Ipython_Pandas_and_Matplotlib.ipynb

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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<h1>PACC 2015 Demos -  IPython Notebook, Pandas & Matplotlib </h1>\n",
      "\n",
      "This notebook will demonstrate:\n",
      "\n",
      "- how ipython notebooks work, why they're useful, and how to share them\n",
      "- what fitbit daily data looks like when it is exported (vs. when it is manipulated in excel). \n",
      "- how to use Pandas to read and process a CSV.\n",
      "- how to use Matplotlib to plot data. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Usually people put all of their imports together in the first cell of the notebook. \n",
      "# I will talk more about this when it becomes relevant, but you can ignore it at first. \n",
      "import pandas\n",
      "import matplotlib\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np\n",
      "\n",
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<h2>IPython Notebook</h2>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "#markdown\n",
      "\n",
      "**bold**\n",
      "\n",
      "*I really mean this!*\n",
      "\n",
      "_____________________________________\n",
      "\n",
      "below is a terminal command: "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ls "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Ipython_Pandas_and_Matplotlib.ipynb  demo notebook.ipynb\r\n",
        "\u001b[34mdata\u001b[m\u001b[m/                                \u001b[34mvenv\u001b[m\u001b[m/\r\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "below is basic python code"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "1+15"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "16"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a = 2"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a + 5"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 7,
       "text": [
        "7"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"Hello, CSTA\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Hello, CSTA\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "while True: \n",
      "    print 'hello'\n",
      "    time.sleep(2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "hello\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "hello"
       ]
      },
      {
       "ename": "KeyboardInterrupt",
       "evalue": "",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-10-34b45b36b43d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0;32mprint\u001b[0m \u001b[0;34m'hello'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "here are some more resources on iPython Notebook basics: \n",
      "\n",
      "http://nbviewer.ipython.org/github/ipython/ipython/blob/1.x/examples/notebooks/Part%201%20-%20Running%20Code.ipynb\n",
      "http://nbviewer.ipython.org/github/ipython/ipython/blob/1.x/examples/notebooks/Part%202%20-%20Basic%20Output.ipynb\n"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Did I show you how cool tab completion is in iPython notebooks?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a."
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "pandas."
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = np.random.normal(size=10000).cumsum()\n",
      "plt.plot(x)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Use github and http://nbviewer.ipython.org to share your notebooks! "
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<h2>Fitbit data </h2>\n",
      "\n",
      "You can download (or \"export\") your fitbit data here: http://www.fitbit.com/premium/export\n",
      "\n",
      "Be aware that: \n",
      "(1) you can only get daily summary data this way and \n",
      "(2) this service costs money, but there is a one-week, one-time free trial. For the purposes of the PACC, the free trial should be enough (you can use my data to practice running your scripts on data in the same format and then download all of your data at once toward the end of the challenge). \n",
      "\n",
      "There is also an API that you can use to get to your data. We'll send more instructions on that at the beginning of Part 2. \n",
      "\n",
      "Below is what your fitbit data looks like from this export. Not a typical CSV file - this will confuse Pandas (especially the header lines in the middle of the file). "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "with open('data/fitbit_export_20150311.csv') as mydata:\n",
      "          print mydata.read()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Body\n",
        "Date,Weight,BMI,Fat\n",
        "\"2014-11-25\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-11-26\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-11-27\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-11-28\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-11-29\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-11-30\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-01\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-02\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-03\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-04\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-05\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-06\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-07\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-08\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-09\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-10\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-11\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-12\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-13\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-14\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-15\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-16\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-17\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-18\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-19\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-20\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-21\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-22\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-23\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-24\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-25\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-26\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-27\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-28\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-29\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-30\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2014-12-31\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-01\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-02\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-03\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-04\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-05\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-06\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-07\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-08\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-09\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-10\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-11\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-12\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-13\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-14\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-15\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-16\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-17\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-18\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-19\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-20\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-21\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-22\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-23\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-24\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-25\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-26\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-27\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-28\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-29\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-30\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-01-31\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-01\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-02\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-03\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-04\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-05\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-06\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-07\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-08\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-09\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-10\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-11\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-12\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-13\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-14\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-15\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-16\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-17\",\"115.72\",\"21.49\",\"0\"\n",
        "\"2015-02-18\",\"115.72\",\"21.49\",\"0\"\n",
        "\n",
        "Foods\n",
        "Date,Calories In\n",
        "\"2014-11-25\",\"0\"\n",
        "\"2014-11-26\",\"0\"\n",
        "\"2014-11-27\",\"0\"\n",
        "\"2014-11-28\",\"0\"\n",
        "\"2014-11-29\",\"0\"\n",
        "\"2014-11-30\",\"0\"\n",
        "\"2014-12-01\",\"0\"\n",
        "\"2014-12-02\",\"0\"\n",
        "\"2014-12-03\",\"0\"\n",
        "\"2014-12-04\",\"0\"\n",
        "\"2014-12-05\",\"0\"\n",
        "\"2014-12-06\",\"0\"\n",
        "\"2014-12-07\",\"0\"\n",
        "\"2014-12-08\",\"0\"\n",
        "\"2014-12-09\",\"0\"\n",
        "\"2014-12-10\",\"0\"\n",
        "\"2014-12-11\",\"0\"\n",
        "\"2014-12-12\",\"0\"\n",
        "\"2014-12-13\",\"0\"\n",
        "\"2014-12-14\",\"0\"\n",
        "\"2014-12-15\",\"0\"\n",
        "\"2014-12-16\",\"0\"\n",
        "\"2014-12-17\",\"0\"\n",
        "\"2014-12-18\",\"0\"\n",
        "\"2014-12-19\",\"0\"\n",
        "\"2014-12-20\",\"0\"\n",
        "\"2014-12-21\",\"0\"\n",
        "\"2014-12-22\",\"0\"\n",
        "\"2014-12-23\",\"0\"\n",
        "\"2014-12-24\",\"0\"\n",
        "\"2014-12-25\",\"0\"\n",
        "\"2014-12-26\",\"0\"\n",
        "\"2014-12-27\",\"0\"\n",
        "\"2014-12-28\",\"0\"\n",
        "\"2014-12-29\",\"0\"\n",
        "\"2014-12-30\",\"0\"\n",
        "\"2014-12-31\",\"0\"\n",
        "\"2015-01-01\",\"0\"\n",
        "\"2015-01-02\",\"0\"\n",
        "\"2015-01-03\",\"0\"\n",
        "\"2015-01-04\",\"0\"\n",
        "\"2015-01-05\",\"0\"\n",
        "\"2015-01-06\",\"0\"\n",
        "\"2015-01-07\",\"0\"\n",
        "\"2015-01-08\",\"0\"\n",
        "\"2015-01-09\",\"0\"\n",
        "\"2015-01-10\",\"0\"\n",
        "\"2015-01-11\",\"0\"\n",
        "\"2015-01-12\",\"0\"\n",
        "\"2015-01-13\",\"0\"\n",
        "\"2015-01-14\",\"0\"\n",
        "\"2015-01-15\",\"0\"\n",
        "\"2015-01-16\",\"0\"\n",
        "\"2015-01-17\",\"0\"\n",
        "\"2015-01-18\",\"0\"\n",
        "\"2015-01-19\",\"0\"\n",
        "\"2015-01-20\",\"0\"\n",
        "\"2015-01-21\",\"0\"\n",
        "\"2015-01-22\",\"0\"\n",
        "\"2015-01-23\",\"0\"\n",
        "\"2015-01-24\",\"0\"\n",
        "\"2015-01-25\",\"0\"\n",
        "\"2015-01-26\",\"0\"\n",
        "\"2015-01-27\",\"0\"\n",
        "\"2015-01-28\",\"0\"\n",
        "\"2015-01-29\",\"0\"\n",
        "\"2015-01-30\",\"0\"\n",
        "\"2015-01-31\",\"0\"\n",
        "\"2015-02-01\",\"0\"\n",
        "\"2015-02-02\",\"0\"\n",
        "\"2015-02-03\",\"0\"\n",
        "\"2015-02-04\",\"0\"\n",
        "\"2015-02-05\",\"0\"\n",
        "\"2015-02-06\",\"0\"\n",
        "\"2015-02-07\",\"0\"\n",
        "\"2015-02-08\",\"0\"\n",
        "\"2015-02-09\",\"0\"\n",
        "\"2015-02-10\",\"0\"\n",
        "\"2015-02-11\",\"0\"\n",
        "\"2015-02-12\",\"0\"\n",
        "\"2015-02-13\",\"0\"\n",
        "\"2015-02-14\",\"0\"\n",
        "\"2015-02-15\",\"0\"\n",
        "\"2015-02-16\",\"0\"\n",
        "\"2015-02-17\",\"0\"\n",
        "\"2015-02-18\",\"0\"\n",
        "\n",
        "Activities\n",
        "Date,Calories Burned,Steps,Distance,Floors,Minutes Sedentary,Minutes Lightly Active,Minutes Fairly Active,Minutes Very Active,Activity Calories\n",
        "\"2014-11-25\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-26\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-27\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-28\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-29\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-30\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-01\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-02\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-03\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-04\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-05\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-06\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-07\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-08\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-09\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-10\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-11\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-12\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-13\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-14\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-15\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-16\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-17\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-18\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-19\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-20\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-21\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-22\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-23\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-24\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-25\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-26\",\"1,729\",\"3,620\",\"1.45\",\"0\",\"1,247\",\"141\",\"52\",\"0\",\"474\"\n",
        "\"2014-12-27\",\"1,545\",\"4,490\",\"1.8\",\"0\",\"1,322\",\"66\",\"32\",\"20\",\"374\"\n",
        "\"2014-12-28\",\"1,611\",\"4,723\",\"1.9\",\"0\",\"1,254\",\"106\",\"78\",\"2\",\"492\"\n",
        "\"2014-12-29\",\"1,639\",\"5,335\",\"2.16\",\"0\",\"1,258\",\"119\",\"49\",\"14\",\"519\"\n",
        "\"2014-12-30\",\"1,442\",\"2,555\",\"1.03\",\"0\",\"1,339\",\"70\",\"24\",\"7\",\"273\"\n",
        "\"2014-12-31\",\"1,576\",\"4,482\",\"1.8\",\"0\",\"1,290\",\"91\",\"46\",\"13\",\"428\"\n",
        "\"2015-01-01\",\"1,492\",\"2,593\",\"1.04\",\"0\",\"1,305\",\"96\",\"39\",\"0\",\"332\"\n",
        "\"2015-01-02\",\"1,517\",\"4,196\",\"1.68\",\"0\",\"1,297\",\"54\",\"30\",\"20\",\"340\"\n",
        "\"2015-01-03\",\"1,524\",\"3,397\",\"1.36\",\"0\",\"764\",\"108\",\"30\",\"6\",\"380\"\n",
        "\"2015-01-04\",\"1,740\",\"6,839\",\"2.75\",\"0\",\"1,209\",\"145\",\"64\",\"22\",\"657\"\n",
        "\"2015-01-05\",\"2,064\",\"13,118\",\"5.37\",\"0\",\"1,023\",\"149\",\"111\",\"52\",\"1,036\"\n",
        "\"2015-01-06\",\"1,902\",\"10,727\",\"4.45\",\"0\",\"705\",\"107\",\"74\",\"53\",\"818\"\n",
        "\"2015-01-07\",\"1,886\",\"10,022\",\"4.1\",\"0\",\"570\",\"134\",\"75\",\"46\",\"829\"\n",
        "\"2015-01-08\",\"2,300\",\"18,950\",\"7.68\",\"0\",\"500\",\"121\",\"122\",\"105\",\"1,314\"\n",
        "\"2015-01-09\",\"2,171\",\"15,803\",\"6.56\",\"0\",\"583\",\"135\",\"64\",\"95\",\"1,136\"\n",
        "\"2015-01-10\",\"1,789\",\"7,965\",\"3.21\",\"0\",\"736\",\"132\",\"55\",\"37\",\"697\"\n",
        "\"2015-01-11\",\"1,564\",\"4,524\",\"1.82\",\"0\",\"867\",\"86\",\"31\",\"20\",\"412\"\n",
        "\"2015-01-12\",\"1,872\",\"10,063\",\"4.07\",\"0\",\"735\",\"120\",\"74\",\"47\",\"794\"\n",
        "\"2015-01-13\",\"2,053\",\"12,232\",\"4.98\",\"0\",\"588\",\"184\",\"98\",\"50\",\"1,044\"\n",
        "\"2015-01-14\",\"1,866\",\"9,979\",\"4.26\",\"0\",\"719\",\"118\",\"66\",\"48\",\"798\"\n",
        "\"2015-01-15\",\"2,177\",\"16,538\",\"6.72\",\"0\",\"1,119\",\"137\",\"93\",\"91\",\"1,185\"\n",
        "\"2015-01-16\",\"1,468\",\"3,229\",\"1.33\",\"0\",\"1,335\",\"66\",\"26\",\"13\",\"308\"\n",
        "\"2015-01-17\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-18\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-19\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-20\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-21\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-22\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-23\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-24\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-25\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-26\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-27\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-28\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-29\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-30\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-31\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-01\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-02\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-03\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-04\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-05\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-06\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-07\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-08\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-09\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-10\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-11\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-12\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-13\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-14\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-15\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-16\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-17\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-18\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\n",
        "\n",
        "Sleep\n",
        "Date,Minutes Asleep,Minutes Awake,Number of Awakenings,Time in Bed\n",
        "\"2014-11-25\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-26\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-27\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-28\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-29\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-11-30\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-01\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-02\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-03\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-04\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-05\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-06\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-07\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-08\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-09\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-10\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-11\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-12\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-13\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-14\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-15\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-16\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-17\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-18\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-19\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-20\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-21\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-22\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-23\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-24\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-25\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-26\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-27\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-28\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-29\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-30\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2014-12-31\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-01\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-02\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-03\",\"420\",\"144\",\"14\",\"571\"\n",
        "\"2015-01-04\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-05\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-06\",\"462\",\"32\",\"12\",\"591\"\n",
        "\"2015-01-07\",\"497\",\"73\",\"17\",\"570\"\n",
        "\"2015-01-08\",\"435\",\"60\",\"12\",\"564\"\n",
        "\"2015-01-09\",\"527\",\"32\",\"11\",\"591\"\n",
        "\"2015-01-10\",\"445\",\"25\",\"12\",\"480\"\n",
        "\"2015-01-11\",\"402\",\"17\",\"11\",\"480\"\n",
        "\"2015-01-12\",\"422\",\"58\",\"17\",\"480\"\n",
        "\"2015-01-13\",\"401\",\"9\",\"7\",\"445\"\n",
        "\"2015-01-14\",\"524\",\"21\",\"10\",\"564\"\n",
        "\"2015-01-15\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-16\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-17\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-18\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-19\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-20\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-21\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-22\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-23\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-24\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-25\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-26\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-27\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-28\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-29\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-30\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-01-31\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-01\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-02\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-03\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-04\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-05\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-06\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-07\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-08\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-09\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-10\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-11\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-12\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-13\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-14\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-15\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-16\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-17\",\"0\",\"0\",\"0\",\"0\"\n",
        "\"2015-02-18\",\"0\",\"0\",\"0\",\"0\"\n",
        "\n",
        "food_log_20141125\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141126\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141127\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141128\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141129\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141130\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141201\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141202\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141203\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141204\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141205\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141206\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141207\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141208\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141209\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141210\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141211\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141212\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141213\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141214\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141215\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141216\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141217\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141218\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141219\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141220\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141221\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141222\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141223\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141224\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141225\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141226\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141227\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141228\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141229\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141230\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20141231\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150101\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150102\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150103\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150104\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150105\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150106\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150107\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150108\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"63.2 fl oz\"\n",
        "\n",
        "food_log_20150109\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0.9 fl oz\"\n",
        "\n",
        "food_log_20150110\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150111\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150112\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150113\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150114\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150115\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150116\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150117\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150118\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150119\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150120\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150121\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150122\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150123\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150124\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150125\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150126\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150127\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150128\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150129\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150130\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150131\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150201\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150202\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150203\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150204\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150205\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150206\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150207\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150208\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150209\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150210\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150211\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150212\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150213\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150214\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150215\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150216\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150217\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "food_log_20150218\n",
        "Daily Totals\n",
        "\"\",\"Calories\",\"0\"\n",
        "\"\",\"Fat\",\"0 g\"\n",
        "\"\",\"Fiber\",\"0 g\"\n",
        "\"\",\"Carbs\",\"0 g\"\n",
        "\"\",\"Sodium\",\"0 mg\"\n",
        "\"\",\"Protein\",\"0 g\"\n",
        "\"\",\"Water\",\"0 fl oz\"\n",
        "\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I created a file for each of the different types of fitbit data that I actually had entries for (sleep, steps, scale) by copy/pasting into new text files. Now they look like this: \n",
      "\n",
      "(Note that I'm using terminal commands here to show this info)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ls data/fitbit*"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "data/fitbit_export_20150311.csv  data/fitbit_sleep.csv\r\n",
        "data/fitbit_scale.csv            data/fitbit_steps.csv\r\n"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "!head data/fitbit_steps.csv"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Date,Calories Burned,Steps,Distance,Floors,Minutes Sedentary,Minutes Lightly Active,Minutes Fairly Active,Minutes Very Active,Activity Calories\r\n",
        "\"2014-11-25\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-11-26\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-11-27\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-11-28\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-11-29\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-11-30\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-12-01\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-12-02\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n",
        "\"2014-12-03\",\"1,222\",\"0\",\"0\",\"0\",\"1,440\",\"0\",\"0\",\"0\",\"0\"\r\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "You <em>could</em> just process all of this by hand ... "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "day_to_steps = {}\n",
      "with open('data/fitbit_steps.csv') as my_steps:\n",
      "    my_steps.readline()  # get past the header\n",
      "    for line in my_steps:\n",
      "        line = line.replace('\"', '')  # get rid of those pesky quotation marks that prevent the numbers from being read as ints\n",
      "        line = line.split(',')\n",
      "        day_to_steps[line[0]] = int(line[2])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print sum(day_to_steps.values())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "26135\n"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "But it starts to get old pretty fast. Not the best. Here's where pandas comes in. \n",
      "\n",
      "<h2>Pandas </h2>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "steps = pandas.read_csv('data/fitbit_steps.csv') "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "steps"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<pre>\n",
        "&lt;class 'pandas.core.frame.DataFrame'&gt;\n",
        "Int64Index: 86 entries, 0 to 85\n",
        "Data columns (total 10 columns):\n",
        "Date                      86  non-null values\n",
        "Calories Burned           86  non-null values\n",
        "Steps                     86  non-null values\n",
        "Distance                  86  non-null values\n",
        "Floors                    86  non-null values\n",
        "Minutes Sedentary         86  non-null values\n",
        "Minutes Lightly Active    86  non-null values\n",
        "Minutes Fairly Active     86  non-null values\n",
        "Minutes Very Active       86  non-null values\n",
        "Activity Calories         86  non-null values\n",
        "dtypes: float64(1), int64(4), object(5)\n",
        "</pre>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "<class 'pandas.core.frame.DataFrame'>\n",
        "Int64Index: 86 entries, 0 to 85\n",
        "Data columns (total 10 columns):\n",
        "Date                      86  non-null values\n",
        "Calories Burned           86  non-null values\n",
        "Steps                     86  non-null values\n",
        "Distance                  86  non-null values\n",
        "Floors                    86  non-null values\n",
        "Minutes Sedentary         86  non-null values\n",
        "Minutes Lightly Active    86  non-null values\n",
        "Minutes Fairly Active     86  non-null values\n",
        "Minutes Very Active       86  non-null values\n",
        "Activity Calories         86  non-null values\n",
        "dtypes: float64(1), int64(4), object(5)"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "steps.Steps[42:60]  # indexing (treating it like an array)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "step_sum = 0\n",
      "for s in steps.Steps:\n",
      "    step_sum = step_sum + int(s)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "ValueError",
       "evalue": "invalid literal for int() with base 10: '3,620'",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
        "\u001b[0;32m<ipython-input-22-058ff7e3a4a8>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mstep_sum\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ms\u001b[0m \u001b[0;32min\u001b[0m \u001b[0msteps\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSteps\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mstep_sum\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstep_sum\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[0;31mValueError\u001b[0m: invalid literal for int() with base 10: '3,620'"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "steps_better = pandas.read_csv('data/fitbit_steps.csv', thousands=',')\n",
      "step_sum = 0\n",
      "for s in steps_better.Steps:\n",
      "    step_sum = step_sum + int(s)\n",
      "step_sum"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "175380"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### back to part 1 data "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "volleyball_player = pandas.read_csv('data/player_data_volleyball.csv')\n",
      "soccer_player = pandas.read_csv('data/player_data_soccer.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "volleyball_player"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "volleyball_player['GEN. SORNESS'][:10]  # you might want to make the column names not include spaces/special characters, \n",
      "                                        # but here's another way to get at the data (besides the '.') "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "0    3\n",
        "1    4\n",
        "2    3\n",
        "3    3\n",
        "4    4\n",
        "5    3\n",
        "6    4\n",
        "7    2\n",
        "8    2\n",
        "9    2\n",
        "Name: GEN. SORNESS, dtype: int64"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "More on getting started with Pandas (includes some plotting basics): \n",
      "\n",
      "http://nbviewer.ipython.org/github/twiecki/financial-analysis-python-tutorial/blob/master/1.%20Pandas%20Basics.ipynb\n",
      "\n",
      "http://pandas.pydata.org/pandas-docs/dev/tutorials.html\n",
      "\n",
      "http://pandas.pydata.org/pandas-docs/dev/basics.html"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "volleyball_player.head()  # prettier formatting"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Athlete ID </th>\n",
        "      <th>Day of Week (1 is Sunday)</th>\n",
        "      <th>Date</th>\n",
        "      <th>FATIGUE</th>\n",
        "      <th>SLEEP QUALITY</th>\n",
        "      <th>GEN. SORNESS</th>\n",
        "      <th>STRESS</th>\n",
        "      <th>MOOD</th>\n",
        "      <th>HOURS SLEPT</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 15</td>\n",
        "      <td> 1</td>\n",
        "      <td> 8/24/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 15</td>\n",
        "      <td> 2</td>\n",
        "      <td> 8/25/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 15</td>\n",
        "      <td> 3</td>\n",
        "      <td> 8/26/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 15</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8/27/14</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 15</td>\n",
        "      <td> 5</td>\n",
        "      <td> 8/28/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 28,
       "text": [
        "   Athlete ID   Day of Week (1 is Sunday)     Date  FATIGUE  SLEEP QUALITY  \\\n",
        "0           15                          1  8/24/14        3              4   \n",
        "1           15                          2  8/25/14        3              4   \n",
        "2           15                          3  8/26/14        3              4   \n",
        "3           15                          4  8/27/14        4              3   \n",
        "4           15                          5  8/28/14        3              4   \n",
        "\n",
        "   GEN. SORNESS  STRESS  MOOD  HOURS SLEPT  \n",
        "0             3       4     4            8  \n",
        "1             4       4     4            8  \n",
        "2             3       3     4            8  \n",
        "3             3       3     4            8  \n",
        "4             4       4     4            8  "
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "volleyball_player.describe()  # to get general statistics about your data"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Athlete ID </th>\n",
        "      <th>Day of Week (1 is Sunday)</th>\n",
        "      <th>FATIGUE</th>\n",
        "      <th>SLEEP QUALITY</th>\n",
        "      <th>GEN. SORNESS</th>\n",
        "      <th>STRESS</th>\n",
        "      <th>MOOD</th>\n",
        "      <th>HOURS SLEPT</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "      <td> 1157.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
        "      <td>    7.976664</td>\n",
        "      <td>    3.946413</td>\n",
        "      <td>    3.066551</td>\n",
        "      <td>    3.648228</td>\n",
        "      <td>    3.138289</td>\n",
        "      <td>    3.041487</td>\n",
        "      <td>    3.828868</td>\n",
        "      <td>    8.177182</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
        "      <td>    4.368649</td>\n",
        "      <td>    1.969639</td>\n",
        "      <td>    0.763503</td>\n",
        "      <td>    0.704551</td>\n",
        "      <td>    0.685915</td>\n",
        "      <td>    0.792487</td>\n",
        "      <td>    0.565835</td>\n",
        "      <td>    1.209885</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    2.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    7.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
        "      <td>    8.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    8.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
        "      <td>   12.000000</td>\n",
        "      <td>    6.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    9.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
        "      <td>   15.000000</td>\n",
        "      <td>    7.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>   12.000000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "       Athlete ID   Day of Week (1 is Sunday)      FATIGUE  SLEEP QUALITY  \\\n",
        "count  1157.000000                1157.000000  1157.000000    1157.000000   \n",
        "mean      7.976664                   3.946413     3.066551       3.648228   \n",
        "std       4.368649                   1.969639     0.763503       0.704551   \n",
        "min       1.000000                   1.000000     1.000000       1.000000   \n",
        "25%       4.000000                   2.000000     3.000000       3.000000   \n",
        "50%       8.000000                   4.000000     3.000000       4.000000   \n",
        "75%      12.000000                   6.000000     4.000000       4.000000   \n",
        "max      15.000000                   7.000000     5.000000       5.000000   \n",
        "\n",
        "       GEN. SORNESS       STRESS         MOOD  HOURS SLEPT  \n",
        "count   1157.000000  1157.000000  1157.000000  1157.000000  \n",
        "mean       3.138289     3.041487     3.828868     8.177182  \n",
        "std        0.685915     0.792487     0.565835     1.209885  \n",
        "min        1.000000     1.000000     1.000000     4.000000  \n",
        "25%        3.000000     3.000000     4.000000     7.500000  \n",
        "50%        3.000000     3.000000     4.000000     8.000000  \n",
        "75%        4.000000     4.000000     4.000000     9.000000  \n",
        "max        5.000000     5.000000     5.000000    12.000000  "
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "soccer_player.describe()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>ATHLETE_ID</th>\n",
        "      <th>DAY_OF_WEEK</th>\n",
        "      <th>FATIGUE</th>\n",
        "      <th>SLEEP_QUALITY</th>\n",
        "      <th>GENERAL_SORNESS</th>\n",
        "      <th>STRESS</th>\n",
        "      <th>MOOD</th>\n",
        "      <th>HOURS_SLEPT</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>count</th>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "      <td> 2457.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>mean</th>\n",
        "      <td>   14.985755</td>\n",
        "      <td>    4.056980</td>\n",
        "      <td>    3.492063</td>\n",
        "      <td>    3.741555</td>\n",
        "      <td>    3.341880</td>\n",
        "      <td>    3.564917</td>\n",
        "      <td>    3.878714</td>\n",
        "      <td>    8.115181</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>std</th>\n",
        "      <td>    8.425292</td>\n",
        "      <td>    1.967159</td>\n",
        "      <td>    0.790336</td>\n",
        "      <td>    0.757398</td>\n",
        "      <td>    0.876498</td>\n",
        "      <td>    0.762490</td>\n",
        "      <td>    0.636772</td>\n",
        "      <td>    1.137960</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>min</th>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    1.000000</td>\n",
        "      <td>    2.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>25%</th>\n",
        "      <td>    8.000000</td>\n",
        "      <td>    2.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    7.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>50%</th>\n",
        "      <td>   15.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    3.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    8.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>75%</th>\n",
        "      <td>   22.000000</td>\n",
        "      <td>    6.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    4.000000</td>\n",
        "      <td>    9.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>max</th>\n",
        "      <td>   29.000000</td>\n",
        "      <td>    7.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>    5.000000</td>\n",
        "      <td>   15.000000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 30,
       "text": [
        "        ATHLETE_ID  DAY_OF_WEEK      FATIGUE  SLEEP_QUALITY  GENERAL_SORNESS  \\\n",
        "count  2457.000000  2457.000000  2457.000000    2457.000000      2457.000000   \n",
        "mean     14.985755     4.056980     3.492063       3.741555         3.341880   \n",
        "std       8.425292     1.967159     0.790336       0.757398         0.876498   \n",
        "min       1.000000     1.000000     1.000000       1.000000         1.000000   \n",
        "25%       8.000000     2.000000     3.000000       3.000000         3.000000   \n",
        "50%      15.000000     4.000000     4.000000       4.000000         3.000000   \n",
        "75%      22.000000     6.000000     4.000000       4.000000         4.000000   \n",
        "max      29.000000     7.000000     5.000000       5.000000         5.000000   \n",
        "\n",
        "            STRESS         MOOD  HOURS_SLEPT  \n",
        "count  2457.000000  2457.000000  2457.000000  \n",
        "mean      3.564917     3.878714     8.115181  \n",
        "std       0.762490     0.636772     1.137960  \n",
        "min       1.000000     1.000000     2.000000  \n",
        "25%       3.000000     4.000000     7.500000  \n",
        "50%       4.000000     4.000000     8.000000  \n",
        "75%       4.000000     4.000000     9.000000  \n",
        "max       5.000000     5.000000    15.000000  "
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sorted_date = volleyball_player.sort_index(by='Date')\n",
      "sorted_date.tail()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Athlete ID </th>\n",
        "      <th>Day of Week (1 is Sunday)</th>\n",
        "      <th>Date</th>\n",
        "      <th>FATIGUE</th>\n",
        "      <th>SLEEP QUALITY</th>\n",
        "      <th>GEN. SORNESS</th>\n",
        "      <th>STRESS</th>\n",
        "      <th>MOOD</th>\n",
        "      <th>HOURS SLEPT</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>258 </th>\n",
        "      <td> 12</td>\n",
        "      <td> 3</td>\n",
        "      <td> 9/9/14</td>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>859 </th>\n",
        "      <td>  4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 9/9/14</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>613 </th>\n",
        "      <td>  7</td>\n",
        "      <td> 3</td>\n",
        "      <td> 9/9/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1020</th>\n",
        "      <td>  2</td>\n",
        "      <td> 3</td>\n",
        "      <td> 9/9/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>96  </th>\n",
        "      <td> 14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 9/9/14</td>\n",
        "      <td> 4</td>\n",
        "      <td> 5</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 8</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "      Athlete ID   Day of Week (1 is Sunday)    Date  FATIGUE  SLEEP QUALITY  \\\n",
        "258            12                          3  9/9/14        2              2   \n",
        "859             4                          3  9/9/14        4              3   \n",
        "613             7                          3  9/9/14        3              3   \n",
        "1020            2                          3  9/9/14        3              4   \n",
        "96             14                          3  9/9/14        4              5   \n",
        "\n",
        "      GEN. SORNESS  STRESS  MOOD  HOURS SLEPT  \n",
        "258              3       4     4            6  \n",
        "859              4       4     4            7  \n",
        "613              3       3     4            7  \n",
        "1020             3       4     4            8  \n",
        "96               4       4     4            8  "
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sorted_sleep = volleyball_player.sort_index(by='SLEEP QUALITY')\n",
      "sorted_sleep.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Athlete ID </th>\n",
        "      <th>Day of Week (1 is Sunday)</th>\n",
        "      <th>Date</th>\n",
        "      <th>FATIGUE</th>\n",
        "      <th>SLEEP QUALITY</th>\n",
        "      <th>GEN. SORNESS</th>\n",
        "      <th>STRESS</th>\n",
        "      <th>MOOD</th>\n",
        "      <th>HOURS SLEPT</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>925</th>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td>  8/27/14</td>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 3</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "      <td> 6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>598</th>\n",
        "      <td> 7</td>\n",
        "      <td> 2</td>\n",
        "      <td>  8/25/14</td>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>793</th>\n",
        "      <td> 5</td>\n",
        "      <td> 5</td>\n",
        "      <td>  9/25/14</td>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>489</th>\n",
        "      <td> 9</td>\n",
        "      <td> 1</td>\n",
        "      <td>  10/5/14</td>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 3</td>\n",
        "      <td> 9</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>908</th>\n",
        "      <td> 4</td>\n",
        "      <td> 4</td>\n",
        "      <td> 10/29/14</td>\n",
        "      <td> 2</td>\n",
        "      <td> 2</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3</td>\n",
        "      <td> 4</td>\n",
        "      <td> 7</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "     Athlete ID   Day of Week (1 is Sunday)      Date  FATIGUE  SLEEP QUALITY  \\\n",
        "925            3                          4   8/27/14        3              1   \n",
        "598            7                          2   8/25/14        2              1   \n",
        "793            5                          5   9/25/14        2              2   \n",
        "489            9                          1   10/5/14        2              2   \n",
        "908            4                          4  10/29/14        2              2   \n",
        "\n",
        "     GEN. SORNESS  STRESS  MOOD  HOURS SLEPT  \n",
        "925             3       2     3            6  \n",
        "598             3       3     3            4  \n",
        "793             2       3     3            7  \n",
        "489             3       3     3            9  \n",
        "908             4       3     4            7  "
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "date_avgs = volleyball_player.groupby('Date').aggregate(np.average)\n",
      "date_avgs.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Athlete ID </th>\n",
        "      <th>Day of Week (1 is Sunday)</th>\n",
        "      <th>FATIGUE</th>\n",
        "      <th>SLEEP QUALITY</th>\n",
        "      <th>GEN. SORNESS</th>\n",
        "      <th>STRESS</th>\n",
        "      <th>MOOD</th>\n",
        "      <th>HOURS SLEPT</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>10/1/14</th>\n",
        "      <td> 8.000000</td>\n",
        "      <td> 4</td>\n",
        "      <td> 3.200000</td>\n",
        "      <td> 3.666667</td>\n",
        "      <td> 3.066667</td>\n",
        "      <td> 2.866667</td>\n",
        "      <td> 3.800000</td>\n",
        "      <td> 8.333333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10/10/14</th>\n",
        "      <td> 7.857143</td>\n",
        "      <td> 6</td>\n",
        "      <td> 3.285714</td>\n",
        "      <td> 3.714286</td>\n",
        "      <td> 3.357143</td>\n",
        "      <td> 3.000000</td>\n",
        "      <td> 3.928571</td>\n",
        "      <td> 8.357143</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10/11/14</th>\n",
        "      <td> 8.000000</td>\n",
        "      <td> 7</td>\n",
        "      <td> 2.933333</td>\n",
        "      <td> 3.600000</td>\n",
        "      <td> 2.933333</td>\n",
        "      <td> 2.933333</td>\n",
        "      <td> 3.666667</td>\n",
        "      <td> 8.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10/12/14</th>\n",
        "      <td> 7.692308</td>\n",
        "      <td> 1</td>\n",
        "      <td> 3.076923</td>\n",
        "      <td> 3.692308</td>\n",
        "      <td> 3.000000</td>\n",
        "      <td> 3.000000</td>\n",
        "      <td> 3.846154</td>\n",
        "      <td> 7.769231</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10/13/14</th>\n",
        "      <td> 8.000000</td>\n",
        "      <td> 2</td>\n",
        "      <td> 3.066667</td>\n",
        "      <td> 3.533333</td>\n",
        "      <td> 2.933333</td>\n",
        "      <td> 3.066667</td>\n",
        "      <td> 3.866667</td>\n",
        "      <td> 8.700000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 35,
       "text": [
        "          Athlete ID   Day of Week (1 is Sunday)   FATIGUE  SLEEP QUALITY  \\\n",
        "Date                                                                        \n",
        "10/1/14      8.000000                          4  3.200000       3.666667   \n",
        "10/10/14     7.857143                          6  3.285714       3.714286   \n",
        "10/11/14     8.000000                          7  2.933333       3.600000   \n",
        "10/12/14     7.692308                          1  3.076923       3.692308   \n",
        "10/13/14     8.000000                          2  3.066667       3.533333   \n",
        "\n",
        "          GEN. SORNESS    STRESS      MOOD  HOURS SLEPT  \n",
        "Date                                                     \n",
        "10/1/14       3.066667  2.866667  3.800000     8.333333  \n",
        "10/10/14      3.357143  3.000000  3.928571     8.357143  \n",
        "10/11/14      2.933333  2.933333  3.666667     8.000000  \n",
        "10/12/14      3.000000  3.000000  3.846154     7.769231  \n",
        "10/13/14      2.933333  3.066667  3.866667     8.700000  "
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# empty cells for live demos - ask questions! "
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<h2>Matplotlib</h2>\n",
      "\n",
      "Here are the basics of plotting stuff in matplotlib. \n",
      "\n",
      "<em>Scatter plots & line graphs</em>"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x = [1,2,3]\n",
      "y = [2,4,6]\n",
      "plt.plot(x,y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 36,
       "text": [
        "[<matplotlib.lines.Line2D at 0x106b9a6d0>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x103635d10>"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(x,y, marker='o')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "[<matplotlib.lines.Line2D at 0x106ce7090>]"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x106bc7e10>"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.scatter(x,y)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 38,
       "text": [
        "<matplotlib.collections.PathCollection at 0x106c016d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Ll8rzPIVCoT7XWN67SOuLdu98vdPOzs5WQ0ND768bGhqUk5PT55qbbrqp9z8Dli1bpq6u\nLv3888/RrG3M+vX6z507p+zs7DhONLISYe+6urq0atUqrVmzRitXruz3vPU9jLS+RNjD9PR0PfDA\nA/r666/7/L71vfu7660v2r3zFe158+apvr5eZ8+eVWdnp3bu3KkVK1b0uaaxsbH3u2FNTY2ccwOe\n3Vi0YsUKbd++XZJ07Ngx3XzzzcrMzIzzVCPH+t4557R+/XoFg0E9++yzA15jeQ/9rM/qHjY1Nam5\nuVmS1N7ergMHDqioqKjPNZb3zs/6ot07X8cjycnJeuutt7R06VL19PRo/fr1ys/P1zvvvCNJevLJ\nJ7Vr1y69/fbbSk5OVkpKinbs2DGkRcbD6tWrdejQITU1NSk3N1ebN29WV1eXpGtrKy0t1d69ezVl\nyhSlpqaa+4BRpPVZ3jtJOnr0qD744APNmjWr91+IV155RT/++KMk+3voZ31W9/DixYuqqKhQOBxW\nOBxWeXm5lixZ0qctlvfOz/qi3Ts+XAMAhvB/+QMAQ4g2ABhCtAHAEKINAIYQbQAwhGgDgCFEGwAM\nIdoAYMj/A7naW8EZOXmnAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x106cf3090>"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "x1 = volleyball_player.MOOD\n",
      "y1 = volleyball_player.STRESS\n",
      "plt.scatter(x1,y1)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 33,
       "text": [
        "<matplotlib.collections.PathCollection at 0x106bfbe10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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JEvLz823H6RK+FLQfX0RERM4XTXfqSkIREUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVE\nHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApaRMRRKmgR\nEUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApa\nRMRRHRb0woULyczM5Prrr++OPCIiEtFhQRcVFVFaWtodWaSbHT16lPfff5/W1lbbUXx35swZfvCD\nH7Bx40bbUbrE559/zuLFi3nttddsR+kS9fX17Nu3j/r6ettR7DJRqKysNCNGjLjgY1EeQhxy9uxZ\nM2TIKAM9DSSa5OSBpqqqynYs3/z85z83kGIgMTJjsvnLX/5iO5ZvpkyZYiDJQB8DPYzn9bYdyVer\nV6820MtAqoHe5sknn7QdqUtE051ag74M3XvvPA4digdqgNPU109mwoTbbMfyzeLF3wcKgdPAF8AQ\n0tIy7Iby0Y4d7wJrgFPARxjTi6FDh1pO5Y/KykqWL18FlAK1wDYee6yYo0ePWk5mhwr6MvTOO+8B\ni4EUIB54mGPHPrcbyldxwBLCs/UBFmNMot1IPjly5AhQDzwYuWcwMJ1Dhw5Zy+SnYDAIDAJuitwT\nAAZSXl5uK5JVCX4cpLi4uO3jQCBAIBDw47DSRQYPzuTTT39PuKQ94A369Em2nMpvO4AxQCvwOtBk\nN45PcnJygF5AGXAz0AjsIjU11WYs34waNQo4BnwKXAUcBT5j5MiRVnP5IRgMRr4BdUI0ayVag44t\n1dXVplevDANDDYw1npdsysrKbMfyzfTp0yPrz2MjM6aYl19+2XYs36SnpxvobWCigSwDKaapqcl2\nLN/MnHlXZH09YKCPKSz8R9uRukQ03elFdvxac+bMoaysjJMnT9K/f39WrVpFUVFR2+Oe59HBIcRB\n9fX1PPPMMzQ0NLBgwQKuuuoq25F8tXHjRlasWMEVV1xBWVkZ1113ne1Ivlq8eDGbN28mMzOT999/\nn169etmO5KutW7eye/dubrzxRm67LXZ+P3KuaLqzw4L244uIiMj5oulO/ZJQRMRRKmgREUepoEVE\nHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApaRMRRKmgR\nEUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFxlApa\nRMRRKmgREUepoEVEHKWCFhFxVIcFXVpaynXXXcc111zDk08+2R2ZRESEDgo6FArx8MMPU1paygcf\nfMDmzZv58MMPuyubE4LBoO0IXUrzXdpieb5Yni1a7Rb03r17GTJkCDk5OfTo0YO7776bV155pbuy\nOSHWXySa79IWy/PF8mzRaregjx8/zqBBg9puZ2dnc/z48S4PJSIiHRS053ndlUNERP6Wacc777xj\npk2b1nb7iSeeMGvWrDlvn9zcXANo06ZNm7ZObLm5ue3VrzHGGM8YY/gaLS0tDB06lDfeeIOBAwcy\nduxYNm/ezLBhw77uU0RExCcJ7T6YkMDPfvYzpk2bRigU4v7771c5i4h0k3bPoEVExJ5vdCVhLF/E\nsnDhQjIzM7n++uttR+kSVVVVTJo0ieHDhzNixAiefvpp25F8debMGcaNG0d+fj55eXksX77cdiTf\nhUIhCgoKmDFjhu0ovsvJyWHkyJEUFBQwduxY23F8V1tby+zZsxk2bBh5eXns2bPnwjt2uEr9NVpa\nWkxubq6prKw0zc3NZtSoUeaDDz642MM556233jIVFRVmxIgRtqN0iRMnTpj9+/cbY4ypq6sz1157\nbUw9f8YY09DQYIwx5uzZs2bcuHGmvLzcciJ//eQnPzH33HOPmTFjhu0ovsvJyTEnT560HaPLzJs3\nzzz33HPGmPDrs7a29oL7XfQZdKxfxDJhwgT69etnO0aXycrKIj8/H4Dk5GSGDRvGZ599ZjmVvxIT\nEwFobm4mFAqRlpZmOZF/jh07xrZt21i0aBEmRlcpY3WuU6dOUV5ezsKFC4Hw7/pSU1MvuO9FF7Qu\nYokdR44cYf/+/YwbN852FF+1traSn59PZmYmkyZNIi8vz3Yk3yxdupSnnnqKuLjY/P/OPM9jypQp\njBkzhmeffdZ2HF9VVlaSkZFBUVERo0eP5oEHHqCxsfGC+170s6uLWGJDfX09s2fPpqSkhOTkZNtx\nfBUXF8eBAwc4duwYb731VsxcOrx161b69+9PQUFBzJ5l7tq1i/379/Paa6+xYcMGysvLbUfyTUtL\nCxUVFTz00ENUVFSQlJTEmjVrLrjvRRf0t771LaqqqtpuV1VVkZ2dfbGHEwvOnj3LrFmzuPfee5k5\nc6btOF0mNTWV6dOn84c//MF2FF/s3r2bLVu2MHjwYObMmcObb77JvHnzbMfy1YABAwDIyMigsLCQ\nvXv3Wk7kn+zsbLKzs7nhhhsAmD17NhUVFRfc96ILesyYMXz88cccOXKE5uZmXnzxRe64446LPZx0\nM2MM999/P3l5eXzve9+zHcd3NTU11NbWAtDU1MT27dspKCiwnMofTzzxBFVVVVRWVvLrX/+am2++\nmU2bNtmO5ZvGxkbq6uoAaGho4PXXX4+pv6bKyspi0KBBHDx4EIAdO3YwfPjwC+7b7oUq7Yn1i1jm\nzJlDWVkZJ0+eZNCgQaxatYqioiLbsXyza9cuXnjhhbY/ZQJYvXo1t956q+Vk/jhx4gTz58+ntbWV\n1tZW7rvvPiZPnmw7VpeIteXG6upqCgsLgfBywNy5c5k6darlVP5av349c+fOpbm5mdzcXJ5//vkL\n7qcLVUREHBWbvwIWEYkBKmgREUepoEVEHKWCFhFxlApaRMRRKmgREUepoEVEHKWCFhFx1P8BpyvA\nvD/OchEAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x106bc7e90>"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<em>Histograms</em> "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "my_data = [1,1,1,2,2,3,1,1,2,3,4,4,2,1]\n",
      "plt.hist(my_data, bins=2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 40,
       "text": [
        "(array([ 10.,   4.]), array([ 1. ,  2.5,  4. ]), <a list of 2 Patch objects>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x106c208d0>"
       ]
      }
     ],
     "prompt_number": 40
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}