BA501_Python_plotly.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# plotly\n",
    "# https://plot.ly/python/ipython-notebook-tutorial/\n",
    "# interactivity\n",
    "# makes more sense..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 262,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import plotly.plotly as py\n",
    "import plotly.figure_factory as ff"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 263,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import scipy as sp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 264,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# set credentials\n",
    "plotly.tools.set_credentials_file(username='mingchang0804', api_key='lpbaXASTRzJWvoeGSzbk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 267,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"https://raw.githubusercontent.com/plotly/datasets/master/school_earnings.csv\")\n",
    "\n",
    "# convert this to a json file\n",
    "table = ff.create_table(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 268,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mingchang0804/65.embed\" height=\"710px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 268,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "py.iplot(table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import plotly.graph_objs as go"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# explore what's available\n",
    "# go."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mingchang0804/67.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 275,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# bar charts\n",
    "data = [go.Bar(x=df.School,\n",
    "            y=df.gap)]\n",
    "#data[0].y\n",
    "py.iplot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# time series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 277,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "file_location = \"/Users/mingchang/Downloads/\"\n",
    "file_name = \"orders_new.csv\"\n",
    "my_data = pd.read_csv(file_location + file_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 278,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def GetSeries(my_data, my_id):\n",
    "    table = my_data[[\"date\", \"spend_usd\"]][my_data.experiment_id == my_id]\n",
    "    series = table.groupby('date')['spend_usd'].sum()\n",
    "    return(series)\n",
    "\n",
    "my_series = GetSeries(my_data, 12624549)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 279,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'2017-04-01', u'2017-04-02', u'2017-04-03', u'2017-04-04',\n",
       "       u'2017-04-05', u'2017-04-06', u'2017-04-07'],\n",
       "      dtype='object', name=u'date')"
      ]
     },
     "execution_count": 279,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_series.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = [go.Scatter(x=my_series.index, y=my_series)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 281,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'type': 'scatter',\n",
       " 'x': Index([u'2017-04-01', u'2017-04-02', u'2017-04-03', u'2017-04-04',\n",
       "        u'2017-04-05', u'2017-04-06', u'2017-04-07'],\n",
       "       dtype='object', name=u'date'),\n",
       " 'y': date\n",
       " 2017-04-01    16047.543276\n",
       " 2017-04-02    10098.424397\n",
       " 2017-04-03     8810.436441\n",
       " 2017-04-04     7717.685555\n",
       " 2017-04-05     8376.836991\n",
       " 2017-04-06     9793.380668\n",
       " 2017-04-07    10152.279732\n",
       " Name: spend_usd, dtype: float64}"
      ]
     },
     "execution_count": 281,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 282,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mingchang0804/69.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 282,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "py.iplot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# plot 2 series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "red_series = GetSeries(my_data, 12624549)\n",
    "blue_series = GetSeries(my_data, 12624548)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2017-04-01    18232.061711\n",
       "2017-04-02     9060.614970\n",
       "2017-04-03    12151.588315\n",
       "2017-04-04     8869.867894\n",
       "2017-04-05     9759.266316\n",
       "2017-04-06     8442.963212\n",
       "2017-04-07    10997.229475\n",
       "Name: spend_usd, dtype: float64"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "blue_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "red = go.Scatter(x=red_series.index, y=red_series, line = dict(color = 'red'), name=\"Red\")\n",
    "blue = go.Scatter(x=blue_series.index, y=blue_series, line = dict(color = 'blue'), name=\"Blue\")\n",
    "data = [red, blue]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'line': {'color': 'red'},\n",
       " 'name': 'Red',\n",
       " 'type': 'scatter',\n",
       " 'x': Index([u'2017-04-01', u'2017-04-02', u'2017-04-03', u'2017-04-04',\n",
       "        u'2017-04-05', u'2017-04-06', u'2017-04-07'],\n",
       "       dtype='object', name=u'date'),\n",
       " 'y': date\n",
       " 2017-04-01    16047.543276\n",
       " 2017-04-02    10098.424397\n",
       " 2017-04-03     8810.436441\n",
       " 2017-04-04     7717.685555\n",
       " 2017-04-05     8376.836991\n",
       " 2017-04-06     9793.380668\n",
       " 2017-04-07    10152.279732\n",
       " Name: spend_usd, dtype: float64}"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mingchang0804/71.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 287,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "py.iplot(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<iframe id=\"igraph\" scrolling=\"no\" style=\"border:none;\" seamless=\"seamless\" src=\"https://plot.ly/~mingchang0804/73.embed\" height=\"525px\" width=\"100%\"></iframe>"
      ],
      "text/plain": [
       "<plotly.tools.PlotlyDisplay object>"
      ]
     },
     "execution_count": 288,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "layout = dict(\n",
    "    title = \"Red vs. Blue\",\n",
    "    yaxis=dict(\n",
    "        title='Average user spend'\n",
    "    )\n",
    ")\n",
    "fig = dict(data=data, layout=layout)\n",
    "py.iplot(fig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import plotly.graph_objs as go\n",
    "import plotly.plotly as py\n",
    "\n",
    "from ipywidgets import widgets \n",
    "from IPython.display import display, clear_output, Image\n",
    "from plotly.graph_objs import *\n",
    "from plotly.widgets import GraphWidget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# most common: text input box\n",
    "# https://plot.ly/python/textbox-widget/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from IPython.html import widgets \n",
    "from IPython.display import display, clear_output\n",
    "from plotly.graph_objs import *\n",
    "from plotly.widgets import GraphWidget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "button = widgets.Button(description=\"Submit\")\n",
    "\n",
    "text_input = widgets.Text(\n",
    "    description='Exp:',\n",
    "    value='12624549',\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "valid = widgets.Valid(\n",
    "    value=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "message = widgets.HTML(\n",
    "    value=\"\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "g2=GraphWidget(\"https://plot.ly/~mingchang0804/53\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "exp_id=12624549\n",
    "my_series = GetSeries(my_data, exp_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2017-04-01    54019.941288\n",
       "2017-04-02    34642.988992\n",
       "2017-04-03    28645.762133\n",
       "2017-04-04    27604.259313\n",
       "2017-04-05    33149.441763\n",
       "2017-04-06    29310.726245\n",
       "2017-04-07    34640.122009\n",
       "Name: spend_usd, dtype: float64"
      ]
     },
     "execution_count": 219,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "my_series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "g2.plot({'data': [{'x': my_series.index, 'y': my_series }]})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "plotly.widgets.graph_widget.GraphWidget"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(g2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "our_list = [\"12624549\", \"12624548\"]\n",
    "df = my_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>date</th>\n",
       "      <th>experiment_id</th>\n",
       "      <th>order_id</th>\n",
       "      <th>spend_usd</th>\n",
       "      <th>user_id</th>\n",
       "      <th>vertical</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>US</td>\n",
       "      <td>2017-04-02</td>\n",
       "      <td>12624549</td>\n",
       "      <td>6720123150182430132</td>\n",
       "      <td>49.99</td>\n",
       "      <td>3659561261588336546</td>\n",
       "      <td>ANDROID_APPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>US</td>\n",
       "      <td>2017-04-01</td>\n",
       "      <td>12624549</td>\n",
       "      <td>17511438899767627798</td>\n",
       "      <td>0.99</td>\n",
       "      <td>3659561261588336546</td>\n",
       "      <td>ANDROID_APPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>US</td>\n",
       "      <td>2017-04-04</td>\n",
       "      <td>12624549</td>\n",
       "      <td>1549342062436664018</td>\n",
       "      <td>39.99</td>\n",
       "      <td>3659561261588336546</td>\n",
       "      <td>ANDROID_APPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>US</td>\n",
       "      <td>2017-04-04</td>\n",
       "      <td>12624549</td>\n",
       "      <td>7771425263197855716</td>\n",
       "      <td>19.99</td>\n",
       "      <td>3659561261588336546</td>\n",
       "      <td>ANDROID_APPS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>US</td>\n",
       "      <td>2017-04-01</td>\n",
       "      <td>12624549</td>\n",
       "      <td>17943210556580942992</td>\n",
       "      <td>19.99</td>\n",
       "      <td>3659561261588336546</td>\n",
       "      <td>ANDROID_APPS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country        date  experiment_id              order_id  spend_usd  \\\n",
       "0      US  2017-04-02       12624549   6720123150182430132      49.99   \n",
       "1      US  2017-04-01       12624549  17511438899767627798       0.99   \n",
       "2      US  2017-04-04       12624549   1549342062436664018      39.99   \n",
       "3      US  2017-04-04       12624549   7771425263197855716      19.99   \n",
       "4      US  2017-04-01       12624549  17943210556580942992      19.99   \n",
       "\n",
       "               user_id      vertical  \n",
       "0  3659561261588336546  ANDROID_APPS  \n",
       "1  3659561261588336546  ANDROID_APPS  \n",
       "2  3659561261588336546  ANDROID_APPS  \n",
       "3  3659561261588336546  ANDROID_APPS  \n",
       "4  3659561261588336546  ANDROID_APPS  "
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def isTextValid(text):\n",
    "    if text_input.value.upper() in our_list:\n",
    "        valid.value=True\n",
    "        exp_id = int(text_input.value)\n",
    "        my_series = GetSeries(my_data, exp_id)\n",
    "        print(my_series)\n",
    "        g2.plot({'data': [{'x': my_series.index, 'y': my_series }]})\n",
    "        g2.relayout({'title': 'Experiment: {}'.format(text_input.value)})\n",
    "        message.value = \"\"\n",
    "    else: \n",
    "        valid.value=False\n",
    "        message.value = \"<font color=\\\"red\\\">Can't find that experiment id</font>\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# listener\n",
    "button.on_click(isTextValid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date\n",
      "2017-04-01    54019.941288\n",
      "2017-04-02    34642.988992\n",
      "2017-04-03    28645.762133\n",
      "2017-04-04    27604.259313\n",
      "2017-04-05    33149.441763\n",
      "2017-04-06    29310.726245\n",
      "2017-04-07    34640.122009\n",
      "Name: spend_usd, dtype: float64\n",
      "date\n",
      "2017-04-01    55504.518743\n",
      "2017-04-02    31317.138253\n",
      "2017-04-03    31583.940583\n",
      "2017-04-04    23615.742230\n",
      "2017-04-05    30899.812674\n",
      "2017-04-06    27768.181870\n",
      "2017-04-07    32957.001652\n",
      "Name: spend_usd, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "container = widgets.HBox(children=[text_input, button, valid, message])\n",
    "display(container)\n",
    "display(g2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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