NIJ EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import psycopg2\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "%matplotlib inline "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opened database successfully\n"
     ]
    }
   ],
   "source": [
    "# connect to postgres db on vb\n",
    "\n",
    "try:\n",
    "    conn = psycopg2.connect(database='vagrant', user='eruser', password = 'emergency', host='localhost', port='5432')\n",
    "    print(\"Opened database successfully\")\n",
    "    \n",
    "except psycopg2.Error as e:\n",
    "    print(\"I am unable to connect to the database\")\n",
    "    print(e)\n",
    "    print(e.pgcode)\n",
    "    print(e.pgerror)\n",
    "    print(traceback.format_exc())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SQL QUERY = SELECT census_tract, date_trunc('week', occ_date) AS week, count(*) AS num\n",
      "    FROM crimes\n",
      "    GROUP BY week, census_tract\n",
      "    ORDER BY week, census_tract;\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>census_tract</th>\n",
       "      <th>week</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>100.0</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>200.0</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>301.0</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>302.0</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>401.0</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   census_tract                      week  num\n",
       "0         100.0 2012-02-27 00:00:00+00:00   13\n",
       "1         200.0 2012-02-27 00:00:00+00:00   12\n",
       "2         301.0 2012-02-27 00:00:00+00:00    8\n",
       "3         302.0 2012-02-27 00:00:00+00:00    1\n",
       "4         401.0 2012-02-27 00:00:00+00:00   10"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''\n",
    "query psql to pull number of crimes by census track by week from 2012 - 2016\n",
    "inserts query result in pandas df called df2\n",
    "'''\n",
    "\n",
    "cur = conn.cursor()\n",
    "QUERY='''SELECT census_tract, date_trunc('week', occ_date) AS week, count(*) AS num\n",
    "    FROM crimes\n",
    "    GROUP BY week, census_tract\n",
    "    ORDER BY week, census_tract;'''\n",
    "\n",
    "try:\n",
    "    print(\"SQL QUERY = \"+QUERY)\n",
    "    cur.execute(QUERY)\n",
    "\n",
    "except Exception as e:\n",
    "    print(e.pgerror)\n",
    "    \n",
    "# Extract the column names and insert them in header\n",
    "col_names = []\n",
    "for elt in cur.description:\n",
    "    col_names.append(elt[0])    \n",
    "    \n",
    "D = cur.fetchall() #convert query result to list\n",
    "#pprint(D)\n",
    "df = pd.DataFrame(D) #convert to pandas df\n",
    "#conn.close()\n",
    "df.head() # print the df head\n",
    "\n",
    "\n",
    "# Create the dataframe, passing in the list of col_names extracted from the description\n",
    "df2 = pd.DataFrame(D, columns=col_names)\n",
    "df2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#conn.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 37559 entries, 0 to 37558\n",
      "Data columns (total 3 columns):\n",
      "census_tract    37310 non-null float64\n",
      "week            37559 non-null datetime64[ns, psycopg2.tz.FixedOffsetTimezone(offset=0, name=None)]\n",
      "num             37559 non-null int64\n",
      "dtypes: datetime64[ns, psycopg2.tz.FixedOffsetTimezone(offset=0, name=None)](1), float64(1), int64(1)\n",
      "memory usage: 880.4 KB\n"
     ]
    }
   ],
   "source": [
    "df2.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>census_tract</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>10600.0</td>\n",
       "      <td>42243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>5100.0</td>\n",
       "      <td>33976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>8100.0</td>\n",
       "      <td>20417</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>9000.0</td>\n",
       "      <td>15897</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2303.0</td>\n",
       "      <td>15784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>8301.0</td>\n",
       "      <td>14877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2100.0</td>\n",
       "      <td>14727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>8202.0</td>\n",
       "      <td>14648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1101.0</td>\n",
       "      <td>14334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2402.0</td>\n",
       "      <td>12184</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>9201.0</td>\n",
       "      <td>12139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>601.0</td>\n",
       "      <td>11364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>7202.0</td>\n",
       "      <td>11132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1701.0</td>\n",
       "      <td>10617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>502.0</td>\n",
       "      <td>10415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>7300.0</td>\n",
       "      <td>10368</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>4001.0</td>\n",
       "      <td>10283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>9101.0</td>\n",
       "      <td>9940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>5200.0</td>\n",
       "      <td>9648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>602.0</td>\n",
       "      <td>9439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>5000.0</td>\n",
       "      <td>9135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>9701.0</td>\n",
       "      <td>9045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>4101.0</td>\n",
       "      <td>8940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>8201.0</td>\n",
       "      <td>8923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>5600.0</td>\n",
       "      <td>8797</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     census_tract    num\n",
       "168       10600.0  42243\n",
       "80         5100.0  33976\n",
       "117        8100.0  20417\n",
       "129        9000.0  15897\n",
       "35         2303.0  15784\n",
       "120        8301.0  14877\n",
       "33         2100.0  14727\n",
       "119        8202.0  14648\n",
       "17         1101.0  14334\n",
       "37         2402.0  12184\n",
       "132        9201.0  12139\n",
       "8           601.0  11364\n",
       "107        7202.0  11132\n",
       "27         1701.0  10617\n",
       "7           502.0  10415\n",
       "108        7300.0  10368\n",
       "67         4001.0  10283\n",
       "130        9101.0   9940\n",
       "81         5200.0   9648\n",
       "9           602.0   9439\n",
       "79         5000.0   9135\n",
       "143        9701.0   9045\n",
       "69         4101.0   8940\n",
       "118        8201.0   8923\n",
       "83         5600.0   8797"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# look at number of crimes by census track\n",
    "grouped_by_ct = df2.groupby('census_tract')['num'].sum().reset_index() # total crimes by census tract, resets index\n",
    "grouped_by_ct.sort_values('num', ascending=False)[:25] # sort by num descending, show top 25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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88847KC4uxqVLl/DFF19g6dKliIiIQGBgIIDbJ+MqFAokJyfjzJkzyMvLQ3Z2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\nk4MlMAwGg8FgMJocLIFhMBgMBoPR5Pg/0MXkHLo7KFgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6d0d1048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# barchart of top 25 census tracks with highest total crime\n",
    "top_25 = grouped_by_ct.sort_values('num', ascending=False)[:25]\n",
    "sns.set_style(\"whitegrid\")\n",
    "top_25_barplot = sns.barplot(x= top_25['census_tract'],y = top_25['num'], order = top_25['census_tract'], )\n",
    "for item in top_25_barplot.get_xticklabels():\n",
    "    item.set_rotation(90) # rotates x axis labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Census tracts 10600, 5100, and 8100 have significantly higher total number of crimes from 2012-November 2016."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "median crimes/tract = 2533.0\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>census_tract</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>235.000000</td>\n",
       "      <td>235.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>16060.055319</td>\n",
       "      <td>3650.965957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>64148.953564</td>\n",
       "      <td>5020.966842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3602.500000</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8100.000000</td>\n",
       "      <td>2533.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>21050.000000</td>\n",
       "      <td>5517.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>980000.000000</td>\n",
       "      <td>42243.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        census_tract           num\n",
       "count     235.000000    235.000000\n",
       "mean    16060.055319   3650.965957\n",
       "std     64148.953564   5020.966842\n",
       "min       100.000000      1.000000\n",
       "25%      3602.500000      5.000000\n",
       "50%      8100.000000   2533.000000\n",
       "75%     21050.000000   5517.500000\n",
       "max    980000.000000  42243.000000"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# some summary stats\n",
    "print('median crimes/tract = '+str(grouped_by_ct['num'].median()))\n",
    "grouped_by_ct.describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>census_tract</th>\n",
       "      <th>week</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>10600.0</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>10600.0</td>\n",
       "      <td>2012-03-05 00:00:00+00:00</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>441</th>\n",
       "      <td>10600.0</td>\n",
       "      <td>2012-03-12 00:00:00+00:00</td>\n",
       "      <td>166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>591</th>\n",
       "      <td>10600.0</td>\n",
       "      <td>2012-03-19 00:00:00+00:00</td>\n",
       "      <td>122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>740</th>\n",
       "      <td>10600.0</td>\n",
       "      <td>2012-03-26 00:00:00+00:00</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     census_tract                      week  num\n",
       "141       10600.0 2012-02-27 00:00:00+00:00   79\n",
       "291       10600.0 2012-03-05 00:00:00+00:00  153\n",
       "441       10600.0 2012-03-12 00:00:00+00:00  166\n",
       "591       10600.0 2012-03-19 00:00:00+00:00  122\n",
       "740       10600.0 2012-03-26 00:00:00+00:00  137"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's look at census tract 10600 in greater detail\n",
    "\n",
    "df2[df2['census_tract'] == 10600.0].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f5d6af82b38>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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E0T0wg9+90qOFRWnC5ncL46KAQEmhNnfiPQmVNXGWAmS1KMvlbQyTDbKsIJzuRFgNRK2U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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6af9ccf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ct_by_week_1 = df2[df2['census_tract'] == 10600.0]\n",
    "#ct_by_week_1_series = pd.Series(ct_by_week_1['num'], index = ct_by_week_1['week'])\n",
    "plot1 = ct_by_week_1.loc[:,['week', 'num']].plot()\n",
    "plot1.set_xlabel(\"week\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5d6af09a58>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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BBjKbxaTIOaivceBrn5VEwfWXrMOVF61CpdOqu4+xoCcSCkmMNAhSLkOm5MWB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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6aed6390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2[df2['census_tract'] == 5100.0].loc[:,['week', 'num']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5d6ae7f208>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UVjOvq56Noq2tDcl4FACQSGVw5PgJAEZQYiSgYCQB9PQNoK3Nuu6DxYG2kEva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\nBKELiQSCIAiCIHT5/wEHDBWL6iKHvgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6ae87358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2[df2['census_tract'] == 8100.0].loc[:,['week', 'num']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5d6adeee80>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Cj4iIiFiCQo+IiIhYgkKPiIiIWIJCj4iIiFiCQo+IiIhYgkKPiIiIWIJCj4iIiFiCQo+I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\nS9v6txIAgm1B3H7TwMAWI+0yYlA0L/7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+v8sZOaCsrCz68ssvacOGDRQaGmox32w2U3x8\nPC1YsICqqqooPz+fJkyYQBkZGULM+fPnSaVS0SeffEK1tbWUk5ND48aNo99//12IUavV5O/vT/v2\n7aOamhp6//33KTQ0lJqamoSYdevWUUxMDBUXF1NFRQXNmTOHXnrppZ5NQC+yJQcDxZEjRygzM5N+\n+eUXksvl9Ouvv4rmb9u2jUJDQykvL4+qq6tp8eLFNHHiRDIajUJMUlISTZ8+nUpLS+nEiRM0adIk\nWrFihTDfYDBQZGQkrVq1impqakitVlNgYCB9++23Qswff/xB48aNo507d1JtbS1t3ryZFAoFnTlz\npueT0EULFy4Ujo2qqipatGgRxcTE0PXr14UYa32kN/urvTh8+DAdOXKE6urqqK6ujjIyMkihUFBN\nTQ0Rcc6s0Wg0FBsbS88//zylpaUJz3PeLGVlZVF8fDw1NTWRVqslrVZLly9fFub3t5w5ZNFzy969\nezssen777TcaN26cKJl79uyhkJAQam1tJSKi9PR0io+PFy23bNkyWrhwoTA9a9Ys+vDDD4XptrY2\nio6OpuzsbCJqfwNTKBR06NAhIaa2tpZ8fX1Jo9F0z072MWs5GKh8fX0tip7IyEjatWuXMG0wGEip\nVJJarSYiopqaGvL19aWKigohJj8/n/z8/Oiff/4hIqLc3FwKCwsTjkMioo0bN9KUKVOE6XfeeYfe\neOMN0bpnz55NycnJ3bV7PaapqYl8fX2ppKSEiGzrI73VX+1dWFgYfffdd5wzK5qbm2nSpEl09OhR\neuWVV4Sih/PWsaysLJo+fXqH8/pjzhzy6y1rNBoNxo4dKxqPKyoqCgaDATU1NUJMRESEaLmoqCic\nPHkSANDa2oqKigphDDIAkEgkiIiIEGLKyspgNptFMaNHj8aIESPw559/9tj+9RZbcuAozp8/D61W\niwkTJgjPDR06FIGBgUIuTp48CVdXV2FQXQCIiIiARCKBRqMB0H7chYaGwsnpf2MFR0VF4ezZszAY\nDEI7nR2b9sxgMEAikeDhhx8GAJSXl1vtI73VX+1VW1sb1Go1rl+/DpVKxTmzIiUlBbGxsaLtBmx7\nPXbUvNXV1SE6OhpPP/00Vq5ciQsXLgDon/2Ti54OaLVai5HU3d3dAQCNjY3C3ztjhg0bhubmZphM\nJly+fBlms1lY7vYYrVYLAGhqaoJMJrMYcfb2mP7Mlhw4Cq1WC4lE0mkutFqtxcC3UqkUrq6uohhb\njs3+mHMiQlpaGoKDgzFmzBgA7ftrrY/0Vn+1N6dPn0ZQUBCUSiXWr1+PrVu3wsfHh3PWCbVajcrK\nSixfvtxini2vx46Yt8DAQGzYsAFffPEF1q9fj/r6eiQkJODatWv98lhzsh7SP3z66afYvn37XedL\nJBL89NNP8Pb2vq/1SCSS+1qeiKy2YUtMfzbQ968ruuN4oPavqa3G2LsPPvgANTU1+Oqrr6zG2noM\n9UZ/7SujR4/GDz/8AL1ej0OHDuHdd99FTk7OXeMdPWcXL15EWloadu7cCZlMZvNyjp632wfkHjt2\nrHADxYEDBzBkyJAOl7HnnA2YomfBggWYOXNmpzEjR460qS13d3eUlZWJnrtVTd6qND08PCyuUG9q\nasLQoUMxePBguLm5QSqVWlShOp1OqGjd3d3R2tqK5uZmUaV8e0x/ZksOHIW7uzuICFqtVvRpRafT\nwc/PT4jR6XSi5cxmM/R6vbCMu7t7h8fd7WeRPDw8Osz5nZ+S7ElKSgry8/ORm5sLT09P4Xlb+khv\n9Vd74+TkJLymKRQKlJaWYvfu3ZgyZQrnrAPl5eXQ6XR44YUXhA8BZrMZx48fR25uLrZv3w6TycR5\ns8LFxQVeXl44d+4cwsPD+92xNmC+3nJzc4O3t3enj9uvg+iMSqXC6dOnRW9ABQUFcHFxgY+PjxBT\nWFgoWq6goAAqlQoAIJPJoFAoRDFEhMLCQgQFBQEA/P39IZVKRTFnz55FQ0ODENOf2ZIDRzFy5Ei4\nu7ujqKhIeK65uRkajUbIhUqlgl6vx6lTp4SYwsJCEBECAgKEmJKSEpjNZiGmoKAA3t7ecHFxEWI6\nOzbtTUpKCvLy8rB7926MGDFCNM+WPtJb/dXetbW1wWQycc7uIiIiAj/++CO+//577N+/H/v374e/\nvz+mTZuG/fv3Q6lUwsnJifNmRUtLC86fP4/hw4f3z2OtS5c9DxANDQ1UWVlJWVlZNH78eKqsrKTK\nykpqaWkhovZb7KZOnUpJSUlUWVlJ+fn5FB4eTps2bRLauHWLXXp6unCLnUKhoIKCAiFGrVaTUqkU\n3WIXFhYmuoo9OTmZYmJiqKioiMrKygbkLevWcjBQtLS0UGVlJZ06dYp8fX1p165dVFlZSQ0NDURE\nlJ2dTWFhYZSXl0dVVVW0ePFiiouLE92yvnDhQpoxYwZpNBo6fvw4TZo0iVauXCnMv/2W9TNnzpBa\nrSaVSmVxy7pCoRBuWd+yZQv5+/vb5S3rycnJFBISQiUlJdTY2Cg8/v33X1FMZ32kN/urvcjIyKCS\nkhKqr6+n6upq2rhxI/n5+dHRo0eJiHNmq9vv3iLivHVkw4YNdOzYMaqvr6cTJ07Qa6+9RuHh4aTT\n6Yio/+XMIYue1atXk1wut3gcO3ZMiGloaKBFixaRSqWi8PBwSk9PJ7PZLGqnuLiYZsyYQUqlkuLi\n4mjfvn0W68rJyaGYmBhSKpU0e/ZsKi0tFc03Go2UkpJCYWFhpFKpaMmSJaTVantmx/uItRwMFMXF\nxeTr62txXK1evVqI2bJlC0VGRlJAQAAtWLCA6urqRG1cvXqVVqxYQePHj6eQkBBas2YNXbt2TRRT\nVVVFCQkJFBAQQE899RTt2LHDYlsOHjxIkydPJqVSSfHx8ZSfn98zO32fOsqXXC4X9SVb+khv9Vd7\n8d5771FsbCwplUqKiIig+fPnCwUPEefMVomJiaKih/NmadmyZRQdHU1KpZKeeuopWr58OZ07d06Y\n399yJiHqB1c4MsYYY4zdpwFzTQ9jjDHGWGe46GGMMcaYQ+CihzHGGGMOgYsexhhjjDkELnoYY4wx\n5hC46GGMMcaYQ+CihzHGGGMOgYsexhhjjDkELnoYY4wx5hC46GGMMcaYQ+CihzHGGGMOgYsexhhj\njDkELnoYY3Zn9erVmDp1Ko4dO4YZM2YgKCgIs2bNQkVFBQDg77//hlwux6FDh0TLpaamIjY2Vpje\nu3cv5HI5ysvLkZSUBJVKhWeeeQaFhYUgImRmZiIyMhKRkZHIyMjo1X1kjPU+LnoYY3ZHIpGgsbER\nqampeP3115GZmQmj0YglS5bAbDZ3upxEIhFNA+1FVExMDD777DN4enri7bffRmpqKi5duoT09HQk\nJCQgOzsbarW6x/eNMdZ3nPp6AxhjrCN6vR65ubnw8fEBADg7O+PVV1+FRqOBp6dnl9pKTEzEnDlz\nAADDhw/H1KlTUV5ejq+//hoAEBkZiby8PBw8eBDPPfdc9+4IY8xu8JkexphdGj58uFDwAMCYMWNA\nRLh48WKX2pFIJIiIiBCmvby8AADh4eGiOC8vL1y4cOHeN5gxZve46GGM2SUXFxfRtEwmAwCYTKb7\nautWOw899JAoZvDgwTAajV1umzHWf3DRwxjrd4YMGQIAaG1tFT1/9erVvtgcxlg/wUUPY6zfGTZs\nGGQyGWpra4XnTCYTSkpK+nCrGGP2ji9kZoz1OxKJBHFxccjNzcV///tfuLm5IScnp683izFm5/hM\nD2PMLt1+63lHz61duxZhYWFITU1FcnIynnzyScTFxdnctrX2GWMDj4SIqK83gjHGGGOsp/GZHsYY\nY4w5BC56GGOMMeYQuOhhjDHGmEPgoocxxhhjDoGLHsYYY4w5BC56GGOMMeYQuOhhjDHGmEPgoocx\nxhhjDoGLHsYYY4w5BC56GGOMMeYQuOhhjDHGmEP4f/4tPHpFtMAIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d9c4bcac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(grouped_by_ct['num'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The mean is notably higher than the median which suggests a right skewed distribution with outliers on the high side."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>census_tract</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>22107.0</td>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>9604.0</td>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>30600.0</td>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>9605.0</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>9801.0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>10410.0</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>30501.0</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>30200.0</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>22201.0</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>10100.0</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>10407.0</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>9603.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>10303.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>21802.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>10408.0</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>10411.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>10002.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>9907.0</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>10304.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>10305.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>22702.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>9905.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>10409.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>20304.0</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>22108.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>30801.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>10402.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>9904.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>10405.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>32005.0</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>21500.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>33000.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>40302.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>40411.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>41105.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>31812.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>41110.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>21100.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>41327.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>42300.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>42500.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>20503.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>31907.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>31617.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>23201.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>22101.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>31611.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>31509.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>31403.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>31300.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>31200.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>31003.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>22103.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>10306.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>30700.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>22602.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>22707.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>22710.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>20303.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>30401.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>75 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     census_tract  num\n",
       "186       22107.0   29\n",
       "140        9604.0   28\n",
       "206       30600.0   25\n",
       "141        9605.0   20\n",
       "145        9801.0   18\n",
       "166       10410.0   18\n",
       "204       30501.0   17\n",
       "200       30200.0   16\n",
       "188       22201.0   13\n",
       "155       10100.0    8\n",
       "163       10407.0    7\n",
       "139        9603.0    6\n",
       "157       10303.0    6\n",
       "183       21802.0    6\n",
       "164       10408.0    6\n",
       "167       10411.0    5\n",
       "154       10002.0    5\n",
       "152        9907.0    5\n",
       "158       10304.0    4\n",
       "159       10305.0    4\n",
       "193       22702.0    4\n",
       "150        9905.0    4\n",
       "165       10409.0    4\n",
       "171       20304.0    4\n",
       "187       22108.0    3\n",
       "208       30801.0    3\n",
       "161       10402.0    3\n",
       "149        9904.0    3\n",
       "162       10405.0    3\n",
       "221       32005.0    3\n",
       "..            ...  ...\n",
       "180       21500.0    1\n",
       "223       33000.0    1\n",
       "224       40302.0    1\n",
       "225       40411.0    1\n",
       "227       41105.0    1\n",
       "218       31812.0    1\n",
       "228       41110.0    1\n",
       "176       21100.0    1\n",
       "230       41327.0    1\n",
       "231       42300.0    1\n",
       "232       42500.0    1\n",
       "172       20503.0    1\n",
       "219       31907.0    1\n",
       "217       31617.0    1\n",
       "196       23201.0    1\n",
       "184       22101.0    1\n",
       "215       31611.0    1\n",
       "214       31509.0    1\n",
       "213       31403.0    1\n",
       "212       31300.0    1\n",
       "211       31200.0    1\n",
       "210       31003.0    1\n",
       "185       22103.0    1\n",
       "160       10306.0    1\n",
       "207       30700.0    1\n",
       "191       22602.0    1\n",
       "194       22707.0    1\n",
       "195       22710.0    1\n",
       "170       20303.0    1\n",
       "202       30401.0    1\n",
       "\n",
       "[75 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# which census tracts have the lowest amount of crime?\n",
    "grouped_by_ct.sort_values('num', ascending=False)[-75:] # sort by num descending, show top 25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 51 census tracts with 3 or fewer crimes\n"
     ]
    }
   ],
   "source": [
    "low_75 = grouped_by_ct.sort_values('num', ascending=False)[-75:] \n",
    "n = sum([1 for x in low_75['num'] if x <= 3])\n",
    "\n",
    "print('there are {} census tracts with 3 or fewer crimes'.format(n))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5d6ad7c5c0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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i1QIAAE/4/X/BCwsLtWfPHg0YMEAvvPCCTp48qRUrVuj06dNatWqVvzffI4mtum+WlFXr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\nLwsOhwAAQoHXKxb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xxmRnZ5uZM2eaP//5z+bjjz/u8JKpa6+91tx5553m0KFDZvv27Wba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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6ad43208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#let's visualize what weekly crime trends for one of those \"few crime\" tracts look like\n",
    "df2[df2['census_tract'] == 22107.0].loc[:,['week', 'num']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/vagrant/miniconda3/lib/python3.5/site-packages/matplotlib/axes/_base.py:2782: UserWarning: Attempting to set identical left==right results\n",
      "in singular transformations; automatically expanding.\n",
      "left=6797.0, right=6797.0\n",
      "  'left=%s, right=%s') % (left, right))\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5d6ac9b080>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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MUBoAAIARSgMAADBCaQAAAEYoDQAAwAilAQAAGKE0AAAAI5QGAABghNIAAACMUBoAAIAR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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6acf29e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df2[df2['census_tract'] == 21500.0].loc[:,['week', 'num']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SQL QUERY = SELECT DISTINCT case_desc \n",
      "    FROM crimes\n",
      "    ORDER BY case_desc;\n",
      "100\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case_desc</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ACCIDENT - HIT AND RUN - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ACCIDENT - HIT &amp; RUN - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ACCIDENT - INJURY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACCIDENT - NON INJURY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACCIDENT - UNKNOWN INJURY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ANIMAL PROBLEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ANIMAL PROBLEM - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AREA CHECK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ASSAULT - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ASSAULT - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ASSAULT - WITH WEAPON *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ASSISTANCE - FIRE / EMS NEED POLICE *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ASSISTANCE - RESPONDER EMERGENCY *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ASSIST - CITIZEN OR AGENCY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>BOMB - DEVICE DISCOVERED (33B) *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>BOMB OR CHEM POLICE INVESTIGATION (33B/33C)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>BOMB - THREAT (33B)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>BURGLARY - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>BURGLARY - PRIORITY *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>CHEMICAL OR BIOLOGICAL (33C)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>CHEMICAL OR BIOLOGICAL THREAT (33CTH)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>CIVIL - CIVIL PROBLEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>CIVIL - EVICTION</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>CIVIL - PROPERTY SEIZURE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>CIVIL - SERVE PAPERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>CIVIL - STANDBY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>DELIVER MESSAGE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>DETOX TRANSPORT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>DISTURBANCE - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>DISTURBANCE - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>STABBING - WITH WEAPON *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>SUBJECT STOP - SDC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>SUSPICIOUS - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>SUSPICIOUS SUBJ, VEH, OR CIRCUMSTANCE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>SUSPICIOUS - WITH WEAPON *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>THEFT - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>THEFT - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>THEFT - SUBJECT IN CUSTODY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>THREAT - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>THREAT - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>THREAT - WITH WEAPON *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>TRAFFIC PURSUIT *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>TRAFFIC STOP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>TRANSPORT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>TRIMET INCIDENT - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>TRIMET INCIDENT - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>TRIMET INCIDENT - WITH WEAPON *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>UNWANTED PERSON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>UNWANTED PERSON - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>UNWANTED PERSON - WITH WEAPON *H</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>VANDALISM - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>VANDALISM - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>VEHICLE RECOVERED</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>VEHICLE STOLEN - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>VEHICLE STOLEN - PRIORITY</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>VICE-DRUGS, LIQUOR, PROSTITUTION, GAMBLING</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>WARRANT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>WARRANT - WALK-IN / COUNTER</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>WELFARE CHECK - COLD</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>WELFARE CHECK - PRIORITY</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      case_desc\n",
       "0   ACCIDENT - HIT AND RUN - COLD              \n",
       "1   ACCIDENT - HIT & RUN - PRIORITY            \n",
       "2   ACCIDENT - INJURY                          \n",
       "3   ACCIDENT - NON INJURY                      \n",
       "4   ACCIDENT - UNKNOWN INJURY                  \n",
       "5   ANIMAL PROBLEM                             \n",
       "6   ANIMAL PROBLEM - PRIORITY                  \n",
       "7   AREA CHECK                                 \n",
       "8   ASSAULT - COLD                             \n",
       "9   ASSAULT - PRIORITY                         \n",
       "10  ASSAULT - WITH WEAPON *H                   \n",
       "11  ASSISTANCE - FIRE / EMS NEED POLICE *H     \n",
       "12  ASSISTANCE - RESPONDER EMERGENCY *H        \n",
       "13  ASSIST - CITIZEN OR AGENCY                 \n",
       "14  BOMB - DEVICE DISCOVERED (33B) *H          \n",
       "15  BOMB OR CHEM POLICE INVESTIGATION (33B/33C)\n",
       "16  BOMB - THREAT (33B)                        \n",
       "17  BURGLARY - COLD                            \n",
       "18  BURGLARY - PRIORITY *H                     \n",
       "19  CHEMICAL OR BIOLOGICAL (33C)               \n",
       "20  CHEMICAL OR BIOLOGICAL THREAT (33CTH)      \n",
       "21  CIVIL - CIVIL PROBLEM                      \n",
       "22  CIVIL - EVICTION                           \n",
       "23  CIVIL - PROPERTY SEIZURE                   \n",
       "24  CIVIL - SERVE PAPERS                       \n",
       "25  CIVIL - STANDBY                            \n",
       "26  DELIVER MESSAGE                            \n",
       "27  DETOX TRANSPORT                            \n",
       "28  DISTURBANCE - COLD                         \n",
       "29  DISTURBANCE - PRIORITY                     \n",
       "..                                          ...\n",
       "70  STABBING - WITH WEAPON *H                  \n",
       "71  SUBJECT STOP - SDC                         \n",
       "72  SUSPICIOUS - PRIORITY                      \n",
       "73  SUSPICIOUS SUBJ, VEH, OR CIRCUMSTANCE      \n",
       "74  SUSPICIOUS - WITH WEAPON *H                \n",
       "75  THEFT - COLD                               \n",
       "76  THEFT - PRIORITY                           \n",
       "77  THEFT - SUBJECT IN CUSTODY                 \n",
       "78  THREAT - COLD                              \n",
       "79  THREAT - PRIORITY                          \n",
       "80  THREAT - WITH WEAPON *H                    \n",
       "81  TRAFFIC PURSUIT *H                         \n",
       "82  TRAFFIC STOP                               \n",
       "83  TRANSPORT                                  \n",
       "84  TRIMET INCIDENT - COLD                     \n",
       "85  TRIMET INCIDENT - PRIORITY                 \n",
       "86  TRIMET INCIDENT - WITH WEAPON *H           \n",
       "87  UNWANTED PERSON                            \n",
       "88  UNWANTED PERSON - PRIORITY                 \n",
       "89  UNWANTED PERSON - WITH WEAPON *H           \n",
       "90  VANDALISM - COLD                           \n",
       "91  VANDALISM - PRIORITY                       \n",
       "92  VEHICLE RECOVERED                          \n",
       "93  VEHICLE STOLEN - COLD                      \n",
       "94  VEHICLE STOLEN - PRIORITY                  \n",
       "95  VICE-DRUGS, LIQUOR, PROSTITUTION, GAMBLING \n",
       "96  WARRANT                                    \n",
       "97  WARRANT - WALK-IN / COUNTER                \n",
       "98  WELFARE CHECK - COLD                       \n",
       "99  WELFARE CHECK - PRIORITY                   \n",
       "\n",
       "[100 rows x 1 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# how many types of crime in db?\n",
    "cur = conn.cursor()\n",
    "QUERY='''SELECT DISTINCT case_desc \n",
    "    FROM crimes\n",
    "    ORDER BY case_desc;'''\n",
    "    \n",
    "try:\n",
    "    print(\"SQL QUERY = \"+QUERY)\n",
    "    cur.execute(QUERY)\n",
    "\n",
    "except Exception as e:\n",
    "    print(e.pgerror)    \n",
    "\n",
    "# Extract the column names and insert them in header\n",
    "col_names = []\n",
    "for elt in cur.description:\n",
    "    col_names.append(elt[0])    \n",
    "    \n",
    "D = cur.fetchall() #convert query result to list\n",
    "#pprint(D)\n",
    "\n",
    "# Create the dataframe, passing in the list of col_names extracted from the description\n",
    "df4 = pd.DataFrame(D, columns=col_names)\n",
    "print(len(df4))\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SQL QUERY = SELECT  case_desc, date_trunc('week', occ_date) AS week, count(*) AS num\n",
      "    FROM crimes\n",
      "    GROUP BY week, case_desc\n",
      "    ORDER BY week, case_desc;\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case_desc</th>\n",
       "      <th>week</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ACCIDENT - HIT AND RUN - COLD</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ACCIDENT - HIT &amp; RUN - PRIORITY</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ACCIDENT - INJURY</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACCIDENT - NON INJURY</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ACCIDENT - UNKNOWN INJURY</td>\n",
       "      <td>2012-02-27 00:00:00+00:00</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     case_desc                      week  num\n",
       "0  ACCIDENT - HIT AND RUN - COLD               2012-02-27 00:00:00+00:00   32\n",
       "1  ACCIDENT - HIT & RUN - PRIORITY             2012-02-27 00:00:00+00:00   19\n",
       "2  ACCIDENT - INJURY                           2012-02-27 00:00:00+00:00   30\n",
       "3  ACCIDENT - NON INJURY                       2012-02-27 00:00:00+00:00   66\n",
       "4  ACCIDENT - UNKNOWN INJURY                   2012-02-27 00:00:00+00:00   12"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# try aggregating by crime type\n",
    "\n",
    "'''\n",
    "query psql to pull number of crimes by case_desc by week from 2012 - 2016\n",
    "inserts query result in pandas df called df3\n",
    "'''\n",
    "\n",
    "cur = conn.cursor()\n",
    "QUERY='''SELECT  case_desc, date_trunc('week', occ_date) AS week, count(*) AS num\n",
    "    FROM crimes\n",
    "    GROUP BY week, case_desc\n",
    "    ORDER BY week, case_desc;'''\n",
    "\n",
    "\n",
    "try:\n",
    "    print(\"SQL QUERY = \"+QUERY)\n",
    "    cur.execute(QUERY)\n",
    "\n",
    "except Exception as e:\n",
    "    print(e.pgerror)\n",
    "    \n",
    "# Extract the column names and insert them in header\n",
    "col_names = []\n",
    "for elt in cur.description:\n",
    "    col_names.append(elt[0])    \n",
    "    \n",
    "D = cur.fetchall() #convert query result to list\n",
    "#pprint(D)\n",
    "\n",
    "# Create the dataframe, passing in the list of col_names extracted from the description\n",
    "df3 = pd.DataFrame(D, columns=col_names)\n",
    "df3.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 17036 entries, 0 to 17035\n",
      "Data columns (total 3 columns):\n",
      "case_desc    17036 non-null object\n",
      "week         17036 non-null datetime64[ns, psycopg2.tz.FixedOffsetTimezone(offset=0, name=None)]\n",
      "num          17036 non-null int64\n",
      "dtypes: datetime64[ns, psycopg2.tz.FixedOffsetTimezone(offset=0, name=None)](1), int64(1), object(1)\n",
      "memory usage: 399.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df3.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ACCIDENT - HIT AND RUN - COLD              \n",
      "ACCIDENT - HIT & RUN - PRIORITY            \n",
      "ACCIDENT - INJURY                          \n",
      "ACCIDENT - NON INJURY                      \n",
      "ACCIDENT - UNKNOWN INJURY                  \n",
      "ANIMAL PROBLEM                             \n",
      "ANIMAL PROBLEM - PRIORITY                  \n",
      "AREA CHECK                                 \n",
      "ASSAULT - COLD                             \n",
      "ASSAULT - PRIORITY                         \n",
      "ASSAULT - WITH WEAPON *H                   \n",
      "ASSIST - CITIZEN OR AGENCY                 \n",
      "BOMB - DEVICE DISCOVERED (33B) *H          \n",
      "BOMB - THREAT (33B)                        \n",
      "BURGLARY - COLD                            \n",
      "BURGLARY - PRIORITY *H                     \n",
      "CIVIL - CIVIL PROBLEM                      \n",
      "CIVIL - STANDBY                            \n",
      "DELIVER MESSAGE                            \n",
      "DETOX TRANSPORT                            \n",
      "DISTURBANCE - COLD                         \n",
      "DISTURBANCE - PRIORITY                     \n",
      "DISTURBANCE - WITH WEAPON *H               \n",
      "DRIVING UNDER INFLUENCE                    \n",
      "FOLLOW-UP                                  \n",
      "FRAUD - COLD                               \n",
      "HAZARD - HAZARDOUS CONDITION               \n",
      "HAZARD - WRONG-WAY DRIVER *H               \n",
      "ILLEGAL DUMPING - COLD                     \n",
      "NOISE DISTURBANCE                          \n",
      "PARKING PROBLEM                            \n",
      "PARTY DISTURBANCE                          \n",
      "PREMISE CHECK                              \n",
      "PROPERTY LOST, FOUND, RECOVERED            \n",
      "PROWLER                                    \n",
      "RIVER - MARINE INCIDENT                    \n",
      "ROBBERY - COLD                             \n",
      "ROBBERY - PRIORITY *H                      \n",
      "SCHOOL INCIDENT - COLD                     \n",
      "SCHOOL INCIDENT - PRIORITY                 \n",
      "SHOTS FIRED                                \n",
      "SUSPICIOUS - PRIORITY                      \n",
      "SUSPICIOUS SUBJ, VEH, OR CIRCUMSTANCE      \n",
      "SUSPICIOUS - WITH WEAPON *H                \n",
      "THEFT - COLD                               \n",
      "THEFT - PRIORITY                           \n",
      "THREAT - COLD                              \n",
      "THREAT - PRIORITY                          \n",
      "THREAT - WITH WEAPON *H                    \n",
      "TRIMET INCIDENT - COLD                     \n",
      "TRIMET INCIDENT - PRIORITY                 \n"
     ]
    }
   ],
   "source": [
    "# another way to look at the crime types\n",
    "for i, crime in df3.iterrows():\n",
    "    print(crime['case_desc'])\n",
    "    if i == 50:\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>case_desc</th>\n",
       "      <th>num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>DISTURBANCE - PRIORITY</td>\n",
       "      <td>97361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>UNWANTED PERSON</td>\n",
       "      <td>90922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>SUSPICIOUS SUBJ, VEH, OR CIRCUMSTANCE</td>\n",
       "      <td>55560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>WELFARE CHECK - PRIORITY</td>\n",
       "      <td>55481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>THEFT - COLD</td>\n",
       "      <td>51437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>WELFARE CHECK - COLD</td>\n",
       "      <td>49273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>HAZARD - HAZARDOUS CONDITION</td>\n",
       "      <td>28296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AREA CHECK</td>\n",
       "      <td>28106</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>NOISE DISTURBANCE</td>\n",
       "      <td>28099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ASSIST - CITIZEN OR AGENCY</td>\n",
       "      <td>28093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACCIDENT - NON INJURY</td>\n",
       "      <td>26047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>THEFT - PRIORITY</td>\n",
       "      <td>23469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>VEHICLE STOLEN - COLD</td>\n",
       "      <td>22255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>SUSPICIOUS - PRIORITY</td>\n",
       "      <td>20892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>BURGLARY - COLD</td>\n",
       "      <td>17733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>PREMISE CHECK</td>\n",
       "      <td>16504</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ASSAULT - PRIORITY</td>\n",
       "      <td>15171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ACCIDENT - HIT AND RUN - COLD</td>\n",
       "      <td>14842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>VICE-DRUGS, LIQUOR, PROSTITUTION, GAMBLING</td>\n",
       "      <td>14280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>FOLLOW-UP</td>\n",
       "      <td>13879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>PROPERTY LOST, FOUND, RECOVERED</td>\n",
       "      <td>13394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ACCIDENT - INJURY</td>\n",
       "      <td>12899</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>THREAT - COLD</td>\n",
       "      <td>12376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>CIVIL - CIVIL PROBLEM</td>\n",
       "      <td>12256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>VANDALISM - COLD</td>\n",
       "      <td>11842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      case_desc    num\n",
       "29  DISTURBANCE - PRIORITY                       97361\n",
       "87  UNWANTED PERSON                              90922\n",
       "74  SUSPICIOUS SUBJ, VEH, OR CIRCUMSTANCE        55560\n",
       "99  WELFARE CHECK - PRIORITY                     55481\n",
       "75  THEFT - COLD                                 51437\n",
       "98  WELFARE CHECK - COLD                         49273\n",
       "44  HAZARD - HAZARDOUS CONDITION                 28296\n",
       "7   AREA CHECK                                   28106\n",
       "50  NOISE DISTURBANCE                            28099\n",
       "11  ASSIST - CITIZEN OR AGENCY                   28093\n",
       "3   ACCIDENT - NON INJURY                        26047\n",
       "76  THEFT - PRIORITY                             23469\n",
       "93  VEHICLE STOLEN - COLD                        22255\n",
       "72  SUSPICIOUS - PRIORITY                        20892\n",
       "17  BURGLARY - COLD                              17733\n",
       "54  PREMISE CHECK                                16504\n",
       "9   ASSAULT - PRIORITY                           15171\n",
       "1   ACCIDENT - HIT AND RUN - COLD                14842\n",
       "95  VICE-DRUGS, LIQUOR, PROSTITUTION, GAMBLING   14280\n",
       "38  FOLLOW-UP                                    13879\n",
       "55  PROPERTY LOST, FOUND, RECOVERED              13394\n",
       "2   ACCIDENT - INJURY                            12899\n",
       "78  THREAT - COLD                                12376\n",
       "21  CIVIL - CIVIL PROBLEM                        12256\n",
       "90  VANDALISM - COLD                             11842"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_by_crime = df3.groupby('case_desc')['num'].sum().reset_index()     \n",
    "#grouped_by_ct = df2.groupby('census_tract')['num'].sum().reset_index() # total crimes by census tract, resets index\n",
    "top_25_crimes = grouped_by_crime.sort_values('num', ascending=False)[:25] # sort by num descending, show top 25  \n",
    "grouped_by_crime.sort_values('num', ascending=False)[:25]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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dIIQQQkgLtMmAr6ioCNeuXcOePXvQr18/AEDHjh3Rs2fPJtd1//59PHr0CFFR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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5d6abf37b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "top_25_crimeplot= sns.barplot(y= top_25_crimes['case_desc'],x = top_25_crimes['num'], order = top_25_crimes['case_desc'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda root]",
   "language": "python",
   "name": "conda-root-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}