chicago-crime-analysis/crimes.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e52e43de",
   "metadata": {},
   "source": [
    "### Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geoplot as gplt\n",
    "import geopandas as gpd\n",
    "import geoplot.crs as gcrs\n",
    "import pandas as pd\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "733941c8",
   "metadata": {},
   "source": [
    "### Data Ingest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "1edc840b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_17408/2120724538.py:2: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
      "  orgdata = pd.read_csv(\n"
     ]
    }
   ],
   "source": [
    "# read raw data\n",
    "orgdata = pd.read_csv(\n",
    "  \"data/crimes.csv\", \n",
    "  usecols=[\"DATE OF OCCURRENCE\", \"FBI CD\", \"beat_num\"],\n",
    "  parse_dates=[\"DATE OF OCCURRENCE\"]\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ba2a1ef5",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "# filter for trailing twelve months and only violent crime\n",
    "data = orgdata[\n",
    "  (orgdata[\"DATE OF OCCURRENCE\"] > \"2022-09-13 00:00:00\") &\n",
    "  (orgdata[\"FBI CD\"].isin([\"01A\", \"02\", \"03\", \"04A\", \"04B\"]))]\n",
    "\n",
    "# get shapefile for CPD beats\n",
    "types = {\n",
    "  \"beat\": int,\n",
    "  \"beat_num\": int,\n",
    "  \"district\": int,\n",
    "  \"sector\": int,\n",
    "}\n",
    "beats = gpd.read_file(\"maps/geo_export_cf56fcdf-4e4b-485b-83b8-f76287821f6a.shp\").astype(types)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12b1398e",
   "metadata": {},
   "source": [
    "#### Verification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "86b9b04d",
   "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>DATE OF OCCURRENCE</th>\n",
       "      <th>beat_num</th>\n",
       "      <th>FBI CD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2022-12-28 10:00:00</td>\n",
       "      <td>1214</td>\n",
       "      <td>04B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2022-10-25 13:00:00</td>\n",
       "      <td>1722</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2023-08-31 19:00:00</td>\n",
       "      <td>833</td>\n",
       "      <td>04B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>2022-11-26 06:15:00</td>\n",
       "      <td>113</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>2022-12-08 15:38:00</td>\n",
       "      <td>1834</td>\n",
       "      <td>01A</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256904</th>\n",
       "      <td>2023-02-04 12:29:00</td>\n",
       "      <td>2234</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256913</th>\n",
       "      <td>2023-03-22 10:47:00</td>\n",
       "      <td>731</td>\n",
       "      <td>04B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256925</th>\n",
       "      <td>2022-11-12 18:35:00</td>\n",
       "      <td>512</td>\n",
       "      <td>04B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256931</th>\n",
       "      <td>2023-07-31 00:00:00</td>\n",
       "      <td>312</td>\n",
       "      <td>04B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>256933</th>\n",
       "      <td>2023-06-18 01:05:00</td>\n",
       "      <td>1824</td>\n",
       "      <td>04B</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>27466 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        DATE OF OCCURRENCE  beat_num FBI CD\n",
       "79     2022-12-28 10:00:00      1214    04B\n",
       "92     2022-10-25 13:00:00      1722     02\n",
       "109    2023-08-31 19:00:00       833    04B\n",
       "170    2022-11-26 06:15:00       113     03\n",
       "188    2022-12-08 15:38:00      1834    01A\n",
       "...                    ...       ...    ...\n",
       "256904 2023-02-04 12:29:00      2234     03\n",
       "256913 2023-03-22 10:47:00       731    04B\n",
       "256925 2022-11-12 18:35:00       512    04B\n",
       "256931 2023-07-31 00:00:00       312    04B\n",
       "256933 2023-06-18 01:05:00      1824    04B\n",
       "\n",
       "[27466 rows x 3 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b6a224a5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 27466 entries, 79 to 256933\n",
      "Data columns (total 3 columns):\n",
      " #   Column              Non-Null Count  Dtype         \n",
      "---  ------              --------------  -----         \n",
      " 0   DATE OF OCCURRENCE  27466 non-null  datetime64[ns]\n",
      " 1   beat_num            27466 non-null  int64         \n",
      " 2   FBI CD              27466 non-null  object        \n",
      "dtypes: datetime64[ns](1), int64(1), object(1)\n",
      "memory usage: 858.3+ KB\n"
     ]
    }
   ],
   "source": [
    "\n",
    "data.info()\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "efa37cbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'geopandas.geodataframe.GeoDataFrame'>\n",
      "RangeIndex: 277 entries, 0 to 276\n",
      "Data columns (total 5 columns):\n",
      " #   Column    Non-Null Count  Dtype   \n",
      "---  ------    --------------  -----   \n",
      " 0   beat      277 non-null    int64   \n",
      " 1   beat_num  277 non-null    int64   \n",
      " 2   district  277 non-null    int64   \n",
      " 3   sector    277 non-null    int64   \n",
      " 4   geometry  277 non-null    geometry\n",
      "dtypes: geometry(1), int64(4)\n",
      "memory usage: 10.9 KB\n"
     ]
    }
   ],
   "source": [
    "beats.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a51e67e8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "beats.plot(legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c57e8c5b",
   "metadata": {},
   "source": [
    "### Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b109d5a8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 274 entries, 0 to 273\n",
      "Data columns (total 2 columns):\n",
      " #   Column    Non-Null Count  Dtype\n",
      "---  ------    --------------  -----\n",
      " 0   beat_num  274 non-null    int64\n",
      " 1   count     274 non-null    int64\n",
      "dtypes: int64(2)\n",
      "memory usage: 4.4 KB\n"
     ]
    }
   ],
   "source": [
    "# count number of occurrances in each beat\n",
    "per_beat = data[\"beat_num\"].value_counts().reset_index(name=\"count\")\n",
    "per_beat.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8ce4d34a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>beat</th>\n",
       "      <th>beat_num</th>\n",
       "      <th>district</th>\n",
       "      <th>sector</th>\n",
       "      <th>geometry</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1713</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.70473 41.97577, -87.70472 41.975...</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>1651</td>\n",
       "      <td>16</td>\n",
       "      <td>5</td>\n",
       "      <td>POLYGON ((-87.90684 41.97656, -87.91070 41.975...</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1914</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.64492 41.96973, -87.64431 41.969...</td>\n",
       "      <td>103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1915</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.63724 41.96599, -87.63644 41.965...</td>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1913</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.65967 41.96903, -87.65967 41.968...</td>\n",
       "      <td>67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   beat  beat_num  district  sector  \\\n",
       "0     1      1713        17       1   \n",
       "1     5      1651        16       5   \n",
       "2     1      1914        19       1   \n",
       "3     1      1915        19       1   \n",
       "4     1      1913        19       1   \n",
       "\n",
       "                                            geometry  count  \n",
       "0  POLYGON ((-87.70473 41.97577, -87.70472 41.975...     47  \n",
       "1  POLYGON ((-87.90684 41.97656, -87.91070 41.975...     12  \n",
       "2  POLYGON ((-87.64492 41.96973, -87.64431 41.969...    103  \n",
       "3  POLYGON ((-87.63724 41.96599, -87.63644 41.965...     55  \n",
       "4  POLYGON ((-87.65967 41.96903, -87.65967 41.968...     67  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merge shapefile and beat data\n",
    "beat_map = beats.merge(per_beat, on=\"beat_num\")\n",
    "beat_map.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bffd054d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>beat</th>\n",
       "      <th>beat_num</th>\n",
       "      <th>district</th>\n",
       "      <th>sector</th>\n",
       "      <th>geometry</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
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       "      <td>1713</td>\n",
       "      <td>17</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.70473 41.97577, -87.70472 41.975...</td>\n",
       "      <td>47</td>\n",
       "      <td>-53.240876</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>1651</td>\n",
       "      <td>16</td>\n",
       "      <td>5</td>\n",
       "      <td>POLYGON ((-87.90684 41.97656, -87.91070 41.975...</td>\n",
       "      <td>12</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1914</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.64492 41.96973, -87.64431 41.969...</td>\n",
       "      <td>103</td>\n",
       "      <td>2.759124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1915</td>\n",
       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.63724 41.96599, -87.63644 41.965...</td>\n",
       "      <td>55</td>\n",
       "      <td>-45.240876</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
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       "      <td>19</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.65967 41.96903, -87.65967 41.968...</td>\n",
       "      <td>67</td>\n",
       "      <td>-33.240876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "    <tr>\n",
       "      <th>269</th>\n",
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       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.58879 41.78612, -87.58844 41.786...</td>\n",
       "      <td>79</td>\n",
       "      <td>-21.240876</td>\n",
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       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>POLYGON ((-87.67917 41.78656, -87.67912 41.784...</td>\n",
       "      <td>129</td>\n",
       "      <td>28.759124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>271</th>\n",
       "      <td>1</td>\n",
       "      <td>313</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.60854 41.78583, -87.60808 41.785...</td>\n",
       "      <td>98</td>\n",
       "      <td>-2.240876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>272</th>\n",
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       "      <td>823</td>\n",
       "      <td>8</td>\n",
       "      <td>2</td>\n",
       "      <td>POLYGON ((-87.69354 41.78458, -87.69354 41.784...</td>\n",
       "      <td>185</td>\n",
       "      <td>84.759124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>273</th>\n",
       "      <td>1</td>\n",
       "      <td>312</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>POLYGON ((-87.60431 41.78043, -87.60400 41.780...</td>\n",
       "      <td>148</td>\n",
       "      <td>47.759124</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>274 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     beat  beat_num  district  sector  \\\n",
       "0       1      1713        17       1   \n",
       "1       5      1651        16       5   \n",
       "2       1      1914        19       1   \n",
       "3       1      1915        19       1   \n",
       "4       1      1913        19       1   \n",
       "..    ...       ...       ...     ...   \n",
       "269     1       314         3       1   \n",
       "270     2       825         8       2   \n",
       "271     1       313         3       1   \n",
       "272     2       823         8       2   \n",
       "273     1       312         3       1   \n",
       "\n",
       "                                              geometry  count  deviations  \n",
       "0    POLYGON ((-87.70473 41.97577, -87.70472 41.975...     47  -53.240876  \n",
       "1    POLYGON ((-87.90684 41.97656, -87.91070 41.975...     12  -88.240876  \n",
       "2    POLYGON ((-87.64492 41.96973, -87.64431 41.969...    103    2.759124  \n",
       "3    POLYGON ((-87.63724 41.96599, -87.63644 41.965...     55  -45.240876  \n",
       "4    POLYGON ((-87.65967 41.96903, -87.65967 41.968...     67  -33.240876  \n",
       "..                                                 ...    ...         ...  \n",
       "269  POLYGON ((-87.58879 41.78612, -87.58844 41.786...     79  -21.240876  \n",
       "270  POLYGON ((-87.67917 41.78656, -87.67912 41.784...    129   28.759124  \n",
       "271  POLYGON ((-87.60854 41.78583, -87.60808 41.785...     98   -2.240876  \n",
       "272  POLYGON ((-87.69354 41.78458, -87.69354 41.784...    185   84.759124  \n",
       "273  POLYGON ((-87.60431 41.78043, -87.60400 41.780...    148   47.759124  \n",
       "\n",
       "[274 rows x 7 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean = beat_map[\"count\"].mean()\n",
    "beat_map[\"deviations\"] = beat_map.apply(lambda row: row[\"count\"] - mean, axis=1)\n",
    "beat_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d83a3b43",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<GeoAxes: title={'center': \"Violent Crime Occurrances Difference from Mean, TTM Sep '23\"}>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "ax = gplt.polyplot(beat_map, projection=gcrs.AlbersEqualArea())\n",
    "ax.set_title(\"Violent Crime Occurrances Difference from Mean, TTM Sep '23\")\n",
    "gplt.choropleth(\n",
    "  beat_map,\n",
    "  hue=\"deviations\",\n",
    "  edgecolor=\"white\",\n",
    "  linewidth=1,\n",
    "  legend=True,\n",
    "  norm=mpl.colors.TwoSlopeNorm(vmin=beat_map[\"deviations\"].min(), vcenter=0, vmax=beat_map[\"deviations\"].max()),\n",
    "  cmap=\"coolwarm\",\n",
    "  ax=ax,\n",
    ")"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "id": "11e96927",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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