
        0.   ,  0.02 ,  0.014,  0.   ,  0.009,  0.005,  0.   ,  0.   ,
        0.   ,  0.   ,  0.052,  0.   ,  0.   ,  0.1  ,  0.093])</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<p>The top 5 features that impact the re-admission</p>
<ul>
<li>X[12]</li>
<li>X[38]</li>
<li>X[4]</li>
<li>X[39]</li>
<li>X[1]</li>
</ul>

</div>
</div>
</div>
<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt">
</div>
<div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h3 id="Boosting">Boosting<a class="anchor-link" href="#Boosting">&#182;</a></h3><p><br>
Lets do some xgb analysis on the data set and see any improvments</p>

</div>
</div>
</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[40]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">mingw_path</span> <span class="o">=</span> <span class="s1">&#39;C:</span><span class="se">\\</span><span class="s1">Program Files</span><span class="se">\\</span><span class="s1">mingw-w64</span><span class="se">\\</span><span class="s1">x86_64-7.2.0-posix-seh-rt_v5-rev0</span><span class="se">\\</span><span class="s1">mingw64</span><span class="se">\\</span><span class="s1">bin&#39;</span>

<span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">&#39;PATH&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">mingw_path</span> <span class="o">+</span> <span class="s1">&#39;;&#39;</span> <span class="o">+</span> <span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s1">&#39;PATH&#39;</span><span class="p">]</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[41]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">xgboost</span> <span class="k">as</span> <span class="nn">xgb</span>
<span class="n">cv_params</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;max_depth&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">10</span><span class="p">,</span><span class="mi">12</span><span class="p">,</span><span class="mi">14</span><span class="p">]}</span>
<span class="n">ind_params</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;learning_rate&#39;</span><span class="p">:</span> <span class="mf">0.1</span><span class="p">,</span> <span class="s1">&#39;n_estimators&#39;</span><span class="p">:</span> <span class="mi">200</span><span class="p">,</span> <span class="s1">&#39;seed&#39;</span><span class="p">:</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;subsample&#39;</span><span class="p">:</span> <span class="mf">0.8</span><span class="p">,</span> <span class="s1">&#39;colsample_bytree&#39;</span><span class="p">:</span> <span class="mf">0.8</span><span class="p">,</span> 
             <span class="s1">&#39;objective&#39;</span><span class="p">:</span> <span class="s1">&#39;binary:logistic&#39;</span><span class="p">}</span>

<span class="n">optimized_GBM</span> <span class="o">=</span> <span class="n">GridSearchCV</span><span class="p">(</span><span class="n">xgb</span><span class="o">.</span><span class="n">XGBClassifier</span><span class="p">(</span><span class="o">**</span><span class="n">ind_params</span><span class="p">),</span> 
                            <span class="n">cv_params</span><span class="p">,</span> 
                             <span class="n">scoring</span> <span class="o">=</span> <span class="s1">&#39;accuracy&#39;</span><span class="p">,</span> <span class="n">cv</span> <span class="o">=</span> <span class="mi">5</span><span class="p">,</span> <span class="n">n_jobs</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1</span><span class="p">)</span> 
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[42]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">optimized_GBM</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[42]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>GridSearchCV(cv=5, error_score=&#39;raise&#39;,
       estimator=XGBClassifier(base_score=0.5, booster=&#39;gbtree&#39;, colsample_bylevel=1,
       colsample_bytree=0.8, gamma=0, learning_rate=0.1, max_delta_step=0,
       max_depth=3, min_child_weight=1, missing=None, n_estimators=200,
       n_jobs=1, nthread=None, objective=&#39;binary:logistic&#39;, random_state=0,
       reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=0, silent=True,
       subsample=0.8),
       fit_params=None, iid=True, n_jobs=-1,
       param_grid={&#39;max_depth&#39;: [10, 12, 14]}, pre_dispatch=&#39;2*n_jobs&#39;,
       refit=True, return_train_score=&#39;warn&#39;, scoring=&#39;accuracy&#39;,
       verbose=0)</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[43]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">optimized_GBM</span><span class="o">.</span><span class="n">cv_results_</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stderr output_text">
<pre>C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;mean_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split0_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split1_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split2_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split3_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;split4_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
C:\Users\rmali\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:122: FutureWarning: You are accessing a training score (&#39;std_train_score&#39;), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True
  warnings.warn(*warn_args, **warn_kwargs)
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt output_prompt">Out[43]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;mean_fit_time&#39;: array([ 77.858,  91.806,  93.085]),
 &#39;mean_score_time&#39;: array([ 0.721,  1.072,  0.888]),
 &#39;mean_test_score&#39;: array([ 0.924,  0.924,  0.924]),
 &#39;mean_train_score&#39;: array([ 0.969,  0.99 ,  0.998]),
 &#39;param_max_depth&#39;: masked_array(data = [10 12 14],
              mask = [False False False],
        fill_value = ?),
 &#39;params&#39;: [{&#39;max_depth&#39;: 10}, {&#39;max_depth&#39;: 12}, {&#39;max_depth&#39;: 14}],
 &#39;rank_test_score&#39;: array([1, 3, 2]),
 &#39;split0_test_score&#39;: array([ 0.925,  0.924,  0.924]),
 &#39;split0_train_score&#39;: array([ 0.969,  0.989,  0.998]),
 &#39;split1_test_score&#39;: array([ 0.923,  0.923,  0.923]),
 &#39;split1_train_score&#39;: array([ 0.969,  0.99 ,  0.998]),
 &#39;split2_test_score&#39;: array([ 0.923,  0.923,  0.923]),
 &#39;split2_train_score&#39;: array([ 0.969,  0.99 ,  0.999]),
 &#39;split3_test_score&#39;: array([ 0.926,  0.925,  0.925]),
 &#39;split3_train_score&#39;: array([ 0.969,  0.99 ,  0.999]),
 &#39;split4_test_score&#39;: array([ 0.925,  0.925,  0.925]),
 &#39;split4_train_score&#39;: array([ 0.969,  0.989,  0.998]),
 &#39;std_fit_time&#39;: array([ 1.503,  4.923,  5.122]),
 &#39;std_score_time&#39;: array([ 0.009,  0.117,  0.195]),
 &#39;std_test_score&#39;: array([ 0.001,  0.001,  0.001]),
 &#39;std_train_score&#39;: array([ 0.,  0.,  0.])}</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[44]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">xgd_mat</span><span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span><span class="n">y_train</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[45]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">tuned_params</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;eta&#39;</span><span class="p">:</span> <span class="mf">0.1</span><span class="p">,</span> <span class="s1">&#39;seed&#39;</span><span class="p">:</span><span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;subsample&#39;</span><span class="p">:</span> <span class="mf">0.8</span><span class="p">,</span> <span class="s1">&#39;colsample_bytree&#39;</span><span class="p">:</span> <span class="mf">0.8</span><span class="p">,</span> 
             <span class="s1">&#39;objective&#39;</span><span class="p">:</span> <span class="s1">&#39;binary:logistic&#39;</span><span class="p">,</span> <span class="s1">&#39;max_depth&#39;</span><span class="p">:</span><span class="mi">14</span><span class="p">}</span> 
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[46]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cv_xgb</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">cv</span><span class="p">(</span><span class="n">params</span> <span class="o">=</span> <span class="n">tuned_params</span><span class="p">,</span> <span class="n">dtrain</span> <span class="o">=</span> <span class="n">xgd_mat</span><span class="p">,</span> <span class="n">num_boost_round</span> <span class="o">=</span> <span class="mi">1000</span><span class="p">,</span> <span class="n">nfold</span> <span class="o">=</span> <span class="mi">5</span><span class="p">,</span>
                <span class="n">metrics</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;error&#39;</span><span class="p">],</span>
                <span class="n">early_stopping_rounds</span> <span class="o">=</span> <span class="mi">100</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[47]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">cv_xgb</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">5</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[47]:</div>


<div class="output_html rendered_html output_subarea output_execute_result">
<div>
<style>
    .dataframe thead tr:only-child th {
        text-align: right;
    }

    .dataframe thead th {
        text-align: left;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }
</style>
<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>test-error-mean</th>
      <th>test-error-std</th>
      <th>train-error-mean</th>
      <th>train-error-std</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>212</th>
      <td>0.075636</td>
      <td>0.002707</td>
      <td>0.001190</td>
      <td>0.000181</td>
    </tr>
    <tr>
      <th>213</th>
      <td>0.075669</td>
      <td>0.002610</td>
      <td>0.001134</td>
      <td>0.000180</td>
    </tr>
    <tr>
      <th>214</th>
      <td>0.075712</td>
      <td>0.002699</td>
      <td>0.001109</td>
      <td>0.000169</td>
    </tr>
    <tr>
      <th>215</th>
      <td>0.075658</td>
      <td>0.002720</td>
      <td>0.001093</td>
      <td>0.000157</td>
    </tr>
    <tr>
      <th>216</th>
      <td>0.075582</td>
      <td>0.002646</td>
      <td>0.001083</td>
      <td>0.000155</td>
    </tr>
  </tbody>
</table>
</div>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[48]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">readmit_gb</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">tuned_params</span><span class="p">,</span> <span class="n">xgd_mat</span><span class="p">,</span> <span class="n">num_boost_round</span> <span class="o">=</span> <span class="mi">216</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[49]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[50]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">importances</span> <span class="o">=</span> <span class="n">readmit_gb</span><span class="o">.</span><span class="n">get_score</span><span class="p">()</span>
<span class="n">importances</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[50]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>{&#39;f0&#39;: 1846,
 &#39;f1&#39;: 2018,
 &#39;f10&#39;: 1835,
 &#39;f11&#39;: 1272,
 &#39;f12&#39;: 2955,
 &#39;f13&#39;: 14173,
 &#39;f14&#39;: 13366,
 &#39;f15&#39;: 12841,
 &#39;f16&#39;: 4444,
 &#39;f17&#39;: 421,
 &#39;f18&#39;: 1345,
 &#39;f19&#39;: 1168,
 &#39;f2&#39;: 931,
 &#39;f20&#39;: 136,
 &#39;f21&#39;: 48,
 &#39;f22&#39;: 2,
 &#39;f23&#39;: 331,
 &#39;f25&#39;: 1062,
 &#39;f26&#39;: 866,
 &#39;f28&#39;: 497,
 &#39;f29&#39;: 437,
 &#39;f3&#39;: 3110,
 &#39;f30&#39;: 22,
 &#39;f33&#39;: 2,
 &#39;f34&#39;: 3405,
 &#39;f35&#39;: 33,
 &#39;f37&#39;: 1717,
 &#39;f38&#39;: 979,
 &#39;f4&#39;: 4619,
 &#39;f5&#39;: 2735,
 &#39;f6&#39;: 7198,
 &#39;f7&#39;: 12246,
 &#39;f8&#39;: 4362,
 &#39;f9&#39;: 11190}</pre>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[51]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">testdmat</span> <span class="o">=</span> <span class="n">xgb</span><span class="o">.</span><span class="n">DMatrix</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
<span class="n">y_xgd_pred</span> <span class="o">=</span> <span class="n">readmit_gb</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">testdmat</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[52]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">importance_frame</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">&#39;Importance&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="n">importances</span><span class="o">.</span><span class="n">values</span><span class="p">()),</span> <span class="s1">&#39;Feature&#39;</span><span class="p">:</span> <span class="nb">list</span><span class="p">(</span><span class="n">importances</span><span class="o">.</span><span class="n">keys</span><span class="p">())})</span>
<span class="n">importance_frame</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="n">by</span> <span class="o">=</span> <span class="s1">&#39;Importance&#39;</span><span class="p">,</span> <span class="n">inplace</span> <span class="o">=</span> <span class="kc">True</span><span class="p">)</span>
<span class="n">importance_frame</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span> <span class="o">=</span> <span class="s1">&#39;barh&#39;</span><span class="p">,</span> <span class="n">x</span> <span class="o">=</span> <span class="s1">&#39;Feature&#39;</span><span class="p">,</span> <span class="n">figsize</span> <span class="o">=</span> <span class="p">(</span><span class="mi">8</span><span class="p">,</span><span class="mi">8</span><span class="p">),</span> <span class="n">color</span> <span class="o">=</span> <span class="s1">&#39;orange&#39;</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt output_prompt">Out[52]:</div>


<div class="output_text output_subarea output_execute_result">
<pre>&lt;matplotlib.axes._subplots.AxesSubplot at 0x22a4e9119b0&gt;</pre>
</div>

</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAfUAAAHVCAYAAADo5GInAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[53]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y_xgd_pred</span><span class="p">[</span><span class="n">y_xgd_pred</span> <span class="o">&gt;</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">y_xgd_pred</span><span class="p">[</span><span class="n">y_xgd_pred</span> <span class="o">&lt;=</span> <span class="mf">0.5</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
</pre></div>

</div>
</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[55]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_xgd_pred</span><span class="p">))</span>
<span class="n">cnf_matrix</span> <span class="o">=</span> <span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_xgd_pred</span><span class="p">)</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>0.926878314858
</pre>
</div>
</div>

</div>
</div>

</div>
<div class="cell border-box-sizing code_cell rendered">
<div class="input">
<div class="prompt input_prompt">In&nbsp;[57]:</div>
<div class="inner_cell">
    <div class="input_area">
<div class=" highlight hl-ipython3"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">15</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">121</span><span class="p">)</span>
<span class="n">plot_roc_curve</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">y_xgd_pred</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">122</span><span class="p">)</span>
<span class="n">plot_confusion_matrix</span><span class="p">(</span><span class="n">cnf_matrix</span><span class="p">,</span> <span class="n">classes</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Non-Readmitted&#39;</span><span class="p">,</span><span class="s1">&#39;Readmitted&#39;</span><span class="p">],</span>
                      <span class="n">title</span><span class="o">=</span><span class="s1">&#39;Confusion matrix, without normalization&#39;</span><span class="p">)</span>

<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>

</div>
</div>
</div>

<div class="output_wrapper">
<div class="output">


<div class="output_area">

<div class="prompt"></div>


<div class="output_subarea output_stream output_stdout output_text">
<pre>Confusion matrix, without normalization
</pre>
</div>
</div>

<div class="output_area">

<div class="prompt"></div>


<div class="output_png output_subarea ">
<img src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABDAAAAI5CAYAAABXS8rkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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"
>
</div>

</div>

</div>
</div>

</div>
    </div>
  </div>
</body>

 
</html>