{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8d469c00",
   "metadata": {
    "papermill": {
     "duration": 0.00758,
     "end_time": "2025-09-03T15:40:33.848929",
     "exception": false,
     "start_time": "2025-09-03T15:40:33.841349",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Imports "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2d145129",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:33.864233Z",
     "iopub.status.busy": "2025-09-03T15:40:33.863922Z",
     "iopub.status.idle": "2025-09-03T15:40:37.758201Z",
     "shell.execute_reply": "2025-09-03T15:40:37.757152Z"
    },
    "papermill": {
     "duration": 3.904241,
     "end_time": "2025-09-03T15:40:37.760007",
     "exception": false,
     "start_time": "2025-09-03T15:40:33.855766",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd, numpy as np\n",
    "import matplotlib.pyplot as plt, seaborn as sns\n",
    "from IPython.display import display\n",
    "import warnings; warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (12,6)\n",
    "plt.rcParams[\"axes.spines.top\"] = False\n",
    "plt.rcParams[\"axes.spines.right\"] = False\n",
    "SEED = 42\n",
    "rng = np.random.default_rng(SEED)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98602892",
   "metadata": {
    "papermill": {
     "duration": 0.006235,
     "end_time": "2025-09-03T15:40:37.772973",
     "exception": false,
     "start_time": "2025-09-03T15:40:37.766738",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Load Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e5f6a25a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:37.788130Z",
     "iopub.status.busy": "2025-09-03T15:40:37.787663Z",
     "iopub.status.idle": "2025-09-03T15:40:38.905714Z",
     "shell.execute_reply": "2025-09-03T15:40:38.904769Z"
    },
    "papermill": {
     "duration": 1.127222,
     "end_time": "2025-09-03T15:40:38.907460",
     "exception": false,
     "start_time": "2025-09-03T15:40:37.780238",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "charging = pd.read_csv(\"/kaggle/input/global-ev-charging-stations/charging_stations_2025_world.csv\")\n",
    "country = pd.read_csv(\"/kaggle/input/global-ev-charging-stations/country_summary_2025.csv\")\n",
    "ev_models = pd.read_csv(\"/kaggle/input/global-ev-charging-stations/ev_models_2025.csv\")\n",
    "world = pd.read_csv(\"/kaggle/input/global-ev-charging-stations/world_summary_2025.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f40a4176",
   "metadata": {
    "papermill": {
     "duration": 0.006495,
     "end_time": "2025-09-03T15:40:38.920974",
     "exception": false,
     "start_time": "2025-09-03T15:40:38.914479",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Summarize Helper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a2d6452e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:38.935388Z",
     "iopub.status.busy": "2025-09-03T15:40:38.935059Z",
     "iopub.status.idle": "2025-09-03T15:40:39.567931Z",
     "shell.execute_reply": "2025-09-03T15:40:39.566830Z"
    },
    "papermill": {
     "duration": 0.641745,
     "end_time": "2025-09-03T15:40:39.569288",
     "exception": false,
     "start_time": "2025-09-03T15:40:38.927543",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Charging Stations ===\n",
      "Shape: (242417, 11) \n",
      "\n",
      "Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 242417 entries, 0 to 242416\n",
      "Data columns (total 11 columns):\n",
      " #   Column          Non-Null Count   Dtype  \n",
      "---  ------          --------------   -----  \n",
      " 0   id              242417 non-null  int64  \n",
      " 1   name            242417 non-null  object \n",
      " 2   city            220228 non-null  object \n",
      " 3   country_code    242416 non-null  object \n",
      " 4   state_province  172419 non-null  object \n",
      " 5   latitude        242417 non-null  float64\n",
      " 6   longitude       242417 non-null  float64\n",
      " 7   ports           242417 non-null  int64  \n",
      " 8   power_kw        237757 non-null  float64\n",
      " 9   power_class     242417 non-null  object \n",
      " 10  is_fast_dc      242417 non-null  bool   \n",
      "dtypes: bool(1), float64(3), int64(2), object(5)\n",
      "memory usage: 18.7+ MB\n",
      "\n",
      "\n",
      "Describe:\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>unique</th>\n",
       "      <th>top</th>\n",
       "      <th>freq</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <td>242417.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>204039.926519</td>\n",
       "      <td>101789.186799</td>\n",
       "      <td>2389.0</td>\n",
       "      <td>122882.0</td>\n",
       "      <td>208085.0</td>\n",
       "      <td>280795.0</td>\n",
       "      <td>460650.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>242417</td>\n",
       "      <td>225282</td>\n",
       "      <td>Shell Recharge/Ubitricity</td>\n",
       "      <td>1166</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>city</th>\n",
       "      <td>220228</td>\n",
       "      <td>41815</td>\n",
       "      <td>London</td>\n",
       "      <td>7665</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>country_code</th>\n",
       "      <td>242416</td>\n",
       "      <td>120</td>\n",
       "      <td>US</td>\n",
       "      <td>82138</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>state_province</th>\n",
       "      <td>172419</td>\n",
       "      <td>5988</td>\n",
       "      <td>CA</td>\n",
       "      <td>17528</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>latitude</th>\n",
       "      <td>242417.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>43.253894</td>\n",
       "      <td>12.692335</td>\n",
       "      <td>-55.811599</td>\n",
       "      <td>38.859333</td>\n",
       "      <td>44.414623</td>\n",
       "      <td>51.41389</td>\n",
       "      <td>81.736061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>longitude</th>\n",
       "      <td>242417.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-32.07416</td>\n",
       "      <td>57.652645</td>\n",
       "      <td>-164.848855</td>\n",
       "      <td>-81.644018</td>\n",
       "      <td>-2.867264</td>\n",
       "      <td>7.883693</td>\n",
       "      <td>178.369254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ports</th>\n",
       "      <td>242417.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.959277</td>\n",
       "      <td>3.931007</td>\n",
       "      <td>-4.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>503.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>power_kw</th>\n",
       "      <td>237757.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>35.253735</td>\n",
       "      <td>2051.557432</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.7</td>\n",
       "      <td>11.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1000000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>power_class</th>\n",
       "      <td>242417</td>\n",
       "      <td>6</td>\n",
       "      <td>AC_L1_(&lt;7.5kW)</td>\n",
       "      <td>107144</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>is_fast_dc</th>\n",
       "      <td>242417</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>191584</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   count  unique                        top    freq  \\\n",
       "id              242417.0     NaN                        NaN     NaN   \n",
       "name              242417  225282  Shell Recharge/Ubitricity    1166   \n",
       "city              220228   41815                     London    7665   \n",
       "country_code      242416     120                         US   82138   \n",
       "state_province    172419    5988                         CA   17528   \n",
       "latitude        242417.0     NaN                        NaN     NaN   \n",
       "longitude       242417.0     NaN                        NaN     NaN   \n",
       "ports           242417.0     NaN                        NaN     NaN   \n",
       "power_kw        237757.0     NaN                        NaN     NaN   \n",
       "power_class       242417       6             AC_L1_(<7.5kW)  107144   \n",
       "is_fast_dc        242417       2                      False  191584   \n",
       "\n",
       "                         mean            std         min        25%  \\\n",
       "id              204039.926519  101789.186799      2389.0   122882.0   \n",
       "name                      NaN            NaN         NaN        NaN   \n",
       "city                      NaN            NaN         NaN        NaN   \n",
       "country_code              NaN            NaN         NaN        NaN   \n",
       "state_province            NaN            NaN         NaN        NaN   \n",
       "latitude            43.253894      12.692335  -55.811599  38.859333   \n",
       "longitude           -32.07416      57.652645 -164.848855 -81.644018   \n",
       "ports                1.959277       3.931007        -4.0        1.0   \n",
       "power_kw            35.253735    2051.557432         0.0        3.7   \n",
       "power_class               NaN            NaN         NaN        NaN   \n",
       "is_fast_dc                NaN            NaN         NaN        NaN   \n",
       "\n",
       "                      50%       75%         max  \n",
       "id               208085.0  280795.0    460650.0  \n",
       "name                  NaN       NaN         NaN  \n",
       "city                  NaN       NaN         NaN  \n",
       "country_code          NaN       NaN         NaN  \n",
       "state_province        NaN       NaN         NaN  \n",
       "latitude        44.414623  51.41389   81.736061  \n",
       "longitude       -2.867264  7.883693  178.369254  \n",
       "ports                 1.0       2.0       503.0  \n",
       "power_kw             11.0      22.0   1000000.0  \n",
       "power_class           NaN       NaN         NaN  \n",
       "is_fast_dc            NaN       NaN         NaN  "
      ]
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      "\n",
      "\n",
      "Head:\n"
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       "      <th>id</th>\n",
       "      <th>name</th>\n",
       "      <th>city</th>\n",
       "      <th>country_code</th>\n",
       "      <th>state_province</th>\n",
       "      <th>latitude</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>307660</td>\n",
       "      <td>Av. de Tarragona</td>\n",
       "      <td>Andorra</td>\n",
       "      <td>AD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.505254</td>\n",
       "      <td>1.528861</td>\n",
       "      <td>10</td>\n",
       "      <td>300.0</td>\n",
       "      <td>DC_ULTRA_(&gt;=150kW)</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>301207</td>\n",
       "      <td>Parquing Costa Rodona</td>\n",
       "      <td>Encamp</td>\n",
       "      <td>AD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.537213</td>\n",
       "      <td>1.727014</td>\n",
       "      <td>10</td>\n",
       "      <td>22.0</td>\n",
       "      <td>AC_HIGH_(22-49kW)</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>301206</td>\n",
       "      <td>Hotel Naudi</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.576811</td>\n",
       "      <td>1.666061</td>\n",
       "      <td>1</td>\n",
       "      <td>11.0</td>\n",
       "      <td>AC_L2_(7.5-21kW)</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>301205</td>\n",
       "      <td>Hotel Piolets Soldeu Centre</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.576466</td>\n",
       "      <td>1.667317</td>\n",
       "      <td>1</td>\n",
       "      <td>22.0</td>\n",
       "      <td>AC_HIGH_(22-49kW)</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>301204</td>\n",
       "      <td>Hotel Serras</td>\n",
       "      <td>NaN</td>\n",
       "      <td>AD</td>\n",
       "      <td>NaN</td>\n",
       "      <td>42.579458</td>\n",
       "      <td>1.659215</td>\n",
       "      <td>3</td>\n",
       "      <td>11.0</td>\n",
       "      <td>AC_L2_(7.5-21kW)</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       id                         name     city country_code state_province  \\\n",
       "0  307660             Av. de Tarragona  Andorra           AD            NaN   \n",
       "1  301207        Parquing Costa Rodona   Encamp           AD            NaN   \n",
       "2  301206                  Hotel Naudi      NaN           AD            NaN   \n",
       "3  301205  Hotel Piolets Soldeu Centre      NaN           AD            NaN   \n",
       "4  301204                 Hotel Serras      NaN           AD            NaN   \n",
       "\n",
       "    latitude  longitude  ports  power_kw         power_class  is_fast_dc  \n",
       "0  42.505254   1.528861     10     300.0  DC_ULTRA_(>=150kW)        True  \n",
       "1  42.537213   1.727014     10      22.0   AC_HIGH_(22-49kW)       False  \n",
       "2  42.576811   1.666061      1      11.0    AC_L2_(7.5-21kW)       False  \n",
       "3  42.576466   1.667317      1      22.0   AC_HIGH_(22-49kW)       False  \n",
       "4  42.579458   1.659215      3      11.0    AC_L2_(7.5-21kW)       False  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "\n",
      "=== Countries ===\n",
      "Shape: (122, 2) \n",
      "\n",
      "Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 122 entries, 0 to 121\n",
      "Data columns (total 2 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   country_code  121 non-null    object\n",
      " 1   stations      122 non-null    int64 \n",
      "dtypes: int64(1), object(1)\n",
      "memory usage: 2.0+ KB\n",
      "\n",
      "\n",
      "Describe:\n"
     ]
    },
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       "              count unique  top freq         mean          std  min   25%  \\\n",
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       "stations      122.0    NaN  NaN  NaN  1987.032787  8420.817716  1.0  5.25   \n",
       "\n",
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       "stations      52.5  531.5  82138.0  "
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       "  country_code  stations\n",
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      "\n",
      "============================================================\n",
      "\n",
      "=== EV Models ===\n",
      "Shape: (63, 7) \n",
      "\n",
      "Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 63 entries, 0 to 62\n",
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      "dtypes: int64(1), object(6)\n",
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      "\n",
      "\n",
      "Describe:\n"
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       "      <td>NaN</td>\n",
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       "               count unique      top freq         mean       std     min  \\\n",
       "make              63     33    Tesla    5          NaN       NaN     NaN   \n",
       "model             63     63  Model S    1          NaN       NaN     NaN   \n",
       "market_regions    63     29    EU/UK   11          NaN       NaN     NaN   \n",
       "powertrain        63      1      BEV   63          NaN       NaN     NaN   \n",
       "first_year      63.0    NaN      NaN  NaN  2020.428571  2.486832  2010.0   \n",
       "body_style        63     11      SUV   25          NaN       NaN     NaN   \n",
       "origin_country    63     14       US   13          NaN       NaN     NaN   \n",
       "\n",
       "                   25%     50%     75%     max  \n",
       "make               NaN     NaN     NaN     NaN  \n",
       "model              NaN     NaN     NaN     NaN  \n",
       "market_regions     NaN     NaN     NaN     NaN  \n",
       "powertrain         NaN     NaN     NaN     NaN  \n",
       "first_year      2020.0  2021.0  2022.0  2025.0  \n",
       "body_style         NaN     NaN     NaN     NaN  \n",
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       "    make       model           market_regions powertrain  first_year  \\\n",
       "0  Tesla     Model S     Global (US/EU/UK/ME)        BEV        2012   \n",
       "1  Tesla     Model 3  Global (US/EU/UK/ME/CN)        BEV        2017   \n",
       "2  Tesla     Model X     Global (US/EU/UK/ME)        BEV        2015   \n",
       "3  Tesla     Model Y  Global (US/EU/UK/ME/CN)        BEV        2020   \n",
       "4  Tesla  Cybertruck             US (limited)        BEV        2023   \n",
       "\n",
       "  body_style origin_country  \n",
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       "4     Pickup             US  "
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      "\n",
      "============================================================\n",
      "\n",
      "=== World Summary ===\n",
      "Shape: (122, 4) \n",
      "\n",
      "Info:\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 122 entries, 0 to 121\n",
      "Data columns (total 4 columns):\n",
      " #   Column            Non-Null Count  Dtype  \n",
      "---  ------            --------------  -----  \n",
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      " 1   country           122 non-null    object \n",
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      " 3   max_power_kw_max  118 non-null    float64\n",
      "dtypes: float64(1), int64(1), object(2)\n",
      "memory usage: 3.9+ KB\n",
      "\n",
      "\n",
      "Describe:\n"
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       "                  count unique            top freq         mean           std  \\\n",
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       "count             122.0    NaN            NaN  NaN  2035.204918   8616.963391   \n",
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       "\n",
       "                  min    25%    50%    75%        max  \n",
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       "count             1.0   5.25   57.0  564.0    83821.0  \n",
       "max_power_kw_max  7.0  72.75  180.0  357.5  1000000.0  "
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       "      <td>83821</td>\n",
       "      <td>600.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GB</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>27437</td>\n",
       "      <td>560.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>DE</td>\n",
       "      <td>Germany</td>\n",
       "      <td>24465</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>CA</td>\n",
       "      <td>Canada</td>\n",
       "      <td>18203</td>\n",
       "      <td>400.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ES</td>\n",
       "      <td>Spain</td>\n",
       "      <td>17864</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country_code         country  count  max_power_kw_max\n",
       "0           US   United States  83821             600.0\n",
       "1           GB  United Kingdom  27437             560.0\n",
       "2           DE         Germany  24465             400.0\n",
       "3           CA          Canada  18203             400.0\n",
       "4           ES           Spain  17864            1000.0"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "============================================================\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def summarize(df, name):\n",
    "    \n",
    "    print(f\"=== {name} ===\")\n",
    "    \n",
    "    print(\"Shape:\", df.shape, \"\\n\")\n",
    "    \n",
    "    print(\"Info:\")\n",
    "    df.info()\n",
    "    print(\"\\n\")\n",
    "    \n",
    "    print(\"Describe:\")\n",
    "    display(df.describe(include=\"all\").transpose())\n",
    "    print(\"\\n\")\n",
    "    \n",
    "    print(\"Head:\")\n",
    "    display(df.head())\n",
    "    print(\"\\n\" + \"=\"*60 + \"\\n\")\n",
    "\n",
    "# --- Summaries ---\n",
    "summarize(charging, \"Charging Stations\")\n",
    "summarize(country, \"Countries\")\n",
    "summarize(ev_models, \"EV Models\")\n",
    "summarize(world, \"World Summary\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0188e01",
   "metadata": {
    "papermill": {
     "duration": 0.008284,
     "end_time": "2025-09-03T15:40:39.586695",
     "exception": false,
     "start_time": "2025-09-03T15:40:39.578411",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data Cleaning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a6646e7",
   "metadata": {
    "papermill": {
     "duration": 0.008135,
     "end_time": "2025-09-03T15:40:39.603142",
     "exception": false,
     "start_time": "2025-09-03T15:40:39.595007",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Missing & Duplicates\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "ebd1bcbb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:39.621240Z",
     "iopub.status.busy": "2025-09-03T15:40:39.620896Z",
     "iopub.status.idle": "2025-09-03T15:40:39.911388Z",
     "shell.execute_reply": "2025-09-03T15:40:39.910103Z"
    },
    "papermill": {
     "duration": 0.301746,
     "end_time": "2025-09-03T15:40:39.913179",
     "exception": false,
     "start_time": "2025-09-03T15:40:39.611433",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=== Missing Values ===\n",
      "\n",
      "Charging\n",
      "id                    0\n",
      "name                  0\n",
      "city              22189\n",
      "country_code          1\n",
      "state_province    69998\n",
      "latitude              0\n",
      "longitude             0\n",
      "ports                 0\n",
      "power_kw           4660\n",
      "power_class           0\n",
      "is_fast_dc            0\n",
      "dtype: int64\n",
      "\n",
      "Country\n",
      "country_code    1\n",
      "stations        0\n",
      "dtype: int64\n",
      "\n",
      "EV Models\n",
      "make              0\n",
      "model             0\n",
      "market_regions    0\n",
      "powertrain        0\n",
      "first_year        0\n",
      "body_style        0\n",
      "origin_country    0\n",
      "dtype: int64\n",
      "\n",
      "World\n",
      "country_code        1\n",
      "country             0\n",
      "count               0\n",
      "max_power_kw_max    4\n",
      "dtype: int64\n",
      "\n",
      "=== Duplicates ===\n",
      "Charging: 0\n",
      "Country: 0\n",
      "EV Models: 0\n",
      "World: 0\n"
     ]
    }
   ],
   "source": [
    "print(\"=== Missing Values ===\")\n",
    "for df, name in [(charging,\"Charging\"), (country,\"Country\"),\n",
    "                (ev_models,\"EV Models\"), (world,\"World\")]:\n",
    "    print(f\"\\n{name}\")\n",
    "    print(df.isna().sum())  \n",
    "\n",
    "print(\"\\n=== Duplicates ===\")\n",
    "print(\"Charging:\", charging.duplicated().sum())\n",
    "print(\"Country:\", country.duplicated().sum())\n",
    "print(\"EV Models:\", ev_models.duplicated().sum())\n",
    "print(\"World:\", world.duplicated().sum())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6115b49e",
   "metadata": {
    "papermill": {
     "duration": 0.00833,
     "end_time": "2025-09-03T15:40:39.930442",
     "exception": false,
     "start_time": "2025-09-03T15:40:39.922112",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Clean Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ae33d17f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:39.948990Z",
     "iopub.status.busy": "2025-09-03T15:40:39.948662Z",
     "iopub.status.idle": "2025-09-03T15:40:40.039806Z",
     "shell.execute_reply": "2025-09-03T15:40:40.038791Z"
    },
    "papermill": {
     "duration": 0.102635,
     "end_time": "2025-09-03T15:40:40.041645",
     "exception": false,
     "start_time": "2025-09-03T15:40:39.939010",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Fill missing city/state with \"Unknown\"\n",
    "charging[\"city\"] = charging[\"city\"].fillna(\"Unknown\")\n",
    "charging[\"state_province\"] = charging[\"state_province\"].fillna(\"Unknown\")\n",
    "\n",
    "# Fill missing power with median \n",
    "charging[\"power_kw\"] = charging[\"power_kw\"].fillna(charging[\"power_kw\"].median())\n",
    "\n",
    "# Drop rows with no country_code \n",
    "charging = charging.dropna(subset=[\"country_code\"])\n",
    "country = country.dropna(subset=[\"country_code\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d09d59a4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:40.060818Z",
     "iopub.status.busy": "2025-09-03T15:40:40.060403Z",
     "iopub.status.idle": "2025-09-03T15:40:40.096726Z",
     "shell.execute_reply": "2025-09-03T15:40:40.095473Z"
    },
    "papermill": {
     "duration": 0.047886,
     "end_time": "2025-09-03T15:40:40.098368",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.050482",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Charging shape: (242416, 11)\n",
      "Country shape: (121, 2)\n",
      "EV Models shape: (63, 7)\n",
      "World shape: (122, 4)\n"
     ]
    }
   ],
   "source": [
    "charging[\"country_code\"] = charging[\"country_code\"].astype(\"category\")\n",
    "if \"power_class\" in charging.columns:\n",
    "    charging[\"power_class\"] = charging[\"power_class\"].astype(\"category\")\n",
    "charging[\"is_fast_dc\"] = charging[\"is_fast_dc\"].astype(bool)\n",
    "\n",
    "print(\"Charging shape:\", charging.shape)\n",
    "print(\"Country shape:\", country.shape)\n",
    "print(\"EV Models shape:\", ev_models.shape)\n",
    "print(\"World shape:\", world.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfc23957",
   "metadata": {
    "papermill": {
     "duration": 0.008293,
     "end_time": "2025-09-03T15:40:40.115461",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.107168",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Sanity Checks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2b8d0e59",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:40.133998Z",
     "iopub.status.busy": "2025-09-03T15:40:40.133632Z",
     "iopub.status.idle": "2025-09-03T15:40:40.191837Z",
     "shell.execute_reply": "2025-09-03T15:40:40.190826Z"
    },
    "papermill": {
     "duration": 0.069476,
     "end_time": "2025-09-03T15:40:40.193447",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.123971",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Realistic max power_kw (P99.5): 350.0\n",
      "99th percentile power_kw: 350.0\n"
     ]
    }
   ],
   "source": [
    "charging = charging[(charging[\"latitude\"].between(-90, 90)) &\n",
    "                    (charging[\"longitude\"].between(-180, 180))]\n",
    "\n",
    "print(\"Realistic max power_kw (P99.5):\", charging[\"power_kw\"].quantile(0.995))\n",
    "print(\"99th percentile power_kw:\", charging[\"power_kw\"].quantile(0.99))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54a18606",
   "metadata": {
    "papermill": {
     "duration": 0.008573,
     "end_time": "2025-09-03T15:40:40.210833",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.202260",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2f1e0cd7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:40.295465Z",
     "iopub.status.busy": "2025-09-03T15:40:40.295173Z",
     "iopub.status.idle": "2025-09-03T15:40:40.324122Z",
     "shell.execute_reply": "2025-09-03T15:40:40.323118Z"
    },
    "papermill": {
     "duration": 0.106323,
     "end_time": "2025-09-03T15:40:40.325862",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.219539",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "charging[\"station_type\"] = charging[\"is_fast_dc\"].map({True:\"Fast DC\", False:\"Normal / AC\"})\n",
    "\n",
    "# Buckets\n",
    "power_bins   = [0, 22, 50, 150, 350, np.inf]\n",
    "power_labels = [\"≤22kW AC\",\"22–50kW DC\",\"50–150kW DC\",\"150–350kW DC\",\"Ultra >350kW\"]\n",
    "\n",
    "power_kw_viz = charging[\"power_kw\"].clip(upper=charging[\"power_kw\"].quantile(0.995))\n",
    "power_bucket_viz = pd.cut(power_kw_viz, bins=power_bins, labels=power_labels)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e5b73da",
   "metadata": {
    "papermill": {
     "duration": 0.008707,
     "end_time": "2025-09-03T15:40:40.343612",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.334905",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "\n",
    "# Country Dashboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d376a6f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:40.362253Z",
     "iopub.status.busy": "2025-09-03T15:40:40.361933Z",
     "iopub.status.idle": "2025-09-03T15:40:41.821441Z",
     "shell.execute_reply": "2025-09-03T15:40:41.820404Z"
    },
    "papermill": {
     "duration": 1.470895,
     "end_time": "2025-09-03T15:40:41.823165",
     "exception": false,
     "start_time": "2025-09-03T15:40:40.352270",
     "status": "completed"
    },
    "tags": []
   },
   "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>country_code</th>\n",
       "      <th>stations</th>\n",
       "      <th>ports</th>\n",
       "      <th>avg_ports</th>\n",
       "      <th>fast_share</th>\n",
       "      <th>p99_power</th>\n",
       "      <th>fast_share_pct</th>\n",
       "      <th>city</th>\n",
       "      <th>stations_city</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AD</td>\n",
       "      <td>96</td>\n",
       "      <td>259</td>\n",
       "      <td>2.697917</td>\n",
       "      <td>0.062500</td>\n",
       "      <td>186.00</td>\n",
       "      <td>6.2</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AE</td>\n",
       "      <td>131</td>\n",
       "      <td>346</td>\n",
       "      <td>2.641221</td>\n",
       "      <td>0.175573</td>\n",
       "      <td>250.00</td>\n",
       "      <td>17.6</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AF</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>22.00</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Ostholstein</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AL</td>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>1.066667</td>\n",
       "      <td>0.600000</td>\n",
       "      <td>174.68</td>\n",
       "      <td>60.0</td>\n",
       "      <td>Tirane</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AM</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>1.500000</td>\n",
       "      <td>0.250000</td>\n",
       "      <td>146.16</td>\n",
       "      <td>25.0</td>\n",
       "      <td>Ереван</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>AR</td>\n",
       "      <td>22</td>\n",
       "      <td>36</td>\n",
       "      <td>1.636364</td>\n",
       "      <td>0.954545</td>\n",
       "      <td>157.90</td>\n",
       "      <td>95.5</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>AT</td>\n",
       "      <td>1282</td>\n",
       "      <td>3474</td>\n",
       "      <td>2.709828</td>\n",
       "      <td>0.176287</td>\n",
       "      <td>350.00</td>\n",
       "      <td>17.6</td>\n",
       "      <td>Wien</td>\n",
       "      <td>87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>AU</td>\n",
       "      <td>1241</td>\n",
       "      <td>2701</td>\n",
       "      <td>2.176471</td>\n",
       "      <td>0.533441</td>\n",
       "      <td>350.00</td>\n",
       "      <td>53.3</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>AX</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>1.666667</td>\n",
       "      <td>0.666667</td>\n",
       "      <td>50.00</td>\n",
       "      <td>66.7</td>\n",
       "      <td>Mariehamn</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>59.51</td>\n",
       "      <td>50.0</td>\n",
       "      <td>Baku</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country_code  stations  ports  avg_ports  fast_share  p99_power  \\\n",
       "0           AD        96    259   2.697917    0.062500     186.00   \n",
       "1           AE       131    346   2.641221    0.175573     250.00   \n",
       "2           AF         1      1   1.000000    0.000000      22.00   \n",
       "3           AL        15     16   1.066667    0.600000     174.68   \n",
       "4           AM         4      6   1.500000    0.250000     146.16   \n",
       "5           AR        22     36   1.636364    0.954545     157.90   \n",
       "6           AT      1282   3474   2.709828    0.176287     350.00   \n",
       "7           AU      1241   2701   2.176471    0.533441     350.00   \n",
       "8           AX         3      5   1.666667    0.666667      50.00   \n",
       "9           AZ         2      2   1.000000    0.500000      59.51   \n",
       "\n",
       "   fast_share_pct         city  stations_city  \n",
       "0             6.2      Unknown             22  \n",
       "1            17.6        Dubai             59  \n",
       "2             0.0  Ostholstein              1  \n",
       "3            60.0       Tirane              4  \n",
       "4            25.0       Ереван              3  \n",
       "5            95.5      Unknown             12  \n",
       "6            17.6         Wien             87  \n",
       "7            53.3      Unknown             88  \n",
       "8            66.7    Mariehamn              2  \n",
       "9            50.0         Baku              1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "country_dash = (charging.groupby(\"country_code\")\n",
    "    .agg(\n",
    "        stations=(\"id\",\"count\"),\n",
    "        ports=(\"ports\",\"sum\"),\n",
    "        avg_ports=(\"ports\",\"mean\"),\n",
    "        fast_share=(\"is_fast_dc\",\"mean\"),\n",
    "        p99_power=(\"power_kw\", lambda s: s.quantile(0.99))\n",
    "    ).reset_index())\n",
    "country_dash[\"fast_share_pct\"] = (country_dash[\"fast_share\"]*100).round(1)\n",
    "\n",
    "\n",
    "top_city = (charging.groupby([\"country_code\",\"city\"])\n",
    "            .size().reset_index(name=\"stations_city\")\n",
    "            .sort_values([\"country_code\",\"stations_city\"], ascending=[True, False])\n",
    "            .drop_duplicates(\"country_code\"))\n",
    "country_dash = country_dash.merge(top_city[[\"country_code\",\"city\",\"stations_city\"]],\n",
    "                                  on=\"country_code\", how=\"left\")\n",
    "\n",
    "display(country_dash.head(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4bf40f1",
   "metadata": {
    "papermill": {
     "duration": 0.008694,
     "end_time": "2025-09-03T15:40:41.840960",
     "exception": false,
     "start_time": "2025-09-03T15:40:41.832266",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# EDA"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd9ddf4c",
   "metadata": {
    "papermill": {
     "duration": 0.008505,
     "end_time": "2025-09-03T15:40:41.858306",
     "exception": false,
     "start_time": "2025-09-03T15:40:41.849801",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Global Distribution of Stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9cd3164e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:41.877988Z",
     "iopub.status.busy": "2025-09-03T15:40:41.877641Z",
     "iopub.status.idle": "2025-09-03T15:40:42.355897Z",
     "shell.execute_reply": "2025-09-03T15:40:42.354992Z"
    },
    "papermill": {
     "duration": 0.490114,
     "end_time": "2025-09-03T15:40:42.357666",
     "exception": false,
     "start_time": "2025-09-03T15:40:41.867552",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.histplot(world[\"count\"], bins=50, color=\"teal\")\n",
    "plt.title(\"Distribution of Charging Stations per Country\", fontsize=14)\n",
    "plt.xlabel(\"Stations per Country\")\n",
    "plt.ylabel(\"Number of Countries\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d2f6ee8",
   "metadata": {
    "papermill": {
     "duration": 0.009215,
     "end_time": "2025-09-03T15:40:42.377065",
     "exception": false,
     "start_time": "2025-09-03T15:40:42.367850",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Top Countries by Stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "79a98822",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:42.397341Z",
     "iopub.status.busy": "2025-09-03T15:40:42.397016Z",
     "iopub.status.idle": "2025-09-03T15:40:42.680475Z",
     "shell.execute_reply": "2025-09-03T15:40:42.679440Z"
    },
    "papermill": {
     "duration": 0.295835,
     "end_time": "2025-09-03T15:40:42.682132",
     "exception": false,
     "start_time": "2025-09-03T15:40:42.386297",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_countries = country_dash.sort_values(\"stations\", ascending=False).head(15)\n",
    "\n",
    "sns.barplot(\n",
    "    data=top_countries,\n",
    "    x=\"stations\",\n",
    "    y=\"country_code\",\n",
    "    order=top_countries[\"country_code\"],   \n",
    "    palette=\"viridis\"\n",
    ")\n",
    "plt.title(\"Top 15 Countries by Charging Stations (2025)\", fontsize=14)\n",
    "plt.xlabel(\"Number of Stations\")\n",
    "plt.ylabel(\"Country\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64a9e938",
   "metadata": {
    "papermill": {
     "duration": 0.009679,
     "end_time": "2025-09-03T15:40:42.702172",
     "exception": false,
     "start_time": "2025-09-03T15:40:42.692493",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Fast vs Normal Stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8df3bd93",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:42.723406Z",
     "iopub.status.busy": "2025-09-03T15:40:42.723098Z",
     "iopub.status.idle": "2025-09-03T15:40:43.053698Z",
     "shell.execute_reply": "2025-09-03T15:40:43.052784Z"
    },
    "papermill": {
     "duration": 0.342937,
     "end_time": "2025-09-03T15:40:43.055117",
     "exception": false,
     "start_time": "2025-09-03T15:40:42.712180",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Pie Chart\n",
    "order = [False, True]\n",
    "counts = charging[\"is_fast_dc\"].value_counts().reindex(order, fill_value=0)\n",
    "plt.pie(counts.values, labels=[\"Normal / AC\",\"Fast DC\"], autopct=\"%1.1f%%\", startangle=90)\n",
    "plt.title(\"Fast DC vs Normal Charging Stations\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Bar Plot\n",
    "counts = charging[\"is_fast_dc\"].value_counts().reindex([False, True], fill_value=0)\n",
    "sns.barplot(x=[\"Normal / AC\",\"Fast DC\"], y=counts.values)\n",
    "plt.title(\"Fast DC vs Normal Charging Stations\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.xlabel(\"\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53838f69",
   "metadata": {
    "papermill": {
     "duration": 0.011847,
     "end_time": "2025-09-03T15:40:43.078626",
     "exception": false,
     "start_time": "2025-09-03T15:40:43.066779",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Fast share with min threshold "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "903a7084",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:43.104013Z",
     "iopub.status.busy": "2025-09-03T15:40:43.103688Z",
     "iopub.status.idle": "2025-09-03T15:40:43.372813Z",
     "shell.execute_reply": "2025-09-03T15:40:43.371843Z"
    },
    "papermill": {
     "duration": 0.283733,
     "end_time": "2025-09-03T15:40:43.374580",
     "exception": false,
     "start_time": "2025-09-03T15:40:43.090847",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmp = (\n",
    "    charging.groupby(\"country_code\")[\"is_fast_dc\"].agg([\"mean\",\"count\"])\n",
    "    .rename(columns={\"mean\":\"fast_share\",\"count\":\"n_stations\"})\n",
    "    .reset_index()\n",
    ")\n",
    "tmp = tmp[tmp[\"n_stations\"]>=100].sort_values(\"fast_share\", ascending=False).head(15)\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "sns.barplot(data=tmp, x=\"fast_share\", y=\"country_code\", order=tmp[\"country_code\"], color=\"darkgreen\")\n",
    "plt.title(\"Top Countries by Fast DC Share (min 100 stations)\")\n",
    "plt.xlabel(\"Fast DC Share\")\n",
    "plt.ylabel(\"Country\")\n",
    "plt.xlim(0,1)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "74514a4e",
   "metadata": {
    "papermill": {
     "duration": 0.011745,
     "end_time": "2025-09-03T15:40:43.399822",
     "exception": false,
     "start_time": "2025-09-03T15:40:43.388077",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Top Cities by Charging Stations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f78dc1ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:43.425086Z",
     "iopub.status.busy": "2025-09-03T15:40:43.424739Z",
     "iopub.status.idle": "2025-09-03T15:40:43.812803Z",
     "shell.execute_reply": "2025-09-03T15:40:43.811858Z"
    },
    "papermill": {
     "duration": 0.40274,
     "end_time": "2025-09-03T15:40:43.814614",
     "exception": false,
     "start_time": "2025-09-03T15:40:43.411874",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "city_counts = charging.loc[charging[\"city\"] != \"Unknown\", \"city\"] \\\n",
    "                      .value_counts().head(15)\n",
    "\n",
    "city_counts.plot(kind=\"bar\", color=\"coral\")\n",
    "plt.title(\"Top 15 Cities by Number of Charging Stations \", fontsize=14)\n",
    "plt.ylabel(\"Stations\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "94cf0160",
   "metadata": {
    "papermill": {
     "duration": 0.012786,
     "end_time": "2025-09-03T15:40:43.840775",
     "exception": false,
     "start_time": "2025-09-03T15:40:43.827989",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## EV Models Timeline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "23b76251",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:43.868756Z",
     "iopub.status.busy": "2025-09-03T15:40:43.868379Z",
     "iopub.status.idle": "2025-09-03T15:40:44.165563Z",
     "shell.execute_reply": "2025-09-03T15:40:44.164561Z"
    },
    "papermill": {
     "duration": 0.313108,
     "end_time": "2025-09-03T15:40:44.167201",
     "exception": false,
     "start_time": "2025-09-03T15:40:43.854093",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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s69u0atUqxo0bFx9//HG89tprccMNN8TGjRtj8ODB8cADD3zr9mnaUniwtfOdJEl89NFHxcKxrZ3vLb1n1apV2+K3+H3zWwo3jf/1IGxLNtV1+eWXb/V9HDFixLfWvrX6t2ZL22xq/+bD7i+44IIoLCyMe++9N9asWRMPPPBAtGvXbrNXqm2rsp6XV155JcaPHx99+vSJt99+O+644464/vrr45prrolTTz11i/sRSAHwXSOUAoBKqnr16jFgwIAoLCyMv//973H33XdHxFeB0vY67bTTolatWvHBBx/EmWeeudVbATt27Bi1atWKV155JdasWVNi/abbq/bdd9+IiGjfvn3UqlUrZs6cGevWrSvWd+PGjfHiiy+WGGPTN6Jtuo1ve1WrVi323XffGDZsWFEY9dRTT2Vl7NLYdD7LevVUxFe3n0XEZm9be/nll2PdunVF5zoiir6h7r///W+J/ptri4jYaaedYvny5SWCqdWrV5e4tbJevXqx9957x6JFi0qs+6aDDjooMplMTJ8+fav9vln7888/X2LdqlWrit2mWFqvvfZarFq1qkT7pnOx6fxucuKJJ0bTpk3jzjvvjEceeSRWrlwZ55xzTpn3uzVlPS/vvvtuREQcffTRJX42t/SeAsB3kVAKACqxTbfV3X777fHggw9Gw4YN46STTtrucRs1ahQTJ06Mxx9/PIYMGbLVvjVr1oz+/ftHfn5+jBw5sti6CRMmxMSJE2PPPfeM7t27R0REbm5unHzyybF8+fL4wx/+UKz/nXfeGe+8806JfVx00UWRk5MTP/vZzyIvL6/E+hUrVhQ9a2lL5syZs9mrZDa1ffP5VuVp07OIlixZUuZtTzvttMjJyYmbb7652HODvvjii7jiiisiIuKss84q1r969epx8803F7viqKCgIH77299udh8HHXRQrF+/Pu6///6itiRJYvjw4cVuIdtk8ODBsWHDhrjoooti7dq1xdatW7eu6Pa0XXbZJU4++eR48cUX4/e///1mr257+eWXi8LNVq1aRc+ePeONN94oVktExO9+97tYsWLFZuvfmhUrVpS4DXTTs8o6d+5c4rlgNWvWjLPOOivefvvt+OUvfxk1atQodn6zoaznpXXr1hFRMqybM2dOiZ9BAPgu80wpAEjJwoULN/uQ402uvPLKEsFJu3btomfPnjFt2rSI+OpWo68/q2Z79OzZs9R9b7jhhpg6dWr89re/jRdffDEOPvjgWLx4cTzyyCNRp06dGDt2bFSr9v//v65Ro0bFc889F7/+9a/j+eefj/322y/mzp0b//73v+PII4+M//znP8XG79y5c/z1r3+NCy+8MDp06BBHHXVU7LHHHvH555/He++9F1OnTo2zzjorbrvtti3W+Oyzz8YvfvGL6N69e7Rv3z6aNGkS7733Xjz11FNRq1atGDx4cNlP0jbq3bt3ZDKZ+OUvfxlz5syJhg0bRqNGjeLiiy/+1m332GOPuOGGG+Lyyy+PffbZJ04++eSoW7dujB8/PubPnx/HHXdcnH766UX999xzz7j66qtjxIgRRf1zcnLisccei3322Sfmz59fYh8XX3xxjB07Ns4555x49tlno2nTpvHf//43VqxYEV27di16APkmF154YUydOjUefvjhaNeuXRx77LHRoEGDyMvLi4kTJ8Zdd90Vxx9/fERE/PWvf4358+fHsGHD4r777otu3bpFo0aNYsmSJTFz5sxYsGBBLF26tOih+WPGjInu3bvHmWeeGU888US0a9cuZsyYEa+88koccsghZb4y6JBDDolbb701Xn755fjBD35QNE9r165d9Lyobzr//PPjpptuig8//DB+/OMfb/EZV9ujLOfl+9//fnz/+9+Phx9+OJYuXRo/+MEPIi8vL5566qk4+uij49FHH816fQBQIdL6mj8A2FFt+qr6b3t99tlnm93+nnvuKeozY8aMMu9/8uTJSUQk559//rf2Xbp0aRIRSa9evUqs+/jjj5NLLrkkad26dVKjRo1k5513Tk466aTkzTff3OxY77//fnLKKackjRo1SurUqZMccsghydSpU5MRI0YkEZFMnjy5xDYzZsxITj311KRFixZF+9h///2TK6+8Mpk7d25Rv03ndMCAAUVtb7/9dnLppZcm++23X9KkSZMkNzc32X333ZMBAwYkc+bM+dZjT5Itn6tevXolW/rYNGDAgCQikkWLFhVrHzduXNKlS5ckNzc3iYikdevWRetat25dbHlznnzyyaRXr15J/fr1k9zc3KRLly7JH/7wh2T9+vWb7X/HHXcke++9d1KzZs1kt912S37+858na9as2eL7OWnSpOTggw9OcnNzkyZNmiRnnHFG8tFHH23xWDdu3JjceeedyQ9+8IOkbt26SZ06dZJ27dolF1xwQZKXl1es75o1a5Ibb7wxOeCAA5K6desmtWvXTtq2bZscf/zxyb333lviGN58883kqKOOSurVq5fUr18/6du3b/Lmm29u8dxuztfnxFtvvZUcddRRSYMGDZK6desmhx9+eDJz5sytbt+jR48kIpIJEyZ86762ZtP521zNZTkvy5cvTwYNGpS0aNEiqVWrVtKlS5dkzJgxyXvvvVdi7idJ6eYUAFQ2mSQpxVNDAQCgilq3bl3stttuUa9evXjvvfeKXfUHAJQf/8UFAGCHNnbs2Pjkk0/i/PPPF0gBQIpcKQUAwA5p1KhR8fHHH8ff/va3qFu3brzzzjvRsGHDii4LAHYYQikAAHZImUwmatSoEV27do0///nP8YMf/KCiSwKAHYpv3wMAYIfk/80CQMVy0zwAAAAAqRNKAQAAAJC6Kh9KJUkSBQUFLs8GAAAAqESqfCj1+eefR8OGDePzzz+v6FIAAAAA+H+qfCgFAAAAQOUjlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFInlAIAAAAgdUIpAAAAAFJXoaHUtGnTol+/ftGiRYvIZDLxxBNPlOgzd+7cOPbYY6Nhw4ZRt27dOOiggyIvLy/9YgEAAADImgoNpVavXh1du3aNMWPGbHb9u+++Gz169IiOHTvGlClT4o033oirrroqatWqlXKlAAAAAGRTJkmSpKKLiIjIZDLx+OOPx/HHH1/Uduqpp0aNGjXivvvu2+ZxCwoKomHDhrFy5cpo0KBBFioFAAAAYHvlVHQBW7Jx48b417/+FcOGDYs+ffrEa6+9Fm3bto3hw4cXC66+qbCwMAoLC4uWCwoKUqgWAACoavLy8iI/Pz+rY+68887RqlWrrI4J8F1VaUOp5cuXx6pVq2LUqFHx29/+Nm644YaYMGFCnHjiiTF58uTo1avXZrcbOXJkXHvttSlXCwAAVCV5eXnRsUPHWLtubVbHrV2rdsybP08wBRCVOJTauHFjREQcd9xxMWTIkIiI2HfffePFF1+M2267bYuh1PDhw2Po0KFFywUFBdGyZcvyLxgAAKgy8vPzY+26tXHeXudFizotsjLmh2s+jNvn3h75+flCKYCoxKHUzjvvHDk5ObH33nsXa99rr73i+eef3+J2ubm5kZubW97lAQAAO4AWdVpEm/ptKroMgCqpQr99b2tq1qwZBx10UMyfP79Y+zvvvBOtW7euoKoAAAAAyIYKvVJq1apVsXDhwqLlRYsWxezZs6Nx48bRqlWr+MUvfhGnnHJK9OzZM3r37h0TJkyI8ePHx5QpUyquaAAAAAC2W4WGUjNnzozevXsXLW96FtSAAQNi3LhxccIJJ8Rtt90WI0eOjEsuuSQ6dOgQjz32WPTo0aOiSgYAAAAgCyo0lDr00EMjSZKt9hk0aFAMGjQopYoAAAAASEOlfaYUAAAAAFWXUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEidUAoAAACA1AmlAAAAAEhdhYZS06ZNi379+kWLFi0ik8nEE088scW+F1xwQWQymRg9enRq9QEAAABQPio0lFq9enV07do1xowZs9V+jz/+eLz00kvRokWLlCoDAAAAoDzlVOTO+/btG3379t1qnw8++CB+9rOfxcSJE+Poo49OqTIAAAAAylOFhlLfZuPGjXHGGWfEL37xi+jUqVOptiksLIzCwsKi5YKCgvIqDwAAAIBtVKkfdH7DDTdETk5OXHLJJaXeZuTIkdGwYcOiV8uWLcuxQgAAAAC2RaUNpWbNmhV/+tOfYty4cZHJZEq93fDhw2PlypVFryVLlpRjlQAAAABsi0obSv33v/+N5cuXR6tWrSInJydycnLi/fffj8svvzzatGmzxe1yc3OjQYMGxV4AAAAAVC6V9plSZ5xxRhx++OHF2vr06RNnnHFGDBw4sIKqAgAAACAbKjSUWrVqVSxcuLBoedGiRTF79uxo3LhxtGrVKpo0aVKsf40aNWKXXXaJDh06pF0qAAAAAFlUoaHUzJkzo3fv3kXLQ4cOjYiIAQMGxLhx4yqoKgAAAADKW4WGUoceemgkSVLq/osXLy6/YgAAAABITaV90DkAAAAAVZdQCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDU5VR0AQAAAFRdeXl5kZ+fn7Xxdt5552jVqlXWxgMqjlAKAACAcpGXlxcdO3SMtevWZm3M2rVqx7z58wRTUAUIpQAAACgX+fn5sXbd2jhvr/OiRZ0W2z3eh2s+jNvn3h75+flCKagChFIAAACUqxZ1WkSb+m0qugygkvGgcwAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSJ5QCAAAAIHVCKQAAAABSV6Gh1LRp06Jfv37RokWLyGQy8cQTTxStW79+fVxxxRXRpUuXqFu3brRo0SLOPPPM+PDDDyuuYAAAAACyokJDqdWrV0fXrl1jzJgxJdatWbMmXn311bjqqqvi1VdfjX/+858xf/78OPbYYyugUgAAAACyKacid963b9/o27fvZtc1bNgwnn322WJtf/nLX+L73/9+5OXlRatWrdIoEQAAAIByUKGhVFmtXLkyMplMNGrUaIt9CgsLo7CwsGi5oKAghcoAAKBqy8vLi/z8/KyNt/POO/sfzQA7uO9MKLVu3bq44ooron///tGgQYMt9hs5cmRce+21KVYGAABVW15eXnTs0DHWrlubtTFr16od8+bPE0wB7MC+E6HU+vXr4+STT44kSeLWW2/dat/hw4fH0KFDi5YLCgqiZcuW5V0iAABUWfn5+bF23do4b6/zokWdFts93odrPozb594e+fn5QimAHVilD6U2BVLvv/9+TJo0aatXSUVE5ObmRm5ubkrVAQDAjqNFnRbRpn6bii4DgCqiUodSmwKpBQsWxOTJk6NJkyYVXRIAAAAAWVChodSqVati4cKFRcuLFi2K2bNnR+PGjWPXXXeNk046KV599dV4+umnY8OGDbFs2bKIiGjcuHHUrFmzosoGAAAAYDtVaCg1c+bM6N27d9HypmdBDRgwIK655pp46qmnIiJi3333Lbbd5MmT49BDD02rTAAAAACyrEJDqUMPPTSSJNni+q2tAwAAAOC7q1pFFwAAAADAjkcoBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqtjuU2rBhQ8yePTs+++yzbNQDAAAAwA6gzKHUZZddFnfddVdEfBVI9erVK/bff/9o2bJlTJkyJdv1AQAAAFAFlTmUevTRR6Nr164RETF+/PhYtGhRzJs3L4YMGRK/+tWvsl4gAAAAAFVPmUOp/Pz82GWXXSIi4t///nf85Cc/ifbt28egQYPizTffzHqBAAAAAFQ9ZQ6lmjdvHm+//XZs2LAhJkyYEEcccURERKxZsyaqV6+e9QIBAAAAqHpyyrrBwIED4+STT45dd901MplMHH744RER8fLLL0fHjh2zXiAAAAAAVU+ZQ6lrrrkmOnfuHEuWLImf/OQnkZubGxER1atXjyuvvDLrBQIAAABQ9ZQ5lIqIOOmkk0q0DRgwYLuLAQAAAGDHUKpQ6pZbbin1gJdccsk2FwMAAADAjqFUodQf//jHUg2WyWSEUgAAAAB8q1KFUosWLSrvOgAAAADYgVTb1g2/+OKLmD9/fnz55ZfbvPNp06ZFv379okWLFpHJZOKJJ54otj5Jkrj66qtj1113jdq1a8fhhx8eCxYs2Ob9AQAAAFA5lDmUWrNmTZx99tlRp06d6NSpU+Tl5UVExM9+9rMYNWpUmcZavXp1dO3aNcaMGbPZ9TfeeGPccsstcdttt8XLL78cdevWjT59+sS6devKWjYAAAAAlUiZQ6nhw4fH66+/HlOmTIlatWoVtR9++OHx0EMPlWmsvn37xm9/+9s44YQTSqxLkiRGjx4dv/71r+O4446LffbZJ+6999748MMPS1xRBQAAAMB3S5lDqSeeeCL+8pe/RI8ePSKTyRS1d+rUKd59992sFbZo0aJYtmxZHH744UVtDRs2jIMPPjimT5++xe0KCwujoKCg2AsAAACAyqXModTHH38czZo1K9G+evXqYiHV9lq2bFlERDRv3rxYe/PmzYvWbc7IkSOjYcOGRa+WLVtmrSYAAAAAsqPModSBBx4Y//rXv4qWNwVRd955Z3Tr1i17lW2j4cOHx8qVK4teS5YsqeiSAAAAAPiGnLJu8Lvf/S769u0bb7/9dnz55Zfxpz/9Kd5+++148cUXY+rUqVkrbJdddomIiI8++ih23XXXovaPPvoo9t133y1ul5ubG7m5uVmrAwAAAIDsK/OVUj169IjZs2fHl19+GV26dIn//Oc/0axZs5g+fXoccMABWSusbdu2scsuu8Rzzz1X1FZQUBAvv/xypbgiCwAAAIBtV+YrpSIi9thjj7jjjju2e+erVq2KhQsXFi0vWrQoZs+eHY0bN45WrVrFZZddFr/97W+jXbt20bZt27jqqquiRYsWcfzxx2/3vgEAAACoOKUKpcryDXYNGjQodd+ZM2dG7969i5aHDh0aEREDBgyIcePGxbBhw2L16tVx3nnnxYoVK6JHjx4xYcKEqFWrVqn3AQAAAEDlU6pQqlGjRqX+Zr0NGzaUeueHHnpoJEmyxfWZTCauu+66uO6660o9JgAAAACVX6lCqcmTJxf9++LFi+PKK6+Ms846q+jZTtOnT4977rknRo4cWT5VAgAAAFCllCqU6tWrV9G/X3fddXHzzTdH//79i9qOPfbY6NKlS9x+++0xYMCA7FcJAAAAQJVS5m/fmz59ehx44IEl2g888MCYMWNGVooCAAAAoGorcyjVsmXLzX7z3p133hktW7bMSlEAAAAAVG2lun3v6/74xz/Gj3/843jmmWfi4IMPjoiIGTNmxIIFC+Kxxx7LeoEAAAAAVD1lvlLqqKOOigULFkS/fv3i008/jU8//TT69esX77zzThx11FHlUSMAAAAAVUyZr5SKiNhtt93id7/7XbZrAQAAAGAHsU2h1IoVK+Kuu+6KuXPnRkREp06dYtCgQdGwYcOsFgcAAABA1VTm2/dmzpwZe+yxR/zxj38sun3v5ptvjj322CNeffXV8qgRAAAAgCqmzFdKDRkyJI499ti44447Iifnq82//PLLOOecc+Kyyy6LadOmZb1IAAAAAKqWModSM2fOLBZIRUTk5OTEsGHD4sADD8xqcQAAAABUTWW+fa9BgwaRl5dXon3JkiVRv379rBQFAAAAQNVW5lDqlFNOibPPPjseeuihWLJkSSxZsiQefPDBOOecc6J///7lUSMAAAAAVUyZb9+76aabIpPJxJlnnhlffvllRETUqFEjLrzwwhg1alTWCwQAAACg6ilzKFWzZs3405/+FCNHjox33303IiL22GOPqFOnTtaLAwAAAKBqKnMotUmdOnWiS5cu2awFAAAAgB1EqUOpQYMGlarf3Xffvc3FAAAAALBjKHUoNW7cuGjdunXst99+kSRJedYEAAAAQBVX6lDqwgsvjAceeCAWLVoUAwcOjNNPPz0aN25cnrUBAAAAUEVVK23HMWPGxNKlS2PYsGExfvz4aNmyZZx88skxceJEV04BAAAAUCalDqUiInJzc6N///7x7LPPxttvvx2dOnWKiy66KNq0aROrVq0qrxoBAAAAqGLKFEoV27BatchkMpEkSWzYsCGbNQEAAABQxZUplCosLIwHHnggjjjiiGjfvn28+eab8Ze//CXy8vKiXr165VUjAAAAAFVMqR90ftFFF8WDDz4YLVu2jEGDBsUDDzwQO++8c3nWBgAAAEAVVepQ6rbbbotWrVrF7rvvHlOnTo2pU6dutt8///nPrBUHAAAAQNVU6lDqzDPPjEwmU561AAAAALCDKHUoNW7cuHIsAwAAAIAdyTZ/+x4AAAAAbCuhFAAAAACpE0oBAAAAkDqhFAAAAACpK1Uotf/++8dnn30WERHXXXddrFmzplyLAgAAAKBqK1UoNXfu3Fi9enVERFx77bWxatWqci0KAAAAgKotpzSd9t133xg4cGD06NEjkiSJm266KerVq7fZvldffXVWCwQAAACg6ilVKDVu3LgYMWJEPP3005HJZOKZZ56JnJySm2YyGaEUAAAAAN+qVKFUhw4d4sEHH4yIiGrVqsVzzz0XzZo1K9fCAAAAAKi6ShVKfd3GjRvLow4AAAAAdiBlDqUiIt59990YPXp0zJ07NyIi9t5777j00ktjjz32yGpxAAAAAFRNpfr2va+bOHFi7L333jFjxozYZ599Yp999omXX345OnXqFM8++2x51AgAAABAFVPmK6WuvPLKGDJkSIwaNapE+xVXXBFHHHFE1ooDAAAAoGoq85VSc+fOjbPPPrtE+6BBg+Ltt9/OSlEAAAAAVG1lDqWaNm0as2fPLtE+e/Zs38gHAAAAQKmU+fa9c889N84777x477334oc//GFERLzwwgtxww03xNChQ7NeIAAAAABVT5lDqauuuirq168ff/jDH2L48OEREdGiRYu45ppr4pJLLsl6gQAAAABUPWUOpTKZTAwZMiSGDBkSn3/+eURE1K9fP+uFAQAAAFB1lTmU+jphFAAAAADboswPOgcAAACA7SWUAgAAACB1QikAAAAAUlemUGr9+vVx2GGHxYIFC8qrnmI2bNgQV111VbRt2zZq164de+yxR/zmN7+JJElS2T8AAAAA5aNMDzqvUaNGvPHGG+VVSwk33HBD3HrrrXHPPfdEp06dYubMmTFw4MBo2LBhXHLJJanVAQAAAEB2lfn2vdNPPz3uuuuu8qilhBdffDGOO+64OProo6NNmzZx0kknxZFHHhkzZsxIZf8AAAAAlI8yXSkVEfHll1/G3XffHf/3f/8XBxxwQNStW7fY+ptvvjlrxf3whz+M22+/Pd55551o3759vP766/H8889vdR+FhYVRWFhYtFxQUJC1egAAAADIjjKHUm+99Vbsv//+ERHxzjvvFFuXyWSyU9X/c+WVV0ZBQUF07NgxqlevHhs2bIjrr78+fvrTn25xm5EjR8a1116b1ToAAAAAyK4yh1KTJ08ujzo26+GHH477778//vGPf0SnTp1i9uzZcdlll0WLFi1iwIABm91m+PDhMXTo0KLlgoKCaNmyZVolAwAAAFAKZQ6lNlm4cGG8++670bNnz6hdu3YkSZL1K6V+8YtfxJVXXhmnnnpqRER06dIl3n///Rg5cuQWQ6nc3NzIzc3Nah0AAAAAZFeZH3T+ySefxGGHHRbt27ePo446KpYuXRoREWeffXZcfvnlWS1uzZo1Ua1a8RKrV68eGzduzOp+AAAAAEhXmUOpIUOGRI0aNSIvLy/q1KlT1H7KKafEhAkTslpcv3794vrrr49//etfsXjx4nj88cfj5ptvjhNOOCGr+wEAAAAgXWW+fe8///lPTJw4MXbbbbdi7e3atYv3338/a4VFRPz5z3+Oq666Ki666KJYvnx5tGjRIs4///y4+uqrs7ofAAAAANJV5lBq9erVxa6Q2uTTTz/N+rOc6tevH6NHj47Ro0dndVwAAAAAKlaZb9875JBD4t577y1azmQysXHjxrjxxhujd+/eWS0OAAAAgKqpzFdK3XjjjXHYYYfFzJkz44svvohhw4bFnDlz4tNPP40XXnihPGoEAAAAoIop85VSnTt3jnfeeSd69OgRxx13XKxevTpOPPHEeO2112KPPfYojxoBAAAAqGLKfKVURETDhg3jV7/6VbZrAQAAAGAHsU2h1GeffRZ33XVXzJ07NyIi9t577xg4cGA0btw4q8UBAAAAUDWV+fa9adOmRZs2beKWW26Jzz77LD777LO45ZZbom3btjFt2rTyqBEAAACAKqbMV0oNHjw4TjnllLj11lujevXqERGxYcOGuOiii2Lw4MHx5ptvZr1IAAAAAKqWMl8ptXDhwrj88suLAqmIiOrVq8fQoUNj4cKFWS0OAAAAgKqpzKHU/vvvX/Qsqa+bO3dudO3aNStFAQAAAFC1ler2vTfeeKPo3y+55JK49NJLY+HChfGDH/wgIiJeeumlGDNmTIwaNap8qgQAAACgSilVKLXvvvtGJpOJJEmK2oYNG1ai32mnnRannHJK9qoDAAAAoEoqVSi1aNGi8q4DAAAAgB1IqUKp1q1bl3cdAAAAAOxAShVKfdOHH34Yzz//fCxfvjw2btxYbN0ll1ySlcIAAAAAqLrKHEqNGzcuzj///KhZs2Y0adIkMplM0bpMJiOUAgAAAOBblTmUuuqqq+Lqq6+O4cOHR7Vq1cqjJgAAAACquDKnSmvWrIlTTz1VIAUAAADANitzsnT22WfHI488Uh61AAAAALCDKPPteyNHjoxjjjkmJkyYEF26dIkaNWoUW3/zzTdnrTgAAAAAqqZtCqUmTpwYHTp0iIgo8aBzAAAAAPg2ZQ6l/vCHP8Tdd98dZ511VjmUAwAAAMCOoMzPlMrNzY3u3buXRy0AAAAA7CDKHEpdeuml8ec//7k8agEAAABgB1Hm2/dmzJgRkyZNiqeffjo6depU4kHn//znP7NWHAAAAABVU5lDqUaNGsWJJ55YHrUAAAAAsIMocyg1duzY8qgDAAAAgB1ImZ8pBQAAAADbq8xXSrVt2zYymcwW17/33nvbVRAAAAAAVV+ZQ6nLLrus2PL69evjtddeiwkTJsQvfvGLbNUFAAAAQBVW5lDq0ksv3Wz7mDFjYubMmdtdEAAAAABVX9aeKdW3b9947LHHsjUcAAAAAFVY1kKpRx99NBo3bpyt4QAAAACowsp8+95+++1X7EHnSZLEsmXL4uOPP46//vWvWS0OAAAAgKqpzKHU8ccfX2y5WrVq0bRp0zj00EOjY8eO2aoLAAAAgCqszKHUiBEjyqMOAAAAAHYgWXumFAAAAACUVqmvlKpWrVqxZ0ltTiaTiS+//HK7iwIAAACgait1KPX4449vcd306dPjlltuiY0bN2alKAAAAACqtlKHUscdd1yJtvnz58eVV14Z48ePj5/+9Kdx3XXXZbU4AAAAAKqmbXqm1IcffhjnnntudOnSJb788suYPXt23HPPPdG6dets1wcAAABAFVSmUGrlypVxxRVXxJ577hlz5syJ5557LsaPHx+dO3cur/oAAAAAqIJKffvejTfeGDfccEPssssu8cADD2z2dj4AAAAAKI1Sh1JXXnll1K5dO/bcc8+455574p577tlsv3/+859ZKw4AAACAqqnUodSZZ54ZmUymPGsBAAAAYAdR6lBq3Lhx5VgGAAAAADuSbfr2PQAAAADYHkIpAAAAAFInlAIAAAAgdZU+lPrggw/i9NNPjyZNmkTt2rWjS5cuMXPmzIouCwAAAIDtUOoHnVeEzz77LLp37x69e/eOZ555Jpo2bRoLFiyInXbaqaJLAwAAAGA7VOpQ6oYbboiWLVvG2LFji9ratm1bgRUBAAAAkA2V+va9p556Kg488MD4yU9+Es2aNYv99tsv7rjjjoouCwAAAIDtVKmvlHrvvffi1ltvjaFDh8Yvf/nLeOWVV+KSSy6JmjVrxoABAza7TWFhYRQWFhYtFxQUpFUuAAA7iLy8vMjPz8/aeDvvvHO0atUqa+MBFcvvCCidSh1Kbdy4MQ488MD43e9+FxER++23X7z11ltx2223bTGUGjlyZFx77bVplgkAwA4kLy8vOnboGGvXrc3amLVr1Y558+f5oxOqAL8joPQqdSi16667xt57712sba+99orHHntsi9sMHz48hg4dWrRcUFAQLVu2LLcaAQDYseTn58fadWvjvL3OixZ1Wmz3eB+u+TBun3t75Ofn+4MTqgC/I6D0KnUo1b1795g/f36xtnfeeSdat269xW1yc3MjNze3vEsDAGAH16JOi2hTv01FlwFUUn5HwLer1A86HzJkSLz00kvxu9/9LhYuXBj/+Mc/4vbbb4/BgwdXdGkAAAAAbIdKHUoddNBB8fjjj8cDDzwQnTt3jt/85jcxevTo+OlPf1rRpQEAAACwHSr17XsREcccc0wcc8wxFV0GAAAAAFlUqa+UAgAAAKBqEkoBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACpE0oBAAAAkDqhFAAAAACp+06FUqNGjYpMJhOXXXZZRZcCAAAAwHb4zoRSr7zySvztb3+LffbZp6JLAQAAAGA7fSdCqVWrVsVPf/rTuOOOO2KnnXaq6HIAAAAA2E7fiVBq8ODBcfTRR8fhhx9e0aUAAAAAkAU5FV3At3nwwQfj1VdfjVdeeaVU/QsLC6OwsLBouaCgoLxKAwAAAGAbVeorpZYsWRKXXnpp3H///VGrVq1SbTNy5Mho2LBh0atly5blXCUAAAAAZVWpQ6lZs2bF8uXLY//994+cnJzIycmJqVOnxi233BI5OTmxYcOGEtsMHz48Vq5cWfRasmRJBVQOAAAAwNZU6tv3DjvssHjzzTeLtQ0cODA6duwYV1xxRVSvXr3ENrm5uZGbm5tWiQAAAABsg0odStWvXz86d+5crK1u3brRpEmTEu0AAAAAfHdU6tv3AAAAAKiaKvWVUpszZcqUii4BAAAAgO3kSikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUpdT0QUAAJCevLy8yM/Pz9p4O++8c7Rq1Spr4wEAOw6hFADADiIvLy86dugYa9etzdqYtWvVjnnz5wmmAIAyE0oBAOwg8vPzY+26tXHeXudFizottnu8D9d8GLfPvT3y8/OFUgBAmQmlAAB2MC3qtIg29dtUdBkAwA7Og84BAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUCaUAAAAASJ1QCgAAAIDUVfpQauTIkXHQQQdF/fr1o1mzZnH88cfH/PnzK7osAAAAALZDpQ+lpk6dGoMHD46XXnopnn322Vi/fn0ceeSRsXr16oouDQAAAIBtlFPRBXybCRMmFFseN25cNGvWLGbNmhU9e/asoKoAAAAA2B6V/kqpb1q5cmVERDRu3LiCKwEAAABgW1X6K6W+buPGjXHZZZdF9+7do3PnzpvtU1hYGIWFhUXLBQUFaZUHAAAAQCl9p66UGjx4cLz11lvx4IMPbrHPyJEjo2HDhkWvli1bplghAAAAAKXxnQmlLr744nj66adj8uTJsdtuu22x3/Dhw2PlypVFryVLlqRYJQAAAAClUelv30uSJH72s5/F448/HlOmTIm2bdtutX9ubm7k5uamVB0AAAAA26LSh1KDBw+Of/zjH/Hkk09G/fr1Y9myZRER0bBhw6hdu3YFVwcAAADAtqj0t+/deuutsXLlyjj00ENj1113LXo99NBDFV0aAAAAANuo0l8plSRJRZcAAAAAQJZV+iulAAAAAKh6hFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqhFIAAAAApE4oBQAAAEDqciq6AMomLy8v8vPzszbezjvvHK1atcraeGSP9xpKz8/L9sv2OYz4bpxHcwcAssNniez4LhxzNgmlvkPy8vKiY4eOsXbd2qyNWbtW7Zg3f94ONem/C7zXUHp+XrZfeZzDiMp/Hs0dAMgOnyV8lthWQqnvkPz8/Fi7bm2ct9d50aJOi+0e78M1H8btc2+P/Pz8HWbCf1d4r6H0/Lxsv2yfw4jvxnk0dwAgO3yW8FliWwmlvoNa1GkRbeq3qegySIH3GkrPz8v221HP4Y563ACQbTvqf1N31OPOBg86BwAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUieUAgAAACB1QikAAAAAUvedCKXGjBkTbdq0iVq1asXBBx8cM2bMqOiSAAAAANgOlT6Ueuihh2Lo0KExYsSIePXVV6Nr167Rp0+fWL58eUWXBgAAAMA2qvSh1M033xznnntuDBw4MPbee++47bbbok6dOnH33XdXdGkAAAAAbKNKHUp98cUXMWvWrDj88MOL2qpVqxaHH354TJ8+vQIrAwAAAGB75FR0AVuTn58fGzZsiObNmxdrb968ecybN2+z2xQWFkZhYWHR8sqVKyMioqCgoPwKTcmqVasiImLx54tj3YZ12z3esjXLIiJi1qxZRWNnQ7Vq1WLjxo2VdrzyGDPb482fPz8iKvd7vSO+L+Ux5o5Y44748xJRuc9jts9hxHfj986OOHd2xGMuj/G+C+dxRzzmiMr98xLx3XivzZ3t55h3nJ+X8nqvV61aVSUyjIiI+vXrRyaT2eL6TJIkSYr1lMmHH34Y3/ve9+LFF1+Mbt26FbUPGzYspk6dGi+//HKJba655pq49tpr0ywTAAAAgG9YuXJlNGjQYIvrK/WVUjvvvHNUr149Pvroo2LtH330Ueyyyy6b3Wb48OExdOjQouWNGzfGp59+Gk2aNNlqOvddUFBQEC1btowlS5Zs9U1lx2R+sDXmB1tjfvBtzBG2xvxga8wPtsb8qPrq16+/1fWVOpSqWbNmHHDAAfHcc8/F8ccfHxFfhUzPPfdcXHzxxZvdJjc3N3Jzc4u1NWrUqJwrTVeDBg38wLJF5gdbY36wNeYH38YcYWvMD7bG/GBrzI8dV6UOpSIihg4dGgMGDIgDDzwwvv/978fo0aNj9erVMXDgwIouDQAAAIBtVOlDqVNOOSU+/vjjuPrqq2PZsmWx7777xoQJE0o8/BwAAACA745KH0pFRFx88cVbvF1vR5KbmxsjRowocXsiRJgfbJ35wdaYH3wbc4StMT/YGvODrTE/qNTfvgcAAABA1VStogsAAAAAYMcjlAIAAAAgdUIpAAAAAFInlErZyJEj46CDDor69etHs2bN4vjjj4/58+cX67Nu3boYPHhwNGnSJOrVqxc//vGP46OPPirW55JLLokDDjggcnNzY999993svt5444045JBDolatWtGyZcu48cYby+uwyJK05seUKVPiuOOOi1133TXq1q0b++67b9x///3leWhkQZq/PzZZuHBh1K9fPxo1apTloyHb0pwfSZLETTfdFO3bt4/c3Nz43ve+F9dff315HRpZkOb8mDhxYvzgBz+I+vXrR9OmTePHP/5xLF68uJyOjGzIxvx4/fXXo3///tGyZcuoXbt27LXXXvGnP/2pxL6mTJkS+++/f+Tm5saee+4Z48aNK+/DYzulNT/++c9/xhFHHBFNmzaNBg0aRLdu3WLixImpHCPbLs3fH5u88MILkZOT862fY/luEEqlbOrUqTF48OB46aWX4tlnn43169fHkUceGatXry7qM2TIkBg/fnw88sgjMXXq1Pjwww/jxBNPLDHWoEGD4pRTTtnsfgoKCuLII4+M1q1bx6xZs+L3v/99XHPNNXH77beX27Gx/dKaHy+++GLss88+8dhjj8Ubb7wRAwcOjDPPPDOefvrpcjs2tl9a82OT9evXR//+/eOQQw7J+rGQfWnOj0svvTTuvPPOuOmmm2LevHnx1FNPxfe///1yOS6yI635sWjRojjuuOPiRz/6UcyePTsmTpwY+fn5mx2HyiMb82PWrFnRrFmz+Pvf/x5z5syJX/3qVzF8+PD4y1/+UtRn0aJFcfTRR0fv3r1j9uzZcdlll8U555wjeKjk0pof06ZNiyOOOCL+/e9/x6xZs6J3797Rr1+/eO2111I9XsomrfmxyYoVK+LMM8+Mww47LJXjIwUJFWr58uVJRCRTp05NkiRJVqxYkdSoUSN55JFHivrMnTs3iYhk+vTpJbYfMWJE0rVr1xLtf/3rX5OddtopKSwsLGq74oorkg4dOmT/ICg35TU/Nueoo45KBg4cmJW6SUd5z49hw4Ylp59+ejJ27NikYcOG2S6fclZe8+Ptt99OcnJyknnz5pVb7ZS/8pofjzzySJKTk5Ns2LChqO2pp55KMplM8sUXX2T/QCgX2zs/NrnooouS3r17Fy0PGzYs6dSpU7E+p5xyStKnT58sHwHlqbzmx+bsvffeybXXXpudwklFec+PU045Jfn1r39dpr9zqNxcKVXBVq5cGRERjRs3joivUuL169fH4YcfXtSnY8eO0apVq5g+fXqpx50+fXr07NkzatasWdTWp0+fmD9/fnz22WdZqp7yVl7zY0v72rQfvhvKc35MmjQpHnnkkRgzZkz2CiZV5TU/xo8fH7vvvns8/fTT0bZt22jTpk2cc8458emnn2b3AChX5TU/DjjggKhWrVqMHTs2NmzYECtXroz77rsvDj/88KhRo0Z2D4Jyk6358c3PFtOnTy82RsRXn0+39zMM6Sqv+fFNGzdujM8//9zn0++Y8pwfY8eOjffeey9GjBhRDpVTUYRSFWjjxo1x2WWXRffu3aNz584REbFs2bKoWbNmiee3NG/ePJYtW1bqsZctWxbNmzcvMcamdVR+5Tk/vunhhx+OV155JQYOHLg9JZOi8pwfn3zySZx11lkxbty4aNCgQTbLJiXlOT/ee++9eP/99+ORRx6Je++9N8aNGxezZs2Kk046KZuHQDkqz/nRtm3b+M9//hO//OUvIzc3Nxo1ahT/+9//4uGHH87mIVCOsjU/XnzxxXjooYfivPPOK2rb0ufTgoKCWLt2bXYPhHJRnvPjm2666aZYtWpVnHzyyVmrn/JVnvNjwYIFceWVV8bf//73yMnJKbdjIH3ezQo0ePDgeOutt+L555+v6FKohNKaH5MnT46BAwfGHXfcEZ06dSrXfZE95Tk/zj333DjttNOiZ8+eWR+bdJTn/Ni4cWMUFhbGvffeG+3bt4+IiLvuuisOOOCAmD9/fnTo0CHr+yS7ynN+LFu2LM4999wYMGBA9O/fPz7//PO4+uqr46STTopnn302MplM1vdJdmVjfrz11ltx3HHHxYgRI+LII4/MYnVUtLTmxz/+8Y+49tpr48knn4xmzZpt875IV3nNjw0bNsRpp50W1157bdFnD6oOV0pVkIsvvjiefvrpmDx5cuy2225F7bvsskt88cUXsWLFimL9P/roo9hll11KPf4uu+xS4htzNi2XZRwqRnnPj02mTp0a/fr1iz/+8Y9x5plnbm/ZpKS858ekSZPipptuipycnMjJyYmzzz47Vq5cGTk5OXH33Xdn6zAoJ+U9P3bdddfIyckp9qFwr732ioiIvLy87Sueclfe82PMmDHRsGHDuPHGG2O//faLnj17xt///vd47rnn4uWXX87WYVBOsjE/3n777TjssMPivPPOi1//+tfF1m3p82mDBg2idu3a2T0Ysq6858cmDz74YJxzzjnx8MMPl7jdk8qrPOfH559/HjNnzoyLL7646PPpddddF6+//nrk5OTEpEmTyvXYKF9CqZQlSRIXX3xxPP744zFp0qRo27ZtsfUHHHBA1KhRI5577rmitvnz50deXl5069at1Pvp1q1bTJs2LdavX1/U9uyzz0aHDh1ip5122v4DoVykNT8ivvpK5qOPPjpuuOGGrV46TeWR1vyYPn16zJ49u+h13XXXRf369WP27NlxwgknZO14yK605kf37t3jyy+/jHfffbeo7Z133omIiNatW2/nUVBe0pofa9asiWrVin+8rF69ekR8dZUdlVO25secOXOid+/eMWDAgLj++utL7Kdbt27Fxoj46vNpWT/DkK605kdExAMPPBADBw6MBx54II4++ujyOSCyKo350aBBg3jzzTeLfT694IILokOHDjF79uw4+OCDy/cgKV8V94z1HdOFF16YNGzYMJkyZUqydOnSoteaNWuK+lxwwQVJq1atkkmTJiUzZ85MunXrlnTr1q3YOAsWLEhee+215Pzzz0/at2+fvPbaa8lrr71W9G17K1asSJo3b56cccYZyVtvvZU8+OCDSZ06dZK//e1vqR4vZZPW/Jg0aVJSp06dZPjw4cX288knn6R6vJRNWvPjm3z73ndDWvNjw4YNyf7775/07NkzefXVV5OZM2cmBx98cHLEEUekeryUTVrz47nnnksymUxy7bXXJu+8804ya9aspE+fPknr1q2L7YvKJRvz480330yaNm2anH766cXGWL58eVGf9957L6lTp07yi1/8Ipk7d24yZsyYpHr16smECRNSPV7KJq35cf/99yc5OTnJmDFjivVZsWJFqsdL2aQ1P77Jt+9VHUKplEXEZl9jx44t6rN27drkoosuSnbaaaekTp06yQknnJAsXbq02Di9evXa7DiLFi0q6vP6668nPXr0SHJzc5Pvfe97yahRo1I6SrZVWvNjwIABm13fq1ev9A6WMkvz98fXCaW+G9KcHx988EFy4oknJvXq1UuaN2+enHXWWULtSi7N+fHAAw8k++23X1K3bt2kadOmybHHHpvMnTs3pSNlW2RjfowYMWKzY7Ru3brYviZPnpzsu+++Sc2aNZPdd9+92D6onNKaH1v6/TJgwID0DpYyS/P3x9cJpaqOTJIkybddTQUAAAAA2eSZUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAFDOkiSJww8/PPr06VNi3V//+tdo1KhR/O9//6uAygAAKo5QCgCgnGUymRg7dmy8/PLL8be//a2ofdGiRTFs2LD485//HLvttltW97l+/fqsjgcAkG1CKQCAFLRs2TL+9Kc/xc9//vNYtGhRJEkSZ599dhx55JGx3377Rd++faNevXrRvHnzOOOMMyI/P79o2wkTJkSPHj2iUaNG0aRJkzjmmGPi3XffLVq/ePHiyGQy8dBDD0WvXr2iVq1acf/991fEYQIAlFomSZKkoosAANhRHH/88bFy5co48cQT4ze/+U3MmTMnOnXqFOecc06ceeaZsXbt2rjiiiviyy+/jEmTJkVExGOPPRaZTCb22WefWLVqVVx99dWxePHimD17dlSrVi0WL14cbdu2jTZt2sQf/vCH2G+//aJWrVqx6667VvDRAgBsmVAKACBFy5cvj06dOsWnn34ajz32WLz11lvx3//+NyZOnFjU53//+1+0bNky5s+fH+3bty8xRn5+fjRt2jTefPPN6Ny5c1EoNXr06Lj00kvTPBwAgG3m9j0AgBQ1a9Yszj///Nhrr73i+OOPj9dffz0mT54c9erVK3p17NgxIqLoFr0FCxZE//79Y/fdd48GDRpEmzZtIiIiLy+v2NgHHnhgqscCALA9ciq6AACAHU1OTk7k5Hz1MWzVqlXRr1+/uOGGG0r023T7Xb9+/aJ169Zxxx13RIsWLWLjxo3RuXPn+OKLL4r1r1u3bvkXDwCQJUIpAIAKtP/++8djjz0Wbdq0KQqqvu6TTz6J+fPnxx133BGHHHJIREQ8//zzaZcJAJB1bt8DAKhAgwcPjk8//TT69+8fr7zySrz77rsxceLEGDhwYGzYsCF22mmnaNKkSdx+++2xcOHCmDRpUgwdOrSiywYA2G5CKQCACtSiRYt44YUXYsOGDXHkkUdGly5d4rLLLotGjRpFtWrVolq1avHggw/GrFmzonPnzjFkyJD4/e9/X9FlAwBsN9++BwAAAEDqXCkFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACkTigFAAAAQOqEUgAAAACk7v8DIoUbE9yySCQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.histplot(ev_models[\"first_year\"], bins=50, color=\"purple\")\n",
    "plt.title(\"EV Models Introduced by Year\", fontsize=14)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Number of Models\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c3a2755",
   "metadata": {
    "papermill": {
     "duration": 0.01325,
     "end_time": "2025-09-03T15:40:44.194195",
     "exception": false,
     "start_time": "2025-09-03T15:40:44.180945",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Popular EV Makes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "bc421c1f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:44.221986Z",
     "iopub.status.busy": "2025-09-03T15:40:44.221630Z",
     "iopub.status.idle": "2025-09-03T15:40:44.451143Z",
     "shell.execute_reply": "2025-09-03T15:40:44.450211Z"
    },
    "papermill": {
     "duration": 0.245485,
     "end_time": "2025-09-03T15:40:44.452855",
     "exception": false,
     "start_time": "2025-09-03T15:40:44.207370",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "top_makes = ev_models[\"make\"].value_counts().head(10)\n",
    "plt.figure(figsize=(10,6))\n",
    "sns.barplot(x=top_makes.values, y=top_makes.index, palette=\"magma\")\n",
    "plt.title(\"Top EV Makes by Number of Models\" , fontsize=14)\n",
    "plt.xlabel(\"Numbers of Models\")\n",
    "plt.ylabel(\"Make\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1af78e6d",
   "metadata": {
    "papermill": {
     "duration": 0.013901,
     "end_time": "2025-09-03T15:40:44.481906",
     "exception": false,
     "start_time": "2025-09-03T15:40:44.468005",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## EV Models by Body Style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "a121436a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:44.513285Z",
     "iopub.status.busy": "2025-09-03T15:40:44.512953Z",
     "iopub.status.idle": "2025-09-03T15:40:44.719351Z",
     "shell.execute_reply": "2025-09-03T15:40:44.718362Z"
    },
    "papermill": {
     "duration": 0.223196,
     "end_time": "2025-09-03T15:40:44.720842",
     "exception": false,
     "start_time": "2025-09-03T15:40:44.497646",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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SaMGCBTp//vxjFWYPDw8tX75c7dq1U5kyZbRs2TL99ttv+vDDD5U+fXqHbevVq6e0adNq7ty58vf3/8+z9v/0999/2y/ZvnPnjkJDQzVlyhSlS5dO77zzjn27MWPGyN/fX+XKlVOnTp108+ZNff311/L29taQIUPs2w0dOlTLly9XpUqV1L17d927d09ff/21Xn31VYWFhcX6/GLFiqlQoUKaO3eufH19Vbx48f/M/Ndff6l06dKqXr26atSooUyZMunChQv66aefFBoaqj59+ihdunSS7v9au7q66vPPP1dERITc3d1VvXp1+z5Knz696tSpo7lz5ypVqlRxTn33b/3799fixYtVv359tW/fXiVKlFBUVJT27NmjefPm6cSJE/bPBwA4OaNjvAMA8P89atoz/WO6r3+6cuWK5e7ubkmy9u/f/8SftX379kdu9+9pzyzLsq5du2b17dvXypIli+Xm5mbly5fPGjNmTKwpwG7evGn16tXLSps2reXp6Wk1aNDAOn36dKxpzyzLss6fP2/16NHDyp49u+Xm5mZlypTJqlGjhjV16lT7Nv+e9uzSpUtWjx49rFdeecXy9PS0vL29rTJlylhz5sz5z5+/Xbt2lqenp/Xnn39atWvXtpInT25lzJjRGjx4sBUdHR3na7p3725JsoKCgv7z/R/497RnLi4uVoYMGayWLVvap4j7p5UrV1oVKlSwkiVLZqVMmdJq0KBBnL+uwcHBVokSJaykSZNaPj4+1uTJk63BgwdbDzusGT16tCXJ+uyzzx4rd2RkpDV+/HjLz8/PypYtm+Xm5malSJHCKleunPXdd9/F+rX+7rvvLB8fH/vUa/+eAm3OnDmWJOutt9566H7657RnlnX/99nAgQOtvHnzWkmTJrXSpUtnlS9f3vriiy+sO3fuPNbPAQBI+GyW9f/nAgEAAHiIvn376vvvv9e5c+eUPHly03GeyPjx49W3b1+dOHHCyP3XixYtUuPGjbVu3TpVqlTphX8+ACDhopADAIBHunXrlrJnz6769esrICDAdJwnYlmWXnvtNaVNm1Zr1qwxkqF+/fo6cOCAjh49+lhztwMAXh7cQw4AAOJ04cIFrVy5UvPmzdPly5fVu3dv05EeW1RUlBYvXqw1a9Zoz549WrRo0QvPMHv2bIWFhem3337T+PHjKeMAgFg4Qw4AAOK0du1aVatWTRkyZNCgQYPUs2dP05Ee24kTJ5Q7d26lSpVK3bt314gRI154BpvNJi8vL/3vf//T5MmTlSQJ50EAAI4o5AAAAAAAGMA85AAAAAAAGEAhBwAAAADAgERfyC3LUmRkpLgyHwAAAACQkCT6Qn7t2jV5e3vr2rVrpqMAAAAAAGCX6As5AAAAAAAJEYUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGCA0UI+cuRIlSpVSilSpFCGDBnUuHFjHTp0yGGbqlWrymazOTzefvttQ4kBAAAAAIgfRgt5cHCwevTooS1btmjFihW6e/euateuraioKIftunTporNnz9ofo0ePNpQYAAAAAID4kcTkhy9fvtzheWBgoDJkyKCdO3eqcuXK9uXJkydXpkyZXnQ8AAAAAACemwR1D3lERIQkKU2aNA7Lf/zxR6VLl06FChXSwIEDdePGjYe+x+3btxUZGenwAAAAAAAgoTF6hvyfYmJi1KdPH1WoUEGFChWyL2/VqpVy5sypLFmyKCwsTB988IEOHTqk+fPnx/k+I0eO1NChQ5973lG7Lj33z4gPA4qlMx0BAAAAABAHm2VZlukQktStWzctW7ZMGzZsULZs2R663erVq1WjRg0dPXpUefLkibX+9u3bun37tv15ZGSksmfProiICKVMmTLe8lLIAQAAAADPIkGcIe/Zs6d+/fVXrVu37pFlXJLKlCkjSQ8t5O7u7nJ3d38uOQEAAAAAiC9GC7llWXrnnXe0YMECrV27Vrlz5/7P1+zevVuSlDlz5uecDgAAAACA58doIe/Ro4eCgoK0aNEipUiRQufOnZMkeXt7K1myZPrzzz8VFBSkunXrKm3atAoLC1Pfvn1VuXJlFSlSxGR0AAAAAACeidFC/u2330qSqlat6rA8ICBA7du3V9KkSbVy5UqNGzdOUVFRyp49u5o1a6aPP/7YQFoAAAAAAOKP8UvWHyV79uwKDg5+QWkAAAAAAHhxEtQ85AAAAAAAvCwo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADDAaCEfOXKkSpUqpRQpUihDhgxq3LixDh065LDNrVu31KNHD6VNm1ZeXl5q1qyZzp8/bygxAAAAAADxw2ghDw4OVo8ePbRlyxatWLFCd+/eVe3atRUVFWXfpm/fvlqyZInmzp2r4OBgnTlzRk2bNjWYGgAAAACAZ2ezLMsyHeKBixcvKkOGDAoODlblypUVERGh9OnTKygoSK+//rok6eDBg/L19dXmzZtVtmzZ/3zPyMhIeXt7KyIiQilTpoy3rKN2XYq393qeBhRLZzoCAAAAACAOCeoe8oiICElSmjRpJEk7d+7U3bt3VbNmTfs2r7zyinLkyKHNmzfH+R63b99WZGSkwwMAAAAAgIQmwRTymJgY9enTRxUqVFChQoUkSefOnVPSpEmVKlUqh20zZsyoc+fOxfk+I0eOlLe3t/2RPXv25x0dAAAAAIAnlmAKeY8ePbR3717Nnj37md5n4MCBioiIsD9Onz4dTwkBAAAAAIg/SUwHkKSePXvq119/1bp165QtWzb78kyZMunOnTsKDw93OEt+/vx5ZcqUKc73cnd3l7u7+/OODAAAAADAMzF6htyyLPXs2VMLFizQ6tWrlTt3bof1JUqUkJubm1atWmVfdujQIZ06dUrlypV70XEBAAAAAIg3Rs+Q9+jRQ0FBQVq0aJFSpEhhvy/c29tbyZIlk7e3tzp16qR+/fopTZo0Spkypd555x2VK1fusUZYBwAAAAAgoTJayL/99ltJUtWqVR2WBwQEqH379pKkr776Si4uLmrWrJlu374tPz8/TZo06QUnBQAAAAAgfiWoecifB+YhZx5yAAAAAEiIEswo6wAAAAAAvEwo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADDAaCFft26dGjRooCxZsshms2nhwoUO69u3by+bzebwqFOnjpmwAAAAAADEI6OFPCoqSq+99pomTpz40G3q1Kmjs2fP2h8//fTTC0wIAAAAAMDzkcTkh/v7+8vf3/+R27i7uytTpkwvKBEAAAAAAC9Ggr+HfO3atcqQIYMKFCigbt266fLly4/c/vbt24qMjHR4AAAAAACQ0CToQl6nTh3NnDlTq1at0ueff67g4GD5+/srOjr6oa8ZOXKkvL297Y/s2bO/wMQAAAAAADwem2VZlukQkmSz2bRgwQI1btz4odscO3ZMefLk0cqVK1WjRo04t7l9+7Zu375tfx4ZGans2bMrIiJCKVOmjLe8o3Zdirf3ep4GFEtnOgIAAAAAIA4J+gz5v/n4+ChdunQ6evToQ7dxd3dXypQpHR4AAAAAACQ0TlXI//rrL12+fFmZM2c2HQUAAAAAgGdidJT169evO5ztPn78uHbv3q00adIoTZo0Gjp0qJo1a6ZMmTLpzz//1Pvvv6+8efPKz8/PYGoAAAAAAJ6d0UK+Y8cOVatWzf68X79+kqR27drp22+/VVhYmGbMmKHw8HBlyZJFtWvX1vDhw+Xu7m4qMgAAAAAA8cJoIa9ataoeNabc77///gLTAAAAAADw4jjVPeQAAAAAACQWFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMOCpCrmPj48uX74ca3l4eLh8fHyeORQAAAAAAIndUxXyEydOKDo6Otby27dv6++//37mUAAAAAAAJHZJnmTjxYsX2///999/l7e3t/15dHS0Vq1apVy5csVbOAAAAAAAEqsnKuSNGzeWJNlsNrVr185hnZubm3LlyqUvv/wy3sIBAAAAAJBYPVEhj4mJkSTlzp1b27dvV7p06Z5LKAAAAAAAErsnKuQPHD9+PL5zAAAAAADwUnmqQi5Jq1at0qpVq3ThwgX7mfMHpk+f/szBAAAAAABIzJ6qkA8dOlTDhg1TyZIllTlzZtlstvjOBQAAAABAovZUhXzy5MkKDAzUm2++Gd95AAAAAAB4KTzVPOR37txR+fLl4zsLAAAAAAAvjacq5J07d1ZQUFB8ZwEAAAAA4KXxVJes37p1S1OnTtXKlStVpEgRubm5OawfO3ZsvIQDAAAAACCxeqpCHhYWpqJFi0qS9u7d67COAd4AAAAAAPhvT1XI16xZE985AAAAAAB4qTzVPeQAAAAAAODZPNUZ8mrVqj3y0vTVq1c/dSAAAAAAAF4GT1XIH9w//sDdu3e1e/du7d27V+3atYuPXAAAAAAAJGpPVci/+uqrOJcPGTJE169ff6ZAAAAAAAC8DOL1HvI2bdpo+vTp8fmWAAAAAAAkSvFayDdv3iwPD4/4fEsAAAAAABKlp7pkvWnTpg7PLcvS2bNntWPHDg0aNCheggEAAAAAkJg9VSH39vZ2eO7i4qICBQpo2LBhql27drwEAwAAAAAgMXuqQh4QEBDfOQAAAAAAeKk8VSF/YOfOnTpw4IAk6dVXX1WxYsXiJRQAAAAAAIndUxXyCxcuqEWLFlq7dq1SpUolSQoPD1e1atU0e/ZspU+fPj4zAgAAAACQ6DzVKOvvvPOOrl27pn379unKlSu6cuWK9u7dq8jISPXq1Su+MwIAAAAAkOg81Rny5cuXa+XKlfL19bUvK1iwoCZOnMigbgAAAAAAPIanOkMeExMjNze3WMvd3NwUExPzzKEAAAAAAEjsnqqQV69eXb1799aZM2fsy/7++2/17dtXNWrUiLdwAAAAAAAkVk9VyL/55htFRkYqV65cypMnj/LkyaPcuXMrMjJSX3/9dXxnBAAAAAAg0Xmqe8izZ8+ukJAQrVy5UgcPHpQk+fr6qmbNmvEaDgAAAACAxOqJzpCvXr1aBQsWVGRkpGw2m2rVqqV33nlH77zzjkqVKqVXX31V69evf15ZAQAAAABINJ6okI8bN05dunRRypQpY63z9vZW165dNXbs2HgLBwAAAABAYvVEhTw0NFR16tR56PratWtr586dzxwKAAAAAIDE7okK+fnz5+Oc7uyBJEmS6OLFi88cCgAAAACAxO6JCnnWrFm1d+/eh64PCwtT5syZnzkUAAAAAACJ3RMV8rp162rQoEG6detWrHU3b97U4MGDVb9+/XgLBwAAAABAYmWzLMt63I3Pnz+v4sWLy9XVVT179lSBAgUkSQcPHtTEiRMVHR2tkJAQZcyY8bkFflKRkZHy9vZWREREnIPRPa1Ruy7F23s9TwOKpTMdAQAAAAAQhyeahzxjxozatGmTunXrpoEDB+pBl7fZbPLz89PEiRMTVBkHAAAAACCheqJCLkk5c+bU0qVLdfXqVR09elSWZSlfvnxKnTr188gHAAAAAECi9MSF/IHUqVOrVKlS8ZkFAAAAAICXxhMN6gYAAAAAAOIHhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwIInpAMADo3ZdMh3hsQwols50BAAAAACJAGfIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAOMFvJ169apQYMGypIli2w2mxYuXOiw3rIsffLJJ8qcObOSJUummjVr6siRI2bCAgAAAAAQj4wW8qioKL322muaOHFinOtHjx6tCRMmaPLkydq6das8PT3l5+enW7duveCkAAAAAADEryQmP9zf31/+/v5xrrMsS+PGjdPHH3+sRo0aSZJmzpypjBkzauHChWrRosWLjAoAAAAAQLxKsPeQHz9+XOfOnVPNmjXty7y9vVWmTBlt3rz5oa+7ffu2IiMjHR4AAAAAACQ0CbaQnzt3TpKUMWNGh+UZM2a0r4vLyJEj5e3tbX9kz579ueYEAAAAAOBpJNhC/rQGDhyoiIgI++P06dOmIwEAAAAAEEuCLeSZMmWSJJ0/f95h+fnz5+3r4uLu7q6UKVM6PAAAAAAASGgSbCHPnTu3MmXKpFWrVtmXRUZGauvWrSpXrpzBZAAAAAAAPDujo6xfv35dR48etT8/fvy4du/erTRp0ihHjhzq06ePPv30U+XLl0+5c+fWoEGDlCVLFjVu3NhcaAAAAAAA4oHRQr5jxw5Vq1bN/rxfv36SpHbt2ikwMFDvv/++oqKi9NZbbyk8PFwVK1bU8uXL5eHhYSoyAAAAAADxwmZZlmU6xPMUGRkpb29vRURExOv95KN2XYq393qeBhRLZzrCY2OfAgAAAHiZJNh7yAEAAAAASMwo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABiQxHQAAM/HqF2XTEd4LAOKpTMdAQAAADCCM+QAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAYkMR0AAJzFqF2XTEd4LAOKpTMdAQAAAI+BM+QAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAxI0IV8yJAhstlsDo9XXnnFdCwAAAAAAJ5ZEtMB/surr76qlStX2p8nSZLgIwMAAAAA8J8SfLtNkiSJMmXKZDoGAAAAAADxKkFfsi5JR44cUZYsWeTj46PWrVvr1KlTj9z+9u3bioyMdHgAAAAAAJDQJOhCXqZMGQUGBmr58uX69ttvdfz4cVWqVEnXrl176GtGjhwpb29v+yN79uwvMDEAAAAAAI8nQRdyf39/vfHGGypSpIj8/Py0dOlShYeHa86cOQ99zcCBAxUREWF/nD59+gUmBgAAAADg8ST4e8j/KVWqVMqfP7+OHj360G3c3d3l7u7+AlMBAAAAAPDkEvQZ8n+7fv26/vzzT2XOnNl0FAAAAAAAnkmCLuTvvfeegoODdeLECW3atElNmjSRq6urWrZsaToaAAAAAADPJEFfsv7XX3+pZcuWunz5stKnT6+KFStqy5YtSp8+veloAAAAAAA8kwRdyGfPnm06AgAAAAAAz0WCvmQdAAAAAIDEikIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYEAS0wEAAC+nUbsumY7wWAYUS2c6AgAASKQ4Qw4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAAUlMBwAAAPFj1K5LpiM8lgHF0pmO8FicZX9KzrNPAQCOOEMOAAAAAIABFHIAAAAAAAygkAMAAAAAYACFHAAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAMoJADAAAAAGAAhRwAAAAAAAMo5AAAAAAAGEAhBwAAAADAAAo5AAAAAAAGUMgBAAAAADAgiekAAAAAeDmM2nXJdITHMqBYOtMRHouz7E+JfRrf2J/xz9Q+5Qw5AAAAAAAGUMgBAAAAADCAQg4AAAAAgAEUcgAAAAAADKCQAwAAAABgAIUcAAAAAAADKOQAAAAAABhAIQcAAAAAwAAKOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAAAAAYIBTFPKJEycqV65c8vDwUJkyZbRt2zbTkQAAAAAAeCYJvpD//PPP6tevnwYPHqyQkBC99tpr8vPz04ULF0xHAwAAAADgqSX4Qj527Fh16dJFHTp0UMGCBTV58mQlT55c06dPNx0NAAAAAICnlsR0gEe5c+eOdu7cqYEDB9qXubi4qGbNmtq8eXOcr7l9+7Zu375tfx4RESFJioyMjNdst65fi9f3e14iI5OajvDY2Kfxi/0Z/9in8Yv9Gf/Yp/HLWfanxD6Nb+zP+Mc+jV/sz/j3vPZpihQpZLPZHrreZlmW9Vw+OR6cOXNGWbNm1aZNm1SuXDn78vfff1/BwcHaunVrrNcMGTJEQ4cOfZExAQAAAACIJSIiQilTpnzo+gR9hvxpDBw4UP369bM/j4mJ0ZUrV5Q2bdpHfjNhWmRkpLJnz67Tp08/8hcMj499Gr/Yn/GPfRq/2J/xj30av9if8Y99Gv/Yp/GL/Rn/nG2fpkiR4pHrE3QhT5cunVxdXXX+/HmH5efPn1emTJnifI27u7vc3d0dlqVKlep5RYx3KVOmdIrfWM6EfRq/2J/xj30av9if8Y99Gr/Yn/GPfRr/2Kfxi/0Z/xLLPk3Qg7olTZpUJUqU0KpVq+zLYmJitGrVKodL2AEAAAAAcDYJ+gy5JPXr10/t2rVTyZIlVbp0aY0bN05RUVHq0KGD6WgAAAAAADy1BF/I//e//+nixYv65JNPdO7cORUtWlTLly9XxowZTUeLV+7u7ho8eHCsy+3x9Nin8Yv9Gf/Yp/GL/Rn/2Kfxi/0Z/9in8Y99Gr/Yn/Evse3TBD3KOgAAAAAAiVWCvoccAAAAAIDEikIOAAAAAIABFHIAAAAAAAygkAMAAAAAYACF3IArV66YjgAAAJ6ju3fvqkaNGjpy5IjpKACABIxCbkCWLFnUokULrVixwnQUAC/Q3bt3lSRJEu3du9d0FCAWfl/GLzc3N4WFhZmOAcCA27dva926dZo1a5amTJmi+fPn6/jx46ZjIYFi2jMDZs2apcDAQK1du1bZs2dX+/bt1b59e+XKlct0tEQhPDxc27Zt04ULFxQTE+Owrm3btoZSOa+ffvpJLVu2jHNd//79NWbMmBecyLn5+PhowYIFeu2110xHSZROnz4tScqePbvhJM7HxcVFpUqVUufOndWiRQulSJHCdCSn17dvX7m7u2vUqFGmoyQqq1at0qpVq+L8d3769OmGUjk39mn82Lhxo8aPH68lS5bo7t278vb2VrJkyXTlyhXdvn1bPj4+euutt/T222/zd+wTSszHoxRyg44fP67AwEDNnDlTp0+fVrVq1dS5c2c1adJESZMmNR3PKS1ZskStW7fW9evXlTJlStlsNvs6m83G7QJPIVWqVPrpp5/k7+/vsLxv376aPXu2zp49ayiZc/r+++81f/58zZo1S2nSpDEdJ1G4d++ehg4dqgkTJuj69euSJC8vL73zzjsaPHiw3NzcDCd0DuvXr1dAQIDmzZunmJgYNWvWTJ07d1alSpVMR3Na77zzjmbOnKl8+fKpRIkS8vT0dFg/duxYQ8mc19ChQzVs2DCVLFlSmTNndvh3XpIWLFhgKJnzYp/Gj4YNGyokJEStWrVSgwYNVLJkSSVLlsy+/tixY1q/fr1++uknhYaGaubMmapVq5bBxM4lMR+PUsgTiJUrVyogIEALFy6Uh4eHWrdurQkTJpiO5XTy58+vunXr6rPPPlPy5MlNx0kUfvvtN7Vu3Vq//vqrKlasKOn+Qeb8+fO1atUqvfLKK4YTOpdixYrp6NGjunv3rnLmzBnrAD0kJMRQMufVrVs3zZ8/X8OGDVO5cuUkSZs3b9aQIUPUuHFjffvtt4YTOpeoqCjNmTNHgYGBWr9+vfLmzatOnTqpXbt2ypQpk+l4TqVatWoPXWez2bR69eoXmCZxyJw5s0aPHq0333zTdJREg30aP6ZMmaKOHTs+1pfA+/fv19mzZ1WjRo0XkCxxSMzHoxTyBOaXX37RW2+9pfDwcEVHR5uO43Q8PT21Z88e+fj4mI6SqAQFBalnz55asWKFvv/+ey1atEhr1qxR/vz5TUdzOkOHDn3k+sGDB7+gJImHt7e3Zs+eHetb86VLl6ply5aKiIgwlMz5HT16VAEBAZo1a5bOnTunOnXqaPHixaZj4SWWNm1abdu2TXny5DEdJdFgn8JZJNbj0SSmA0A6efKkAgICNGPGDPul6506dTIdyyn5+flpx44dFPJ41qpVK4WHh6tChQpKnz69goODlTdvXtOxnBKFO/65u7vHOQZH7ty5uf3nGeXNm1cffvihcubMqYEDB+q3334zHQkvuc6dOysoKEiDBg0yHSXRYJ/Gv08++UTVqlVTuXLl5OHhYTpOopFYj0cp5Ibcvn1bv/zyi6ZPn661a9cqa9asat++vTp06MDgbs+gXr166t+/v/bv36/ChQvHumyoYcOGhpI5l379+sW5PH369CpevLgmTZpkX8Y9kE8uPDxc8+bN059//qn+/fsrTZo0CgkJUcaMGZU1a1bT8ZxOz549NXz4cAUEBMjd3V3S/b9jR4wYoZ49expO57zWrVun6dOn65dffpGLi4uaN2/Ol8VPYceOHZozZ45OnTqlO3fuOKybP3++oVTO69atW5o6dapWrlypIkWKxPp3nn+Tnhz7NP5t3rxZY8eO1b1791SqVClVqVJFVatWVYUKFRzuK8ejvSzHo1yybkD37t01e/Zs3bhxQ40aNVKnTp1Uq1atWINo4Mm5uDx8Jj+bzcZtAI/pUfc9/hP3QD65sLAw1axZU97e3jpx4oQOHTokHx8fffzxxzp16pRmzpxpOqLTadKkiVatWiV3d3f76PWhoaG6c+dOrPvzKECPdubMGQUGBiowMFBHjx5V+fLl1alTJzVv3jzWeAf4b7Nnz1bbtm3l5+enP/74Q7Vr19bhw4d1/vx5NWnSRAEBAaYjOh3uy49/7NPn4969e9q6davWrVun4OBgbdq0Sbdv31apUqW0YcMG0/GcwstyPEohN6BIkSLq1KmT2rRpo7Rp05qOA+AFqlmzpooXL67Ro0crRYoUCg0NlY+PjzZt2qRWrVrpxIkTpiM6nQ4dOjz2thSgh/P399fKlSuVLl06tW3bVh07dlSBAgVMx3JqRYoUUdeuXdWjRw/7n/fcuXOra9euypw583+OKQHA+R0+fFhr1qzRypUrtXDhQnl7e+vSpUumYyEBoZADeKSIiAhFR0fHmqLrypUrSpIkiVKmTGkomXPy9vZWSEiI8uTJ41DIT548qQIFCujWrVumI+Il1bBhQ3Xq1En169eXq6ur6TiJgqenp/bt26dcuXIpbdq0Wrt2rQoXLqwDBw6oevXqTj1NDxKnv/76S5KULVs2w0mc29SpU7V27VoFBwfr9u3bqlSpkqpWraqqVauqSJEiXBX7FBLz8Sj3kBvQtGnTOJd7e3srf/786ty5s9KnT/+CUyUeUVFRCg4OjvN+vV69ehlK5bxatGihBg0aqHv37g7L58yZo8WLF2vp0qWGkjknd3d3RUZGxlp++PBh/tzDKEZPj3+pU6fWtWvXJElZs2bV3r17VbhwYYWHh+vGjRuG0zkv7suPXzExMfr000/15Zdf6vr165KkFClS6N1339VHH330yNsBEbe3335b6dOn17vvvqvu3bvLy8vLdCSnl5iPRzlDbsDDLq8MDw9XaGiowsPDtW7dOhUqVOgFJ3N+u3btUt26dXXjxg1FRUUpTZo0unTpkpInT64MGTLo2LFjpiM6nTRp0mjjxo3y9fV1WH7w4EFVqFBBly9fNpTMOXXu3FmXL1/WnDlzlCZNGoWFhcnV1VWNGzdW5cqVNW7cONMRnU7u3LkfebaBP/ePp3jx4nEuf/BlcZ8+fWL9PYBHa9WqlUqWLKl+/fpp+PDh+vrrr9WoUSOtWLFCxYsXpzw+Be7Lj38DBw7U999/r6FDh6pChQqSpA0bNmjIkCHq0qWLRowYYTih81m4cKHWrVuntWvX6sCBAypWrJj9DHnFihWVPHly0xGdTmI+HqWQJzAxMTHq0qWLLly4oCVLlpiO43SqVq2q/Pnza/LkyfL29lZoaKjc3NzUpk0b9e7d+6FXJ+DhPD09tWXLFhUuXNhh+Z49e1SmTBnO8jyhiIgIvf7669qxY4euXbumLFmy6Ny5cypXrpyWLl3KwFlPYfz48Q7P7969q127dmn58uXq37+/BgwYYCiZc3nY/czh4eEKCQnRli1btHr1avsBO/7blStXdOvWLWXJkkUxMTEaPXq0Nm3apHz58unjjz9W6tSpTUd0OtyXH/+yZMmiyZMnx5qJZtGiRerevbv+/vtvQ8kSh4iICK1fv15z587VTz/9JBcXF25PewqJ+XiUQp4AhYaGyt/fX2fOnDEdxemkSpVKW7duVYECBZQqVSpt3rxZvr6+2rp1q9q1a6eDBw+ajuh0qlWrpkKFCunrr792WN6jRw+FhYVp/fr1hpI5tw0bNigsLEzXr19X8eLFVbNmTdOREp2JEydqx44dnDGLJx999JG2bNmiVatWmY6Clxj35cc/Dw8PhYWFKX/+/A7LDx06pKJFi+rmzZuGkjm3y5cvKzg4WGvXrtXatWu1b98+pU6dWpUqVdKCBQtMx3M6ifl4lHvIEyBPT0+n/pbHJDc3N/u9ThkyZNCpU6fk6+srb29vnT592nA65/Tpp5+qZs2aCg0NtU8htWrVKm3fvl1//PGH4XTO5/Tp08qePbsqVqyoihUrmo6TqPn7+2vgwIEU8njSqlUrfffdd6ZjOJWlS5fK1dVVfn5+Dsv/+OMPRUdHy9/f31Ay58V9+fHvtdde0zfffKMJEyY4LP/mm2/sU0niyTz4kih16tSqXLmyunTpoipVqqhIkSKmozmtxHw8SiFPgFasWBHrW0o8nmLFimn79u3Kly+fqlSpok8++USXLl3SrFmzuCf/KVWoUEGbN2/WmDFjNGfOHCVLlkxFihTR999/r3z58pmO53Ry5cqlihUrqk2bNnr99de5ZPU5mjdvXqzRWPH0XF1dFRMTYzqGUxkwYIBGjRoVa3lMTIwGDBhAIX8Ce/fuVaFChVS5cmWtWLFChQsX1htvvKHevXtr9erVWrFihf0gHU9m9OjRqlevnlauXKly5cpJkjZv3qzTp0879UBZJr399tuqUqUKx57xKDEfj3LJugEPG8k2IiJCO3fu1LRp0zRt2jS1aNHiBSdzfg/uy61WrZouXLigtm3b2u/Xmz59Ot/0wrhdu3YpKChIs2fP1sWLF1WnTh21adNGDRo0kLu7u+l4TqlYsWIOg7pZlqVz587p4sWLmjRpkt566y2D6RKPzz77TMuXL9e6detMR3EayZIl04EDB5QrVy6H5SdOnNCrr76qqKgoM8GckIuLi0qVKqXGjRurTZs2yp49O/flx6MzZ85o4sSJ9lv7fH191b17d2XJksVwMuf3oGox1RkehkJuwMOmj0iRIoUKFCigfv36UcaRIN26dSvWFDPOPO+jSZZlae3atQoKCtIvv/yimJgYNW3aVNOnTzcdzen8exAnFxcXpU+fXlWrVtUrr7xiKJXz+fflqg88+LL4t99+07Jlyxjv4AlkypRJQUFBql69usPylStXqlWrVrpw4YKhZM5n/fr1CggI0Lx58xQTE6NmzZqpc+fOqlSpkuloQJxmzpypMWPG6MiRI5Kk/Pnzq3///nrzzTcNJ3N+ie14lEIO4JFu3Lih999/X3PmzIlzSono6GgDqRKXkJAQderUSWFhYezPp/DXX38pW7Zsca7bsmWLypYt+4ITOafcuXPHuTxlypQqUKCA+vbta7+cFY+na9eu2rx5sxYsWKA8efJIko4ePapmzZqpVKlSmjZtmuGEzicqKkpz5sxRYGCg1q9fr7x586pTp05q166dMmXKZDqeUwoLC4tzuc1mk4eHh3LkyMEVXE9o7NixGjRokHr27OkwldzEiRP16aefqm/fvoYTOp/EfDxKITdg8+bNunz5surXr29fNnPmTA0ePFhRUVFq3Lixvv76a/7ye0z/vlz1UUJCQp5zmsSnR48eWrNmjYYPH64333xTEydO1N9//60pU6Zo1KhRat26temITumvv/5SUFCQgoKCtHfvXpUrV06tW7fW22+/bTqa0ylYsKA2bNgQ637xjRs3ql69egoPDzcTDC+9iIgI1alTRzt27LB/afTXX3+pUqVKmj9/vlKlSmU2oJM7evSoAgICNGvWLJ07d0516tR56G2BeDgXFxf7cVRcl1e7ubnpf//7n6ZMmSIPDw8jGZ1N7ty5NXToULVt29Zh+YwZMzRkyBAdP37cUDLnlZiPRynkBtSpU0fVqlXTBx98IOn+/HnFixdX+/bt5evrqzFjxqhr164aMmSI2aBO4p+Xq966dUuTJk1SwYIF7WdytmzZon379ql79+4aOXKkqZhOK0eOHJo5c6aqVq2qlClTKiQkRHnz5tWsWbP0008/MeDLE5oyZYqCgoK0ceNGvfLKK2rdurVatWqlnDlzmo7mtDp27KiwsDCtWbNGKVKkkCStW7dODRo00JAhQzgT8Yzu3bunW7duycvLy3QUp2RZllasWKHQ0FD7IESVK1c2HSvRiIqK0o8//qiBAwcqPDzcqc+SmbJo0SJ98MEH6t+/v0qXLi1J2rZtm7788ksNHjxY9+7d04ABA/S///1PX3zxheG0zsHDw0N79+5V3rx5HZYfOXJEhQsXZh7yp5Coj0ctvHCZMmWytm/fbn/+4YcfWhUqVLA/nzNnjuXr62simtPr1KmT9fHHH8da/sknn1gdOnQwkMj5eXp6WidPnrQsy7KyZs1qbd261bIsyzp27Jjl6elpMppTypYtm9W/f39r9+7dpqMkGtHR0VaTJk2sKlWqWLdu3bJWr15teXl5WePGjTMdzaksXrzYCggIcFj26aefWu7u7parq6tVq1Yt68qVK2bCAf8SHBxstWvXzvLy8rJSpkxpde7c2dq8ebPpWE6pVKlS1vLly2MtX758uVWqVCnLsixrwYIFlo+Pz4uO5rReffVVa8SIEbGWDx8+3CpUqJCBRM4vMR+PMu2ZAVevXlXGjBntz4ODgx2mPilVqhRzZj+luXPnaseOHbGWt2nTRiVLlmTArKfg4+Oj48ePK0eOHHrllVc0Z84clS5dWkuWLOFyy6dw6tQpRlqNZy4uLpo9e7bq1aun6tWrKywsTCNHjlTPnj1NR3MqY8eO1euvv25/vmnTJn3yyScaNmyYfH199dFHH2n48OEaO3aswZR4mZ05c0aBgYEKDAzU0aNHVb58eU2YMEHNmzeXp6en6XhOa8+ePXFepZUzZ07t2bNHklS0aFGdPXv2RUdzWkOHDtX//vc/rVu3zn4P+caNG7Vq1SrNmTPHcDrnlJiPRynkBmTMmFHHjx9X9uzZdefOHYWEhDhcdn3t2jW5ubkZTOi8kiVLpo0bN8aaj3Djxo3c9/SUOnTooNDQUFWpUkUDBgxQgwYN9M033+ju3bscmD8Fm82m8PBwff/99zpw4ICk+/dAd+rUSd7e3obTOY+4BiEaMmSIWrZsqTZt2qhy5cr2bYoUKfKi4zmlffv2OfyZnjdvnmrVqqWPPvpI0v1LMHv37s2fexjh7++vlStXKl26dGrbtq06duyoAgUKmI6VKLzyyisaNWqUpk6dqqRJk0qS7t69q1GjRtlnqvj7778dTibh0Zo1a6Zt27Zp7NixWrhwoaT7U8lt27ZNxYoVMxvOSSXm41HuITegW7duCg0N1eeff66FCxdqxowZOnPmjP0vwR9//FHjxo3T9u3bDSd1PqNGjdLQoUPVpUsX+31QW7du1fTp0zVo0CANGDDAcELnd+LECft9OxSdJ7djxw75+fkpWbJk9t+j27dv182bN/XHH3+oePHihhM6hweDEP3zn7B/Pn/w/zabjXtKH1OyZMl06NAh5ciRQ5JUunRpvfHGG+rfv78k6eTJkypYsCBzZ8OIhg0bqlOnTqpfv75cXV1Nx0lUNm3apIYNG8rFxcX+7/qePXsUHR2tX3/9VWXLlrUPnPfg7wM83N27d9W1a1cNGjToobNX4NklpuNRCrkBly5dUtOmTbVhwwZ5eXlpxowZatKkiX19jRo1VLZsWY0YMcJgSuc1Z84cjR8/3n720dfXV71791bz5s0NJwOkSpUqKW/evPruu++UJMn9i5Tu3bunzp0769ixY1q3bp3hhM7h5MmTj70tA+Y9nrx582rixIny8/PT9evXlTZtWq1evdp+uWVISIj8/Px08eJFw0kBxLdr167pxx9/1OHDhyVJBQoUUKtWrewDZeLJeHt7a/fu3RRyPBYKuUERERHy8vKK9U3vlStX5OXlZT9jDpi2atUqffXVVw5fcvTp00c1a9Y0nMz5JEuWTLt27bJfBvjA/v37VbJkSd24ccNQMrzsBg4cqIULF+rDDz/U0qVLtWnTJh07dsz+b9TUqVM1c+ZMbdiwwXBS51GlShV16tRJb7zxhpIlS2Y6DoAXpF27dipatCizfMSzxHo8yj3kBj3sftF/z6WLJxMeHq558+bp2LFjeu+995QmTRqFhIQoY8aMypo1q+l4TmfSpEnq3bu3Xn/9dfXu3VvS/ank6tatq6+++ko9evQwnNC5pEyZUqdOnYpVyE+fPs2ZiKc0cuRIZcyYUR07dnRYPn36dF28eNE+xSQe7ZNPPtHff/+tXr16KVOmTPrhhx8cvjD+6aef1KBBA4MJnU+xYsX03nvv6Z133lHz5s3VqVMnlS1b1nQsIE779+/XqVOndOfOHYflDRs2NJTIeeXLl0/Dhg3Txo0bVaJEiViDDvbq1ctQMueVmI9HOUOORCUsLEw1a9aUt7e3Tpw4oUOHDsnHx0cff/yxTp06pZkzZ5qO6HSyZcumAQMGxBqxeuLEifrss8/0999/G0rmnHr16qUFCxboiy++UPny5SXdH3Swf//+atasmcaNG2c2oBPKlSuXgoKC7Pvzga1bt6pFixY6fvy4oWTO5caNG0qePLnpGInOvXv3tHjxYs2YMUPLli1T3rx51bFjR7355psMkoUE4dixY2rSpIn27NkTaywOSYzD8RQedam6zWbTsWPHXmCaxCExH49SyJGo1KxZU8WLF9fo0aOVIkUKhYaGysfHR5s2bVKrVq104sQJ0xGdjpeXl3bv3q28efM6LD9y5IiKFSum69evG0rmnO7cuaP+/ftr8uTJunfvniTJzc1N3bp106hRo+Tu7m44ofPx8PDQgQMHYh0AHTt2TAULFtStW7cMJXMuyZMnV/Xq1dWoUSM1bNiQsvgcXLhwQVOnTtWIESMUHR2tunXrqlevXqpevbrpaHiJNWjQQK6urpo2bZpy586tbdu26fLly3r33Xf1xRdfqFKlSqYjAon6eNTFdAAgPm3fvl1du3aNtTxr1qw6d+6cgUTOr2HDhlqwYEGs5YsWLVL9+vUNJHJuSZMm1fjx43X16lXt3r1bu3fv1pUrV/TVV19Rxp9S9uzZtXHjxljLN27cqCxZshhI5JwOHjwoPz8//fzzz8qZM6fKlCmjESNG2OchxrPZtm2bBg8erC+//FIZMmTQwIEDlS5dOtWvX1/vvfee6Xh4iW3evFnDhg1TunTp5OLiIhcXF1WsWFEjR47k0up4sHHjRt2+fdt0DKeXmI9HuYcciYq7u7siIyNjLT98+LDSp09vIJFzmjBhgv3/CxYsqBEjRmjt2rUqV66cpPv37GzcuFHvvvuuqYhOL3ny5CpcuLAiIyP1xx9/qECBAvL19TUdyyl16dJFffr00d27d+1nGletWqX333+f36NPIEeOHHrnnXf0zjvvKCIiQkuXLtWiRYs0ZswYpUmTRg0bNlTDhg1VpUoVpp16TBcuXNCsWbMUEBCgI0eOqEGDBvrpp5/k5+dnvxy4ffv2qlOnjr744gvDafGyio6Oto9hki5dOp05c0YFChRQzpw5dejQIcPpnJ+/v792794tHx8f01GczstyPMol60hUOnfurMuXL2vOnDlKkyaNwsLC5OrqqsaNG6ty5crcn/uYHneaDu6DenLNmzdX5cqV1bNnT928eVOvvfaaTpw4IcuyNHv2bDVr1sx0RKdjWZYGDBigCRMm2Acj8vDw0AcffKBPPvnEcDrnd/fuXa1Zs0ZLlizR4sWLde3aNX399ddq3bq16WgJXtKkSZUnTx517NhR7du3j/OL4cjISDVq1Ehr1qwxkBC4Px3nu+++q8aNG6tVq1a6evWqPv74Y02dOlU7d+7U3r17TUd0av+8hRJP5mU5HqWQI1GJiIjQ66+/rh07dujatWvKkiWLzp49q3LlymnZsmWxRrkEXrRMmTLp999/12uvvaagoCANHjxYoaGhmjFjhqZOnapdu3aZjui0rl+/rgMHDihZsmTKly8ftwA8J7t27dK9e/dUqlQp01ESvPXr13P/LRK833//XVFRUWratKmOHj2q+vXr6/Dhw0qbNq1+/vlnxjh4RhRy/BcKORKlDRs2KCwsTNevX1eJEiVUo0YN05EASffnIT98+LCyZ8+utm3bKkuWLBo1apROnTqlggULOvWgJEg8wsPDtW3bNl24cEExMTH25TabTW+++abBZM6levXqmj9/vlKlSuWwPDIyUo0bN9bq1avNBAMkrVmzRhUqVFDSpEljrbty5YpSp05tv7UCTy8oKEiNGjXipNAzGjZsmN57771Ys4HcvHlTY8aMceor4ijkSBQ2b96sy5cvOwzqMGPGDA0ePFg3btxQ48aN9fXXX3PG7ClER0crMDBQq1atinVwLokDyieUP39+ffrpp6pXr55y586t2bNnq3r16goNDVWNGjV06dIl0xGdQtOmTRUYGKiUKVOqSZMmjzxonD9//gtM5vyWLFmi1q1b6/r160qZMqXDvrXZbLpy5YrBdM7F1dVVZ8+eVYYMGRyWX7hwQVmzZtXdu3cNJQMkFxcXeXh4qGzZsqpWrZqqVaumsmXLKkkShphCwvOwv08vX76sDBkyOPX0fPyJQ6IwbNgwVa1a1V7I9+zZoy5duqhdu3by9fXVmDFjlCVLFg0ZMsRsUCfUu3dvBQYGql69eipUqBDflj+jPn36qHXr1vLy8lLOnDlVtWpVSdK6detUuHBhs+GciLe3t/33YqpUqRzmzsWzeffdd9WxY0d99tlnzEv+lMLCwiTdH99g//79DrN8REdHa/ny5cqaNaupeIAk6fjx41q9erWCg4P1/fffa/DgwUqePLkqVKhgL+ilSpWSiwuTMj2JadOmaf369apatao6dOign3/+WUOGDNHt27f15ptvaujQoaYjOiXLsuI8Bg0NDVWaNGkMJIo/nCFHopA5c2YtWbJEJUuWlCR99NFHCg4O1oYNGyRJc+fO1eDBg7V//36TMZ1SunTpNHPmTNWtW9d0lERjx44dOn36tGrVqiUvLy9J0m+//aZUqVKpQoUKhtM5j+joaH3xxRdavHix7ty5o+rVq2vIkCFKliyZ6WhOzdPTU3v27OF+x2fg4uJiP3CM6zArWbJk+vrrr9WxY8cXHQ14qGPHjmnt2rVau3atgoOD9ddffylFihQKDw83Hc1pjBs3Th9//LH8/Py0efNm9ejRQ1999ZX69u2r6OhoffnllxozZozeeust01GdxoNbJyIiImJdtRUdHa3r16/r7bff1sSJEw2mfDacIUeicPXqVWXMmNH+PDg4WP7+/vbnpUqV0unTp01Ec3pJkyZV3rx5TcdIVEqWLGn/8ig6Olp79uxR+fLllTp1asPJnMtnn32mIUOGqGbNmkqWLJkmTJigixcvavr06aajOTU/Pz/t2LGDQv4Mjh8/Lsuy5OPjo23btjmMrp40aVJlyJCBqeOQ4Pj4+MjV1VU2m002m00LFy60z1yBxzNlyhRNnTpVrVq10q5du1S6dGlNnjxZnTp1kiRlzZpV3377LYX8CYwbN06WZaljx44aOnSovL297euSJk2qXLly2adBc1acIUeikDNnTs2aNUuVK1fWnTt3lCpVKi1ZssQ+mNuePXtUpUoV7n18Cl9++aWOHTumb775hsvV40GfPn1UuHBhderUSdHR0apSpYo2bdqk5MmT69dff7Vfwo7/li9fPr333nvq2rWrJGnlypWqV6+ebt68ySWWz+D777/XsGHD1KFDBxUuXFhubm4O6xs2bGgoGYD4durUKa1du1Zr1qzR2rVrdenSJZUvX16VKlVSlSpVVKZMmTgHfUPckidProMHDypHjhyS7k/BuXPnTr366quSpKNHj6pUqVK6evWqyZhOo3jx4lq1apVSp06tatWqacmSJfYrCxMTzpAjUahbt64GDBigzz//XAsXLlTy5MkdppoJCwtTnjx5DCZ0Lk2bNnV4vnr1ai1btkyvvvpqrINzBsx6MvPmzVObNm0k3R886/jx4zp48KBmzZqljz76SBs3bjSc0HmcOnXK4VaKmjVrymaz6cyZM8qWLZvBZM6tS5cuku6PzfFvNpvNqQfOeREWL14sf39/ubm5afHixY/cli83YJKPj4+uXr2qChUqqHLlyuratatKlizJoG7PIHny5IqKirI/T58+fawCee/evRcdy2kdOHBAUVFRSp06tdatW6ebN29SyIGEavjw4WratKmqVKkiLy8vzZgxw+Eb3enTp6t27doGEzqXf14OJElNmjQxlCTxuXTpkjJlyiRJWrp0qd544w3lz59fHTt21Pjx4w2ncy737t2Th4eHwzI3NzdGrn5G/55JAU+mcePGOnfunDJkyKDGjRs/dDu+3IBpN2/elHR/zIMkSZLIzc2NWyme0SuvvKKwsDD5+vpKUqzbJQ8ePKhcuXIZSOacihYtqg4dOqhixYqyLEtjxox5aCFn2jMggYiIiJCXl1esf1CuXLkiLy8vLruCcTlz5tR3332nGjVqKHfu3Pr2229Vr1497du3TxUrVuQytifg4uIif39/h+kMlyxZourVqzvM98pVHAAQt4MHD9ovWQ8ODtatW7dUsWJFVa1aVVWqVFGJEiW4BegJbNy4UZ6enipatGic6ydNmqSYmBj17NnzxQZzUocOHdLgwYP1559/KiQkRAULFozzCg6bzaaQkBADCeMHhRzAIx0/flz37t1Tvnz5HJYfOXJEbm5ufNP7hIYMGaJx48Ypc+bMunHjhg4fPix3d3dNnz5d3333nTZv3mw6otPo0KHDY20XEBDwnJMkPlFRUQoODtapU6diDerUq1cvQ6kAPG8HDhyw30/+xx9/SBKjrCNBcHFxsV99lNhQyAE8UpUqVdSxY0e1a9fOYfkPP/ygadOmae3atWaCObF58+bp9OnTeuONN+z3Os+YMUOpUqVSo0aNDKfDy27Xrl2qW7eubty4oaioKKVJk0aXLl1S8uTJlSFDBh07dsx0xARv9erV6tmzp7Zs2aKUKVM6rIuIiFD58uX17bffqnLlyoYSArGdP3/efrZ8zZo1OnLkiNzd3e2XtuPRHjZPNvBfKOQAHillypQKCQmJNfXZ0aNHVbJkSb45BxKZqlWrKn/+/Jo8ebK8vb0VGhoqNzc3tWnTRr1794416CNia9iwoapVq6a+ffvGuX7ChAlas2aNFixY8IKTAf/nwoUL9nnH16xZo8OHD8vNzU2lS5dWtWrVVK1aNZUrV87htiA8XMGCBfXJJ5+oadOmj7xF8siRIxo7dqxy5sypAQMGvMCEzudlGSSTQg7gkby9vbV27VoVK1bMYfnOnTtVtWpVXbt2zVAy5xUcHKwvvvhCBw4ckHT/H/H+/fs7zAwAmJIqVSpt3bpVBQoUUKpUqbR582b5+vpq69atateunQ4ePGg6YoKXM2dOLV++3D6w078dPHhQtWvX1qlTp15wMuD/PBjMrVSpUvYCXr58eSVLlsx0NKe0atUqffDBBzp27Jhq1aqlkiVLKkuWLPLw8NDVq1e1f/9+bdiwQfv27VPPnj314YcfxhpEF47+eZn6o8YycPZBMhllHcAjVa5cWSNHjtRPP/1kHywvOjpaI0eOVMWKFQ2ncz4//PCDOnTooKZNm9rvxd24caNq1KihwMBAtWrVynBCvOzc3NzsBz4ZMmTQqVOn5OvrK29v71gjBiNu58+fjzVF5D8lSZJEFy9efIGJgNiWLFmiqlWrOgyCiadXo0YN7dixQxs2bNDPP/+sH3/8USdPntTNmzeVLl06FStWTG3btlXr1q2VOnVq03Gdwj9n/XjYDCCnT5+Oc5pOZ8IZcgCPtG/fPlWpUkWpUqWyn8Fdv369IiMjtXr1ahUqVMhwQufi6+urt956K9alrGPHjtV3331nP2sOmFK7dm21b99erVq1UpcuXRQWFqZevXpp1qxZunr1qrZu3Wo6YoKXJ08effnllw+d9mz+/Pl67733uB8fRiVPnlzVq1dXo0aN1LBhQ2XMmNF0JOCJhYaGqnjx4k59hpx5DAA80quvvqqwsDA1b95cFy5c0LVr19S2bVsdPHiQMv4Ujh07pgYNGsRa3rBhQx0/ftxAIsDRZ599psyZM0uSRowYodSpU6tbt266ePGipk6dajidc6hbt64GDRqkW7duxVp38+ZNDR48WPXr1zeQDPg/Bw8elJ+fn37++WflzJlTZcqU0YgRI7Rnzx7T0YCXCmfIATzSqVOnlD179jhHDj116pRy5MhhIJXzyps3r/r376+uXbs6LJ88ebK+/PJLHTlyxFAyAPHl/PnzKl68uFxdXdWzZ08VKFBA0v0CNHHiREVHRyskJIQzkkgwIiIitHTpUi1atEjLly9XmjRp1LBhQzVs2FBVqlSx37IGJDSJ4Qw5hRzAI7m6uurs2bOx5n28fPmyMmTI4NR/AZrw7bffqk+fPurYsaPKly8v6f495IGBgRo/fnysog7AOZ08eVLdunXT77//rgeHWjabTX5+fpo4caJy585tOCEQt7t372rNmjVasmSJFi9erGvXrunrr79W69atTUcDYqGQA0j0XFxcdP78eaVPn95h+cmTJ1WwYEFFRUUZSua8FixYoC+//NJ+v7ivr6/69+/PHOQwplixYo89f25ISMhzTpO4XL16VUePHpVlWcqXLx+DOcHp7Nq1S/fu3VOpUqVMR8FL6L+m2gwPD1dwcLBTF3JGWQcQp379+km6f0Zn0KBBSp48uX1ddHS0tm7dqqJFixpK55zu3bunzz77TB07dtSGDRtMxwHs/jn42K1btzRp0iQVLFhQ5cqVkyRt2bJF+/btU/fu3Q0ldF6pU6emyCDBCw8P17Zt23ThwgWH0axtNpvefPNNg8mcy5UrV5QmTRrTMRKV/5oaztvbW23btn1BaZ4PzpADiFO1atUk3Z8zu1y5ckqaNKl9XdKkSZUrVy699957ypcvn6mITsnLy0t79+5Vrly5TEcB4tS5c2dlzpxZw4cPd1g+ePBgnT59WtOnTzeUDMDzsGTJErVu3VrXr19XypQpHa6WsdlsunLlisF0zsXDw0ONGzdWp06dVKtWLdNx4CQo5AAeqUOHDho/frxSpkxpOkqi0KhRIzVt2lTt2rUzHQWIk7e3t3bs2BHry7YjR46oZMmSioiIMJQMwPOQP39+1a1bV5999pnD1XB4crNmzVJgYKDWrl2r7Nmzq3379mrfvj1fwuORKOQA8AJNnjxZQ4cOVevWrVWiRAl5eno6rG/YsKGhZMB9mTJl0qhRo9S+fXuH5YGBgfrggw90/vx5M8EAPBeenp7as2ePfHx8TEdJNI4fP67AwEDNnDlTp0+fVrVq1dS5c2c1adLE4YpDQKKQA3gMO3bs0Jw5c3Tq1CnduXPHYd38+fMNpXJOLi4uD11ns9mcelASJA6jRo3S0KFD1aVLF5UuXVqStHXrVk2fPl2DBg3SgAEDDCcEEJ+aNm2qFi1aqHnz5qajJEorV65UQECAFi5cKA8PD7Vu3VoTJkwwHQsJCIUcwCPNnj1bbdu2lZ+fn/744w/Vrl1bhw8f1vnz59WkSRMFBASYjgggns2ZM0fjx493mAmgd+/eHLADidD333+vYcOGqUOHDipcuLDc3Nwc1nPlVvz45Zdf9NZbbyk8PJwv3+GAQg7gkYoUKaKuXbuqR48eSpEihUJDQ5U7d2517dpVmTNn1tChQ01HdAqrV69Wz549tWXLllj340dERKh8+fKaPHmyKlWqZCghAOBlxJVbz8/JkycVEBCgGTNm2C9d79Spk1q0aGE6GhIQCjmAR/L09NS+ffuUK1cupU2bVmvXrlXhwoV14MABVa9eXWfPnjUd0Sk0bNhQ1apVU9++feNcP2HCBK1Zs0YLFix4wcmA2MLDwzVv3jwdO3ZM7733ntKkSaOQkBBlzJhRWbNmNR0PABKs27dv65dfftH06dO1du1aZc2aVe3bt1eHDh0Y3A1xevhXYgCg+3PoXrt2TZKUNWtW7d27V9L9A/YbN26YjOZUQkNDVadOnYeur127tnbu3PkCEwFxCwsLU/78+fX5559rzJgxCg8Pl3R/vIiBAweaDQcACVj37t2VOXNmdezYUWnTptXSpUt14sQJDR06lDKOh0piOgCAhK1y5cpasWKFChcurDfeeEO9e/fW6tWrtWLFCtWoUcN0PKdx/vz5WPfl/VOSJEl08eLFF5gIiFu/fv3Uvn17jR49WilSpLAvr1u3rlq1amUwGYDnJSoqSsHBwXEO3tqrVy9DqZzPhg0bNHjwYLVp00Zp06Y1HQdOgkIO4JG++eYb3bp1S5L00Ucfyc3NTZs2bVKzZs308ccfG07nPB5cXZA3b94414eFhSlz5swvOBUQ2/bt2zVlypRYy7Nmzapz584ZSATgedq1a5fq1q2rGzduKCoqSmnSpNGlS5eUPHlyZciQgUL+BMLCwkxHgBOikAOIU2RkpKT7Z269vLzsz7t3767u3bubjOaU6tatq0GDBqlOnTry8PBwWHfz5k0NHjxY9evXN5QO+D/u7u72P+//dPjwYaVPn95AIgDPU9++fdWgQQNNnjxZ3t7e2rJli9zc3NSmTRv17t3bdDyn0rRp0ziXe3t7K3/+/OrcuTN/jyIWBnUDECcXFxfZbLb/3I7RVx/P+fPnVbx4cbm6uqpnz54qUKCAJOngwYOaOHGioqOj7YNmASZ17txZly9f1pw5c5QmTRqFhYXJ1dVVjRs3VuXKlTVu3DjTEQHEo1SpUmnr1q0qUKCAUqVKpc2bN8vX11dbt25Vu3btdPDgQdMRnUaHDh3iXB4eHq7Q0FCFh4dr3bp1KlSo0AtOhoSMQg4gTsHBwfb/tyxLdevW1bRp02KNsFylSpUXHc1pnTx5Ut26ddPvv/+uB3/12mw2+fn5aeLEicqdO7fhhMD9afhef/117dixQ9euXVOWLFl09uxZlStXTsuWLZOnp6fpiADiUfr06bVp0ybly5dP+fPn19dffy0/Pz8dPHhQJUqUUFRUlOmIiUJMTIy6dOmiCxcuaMmSJabjIAGhkAN4LA/mIPfx8TEdxeldvXpVR48elWVZypcvn1KnTm06EhDLhg0bFBYWpuvXr6tEiRIM4ggkUrVr11b79u3VqlUrdenSRWFhYerVq5dmzZqlq1evauvWraYjJhqhoaHy9/fXmTNnTEdBAsK0ZwDwgqVOnVqlSpVS6dKlKeNIMDZv3qxff/3V/rxixYry9PTUpEmT1LJlS7311lu6ffu2wYQAnofPPvvMPqjoiBEjlDp1anXr1k0XL17U1KlTDadLXDw9PZkyFrEwqBsAANCwYcNUtWpV++CCe/bsUZcuXdSuXTv5+vpqzJgxypIli4YMGWI2KIB4VbJkSfv/Z8iQQcuXLzeYJnFbsWKF8ufPbzoGEhgKOYDH9jiDvAFwTrt379bw4cPtz2fPnq3SpUvru+++kyRlz55dgwcPppADwEMsXrw4zuURERHauXOnpk2bpmnTpr3gVEjoKOQA4vTvqTtu3bqlt99+O9aATvPnz3+RsQA8J1evXnUY5T84OFj+/v7256VKldLp06dNRAMQz4oVK/bYX7KHhIQ85zSJR+PGjeNcniJFChUoUEDTpk1TixYtXmwoJHgUcgBx8vb2dnjepk0bQ0kAvAgZM2bU8ePHlT17dt25c0chISEaOnSoff21a9fk5uZmMCGA+PLP4njr1i1NmjRJBQsWVLly5SRJW7Zs0b59+9S9e3dDCZ1TTEyM6QhwQoyyDgAA1K1bN4WGhurzzz/XwoULNWPGDJ05c0ZJkyaVJP34448aN26ctm/fbjgpgPjUuXNnZc6c2eGWFUkaPHiwTp8+renTpxtKBrwcGGUdAABo+PDhSpIkiapUqaLvvvtO3333nb2MS9L06dNVu3ZtgwkBPA9z585V27ZtYy1v06aNfvnlFwOJnNe/Z6uQpJkzZyp37tzKkCEDs1UgTlyyDgAAlC5dOq1bt04RERHy8vKSq6urw/q5c+fKy8vLUDoAz0uyZMm0ceNG5cuXz2H5xo0b5eHhYSiVc4prtopOnTqpffv2zFaBh6KQAwAAu3+PH/FAmjRpXnASAC9Cnz591K1bN4WEhKh06dKSpK1bt2r69OkaNGiQ4XTOJa7ZKsqUKcNsFXgkCjkAAADwkhowYIB8fHw0fvx4/fDDD5IkX19fBQQEqHnz5obTORdmq8DToJADAAAAL7HmzZtTvuMBs1XgaTCoGwAAAPASCw8P17Rp0/Thhx/qypUrku7PP/73338bTuZc6tatqwEDBmj9+vUaOHCgkidPrkqVKtnXh4WFKU+ePAYTIiHiDDkAAADwkgoLC1PNmjXl7e2tEydOqHPnzkqTJo3mz5+vU6dOaebMmaYjOo3hw4eradOmqlKliry8vDRjxgxmq8B/Yh5yAAAA4CVVs2ZNFS9eXKNHj1aKFCkUGhoqHx8fbdq0Sa1atdKJEydMR3Q6D5ut4sqVK/Ly8nIo6QBnyAEAAICX1Pbt2zVlypRYy7Nmzapz584ZSOT8mK0CT4J7yAEAAICXlLu7uyIjI2MtP3z4sNKnT28gEfByoZADAAAAL6mGDRtq2LBhunv3riTJZrPp1KlT+uCDD9SsWTPD6YDEj3vIAQAAgJdURESEXn/9de3YsUPXrl1TlixZdPbsWZUrV07Lli2Tp6en6YhAokYhBwAAAF5yGzZsUFhYmK5fv64SJUqoRo0apiMBLwUuWQcAAABeMps3b9avv/5qf16xYkV5enpq0qRJatmypd566y3dvn3bYELg5UAhBwAAAF4yw4YN0759++zP9+zZoy5duqhWrVoaMGCAlixZopEjRxpMCLwcuGQdAAAAeMlkzpxZS5YsUcmSJSVJH330kYKDg7VhwwZJ0ty5czV48GDt37/fZEwg0eMMOQAAAPCSuXr1qjJmzGh/HhwcLH9/f/vzUqVK6fTp0yaiAS8VCjkAAADwksmYMaOOHz8uSbpz545CQkJUtmxZ+/pr167Jzc3NVDzgpUEhBwAAAF4ydevW1YABA7R+/XoNHDhQyZMnV6VKlezrw8LClCdPHoMJgZdDEtMBAAAAALxYw4cPV9OmTVWlShV5eXlpxowZSpo0qX399OnTVbt2bYMJgZcDg7oBAAAAL6mIiAh5eXnJ1dXVYfmVK1fk5eXlUNIBxD8KOQAAAAAABnAPOQAAAAAABlDIAQAAAAAwgEIOAAAAAIABFHIAAAAAAAygkAMAkIBUrVpVffr0idf3DAwMVKpUqeL1PeNTQs8HAMDzQiEHAADx4sSJE7LZbNq9e7fpKAAAOAUKOQAAAAAABlDIAQBIYO7du6eePXvK29tb6dKl06BBg2RZliTp6tWratu2rVKnTq3kyZPL399fR44ccXh9YGCgcuTIoeTJk6tJkya6fPmyfd2JEyfk4uKiHTt2OLxm3Lhxypkzp2JiYh6Z7erVq2rdurXSp0+vZMmSKV++fAoICJAk5c6dW5JUrFgx2Ww2Va1aVevWrZObm5vOnTvn8D59+vRRpUqVHvo5ixYtUvHixeXh4SEfHx8NHTpU9+7d+489BwCAc6GQAwCQwMyYMUNJkiTRtm3bNH78eI0dO1bTpk2TJLVv3147duzQ4sWLtXnzZlmWpbp16+ru3buSpK1bt6pTp07q2bOndu/erWrVqunTTz+1v3euXLlUs2ZNe4l+ICAgQO3bt5eLy6MPDQYNGqT9+/dr2bJlOnDggL799lulS5dOkrRt2zZJ0sqVK3X27FnNnz9flStXlo+Pj2bNmmV/j7t37+rHH39Ux44d4/yM9evXq23bturdu7f279+vKVOmKDAwUCNGjHjCPQkAQMJmsx585Q4AAIyrWrWqLly4oH379slms0mSBgwYoMWLF2vRokXKnz+/Nm7cqPLly0uSLl++rOzZs2vGjBl644031KpVK0VEROi3336zv2eLFi20fPlyhYeHS5LmzJmjt99+W2fPnpW7u7tCQkJUsmRJHTt2TLly5XpkvoYNGypdunSaPn16rHUnTpxQ7ty5tWvXLhUtWtS+fPTo0QoMDNT+/fslSfPnz1e7du107tw5eXp6KjAwUH369LHnq1mzpmrUqKGBAwfa3+OHH37Q+++/rzNnzjzpLgUAIMHiDDkAAAlM2bJl7WVcksqVK6cjR45o//79SpIkicqUKWNflzZtWhUoUEAHDhyQJB04cMBh/YPX/1Pjxo3l6uqqBQsWSLp/iXu1atX+s4xLUrdu3TR79mwVLVpU77//vjZt2vSfr2nfvr2OHj2qLVu22D+vefPm8vT0jHP70NBQDRs2TF5eXvZHly5ddPbsWd24ceM/Pw8AAGdBIQcA4CWTNGlStW3bVgEBAbpz546CgoIeevn4v/n7++vkyZPq27evzpw5oxo1aui999575GsyZMigBg0aKCAgQOfPn9eyZcse+XnXr1/X0KFDtXv3bvtjz549OnLkiDw8PJ7oZwUAICFLYjoAAABwtHXrVofnW7ZsUb58+VSwYEHdu3dPW7dudbhk/dChQypYsKAkydfXN87X/1vnzp1VqFAhTZo0Sffu3VPTpk0fO1/69OnVrl07tWvXTpUqVVL//v31xRdfKGnSpJKk6OjoOD+vZcuWypYtm/LkyaMKFSo89P2LFy+uQ4cOKW/evI+dCQAAZ0QhBwAggTl16pT69eunrl27KiQkRF9//bW+/PJL5cuXT40aNVKXLl00ZcoUpUiRQgMGDFDWrFnVqFEjSVKvXr1UoUIFffHFF2rUqJF+//13LV++PNZn+Pr6qmzZsvrggw/UsWNHJUuW7LGyffLJJypRooReffVV3b59W7/++qt8fX0l3T8TnixZMi1fvlzZsmWTh4eHvL29JUl+fn5KmTKlPv30Uw0bNuw/P6N+/frKkSOHXn/9dbm4uCg0NFR79+51GKAOAABnxyXrAAAkMG3bttXNmzdVunRp9ejRQ71799Zbb70l6f5o6CVKlFD9+vVVrlw5WZalpUuXys3NTdL9+8+/++47jR8/Xq+99pr++OMPffzxx3F+TqdOnXTnzp3Hvlxdun+5+8CBA1WkSBFVrlxZrq6umj17tiQpSZIkmjBhgqZMmaIsWbLYvySQJBcXF7Vv317R0dFq27btIz/Dz89Pv/76q/744w+VKlVKZcuW1VdffaWcOXM+dk4AAJwBo6wDAPCSGj58uObOnauwsLAX8nmdOnXSxYsXtXjx4hfyeQAAJHRcsg4AwEvm+vXrOnHihL755psXcgl4RESE9uzZo6CgIMo4AAD/wCXrAAC8ZHr27KkSJUqoatWqsS5Xf/vttx2mG/vn4+23336qz2vUqJFq166tt99+W7Vq1YqPHwEAgESBS9YBAIDdhQsXFBkZGee6lClTKkOGDC84EQAAiReFHAAAAAAAA7hkHQAAAAAAAyjkAAAAAAAYQCEHAAAAAMAACjkAAAAAAAZQyAEAAAAAMIBCDgAAAACAARRyAAAAAAAM+H/fL72HqNEGXwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ev_models[\"body_style\"].value_counts().plot(kind=\"bar\", color=\"skyblue\")\n",
    "plt.title(\"EV Models by Body Style\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "641df94e",
   "metadata": {
    "papermill": {
     "duration": 0.014748,
     "end_time": "2025-09-03T15:40:44.750818",
     "exception": false,
     "start_time": "2025-09-03T15:40:44.736070",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Scatter plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "3e663d0a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:44.782280Z",
     "iopub.status.busy": "2025-09-03T15:40:44.781409Z",
     "iopub.status.idle": "2025-09-03T15:40:44.999562Z",
     "shell.execute_reply": "2025-09-03T15:40:44.998539Z"
    },
    "papermill": {
     "duration": 0.235701,
     "end_time": "2025-09-03T15:40:45.001273",
     "exception": false,
     "start_time": "2025-09-03T15:40:44.765572",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample = charging.sample(20000, random_state=SEED)\n",
    "plt.figure(figsize=(10,6))\n",
    "plt.scatter(sample[\"longitude\"], sample[\"latitude\"], s=1, alpha=0.25)\n",
    "plt.title(\"Sample of Charging Stations Around the World\")\n",
    "plt.xlabel(\"Longitude\")\n",
    "plt.ylabel(\"Latitude\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66228b51",
   "metadata": {
    "papermill": {
     "duration": 0.015971,
     "end_time": "2025-09-03T15:40:45.034025",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.018054",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Power Buckets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "7eaf6c3b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:45.067421Z",
     "iopub.status.busy": "2025-09-03T15:40:45.067117Z",
     "iopub.status.idle": "2025-09-03T15:40:45.276392Z",
     "shell.execute_reply": "2025-09-03T15:40:45.275463Z"
    },
    "papermill": {
     "duration": 0.228254,
     "end_time": "2025-09-03T15:40:45.278235",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.049981",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bucket_counts = power_bucket_viz.value_counts().reindex(power_labels, fill_value=0)\n",
    "sns.barplot(x=bucket_counts.index, y=bucket_counts.values)\n",
    "plt.title(\"Charging Power Buckets (trimmed for viz)\")\n",
    "plt.xticks(rotation=15)\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"Count\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c17b2de5",
   "metadata": {
    "papermill": {
     "duration": 0.016661,
     "end_time": "2025-09-03T15:40:45.312489",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.295828",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Average Ports by Station"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "61d6fd6e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:45.347728Z",
     "iopub.status.busy": "2025-09-03T15:40:45.347381Z",
     "iopub.status.idle": "2025-09-03T15:40:45.521929Z",
     "shell.execute_reply": "2025-09-03T15:40:45.521013Z"
    },
    "papermill": {
     "duration": 0.194073,
     "end_time": "2025-09-03T15:40:45.523404",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.329331",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Avg ports — Normal/AC: 1.70 | Fast DC: 2.92\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grp = charging.groupby(\"is_fast_dc\")[\"ports\"].mean().rename(index={False:\"Normal/AC\", True:\"Fast DC\"})\n",
    "print(f\"Avg ports — Normal/AC: {grp['Normal/AC']:.2f} | Fast DC: {grp['Fast DC']:.2f}\")\n",
    "\n",
    "sns.barplot(x=grp.index, y=grp.values, palette=\"Set2\")\n",
    "plt.title(\"Average Ports by Station Type\")\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"Avg Ports\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4ece780",
   "metadata": {
    "papermill": {
     "duration": 0.016814,
     "end_time": "2025-09-03T15:40:45.557545",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.540731",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Ports vs Fast DC\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "5c04dd00",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:45.592557Z",
     "iopub.status.busy": "2025-09-03T15:40:45.592256Z",
     "iopub.status.idle": "2025-09-03T15:40:45.807197Z",
     "shell.execute_reply": "2025-09-03T15:40:45.806244Z"
    },
    "papermill": {
     "duration": 0.234351,
     "end_time": "2025-09-03T15:40:45.808745",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.574394",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.boxplot(data=charging.sample(min(50000, len(charging)), random_state=42),\n",
    "                 x=\"is_fast_dc\", y=\"ports\")\n",
    "ax.set_xticklabels([\"Normal/AC\",\"Fast DC\"])\n",
    "plt.title(\"Ports Distribution by Station Type\")\n",
    "plt.xlabel(\"\")\n",
    "plt.ylabel(\"Ports\")\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac834ecd",
   "metadata": {
    "papermill": {
     "duration": 0.017511,
     "end_time": "2025-09-03T15:40:45.845121",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.827610",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "## Cumulative EV Models Over Years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "212e48ef",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:45.882738Z",
     "iopub.status.busy": "2025-09-03T15:40:45.882379Z",
     "iopub.status.idle": "2025-09-03T15:40:46.113654Z",
     "shell.execute_reply": "2025-09-03T15:40:46.112831Z"
    },
    "papermill": {
     "duration": 0.252859,
     "end_time": "2025-09-03T15:40:46.115401",
     "exception": false,
     "start_time": "2025-09-03T15:40:45.862542",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "years = ev_models[\"first_year\"].dropna().astype(int)\n",
    "s = years.value_counts().sort_index()\n",
    "cum = s.cumsum()\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.plot(cum.index, cum.values, marker=\"o\")\n",
    "plt.title(\"Cumulative Count of EV Models Over Time\")\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Cumulative Models\")\n",
    "plt.grid(True)\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "430fb3a1",
   "metadata": {
    "papermill": {
     "duration": 0.01817,
     "end_time": "2025-09-03T15:40:46.152559",
     "exception": false,
     "start_time": "2025-09-03T15:40:46.134389",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Insights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "97df62c0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-09-03T15:40:46.190082Z",
     "iopub.status.busy": "2025-09-03T15:40:46.189756Z",
     "iopub.status.idle": "2025-09-03T15:40:46.224181Z",
     "shell.execute_reply": "2025-09-03T15:40:46.223204Z"
    },
    "papermill": {
     "duration": 0.055212,
     "end_time": "2025-09-03T15:40:46.225800",
     "exception": false,
     "start_time": "2025-09-03T15:40:46.170588",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------------------------\n",
      "Quick Insight Pack:\n",
      "- Total stations: 242,416\n",
      "- Countries covered: 122\n",
      "- Cities with stations: 41815\n",
      "- Global Fast DC share: 21.0%\n",
      "- Max power (kW): 1,000,000\n",
      "- 99th pct power (kW): 350\n",
      "- Top make by models: Tesla (5)\n"
     ]
    }
   ],
   "source": [
    "def pct(x): return f\"{x*100:.1f}%\"\n",
    "countries_covered = world[\"country\"].nunique() if \"country\" in world.columns else world[\"country_code\"].nunique()\n",
    "print(\"-\"*60)\n",
    "print(\"Quick Insight Pack:\")\n",
    "print(f\"- Total stations: {len(charging):,}\")\n",
    "print(f\"- Countries covered: {countries_covered}\")\n",
    "print(f\"- Cities with stations: {charging['city'].nunique()}\")\n",
    "print(f\"- Global Fast DC share: {pct(charging['is_fast_dc'].mean())}\")\n",
    "print(f\"- Max power (kW): {charging['power_kw'].max():,.0f}\")\n",
    "print(f\"- 99th pct power (kW): {charging['power_kw'].quantile(0.99):,.0f}\")\n",
    "mk = ev_models['make'].value_counts()\n",
    "print(f\"- Top make by models: {mk.idxmax()} ({mk.max()})\")\n"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 8183004,
     "sourceId": 12931521,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 31089,
   "isGpuEnabled": false,
   "isInternetEnabled": true,
   "language": "python",
   "sourceType": "notebook"
  },
  "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": "3.11.13"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 18.864149,
   "end_time": "2025-09-03T15:40:47.067354",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2025-09-03T15:40:28.203205",
   "version": "2.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}