SF Crime 2016.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# San Francisco Crime 2016"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "#import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>IncidntNum</th>\n",
       "      <th>Category</th>\n",
       "      <th>Descript</th>\n",
       "      <th>DayOfWeek</th>\n",
       "      <th>Date</th>\n",
       "      <th>Time</th>\n",
       "      <th>PdDistrict</th>\n",
       "      <th>Resolution</th>\n",
       "      <th>Address</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Location</th>\n",
       "      <th>PdId</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>120058272</td>\n",
       "      <td>WEAPON LAWS</td>\n",
       "      <td>POSS OF PROHIBITED WEAPON</td>\n",
       "      <td>Friday</td>\n",
       "      <td>01/29/2016 12:00:00 AM</td>\n",
       "      <td>11:00</td>\n",
       "      <td>SOUTHERN</td>\n",
       "      <td>ARREST, BOOKED</td>\n",
       "      <td>800 Block of BRYANT ST</td>\n",
       "      <td>-122.403405</td>\n",
       "      <td>37.775421</td>\n",
       "      <td>(37.775420706711, -122.403404791479)</td>\n",
       "      <td>12005827212120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>120058272</td>\n",
       "      <td>WEAPON LAWS</td>\n",
       "      <td>FIREARM, LOADED, IN VEHICLE, POSSESSION OR USE</td>\n",
       "      <td>Friday</td>\n",
       "      <td>01/29/2016 12:00:00 AM</td>\n",
       "      <td>11:00</td>\n",
       "      <td>SOUTHERN</td>\n",
       "      <td>ARREST, BOOKED</td>\n",
       "      <td>800 Block of BRYANT ST</td>\n",
       "      <td>-122.403405</td>\n",
       "      <td>37.775421</td>\n",
       "      <td>(37.775420706711, -122.403404791479)</td>\n",
       "      <td>12005827212168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>141059263</td>\n",
       "      <td>WARRANTS</td>\n",
       "      <td>WARRANT ARREST</td>\n",
       "      <td>Monday</td>\n",
       "      <td>04/25/2016 12:00:00 AM</td>\n",
       "      <td>14:59</td>\n",
       "      <td>BAYVIEW</td>\n",
       "      <td>ARREST, BOOKED</td>\n",
       "      <td>KEITH ST / SHAFTER AV</td>\n",
       "      <td>-122.388856</td>\n",
       "      <td>37.729981</td>\n",
       "      <td>(37.7299809672996, -122.388856204292)</td>\n",
       "      <td>14105926363010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>160013662</td>\n",
       "      <td>NON-CRIMINAL</td>\n",
       "      <td>LOST PROPERTY</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>01/05/2016 12:00:00 AM</td>\n",
       "      <td>23:50</td>\n",
       "      <td>TENDERLOIN</td>\n",
       "      <td>NONE</td>\n",
       "      <td>JONES ST / OFARRELL ST</td>\n",
       "      <td>-122.412971</td>\n",
       "      <td>37.785788</td>\n",
       "      <td>(37.7857883766888, -122.412970537591)</td>\n",
       "      <td>16001366271000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>160002740</td>\n",
       "      <td>NON-CRIMINAL</td>\n",
       "      <td>LOST PROPERTY</td>\n",
       "      <td>Friday</td>\n",
       "      <td>01/01/2016 12:00:00 AM</td>\n",
       "      <td>00:30</td>\n",
       "      <td>MISSION</td>\n",
       "      <td>NONE</td>\n",
       "      <td>16TH ST / MISSION ST</td>\n",
       "      <td>-122.419672</td>\n",
       "      <td>37.765050</td>\n",
       "      <td>(37.7650501214668, -122.419671780296)</td>\n",
       "      <td>16000274071000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150495</th>\n",
       "      <td>161061000</td>\n",
       "      <td>ASSAULT</td>\n",
       "      <td>BATTERY</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12/30/2016 12:00:00 AM</td>\n",
       "      <td>21:01</td>\n",
       "      <td>PARK</td>\n",
       "      <td>NONE</td>\n",
       "      <td>OAK ST / STANYAN ST</td>\n",
       "      <td>-122.453982</td>\n",
       "      <td>37.771428</td>\n",
       "      <td>(37.7714278595913, -122.453981622365)</td>\n",
       "      <td>16106100004134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150496</th>\n",
       "      <td>176000742</td>\n",
       "      <td>NON-CRIMINAL</td>\n",
       "      <td>LOST PROPERTY</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12/30/2016 12:00:00 AM</td>\n",
       "      <td>08:00</td>\n",
       "      <td>CENTRAL</td>\n",
       "      <td>NONE</td>\n",
       "      <td>JACKSON ST / SANSOME ST</td>\n",
       "      <td>-122.401857</td>\n",
       "      <td>37.796626</td>\n",
       "      <td>(37.7966261239618, -122.401857374739)</td>\n",
       "      <td>17600074271000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150497</th>\n",
       "      <td>176000758</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>PETTY THEFT OF PROPERTY</td>\n",
       "      <td>Thursday</td>\n",
       "      <td>12/29/2016 12:00:00 AM</td>\n",
       "      <td>20:00</td>\n",
       "      <td>CENTRAL</td>\n",
       "      <td>NONE</td>\n",
       "      <td>PINE ST / TAYLOR ST</td>\n",
       "      <td>-122.412269</td>\n",
       "      <td>37.790673</td>\n",
       "      <td>(37.7906727649886, -122.41226909106)</td>\n",
       "      <td>17600075806372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150498</th>\n",
       "      <td>176000764</td>\n",
       "      <td>LARCENY/THEFT</td>\n",
       "      <td>GRAND THEFT OF PROPERTY</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12/30/2016 12:00:00 AM</td>\n",
       "      <td>10:00</td>\n",
       "      <td>CENTRAL</td>\n",
       "      <td>NONE</td>\n",
       "      <td>200 Block of STOCKTON ST</td>\n",
       "      <td>-122.406659</td>\n",
       "      <td>37.788275</td>\n",
       "      <td>(37.7882745285785, -122.406658711008)</td>\n",
       "      <td>17600076406374</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150499</th>\n",
       "      <td>179002868</td>\n",
       "      <td>OTHER OFFENSES</td>\n",
       "      <td>FRAUDULENT GAME OR TRICK, OBTAINING MONEY OR P...</td>\n",
       "      <td>Friday</td>\n",
       "      <td>12/02/2016 12:00:00 AM</td>\n",
       "      <td>14:00</td>\n",
       "      <td>SOUTHERN</td>\n",
       "      <td>NONE</td>\n",
       "      <td>800 Block of BRYANT ST</td>\n",
       "      <td>-122.403405</td>\n",
       "      <td>37.775421</td>\n",
       "      <td>(37.775420706711, -122.403404791479)</td>\n",
       "      <td>17900286809024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>150500 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        IncidntNum        Category  \\\n",
       "0        120058272     WEAPON LAWS   \n",
       "1        120058272     WEAPON LAWS   \n",
       "2        141059263        WARRANTS   \n",
       "3        160013662    NON-CRIMINAL   \n",
       "4        160002740    NON-CRIMINAL   \n",
       "...            ...             ...   \n",
       "150495   161061000         ASSAULT   \n",
       "150496   176000742    NON-CRIMINAL   \n",
       "150497   176000758   LARCENY/THEFT   \n",
       "150498   176000764   LARCENY/THEFT   \n",
       "150499   179002868  OTHER OFFENSES   \n",
       "\n",
       "                                                 Descript DayOfWeek  \\\n",
       "0                               POSS OF PROHIBITED WEAPON    Friday   \n",
       "1          FIREARM, LOADED, IN VEHICLE, POSSESSION OR USE    Friday   \n",
       "2                                          WARRANT ARREST    Monday   \n",
       "3                                           LOST PROPERTY   Tuesday   \n",
       "4                                           LOST PROPERTY    Friday   \n",
       "...                                                   ...       ...   \n",
       "150495                                            BATTERY    Friday   \n",
       "150496                                      LOST PROPERTY    Friday   \n",
       "150497                            PETTY THEFT OF PROPERTY  Thursday   \n",
       "150498                            GRAND THEFT OF PROPERTY    Friday   \n",
       "150499  FRAUDULENT GAME OR TRICK, OBTAINING MONEY OR P...    Friday   \n",
       "\n",
       "                          Date   Time  PdDistrict      Resolution  \\\n",
       "0       01/29/2016 12:00:00 AM  11:00    SOUTHERN  ARREST, BOOKED   \n",
       "1       01/29/2016 12:00:00 AM  11:00    SOUTHERN  ARREST, BOOKED   \n",
       "2       04/25/2016 12:00:00 AM  14:59     BAYVIEW  ARREST, BOOKED   \n",
       "3       01/05/2016 12:00:00 AM  23:50  TENDERLOIN            NONE   \n",
       "4       01/01/2016 12:00:00 AM  00:30     MISSION            NONE   \n",
       "...                        ...    ...         ...             ...   \n",
       "150495  12/30/2016 12:00:00 AM  21:01        PARK            NONE   \n",
       "150496  12/30/2016 12:00:00 AM  08:00     CENTRAL            NONE   \n",
       "150497  12/29/2016 12:00:00 AM  20:00     CENTRAL            NONE   \n",
       "150498  12/30/2016 12:00:00 AM  10:00     CENTRAL            NONE   \n",
       "150499  12/02/2016 12:00:00 AM  14:00    SOUTHERN            NONE   \n",
       "\n",
       "                         Address           X          Y  \\\n",
       "0         800 Block of BRYANT ST -122.403405  37.775421   \n",
       "1         800 Block of BRYANT ST -122.403405  37.775421   \n",
       "2          KEITH ST / SHAFTER AV -122.388856  37.729981   \n",
       "3         JONES ST / OFARRELL ST -122.412971  37.785788   \n",
       "4           16TH ST / MISSION ST -122.419672  37.765050   \n",
       "...                          ...         ...        ...   \n",
       "150495       OAK ST / STANYAN ST -122.453982  37.771428   \n",
       "150496   JACKSON ST / SANSOME ST -122.401857  37.796626   \n",
       "150497       PINE ST / TAYLOR ST -122.412269  37.790673   \n",
       "150498  200 Block of STOCKTON ST -122.406659  37.788275   \n",
       "150499    800 Block of BRYANT ST -122.403405  37.775421   \n",
       "\n",
       "                                     Location            PdId  \n",
       "0        (37.775420706711, -122.403404791479)  12005827212120  \n",
       "1        (37.775420706711, -122.403404791479)  12005827212168  \n",
       "2       (37.7299809672996, -122.388856204292)  14105926363010  \n",
       "3       (37.7857883766888, -122.412970537591)  16001366271000  \n",
       "4       (37.7650501214668, -122.419671780296)  16000274071000  \n",
       "...                                       ...             ...  \n",
       "150495  (37.7714278595913, -122.453981622365)  16106100004134  \n",
       "150496  (37.7966261239618, -122.401857374739)  17600074271000  \n",
       "150497   (37.7906727649886, -122.41226909106)  17600075806372  \n",
       "150498  (37.7882745285785, -122.406658711008)  17600076406374  \n",
       "150499   (37.775420706711, -122.403404791479)  17900286809024  \n",
       "\n",
       "[150500 rows x 13 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crime_df = pd.read_csv(\"data/sf_crime_2016.csv\")\n",
    "crime_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create a frequency table for category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0            WEAPON LAWS\n",
       "1            WEAPON LAWS\n",
       "2               WARRANTS\n",
       "3           NON-CRIMINAL\n",
       "4           NON-CRIMINAL\n",
       "               ...      \n",
       "150495           ASSAULT\n",
       "150496      NON-CRIMINAL\n",
       "150497     LARCENY/THEFT\n",
       "150498     LARCENY/THEFT\n",
       "150499    OTHER OFFENSES\n",
       "Name: Category, Length: 150500, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category = crime_df['Category']\n",
    "category"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LARCENY/THEFT                  40409\n",
       "OTHER OFFENSES                 19599\n",
       "NON-CRIMINAL                   17866\n",
       "ASSAULT                        13577\n",
       "VANDALISM                       8589\n",
       "VEHICLE THEFT                   6419\n",
       "WARRANTS                        5914\n",
       "BURGLARY                        5802\n",
       "SUSPICIOUS OCC                  5782\n",
       "MISSING PERSON                  4338\n",
       "DRUG/NARCOTIC                   4243\n",
       "ROBBERY                         3299\n",
       "FRAUD                           2635\n",
       "SECONDARY CODES                 1841\n",
       "TRESPASS                        1812\n",
       "WEAPON LAWS                     1658\n",
       "SEX OFFENSES, FORCIBLE           940\n",
       "STOLEN PROPERTY                  882\n",
       "RECOVERED VEHICLE                736\n",
       "DISORDERLY CONDUCT               658\n",
       "PROSTITUTION                     641\n",
       "FORGERY/COUNTERFEITING           619\n",
       "DRUNKENNESS                      465\n",
       "DRIVING UNDER THE INFLUENCE      378\n",
       "ARSON                            286\n",
       "KIDNAPPING                       257\n",
       "EMBEZZLEMENT                     168\n",
       "LIQUOR LAWS                      156\n",
       "RUNAWAY                          140\n",
       "SUICIDE                           69\n",
       "BRIBERY                           66\n",
       "EXTORTION                         60\n",
       "FAMILY OFFENSES                   53\n",
       "LOITERING                         42\n",
       "SEX OFFENSES, NON FORCIBLE        40\n",
       "BAD CHECKS                        34\n",
       "GAMBLING                          20\n",
       "PORNOGRAPHY/OBSCENE MAT            4\n",
       "TREA                               3\n",
       "Name: Category, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_counts = category.value_counts()\n",
    "category_counts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot the top 10 in a bar chart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LARCENY/THEFT     40409\n",
       "OTHER OFFENSES    19599\n",
       "NON-CRIMINAL      17866\n",
       "ASSAULT           13577\n",
       "VANDALISM          8589\n",
       "VEHICLE THEFT      6419\n",
       "WARRANTS           5914\n",
       "BURGLARY           5802\n",
       "SUSPICIOUS OCC     5782\n",
       "MISSING PERSON     4338\n",
       "Name: Category, dtype: int64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_counts.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "category_counts.head(10).plot(kind='barh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Plot counts for day of week"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           SOUTHERN\n",
       "1           SOUTHERN\n",
       "2            BAYVIEW\n",
       "3         TENDERLOIN\n",
       "4            MISSION\n",
       "             ...    \n",
       "150495          PARK\n",
       "150496       CENTRAL\n",
       "150497       CENTRAL\n",
       "150498       CENTRAL\n",
       "150499      SOUTHERN\n",
       "Name: PdDistrict, Length: 150500, dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dow = crime_df['PdDistrict']\n",
    "dow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dow.value_counts().plot(kind='bar')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}