{
 "metadata": {
  "name": "",
  "signature": "sha256:e35117590c5b3bd218d964c85b4920d4f781ff59c108694752b0c13aa8b3a316"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "\n",
      "%matplotlib inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df = pd.read_csv(\"data.csv\", index_col='index')\n",
      "df.index=pd.to_datetime(df.index,format='%Y%m') "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Plot the data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "df.groupby(\"to_network\")['count'].plot()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 25,
       "text": [
        "to_network\n",
        "net_1         Axes(0.125,0.125;0.775x0.775)\n",
        "net_2         Axes(0.125,0.125;0.775x0.775)\n",
        "net_3         Axes(0.125,0.125;0.775x0.775)\n",
        "Name: count, dtype: object"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x112918450>"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}