time-series-plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.data_preprocessor import load_and_process_data, aggregate_to_yearly, filter_data\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import geopandas as gpd\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-11 18:55:31,311 - INFO - Loading the latest recent file: data/lsoa-recent.csv\n",
      "2023-11-11 18:55:31,715 - INFO - Loading the latest historical file: data/lsoa-historical.csv\n"
     ]
    }
   ],
   "source": [
    "df = load_and_process_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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></th>\n",
       "      <th>201903</th>\n",
       "      <th>201904</th>\n",
       "      <th>201905</th>\n",
       "      <th>201906</th>\n",
       "      <th>201907</th>\n",
       "      <th>201908</th>\n",
       "      <th>201909</th>\n",
       "      <th>201910</th>\n",
       "      <th>201911</th>\n",
       "      <th>201912</th>\n",
       "      <th>...</th>\n",
       "      <th>202212</th>\n",
       "      <th>202301</th>\n",
       "      <th>202302</th>\n",
       "      <th>202303</th>\n",
       "      <th>202304</th>\n",
       "      <th>202305</th>\n",
       "      <th>202306</th>\n",
       "      <th>202307</th>\n",
       "      <th>202308</th>\n",
       "      <th>202309</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Borough</th>\n",
       "      <th>Major Category</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Barking and Dagenham</th>\n",
       "      <th>Arson and Criminal Damage</th>\n",
       "      <td>135.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>...</td>\n",
       "      <td>92.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Burglary</th>\n",
       "      <td>127.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>...</td>\n",
       "      <td>104.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>56.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>78.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>48.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Drug Offences</th>\n",
       "      <td>107.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>82.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>...</td>\n",
       "      <td>119.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>40.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Miscellaneous Crimes Against Society</th>\n",
       "      <td>20.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Possession of Weapons</th>\n",
       "      <td>23.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>...</td>\n",
       "      <td>9.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\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",
       "      <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 rowspan=\"5\" valign=\"top\">Westminster</th>\n",
       "      <th>Public Order Offences</th>\n",
       "      <td>261.0</td>\n",
       "      <td>260.0</td>\n",
       "      <td>241.0</td>\n",
       "      <td>287.0</td>\n",
       "      <td>308.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>...</td>\n",
       "      <td>283.0</td>\n",
       "      <td>274.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>230.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>130.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Robbery</th>\n",
       "      <td>340.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>399.0</td>\n",
       "      <td>354.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>366.0</td>\n",
       "      <td>322.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>...</td>\n",
       "      <td>359.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>325.0</td>\n",
       "      <td>286.0</td>\n",
       "      <td>342.0</td>\n",
       "      <td>362.0</td>\n",
       "      <td>388.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>143.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Theft</th>\n",
       "      <td>4139.0</td>\n",
       "      <td>4257.0</td>\n",
       "      <td>3836.0</td>\n",
       "      <td>3760.0</td>\n",
       "      <td>3657.0</td>\n",
       "      <td>3406.0</td>\n",
       "      <td>3169.0</td>\n",
       "      <td>3743.0</td>\n",
       "      <td>3630.0</td>\n",
       "      <td>4128.0</td>\n",
       "      <td>...</td>\n",
       "      <td>5575.0</td>\n",
       "      <td>4653.0</td>\n",
       "      <td>4355.0</td>\n",
       "      <td>4396.0</td>\n",
       "      <td>3944.0</td>\n",
       "      <td>4300.0</td>\n",
       "      <td>4499.0</td>\n",
       "      <td>4574.0</td>\n",
       "      <td>3866.0</td>\n",
       "      <td>1289.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Vehicle Offences</th>\n",
       "      <td>418.0</td>\n",
       "      <td>375.0</td>\n",
       "      <td>369.0</td>\n",
       "      <td>381.0</td>\n",
       "      <td>350.0</td>\n",
       "      <td>308.0</td>\n",
       "      <td>318.0</td>\n",
       "      <td>397.0</td>\n",
       "      <td>370.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>...</td>\n",
       "      <td>302.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>386.0</td>\n",
       "      <td>396.0</td>\n",
       "      <td>405.0</td>\n",
       "      <td>398.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>305.0</td>\n",
       "      <td>296.0</td>\n",
       "      <td>105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Violence Against the Person</th>\n",
       "      <td>899.0</td>\n",
       "      <td>801.0</td>\n",
       "      <td>894.0</td>\n",
       "      <td>910.0</td>\n",
       "      <td>913.0</td>\n",
       "      <td>1017.0</td>\n",
       "      <td>839.0</td>\n",
       "      <td>952.0</td>\n",
       "      <td>926.0</td>\n",
       "      <td>955.0</td>\n",
       "      <td>...</td>\n",
       "      <td>951.0</td>\n",
       "      <td>901.0</td>\n",
       "      <td>829.0</td>\n",
       "      <td>797.0</td>\n",
       "      <td>820.0</td>\n",
       "      <td>947.0</td>\n",
       "      <td>973.0</td>\n",
       "      <td>1045.0</td>\n",
       "      <td>977.0</td>\n",
       "      <td>381.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>320 rows × 162 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                           201903  201904  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              135.0   131.0   \n",
       "                     Burglary                               127.0   122.0   \n",
       "                     Drug Offences                          107.0    98.0   \n",
       "                     Miscellaneous Crimes Against Society    20.0    22.0   \n",
       "                     Possession of Weapons                   23.0    12.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  261.0   260.0   \n",
       "                     Robbery                                340.0   396.0   \n",
       "                     Theft                                 4139.0  4257.0   \n",
       "                     Vehicle Offences                       418.0   375.0   \n",
       "                     Violence Against the Person            899.0   801.0   \n",
       "\n",
       "                                                           201905  201906  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              147.0   115.0   \n",
       "                     Burglary                               134.0   124.0   \n",
       "                     Drug Offences                           82.0    92.0   \n",
       "                     Miscellaneous Crimes Against Society    34.0    28.0   \n",
       "                     Possession of Weapons                   24.0     8.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  241.0   287.0   \n",
       "                     Robbery                                367.0   384.0   \n",
       "                     Theft                                 3836.0  3760.0   \n",
       "                     Vehicle Offences                       369.0   381.0   \n",
       "                     Violence Against the Person            894.0   910.0   \n",
       "\n",
       "                                                           201907  201908  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              136.0   120.0   \n",
       "                     Burglary                               100.0   102.0   \n",
       "                     Drug Offences                           99.0    79.0   \n",
       "                     Miscellaneous Crimes Against Society    17.0    30.0   \n",
       "                     Possession of Weapons                   10.0     8.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  308.0   319.0   \n",
       "                     Robbery                                399.0   354.0   \n",
       "                     Theft                                 3657.0  3406.0   \n",
       "                     Vehicle Offences                       350.0   308.0   \n",
       "                     Violence Against the Person            913.0  1017.0   \n",
       "\n",
       "                                                           201909  201910  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              114.0   113.0   \n",
       "                     Burglary                               117.0   124.0   \n",
       "                     Drug Offences                           83.0    94.0   \n",
       "                     Miscellaneous Crimes Against Society    21.0    22.0   \n",
       "                     Possession of Weapons                   17.0    13.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  291.0   270.0   \n",
       "                     Robbery                                320.0   366.0   \n",
       "                     Theft                                 3169.0  3743.0   \n",
       "                     Vehicle Offences                       318.0   397.0   \n",
       "                     Violence Against the Person            839.0   952.0   \n",
       "\n",
       "                                                           201911  201912  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              105.0   127.0   \n",
       "                     Burglary                               142.0   155.0   \n",
       "                     Drug Offences                          101.0    83.0   \n",
       "                     Miscellaneous Crimes Against Society    24.0    20.0   \n",
       "                     Possession of Weapons                   10.0     6.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  233.0   249.0   \n",
       "                     Robbery                                322.0   442.0   \n",
       "                     Theft                                 3630.0  4128.0   \n",
       "                     Vehicle Offences                       370.0   458.0   \n",
       "                     Violence Against the Person            926.0   955.0   \n",
       "\n",
       "                                                           ...  202212  \\\n",
       "Borough              Major Category                        ...           \n",
       "Barking and Dagenham Arson and Criminal Damage             ...    92.0   \n",
       "                     Burglary                              ...   104.0   \n",
       "                     Drug Offences                         ...   119.0   \n",
       "                     Miscellaneous Crimes Against Society  ...    19.0   \n",
       "                     Possession of Weapons                 ...     9.0   \n",
       "...                                                        ...     ...   \n",
       "Westminster          Public Order Offences                 ...   283.0   \n",
       "                     Robbery                               ...   359.0   \n",
       "                     Theft                                 ...  5575.0   \n",
       "                     Vehicle Offences                      ...   302.0   \n",
       "                     Violence Against the Person           ...   951.0   \n",
       "\n",
       "                                                           202301  202302  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage               96.0    94.0   \n",
       "                     Burglary                               118.0    56.0   \n",
       "                     Drug Offences                          127.0   149.0   \n",
       "                     Miscellaneous Crimes Against Society    22.0    24.0   \n",
       "                     Possession of Weapons                   20.0    16.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  274.0   230.0   \n",
       "                     Robbery                                319.0   325.0   \n",
       "                     Theft                                 4653.0  4355.0   \n",
       "                     Vehicle Offences                       384.0   386.0   \n",
       "                     Violence Against the Person            901.0   829.0   \n",
       "\n",
       "                                                           202303  202304  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              112.0    99.0   \n",
       "                     Burglary                                87.0    96.0   \n",
       "                     Drug Offences                          126.0    91.0   \n",
       "                     Miscellaneous Crimes Against Society    28.0    21.0   \n",
       "                     Possession of Weapons                   13.0    14.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  230.0   270.0   \n",
       "                     Robbery                                286.0   342.0   \n",
       "                     Theft                                 4396.0  3944.0   \n",
       "                     Vehicle Offences                       396.0   405.0   \n",
       "                     Violence Against the Person            797.0   820.0   \n",
       "\n",
       "                                                           202305  202306  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              113.0   124.0   \n",
       "                     Burglary                                78.0    91.0   \n",
       "                     Drug Offences                          111.0   131.0   \n",
       "                     Miscellaneous Crimes Against Society    23.0    22.0   \n",
       "                     Possession of Weapons                   16.0    24.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  283.0   326.0   \n",
       "                     Robbery                                362.0   388.0   \n",
       "                     Theft                                 4300.0  4499.0   \n",
       "                     Vehicle Offences                       398.0   357.0   \n",
       "                     Violence Against the Person            947.0   973.0   \n",
       "\n",
       "                                                           202307  202308  \\\n",
       "Borough              Major Category                                         \n",
       "Barking and Dagenham Arson and Criminal Damage              137.0   122.0   \n",
       "                     Burglary                                74.0   109.0   \n",
       "                     Drug Offences                          150.0    94.0   \n",
       "                     Miscellaneous Crimes Against Society    24.0    15.0   \n",
       "                     Possession of Weapons                   16.0    19.0   \n",
       "...                                                           ...     ...   \n",
       "Westminster          Public Order Offences                  365.0   280.0   \n",
       "                     Robbery                                351.0   350.0   \n",
       "                     Theft                                 4574.0  3866.0   \n",
       "                     Vehicle Offences                       305.0   296.0   \n",
       "                     Violence Against the Person           1045.0   977.0   \n",
       "\n",
       "                                                           202309  \n",
       "Borough              Major Category                                \n",
       "Barking and Dagenham Arson and Criminal Damage               53.0  \n",
       "                     Burglary                                48.0  \n",
       "                     Drug Offences                           40.0  \n",
       "                     Miscellaneous Crimes Against Society    10.0  \n",
       "                     Possession of Weapons                    5.0  \n",
       "...                                                           ...  \n",
       "Westminster          Public Order Offences                  130.0  \n",
       "                     Robbery                                143.0  \n",
       "                     Theft                                 1289.0  \n",
       "                     Vehicle Offences                       105.0  \n",
       "                     Violence Against the Person            381.0  \n",
       "\n",
       "[320 rows x 162 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def group_by(df: pd.DataFrame, columns : list = ['Borough'], agg_func :str ='sum', sort : bool =False) -> pd.DataFrame:\n",
    "    '''\n",
    "    Groups a DataFrame by specified column(s) and applies an aggregation function.\n",
    "\n",
    "    :params df (pd.DataFrame): The DataFrame to group.\n",
    "    :params columns (str or list): The column(s) to group by.\n",
    "    :params agg_func (str or dict, optional): The aggregation function(s) to apply. Default is 'sum'.\n",
    "    :params sort (bool, optional): Whether to sort the grouped data. Default is False.\n",
    "\n",
    "    :returns pd.DataFrame: The grouped DataFrame.\n",
    "    '''\n",
    "    # Ensure columns is a list for consistency\n",
    "    if isinstance(columns, str):\n",
    "        columns = [columns]\n",
    "\n",
    "    # Check if all columns are in DataFrame\n",
    "    missing_columns = [col for col in columns if col not in df.columns]\n",
    "    if missing_columns:\n",
    "        logger.error(f'Column(s) {\", \".join(missing_columns)} not found in dataset')\n",
    "        return None\n",
    "\n",
    "    grouped_df = df.groupby(by=columns).agg(agg_func)\n",
    "\n",
    "    if sort:\n",
    "        grouped_df = grouped_df.sort_values(by=columns)\n",
    "\n",
    "    return grouped_df\n",
    "\n",
    "# Example Usage\n",
    "group_by(df, columns = ['Borough', 'Major Category'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "201004    11817.0\n",
      "201005    12838.0\n",
      "201006    13042.0\n",
      "201007    13126.0\n",
      "201008    11429.0\n",
      "           ...   \n",
      "202305    21418.0\n",
      "202306    22582.0\n",
      "202307    22055.0\n",
      "202308    20619.0\n",
      "202309     8402.0\n",
      "Length: 162, dtype: float64\n",
      "2010    105903.0\n",
      "2011    129711.0\n",
      "2012    127192.0\n",
      "2013    122792.0\n",
      "2014    153594.0\n",
      "2015    179335.0\n",
      "2016    189250.0\n",
      "2017    197415.0\n",
      "2018    207895.0\n",
      "2019    217884.0\n",
      "2020    213175.0\n",
      "2021    227336.0\n",
      "2022    232957.0\n",
      "2023    170708.0\n",
      "dtype: float64\n"
     ]
    }
   ],
   "source": [
    "def get_time_series(df, columns : list = ['Borough', 'Major Category'], agg_func : str = 'sum', crimes : list = ['Theft'], yearly : bool = False):\n",
    "    \n",
    "    grouped_by_borough = group_by(df = df, columns = columns, agg_func=agg_func, sort = True)\n",
    "    yearly_by_borough = aggregate_to_yearly(grouped_by_borough).sort_index(axis = 1)\n",
    "\n",
    "    # Filtered data by borough and by crime\n",
    "    filted_data = filter_data(df = grouped_by_borough.reset_index() if yearly == False else yearly_by_borough.reset_index(),\n",
    "                               column='Major Category', category_filters = crimes).reset_index(drop = True)\n",
    "    yearly_data_sums = filted_data.drop(columns = ['Borough', 'Major Category']).sum()\n",
    "\n",
    "    return yearly_data_sums.sort_index()\n",
    "\n",
    "\n",
    "# Example Usage\n",
    "crimes = ['Violence Against the Person']\n",
    "monthly = get_time_series(df = df, crimes = crimes, yearly=False)\n",
    "yearly = get_time_series(df = df, crimes = crimes, yearly=True)\n",
    "\n",
    "print(monthly)\n",
    "print(yearly)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-11 19:13:33,679 - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n",
      "2023-11-11 19:13:33,689 - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-11-11 19:13:35,147 - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n",
      "2023-11-11 19:13:35,153 - INFO - Using categorical units to plot a list of strings that are all parsable as floats or dates. If these strings should be plotted as numbers, cast to the appropriate data type before plotting.\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1080x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def static_line_plot(data, crimes):\n",
    "    plt.figure(figsize=(15, 6))\n",
    "    sns.lineplot(x=data.index, y=data.values, marker=\"o\", color=\"b\")\n",
    "    plt.title(f'Yearly Trend of {\", \".join(str(crime) for crime in crimes)} Crimes in London (2010-2023)', fontsize=15)\n",
    "    plt.xlabel('Year', fontsize=12)\n",
    "    plt.ylabel('Total Crime Counts', fontsize=12)\n",
    "    plt.grid(True, which=\"both\", ls=\"--\")\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "# Example usage\n",
    "static_line_plot(data = monthly, crimes=crimes)\n",
    "static_line_plot(data = yearly, crimes=crimes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hovertemplate": "Year=%{x}<br>Total Crime Counts=%{y}<extra></extra>",
         "legendgroup": "",
         "line": {
          "color": "#636efa",
          "dash": "solid"
         },
         "marker": {
          "symbol": "circle"
         },
         "mode": "lines+markers",
         "name": "",
         "orientation": "v",
         "showlegend": false,
         "type": "scatter",
         "x": [
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         "yaxis": "y"
        }
       ],
       "layout": {
        "legend": {
         "tracegroupgap": 0
        },
        "plot_bgcolor": "white",
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             },
             "pattern": {
              "fillmode": "overlay",
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          "title": {
           "x": 0.05
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          "xaxis": {
           "automargin": true,
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        },
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        },
        "xaxis": {
         "anchor": "y",
         "domain": [
          0,
          1
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         "gridcolor": "LightPink",
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         "gridwidth": 1,
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          "text": "Total Crime Counts"
         }
        }
       }
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     },
     "metadata": {},
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   ],
   "source": [
    "def interactive_line_plot(data, crimes):\n",
    "    fig = px.line(data, x=data.index.values, y=data.values,\n",
    "                markers=True, title=f'Yearly Trend of {\", \".join(str(crime) for crime in crimes)} Crimes in London (2010-2023)',\n",
    "                labels={'x': 'Year', 'y': 'Total Crime Counts'})\n",
    "\n",
    "    fig.update_layout(xaxis_title='Year',\n",
    "                    yaxis_title='Total Crime Counts',\n",
    "                    xaxis=dict(showgrid=True, gridwidth=1, gridcolor='LightPink'),\n",
    "                    yaxis=dict(showgrid=True, gridwidth=1, gridcolor='LightBlue'),\n",
    "                    plot_bgcolor='white')\n",
    "\n",
    "    fig.show()\n",
    "\n",
    "\n",
    "# Example usage\n",
    "interactive_line_plot(data = monthly, crimes = crimes)\n",
    "interactive_line_plot(data = yearly, crimes = crimes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1080x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def prep_data_for_monthly_heat_maps(df, crimes):\n",
    "        \n",
    "    monthly_totals = get_time_series(df, columns=['Borough', 'Major Category'], crimes=crimes, yearly = False)\n",
    "    monthly_totals = pd.DataFrame(monthly_totals).reset_index()\n",
    "    monthly_totals['Year'] = monthly_totals['index'].str[:4]\n",
    "    monthly_totals['Month'] = monthly_totals['index'].str[4:] \n",
    "    monthly_pivot = monthly_totals.pivot(\"Month\", \"Year\", 0)\n",
    "\n",
    "    return monthly_pivot\n",
    "\n",
    "\n",
    "def static_plot_monthly_heatmaps(monthly_pivot, crimes):\n",
    "    plt.figure(figsize=(15, 8))\n",
    "    sns.heatmap(monthly_pivot, cmap=\"YlGnBu\", linewidths=.5)\n",
    "    plt.title(f'Monthly Distribution of {\", \".join(str(crime) for crime in crimes)} Crimes in London (2010-2023)', fontsize=15)\n",
    "    plt.xlabel('Year', fontsize=12)\n",
    "    plt.ylabel('Month', fontsize=12)\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "# Example useage\n",
    "crimes = ['Violence Against the Person']\n",
    "monthly_pivot = prep_data_for_monthly_heat_maps(df, crimes)\n",
    "static_plot_monthly_heatmaps(monthly_pivot=monthly_pivot, crimes=crimes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "coloraxis": "coloraxis",
         "hovertemplate": "Year: %{x}<br>Month: %{y}<br>Total Crime Counts: %{z}<extra></extra>",
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        },
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   "source": [
    "def interactive_monthly_heat_map(monthly_pivot, crimes):\n",
    "    fig = px.imshow(monthly_pivot,\n",
    "                    labels=dict(x=\"Year\", y=\"Month\", color=\"Total Crime Counts\"),\n",
    "                    x=monthly_pivot.columns,\n",
    "                    y=monthly_pivot.index,\n",
    "                    title=f'Monthly Distribution of {\", \".join(str(crime) for crime in crimes)} Crimes in London (2010-2023)',\n",
    "                    color_continuous_scale='YlGnBu')  # Yellow to Green to Blue color scale\n",
    "\n",
    "    fig.update_xaxes(side=\"bottom\")\n",
    "    fig.update_layout(\n",
    "        xaxis_nticks=36,\n",
    "        width=1000,  # Set the width of the figure\n",
    "        height=800   # Set the height of the figure\n",
    "    )\n",
    "    fig.show()\n",
    "\n",
    "# Example usage\n",
    "interactive_monthly_heat_map(monthly_pivot=monthly_pivot, crimes = crimes)"
   ]
  }
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