A IPython Notebook to analyze the Gaza-Israel 2012 crisis

guardian_gaza.ipynb

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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# A IPython Notebook to analyze the Gaza-Israel 2012 crisis\n",
      "\n",
      "The Guardian is tracking and mapping live ([link](http://www.guardian.co.uk/news/datablog/interactive/2012/nov/19/gaza-israel-verified-incidents-mapped)) the recent incidents in Gaza and Israel. As part of their data-journalism spirit, they are sharing the data as a Google Fusion Table available for access.\n",
      "\n",
      "This notebook is an attempt to show, on the one hand, how the toolkit from the Python stack can be used for a real world data hack and, on the other, to offer deeper analysis beyond mapping of the events, both exploiting the spatial as well as the temporal dimension of the data.\n",
      "\n",
      "+ The source document (`.ipynb` file) is stored on Github as a gist [here](https://gist.github.com/4121857), which means you can fork it and use it as a start for you own data-hack.\n",
      "+ A viewable version is available [here](http://nbviewer.ipython.org/4121857/), via the IPython Notebook Viewer.\n",
      "\n",
      "## Collaborate on the notebook!!!\n",
      "\n",
      "In its initial version (Nov. 20th), the notebook only contains code to stream the data from the Google Fusion Table into a [`pandas`](http://pandas.pydata.org) DataFrame (which means you get the data ready to hack!). Step in and collaborate in making it a good example of how Python can help analyze real world data. Add a new view, quick visualization, summary statistic of fancy model that helps understand the data better!\n",
      "\n",
      "To contribute, just fork the gist as you would with any git repository.\n",
      "\n",
      "*Happy hacking!*"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import matplotlib.pyplot as plt\n",
      "import datetime\n",
      "import urllib2, urllib\n",
      "import pandas as pd\n",
      "from StringIO import StringIO"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 18
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The following cell pulls the data using the API. In the meantime, Google has changed its terms and ways to access it, so this might not work."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Trick from http://stackoverflow.com/questions/7800213/can-i-use-pythons-csv-reader-with-google-fusion-tables\n",
      "\n",
      "request_url = 'https://www.googleapis.com/fusiontables/v1/query'\n",
      "query = 'SELECT * FROM 1KlX4PFF81wlx_TJ4zGudN_NoV_gq_GwrxuVau_M'\n",
      "\n",
      "url = \"%s?%s\" % (request_url, urllib.urlencode({'sql': query}))\n",
      "serv_req = urllib2.Request(url=url)\n",
      "serv_resp = urllib2.urlopen(serv_req)\n",
      "table = serv_resp.read()\n",
      "print '\\nLast pull of data from the Google FusionTable: ', datetime.datetime.now()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def parse_loc(loc, ret_lon=True):\n",
      "    try:\n",
      "        lon, lat = loc.split(',')\n",
      "        lon, lat = lon.strip(' '), lat.strip(' ')\n",
      "        lon, lat = map(float, [lon, lat])\n",
      "        if ret_lon:\n",
      "            return lon\n",
      "        else:\n",
      "            return lat\n",
      "    except:\n",
      "        return None"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "db = pd.read_csv(StringIO(table))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If you cannot pull the data using the API, an easy alternative is to export the table to a `csv` file manually and read it separately:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "db = pd.read_csv('/Users/dani/Desktop/Gaza and Israel incidents mapped.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "db['lon'] = db['Location (approximate)'].apply(lambda x: parse_loc(x))\n",
      "db['lat'] = db['Location (approximate)'].apply(lambda x: parse_loc(x, ret_lon=False))\n",
      "db['Date'] = db['Date'].apply(pd.to_datetime)\n",
      "db.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>Date</th>\n",
        "      <th>Day</th>\n",
        "      <th>Name of place</th>\n",
        "      <th>Location (approximate)</th>\n",
        "      <th>Details</th>\n",
        "      <th>Source url</th>\n",
        "      <th>Image url</th>\n",
        "      <th>Icon 1</th>\n",
        "      <th>lon</th>\n",
        "      <th>lat</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>2012-11-16</td>\n",
        "      <td>   Friday</td>\n",
        "      <td>                      Beit Lahia</td>\n",
        "      <td>     31.5515, 34.5089</td>\n",
        "      <td> Firefighters try to extinguish a fire at a fac...</td>\n",
        "      <td> http://www.guardian.co.uk/news/2012/nov/16/pic...</td>\n",
        "      <td> http://static.guim.co.uk/sys-images/Guardian/P...</td>\n",
        "      <td> placemark_circle_highlight</td>\n",
        "      <td> 31.551500</td>\n",
        "      <td> 34.508900</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2012-11-15</td>\n",
        "      <td> Thursday</td>\n",
        "      <td> Police Station in Deir al-Balah</td>\n",
        "      <td>     31.4205, 34.3513</td>\n",
        "      <td> Israeli aircraft also bombed a police station ...</td>\n",
        "      <td>                                             Wires</td>\n",
        "      <td>                                               NaN</td>\n",
        "      <td> placemark_circle_highlight</td>\n",
        "      <td> 31.420500</td>\n",
        "      <td> 34.351300</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>2012-11-15</td>\n",
        "      <td> Thursday</td>\n",
        "      <td>                     Beit Hanoun</td>\n",
        "      <td>     31.5382, 34.5380</td>\n",
        "      <td> Brothers Tareq Jamal Naser, 16, and Oday Jamal...</td>\n",
        "      <td> http://www.maannews.net/eng/ViewDetails.aspx?I...</td>\n",
        "      <td>                                               NaN</td>\n",
        "      <td> placemark_circle_highlight</td>\n",
        "      <td> 31.538200</td>\n",
        "      <td> 34.538000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>2012-11-15</td>\n",
        "      <td> Thursday</td>\n",
        "      <td>      Sheikh Radwan neighborhood</td>\n",
        "      <td> 31.536297, 34.465828</td>\n",
        "      <td> Violent explosions across Gaza City's Sheikh R...</td>\n",
        "      <td> http://www.maannews.net/eng/ViewDetails.aspx?I...</td>\n",
        "      <td>                                               NaN</td>\n",
        "      <td> placemark_circle_highlight</td>\n",
        "      <td> 31.536297</td>\n",
        "      <td> 34.465828</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>2012-11-15</td>\n",
        "      <td> Thursday</td>\n",
        "      <td>                        Tel Aviv</td>\n",
        "      <td>      32.0718, 34.777</td>\n",
        "      <td> Two rockets from Gaza crashed near Tel Aviv on...</td>\n",
        "      <td> http://www.guardian.co.uk/world/2012/nov/15/is...</td>\n",
        "      <td>                                               NaN</td>\n",
        "      <td> placemark_circle_highlight</td>\n",
        "      <td> 32.071800</td>\n",
        "      <td> 34.777000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "        Date       Day                    Name of place  \\\n",
        "0 2012-11-16    Friday                       Beit Lahia   \n",
        "1 2012-11-15  Thursday  Police Station in Deir al-Balah   \n",
        "2 2012-11-15  Thursday                      Beit Hanoun   \n",
        "3 2012-11-15  Thursday       Sheikh Radwan neighborhood   \n",
        "4 2012-11-15  Thursday                         Tel Aviv   \n",
        "\n",
        "  Location (approximate)                                            Details  \\\n",
        "0       31.5515, 34.5089  Firefighters try to extinguish a fire at a fac...   \n",
        "1       31.4205, 34.3513  Israeli aircraft also bombed a police station ...   \n",
        "2       31.5382, 34.5380  Brothers Tareq Jamal Naser, 16, and Oday Jamal...   \n",
        "3   31.536297, 34.465828  Violent explosions across Gaza City's Sheikh R...   \n",
        "4        32.0718, 34.777  Two rockets from Gaza crashed near Tel Aviv on...   \n",
        "\n",
        "                                          Source url  \\\n",
        "0  http://www.guardian.co.uk/news/2012/nov/16/pic...   \n",
        "1                                              Wires   \n",
        "2  http://www.maannews.net/eng/ViewDetails.aspx?I...   \n",
        "3  http://www.maannews.net/eng/ViewDetails.aspx?I...   \n",
        "4  http://www.guardian.co.uk/world/2012/nov/15/is...   \n",
        "\n",
        "                                           Image url  \\\n",
        "0  http://static.guim.co.uk/sys-images/Guardian/P...   \n",
        "1                                                NaN   \n",
        "2                                                NaN   \n",
        "3                                                NaN   \n",
        "4                                                NaN   \n",
        "\n",
        "                       Icon 1        lon        lat  \n",
        "0  placemark_circle_highlight  31.551500  34.508900  \n",
        "1  placemark_circle_highlight  31.420500  34.351300  \n",
        "2  placemark_circle_highlight  31.538200  34.538000  \n",
        "3  placemark_circle_highlight  31.536297  34.465828  \n",
        "4  placemark_circle_highlight  32.071800  34.777000  "
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "## Very basic descriptive analysis"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "+ Volume of incidents by day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "t = db['Date']\n",
      "t = t.reindex(t)\n",
      "by_day = t.groupby(lambda x: x.day).size()\n",
      "by_day.plot(kind='bar')\n",
      "plt.title('Number of events by day')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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ODxm85PCQwUuOyhtlC2/H/setvMewz4N/tcIcIiJu7UjzT48NAftVnEVERERE\nREREREREREREpH/8PzVSSxM/7DudAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x109683190>"
       ]
      }
     ],
     "prompt_number": 20
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "+ Location of events coloured by day"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "f = plt.figure(figsize=(10, 6))\n",
      "ax = f.add_subplot(111)\n",
      "x, y = db['lon'], db['lat']\n",
      "s = plt.scatter(x, y, marker='.', color='k')\n",
      "for d, day in db.set_index('Date').groupby(lambda x: x.day):\n",
      "    x, y = day['lon'], day['lat']\n",
      "    c = cm.Set1(d/30.)\n",
      "    s = plt.scatter(x, y, marker='^', color=c, label=str(d), s=20)\n",
      "ax.get_yaxis().set_visible(False)\n",
      "ax.get_xaxis().set_visible(False)\n",
      "plt.legend(loc=2)\n",
      "plt.title('Spatial distribution of events by day')\n",
      "ax.set_axis_bgcolor(\"0.2\") "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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kuyzJEAUeERER4O4bkvXeH3JcT6YeUpalaiTTFHhERKTbGzUoxciB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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10aa3c7d0>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# You'll need cartopy for a pretty map\n",
      "import cartopy.crs as ccrs\n",
      "import cartopy.io.img_tiles as cimgt\n",
      "import matplotlib.cm as cm"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "bg = cimgt.OSM()\n",
      "src = ccrs.PlateCarree()\n",
      "\n",
      "f = plt.figure(figsize=(20, 30))\n",
      "ax = plt.axes(projection=bg.crs)\n",
      "ax.add_image(bg, 9, alpha=0.5)\n",
      "\n",
      "x, y = db['lon'], db['lat']\n",
      "extent = [y.min(), y.max(), x.min(), 34]\n",
      "extent = [34, 36, x.min(), x.max()] #Manually tweaked\n",
      "for d, day in db.set_index('Date').groupby(lambda x: x.day):\n",
      "    y, x = day['lon'], day['lat']\n",
      "    c = cm.Set1(d/30.)\n",
      "    s = plt.scatter(x, y, marker='^', color=c, label=str(d), s=40, \\\n",
      "                    transform=src)\n",
      "ax.set_extent(extent, crs=src)\n",
      "plt.legend(loc=2)\n",
      "plt.title('Spatial distribution of events by day')\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",