bike_counters_starting_kit.ipynb

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   "source": [
    "# RAMP on predicting cyclist traffic in Paris\n",
    "\n",
    "Authors: *Roman Yurchak (Symerio)*; also partially inspired by the air_passengers starting kit.\n",
    "\n",
    "\n",
    "## Introduction\n",
    "\n",
    "The dataset was collected with cyclist counters installed by Paris city council in multiple locations. It contains hourly information about cyclist traffic, as well as the following features,\n",
    " - counter name\n",
    " - counter site name\n",
    " - date\n",
    " - counter installation date\n",
    " - latitude and longitude\n",
    " \n",
    "Available features are quite scarce. However, **we can also use any external data that can help us to predict the target variable.** "
   ]
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   "id": "d0a4cf3f-8907-443b-adff-6fe13ef29d65",
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   "outputs": [],
   "source": [
    "from pathlib import Path\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import sklearn"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5117809-38b8-44f8-8b09-a99989ef1d50",
   "metadata": {},
   "source": [
    "# Loading the data with pandas\n",
    "\n",
    "First, download the data files,\n",
    " - [train.parquet](https://github.com/rth/bike_counters/releases/download/v0.1.0/train.parquet)\n",
    " - [test.parquet](https://github.com/rth/bike_counters/releases/download/v0.1.0/test.parquet)\n",
    "\n",
    "and put them to into the data folder.\n",
    "\n",
    "\n",
    "Data is stored in [Parquet format](https://parquet.apache.org/), an efficient columnar data format. We can load the train set with pandas,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "61c60288-e71b-46ae-9eb3-d916d2abc876",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_parquet(Path(\"data\") / \"train.parquet\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "745fedf9-07e4-4020-b3b5-484b721675ed",
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    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>counter_id</th>\n",
       "      <th>counter_name</th>\n",
       "      <th>site_id</th>\n",
       "      <th>site_name</th>\n",
       "      <th>bike_count</th>\n",
       "      <th>date</th>\n",
       "      <th>counter_installation_date</th>\n",
       "      <th>counter_technical_id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "      <th>log_bike_count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>48321</th>\n",
       "      <td>100007049-102007049</td>\n",
       "      <td>28 boulevard Diderot E-O</td>\n",
       "      <td>100007049</td>\n",
       "      <td>28 boulevard Diderot</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>0.693147</td>\n",
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       "      <td>28 boulevard Diderot E-O</td>\n",
       "      <td>100007049</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>2020-09-01 04:00:00</td>\n",
       "      <td>2013-01-18</td>\n",
       "      <td>Y2H15027244</td>\n",
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       "      <td>2.375429</td>\n",
       "      <td>0.000000</td>\n",
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       "      <th>48330</th>\n",
       "      <td>100007049-102007049</td>\n",
       "      <td>28 boulevard Diderot E-O</td>\n",
       "      <td>100007049</td>\n",
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       "      <td>2020-09-01 15:00:00</td>\n",
       "      <td>2013-01-18</td>\n",
       "      <td>Y2H15027244</td>\n",
       "      <td>48.846028</td>\n",
       "      <td>2.375429</td>\n",
       "      <td>1.609438</td>\n",
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       "      <th>48333</th>\n",
       "      <td>100007049-102007049</td>\n",
       "      <td>28 boulevard Diderot E-O</td>\n",
       "      <td>100007049</td>\n",
       "      <td>28 boulevard Diderot</td>\n",
       "      <td>9.0</td>\n",
       "      <td>2020-09-01 18:00:00</td>\n",
       "      <td>2013-01-18</td>\n",
       "      <td>Y2H15027244</td>\n",
       "      <td>48.846028</td>\n",
       "      <td>2.375429</td>\n",
       "      <td>2.302585</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "                counter_id              counter_name    site_id  \\\n",
       "48321  100007049-102007049  28 boulevard Diderot E-O  100007049   \n",
       "48324  100007049-102007049  28 boulevard Diderot E-O  100007049   \n",
       "48327  100007049-102007049  28 boulevard Diderot E-O  100007049   \n",
       "48330  100007049-102007049  28 boulevard Diderot E-O  100007049   \n",
       "48333  100007049-102007049  28 boulevard Diderot E-O  100007049   \n",
       "\n",
       "                  site_name  bike_count                date  \\\n",
       "48321  28 boulevard Diderot         0.0 2020-09-01 02:00:00   \n",
       "48324  28 boulevard Diderot         1.0 2020-09-01 03:00:00   \n",
       "48327  28 boulevard Diderot         0.0 2020-09-01 04:00:00   \n",
       "48330  28 boulevard Diderot         4.0 2020-09-01 15:00:00   \n",
       "48333  28 boulevard Diderot         9.0 2020-09-01 18:00:00   \n",
       "\n",
       "      counter_installation_date counter_technical_id   latitude  longitude  \\\n",
       "48321                2013-01-18          Y2H15027244  48.846028   2.375429   \n",
       "48324                2013-01-18          Y2H15027244  48.846028   2.375429   \n",
       "48327                2013-01-18          Y2H15027244  48.846028   2.375429   \n",
       "48330                2013-01-18          Y2H15027244  48.846028   2.375429   \n",
       "48333                2013-01-18          Y2H15027244  48.846028   2.375429   \n",
       "\n",
       "       log_bike_count  \n",
       "48321        0.000000  \n",
       "48324        0.693147  \n",
       "48327        0.000000  \n",
       "48330        1.609438  \n",
       "48333        2.302585  "
      ]
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   "source": [
    "data.head()"
   ]
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   "cell_type": "markdown",
   "id": "e488c773-761d-48fb-9d26-3c4b55e3f2b7",
   "metadata": {},
   "source": [
    "We can check general information about different columns,"
   ]
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   "cell_type": "code",
   "execution_count": 6,
   "id": "e2649650-6e2a-4641-8221-266c829aec37",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 455163 entries, 48321 to 928462\n",
      "Data columns (total 11 columns):\n",
      " #   Column                     Non-Null Count   Dtype         \n",
      "---  ------                     --------------   -----         \n",
      " 0   counter_id                 455163 non-null  category      \n",
      " 1   counter_name               455163 non-null  category      \n",
      " 2   site_id                    455163 non-null  int64         \n",
      " 3   site_name                  455163 non-null  category      \n",
      " 4   bike_count                 455163 non-null  float64       \n",
      " 5   date                       455163 non-null  datetime64[ns]\n",
      " 6   counter_installation_date  455163 non-null  datetime64[ns]\n",
      " 7   counter_technical_id       455163 non-null  category      \n",
      " 8   latitude                   455163 non-null  float64       \n",
      " 9   longitude                  455163 non-null  float64       \n",
      " 10  log_bike_count             455163 non-null  float64       \n",
      "dtypes: category(4), datetime64[ns](2), float64(4), int64(1)\n",
      "memory usage: 29.5 MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "586ebce3-c013-4c5e-ab78-03a8d8d86d7e",
   "metadata": {},
   "source": [
    "and in particular the number of unique entries in each column,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "0a88d812-daf9-451d-baa6-67bf735ae368",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "counter_id                     56\n",
       "counter_name                   56\n",
       "site_id                        30\n",
       "site_name                      30\n",
       "bike_count                    977\n",
       "date                         8230\n",
       "counter_installation_date      22\n",
       "counter_technical_id           30\n",
       "latitude                       30\n",
       "longitude                      30\n",
       "log_bike_count                977\n",
       "dtype: int64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.nunique(axis=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "db7504b6-d301-4d37-aa55-4d73b0dcedbd",
   "metadata": {},
   "source": [
    "We have a 30 counting sites where sometimes multiple counters are installed per location.  Let's look at the most frequented stations,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "dd1c75a9-1976-4a97-bf11-76d0026b591b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>bike_count</th>\n",
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       "      <th>site_name</th>\n",
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       "      <th>Totem 73 boulevard de Sébastopol</th>\n",
       "      <th>Totem 73 boulevard de Sébastopol S-N</th>\n",
       "      <td>1809231.0</td>\n",
       "    </tr>\n",
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       "      <th>Totem 64 Rue de Rivoli</th>\n",
       "      <th>Totem 64 Rue de Rivoli O-E</th>\n",
       "      <td>1406900.0</td>\n",
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       "      <th>Totem 73 boulevard de Sébastopol</th>\n",
       "      <th>Totem 73 boulevard de Sébastopol N-S</th>\n",
       "      <td>1357868.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67 boulevard Voltaire SE-NO</th>\n",
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       "      <td>1036575.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Totem 64 Rue de Rivoli</th>\n",
       "      <th>Totem 64 Rue de Rivoli E-O</th>\n",
       "      <td>914089.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27 quai de la Tournelle</th>\n",
       "      <th>27 quai de la Tournelle SE-NO</th>\n",
       "      <td>888717.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Quai d'Orsay</th>\n",
       "      <th>Quai d'Orsay E-O</th>\n",
       "      <td>849724.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Totem Cours la Reine</th>\n",
       "      <th>Totem Cours la Reine O-E</th>\n",
       "      <td>806149.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">Face au 48 quai de la marne</th>\n",
       "      <th>Face au 48 quai de la marne SO-NE</th>\n",
       "      <td>806071.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Face au 48 quai de la marne NE-SO</th>\n",
       "      <td>759194.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                       bike_count\n",
       "site_name                        counter_name                                    \n",
       "Totem 73 boulevard de Sébastopol Totem 73 boulevard de Sébastopol S-N   1809231.0\n",
       "Totem 64 Rue de Rivoli           Totem 64 Rue de Rivoli O-E             1406900.0\n",
       "Totem 73 boulevard de Sébastopol Totem 73 boulevard de Sébastopol N-S   1357868.0\n",
       "67 boulevard Voltaire SE-NO      67 boulevard Voltaire SE-NO            1036575.0\n",
       "Totem 64 Rue de Rivoli           Totem 64 Rue de Rivoli E-O              914089.0\n",
       "27 quai de la Tournelle          27 quai de la Tournelle SE-NO           888717.0\n",
       "Quai d'Orsay                     Quai d'Orsay E-O                        849724.0\n",
       "Totem Cours la Reine             Totem Cours la Reine O-E                806149.0\n",
       "Face au 48 quai de la marne      Face au 48 quai de la marne SO-NE       806071.0\n",
       "                                 Face au 48 quai de la marne NE-SO       759194.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby([\"site_name\", \"counter_name\"])[\"bike_count\"].sum().sort_values(\n",
    "    ascending=False\n",
    ").head(10).to_frame()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a1dc688-2649-4f7f-9326-157b08ea4bae",
   "metadata": {},
   "source": [
    "# Visualizing the data\n",
    "\n",
    "\n",
    "Let's visualize the data, starting from the spatial distribution of counters on the map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "4a1fe386-fb15-4d60-b9f8-8b4b2bc175b7",
   "metadata": {},
   "outputs": [
    {
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       "        \n",
       "    \n",
       "            var marker_f84bba580eca32dd0b0294be43745b74 = L.marker(\n",
       "                [48.846028, 2.375429],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_ecb19c32d38121c641a382c780519371 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_deffdff69df6a624b3318e2987ee266f = $(`&lt;div id=&quot;html_deffdff69df6a624b3318e2987ee266f&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;28 boulevard Diderot E-O&lt;/div&gt;`)[0];\n",
       "            popup_ecb19c32d38121c641a382c780519371.setContent(html_deffdff69df6a624b3318e2987ee266f);\n",
       "        \n",
       "\n",
       "        marker_f84bba580eca32dd0b0294be43745b74.bindPopup(popup_ecb19c32d38121c641a382c780519371)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_d428376d9435ab59d0c967eb166510c6 = L.marker(\n",
       "                [48.846028, 2.375429],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_47abf3623adedb99f5cc2b5c273a1e34 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_1d2bb19b2da7aec7b7c541c606520409 = $(`&lt;div id=&quot;html_1d2bb19b2da7aec7b7c541c606520409&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;28 boulevard Diderot O-E&lt;/div&gt;`)[0];\n",
       "            popup_47abf3623adedb99f5cc2b5c273a1e34.setContent(html_1d2bb19b2da7aec7b7c541c606520409);\n",
       "        \n",
       "\n",
       "        marker_d428376d9435ab59d0c967eb166510c6.bindPopup(popup_47abf3623adedb99f5cc2b5c273a1e34)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_84fa3b9083c04f72dd1fd294041e1d5c = L.marker(\n",
       "                [48.83436, 2.377],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_902179bb908ff32de6f675bb38885a5c = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_b6810fad40fd2fca9c100509ab8a5921 = $(`&lt;div id=&quot;html_b6810fad40fd2fca9c100509ab8a5921&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;39 quai François Mauriac NO-SE&lt;/div&gt;`)[0];\n",
       "            popup_902179bb908ff32de6f675bb38885a5c.setContent(html_b6810fad40fd2fca9c100509ab8a5921);\n",
       "        \n",
       "\n",
       "        marker_84fa3b9083c04f72dd1fd294041e1d5c.bindPopup(popup_902179bb908ff32de6f675bb38885a5c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_a466545d289474bcfb9cc8d8fd84afac = L.marker(\n",
       "                [48.83436, 2.377],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_fa29d03778a21b0f96fa3b6b9ec1836f = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_fd41d8597897f38f33e56d5dc2ba2971 = $(`&lt;div id=&quot;html_fd41d8597897f38f33e56d5dc2ba2971&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;39 quai François Mauriac SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_fa29d03778a21b0f96fa3b6b9ec1836f.setContent(html_fd41d8597897f38f33e56d5dc2ba2971);\n",
       "        \n",
       "\n",
       "        marker_a466545d289474bcfb9cc8d8fd84afac.bindPopup(popup_fa29d03778a21b0f96fa3b6b9ec1836f)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_74bad110d7c75d17f39a8274fdb7600c = L.marker(\n",
       "                [48.85372, 2.35702],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_9a2f820d153dc83e4a557308d45476e7 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_678eddbf13e0588fa426639b71bae9f1 = $(`&lt;div id=&quot;html_678eddbf13e0588fa426639b71bae9f1&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;18 quai de l&#x27;Hôtel de Ville NO-SE&lt;/div&gt;`)[0];\n",
       "            popup_9a2f820d153dc83e4a557308d45476e7.setContent(html_678eddbf13e0588fa426639b71bae9f1);\n",
       "        \n",
       "\n",
       "        marker_74bad110d7c75d17f39a8274fdb7600c.bindPopup(popup_9a2f820d153dc83e4a557308d45476e7)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_eb1650516d5f85e8f65dc93cce4afeb4 = L.marker(\n",
       "                [48.85372, 2.35702],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_072f6f0a1f280cbc09aaf08afc221ec8 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_40cbee96be1ca4e50a3a9a973ea074e9 = $(`&lt;div id=&quot;html_40cbee96be1ca4e50a3a9a973ea074e9&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;18 quai de l&#x27;Hôtel de Ville SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_072f6f0a1f280cbc09aaf08afc221ec8.setContent(html_40cbee96be1ca4e50a3a9a973ea074e9);\n",
       "        \n",
       "\n",
       "        marker_eb1650516d5f85e8f65dc93cce4afeb4.bindPopup(popup_072f6f0a1f280cbc09aaf08afc221ec8)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_bd2d6c61599054817f45715a12e7ccad = L.marker(\n",
       "                [48.8484, 2.27586],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_1d3c4855f4dbc40eba6cffb8387ba627 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_3ca01e53bc5b759ebfae29e6b19a5248 = $(`&lt;div id=&quot;html_3ca01e53bc5b759ebfae29e6b19a5248&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Voie Georges Pompidou NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_1d3c4855f4dbc40eba6cffb8387ba627.setContent(html_3ca01e53bc5b759ebfae29e6b19a5248);\n",
       "        \n",
       "\n",
       "        marker_bd2d6c61599054817f45715a12e7ccad.bindPopup(popup_1d3c4855f4dbc40eba6cffb8387ba627)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_acc7367fe65d701a94d223e5bf711624 = L.marker(\n",
       "                [48.8484, 2.27586],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_3cf58bb6deb93470f6b914c8d45933c5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_0cb7159cbc9c27bbb76ca6d788203080 = $(`&lt;div id=&quot;html_0cb7159cbc9c27bbb76ca6d788203080&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Voie Georges Pompidou SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_3cf58bb6deb93470f6b914c8d45933c5.setContent(html_0cb7159cbc9c27bbb76ca6d788203080);\n",
       "        \n",
       "\n",
       "        marker_acc7367fe65d701a94d223e5bf711624.bindPopup(popup_3cf58bb6deb93470f6b914c8d45933c5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2223009f20443cb1db8954e89738420a = L.marker(\n",
       "                [48.86149, 2.37376],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_baa07428e18ae9335aefac54c7b8932e = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_a7fc3419b3d90c4e94d3f439d58a3c55 = $(`&lt;div id=&quot;html_a7fc3419b3d90c4e94d3f439d58a3c55&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;67 boulevard Voltaire SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_baa07428e18ae9335aefac54c7b8932e.setContent(html_a7fc3419b3d90c4e94d3f439d58a3c55);\n",
       "        \n",
       "\n",
       "        marker_2223009f20443cb1db8954e89738420a.bindPopup(popup_baa07428e18ae9335aefac54c7b8932e)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_cbe88deceb9225be67c2184fff752616 = L.marker(\n",
       "                [48.89172, 2.38531],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_ea96ae3bb4e4c043dfdf340d2844549c = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_74fa605ec29ecc8531527d7b87a42918 = $(`&lt;div id=&quot;html_74fa605ec29ecc8531527d7b87a42918&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 48 quai de la marne NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_ea96ae3bb4e4c043dfdf340d2844549c.setContent(html_74fa605ec29ecc8531527d7b87a42918);\n",
       "        \n",
       "\n",
       "        marker_cbe88deceb9225be67c2184fff752616.bindPopup(popup_ea96ae3bb4e4c043dfdf340d2844549c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_fe88bf58fd60fe951559f33cfb8c69d7 = L.marker(\n",
       "                [48.89172, 2.38531],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_e7808a1a83a1a7563e2bf2a625473588 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_9caf42709549bad57a7260b53b89195b = $(`&lt;div id=&quot;html_9caf42709549bad57a7260b53b89195b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 48 quai de la marne SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_e7808a1a83a1a7563e2bf2a625473588.setContent(html_9caf42709549bad57a7260b53b89195b);\n",
       "        \n",
       "\n",
       "        marker_fe88bf58fd60fe951559f33cfb8c69d7.bindPopup(popup_e7808a1a83a1a7563e2bf2a625473588)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_69a54eddcab543f89d5f326b42f381f9 = L.marker(\n",
       "                [48.890457, 2.368852],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_1dbedc23974aa727ab282e3258242699 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_5d808137a19838cc7bb12b55d55a4bba = $(`&lt;div id=&quot;html_5d808137a19838cc7bb12b55d55a4bba&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face 104 rue d&#x27;Aubervilliers N-S&lt;/div&gt;`)[0];\n",
       "            popup_1dbedc23974aa727ab282e3258242699.setContent(html_5d808137a19838cc7bb12b55d55a4bba);\n",
       "        \n",
       "\n",
       "        marker_69a54eddcab543f89d5f326b42f381f9.bindPopup(popup_1dbedc23974aa727ab282e3258242699)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2501b2059628eb180514720fa6a13cce = L.marker(\n",
       "                [48.890457, 2.368852],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_9cf24ec99c8f7a2f6ef9bc4ecdbe7c1e = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_075a1ad3af38eb5c104b53962337cda1 = $(`&lt;div id=&quot;html_075a1ad3af38eb5c104b53962337cda1&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face 104 rue d&#x27;Aubervilliers S-N&lt;/div&gt;`)[0];\n",
       "            popup_9cf24ec99c8f7a2f6ef9bc4ecdbe7c1e.setContent(html_075a1ad3af38eb5c104b53962337cda1);\n",
       "        \n",
       "\n",
       "        marker_2501b2059628eb180514720fa6a13cce.bindPopup(popup_9cf24ec99c8f7a2f6ef9bc4ecdbe7c1e)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_abab91c644c4ce187a2544169358ed32 = L.marker(\n",
       "                [48.829523, 2.38699],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_473217becc63670ce3fafba30b987e2a = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_d6087aa1882b661ac0407da2d4d76303 = $(`&lt;div id=&quot;html_d6087aa1882b661ac0407da2d4d76303&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 70 quai de Bercy N-S&lt;/div&gt;`)[0];\n",
       "            popup_473217becc63670ce3fafba30b987e2a.setContent(html_d6087aa1882b661ac0407da2d4d76303);\n",
       "        \n",
       "\n",
       "        marker_abab91c644c4ce187a2544169358ed32.bindPopup(popup_473217becc63670ce3fafba30b987e2a)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_724843e650a81e0ccd83920ed69c98d3 = L.marker(\n",
       "                [48.829523, 2.38699],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_bb0634f004a754a1278c1b117a5cb381 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_6dfc2c2d6334d0eba4567ea0b1b8060d = $(`&lt;div id=&quot;html_6dfc2c2d6334d0eba4567ea0b1b8060d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 70 quai de Bercy S-N&lt;/div&gt;`)[0];\n",
       "            popup_bb0634f004a754a1278c1b117a5cb381.setContent(html_6dfc2c2d6334d0eba4567ea0b1b8060d);\n",
       "        \n",
       "\n",
       "        marker_724843e650a81e0ccd83920ed69c98d3.bindPopup(popup_bb0634f004a754a1278c1b117a5cb381)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_3bb266d70d413915708501c53db9ea03 = L.marker(\n",
       "                [48.82636, 2.30303],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_efc12a73ee95786c34825e6b2b75c88e = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_d11a10168d3bb6e475f164d2eb476f55 = $(`&lt;div id=&quot;html_d11a10168d3bb6e475f164d2eb476f55&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;6 rue Julia Bartet NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_efc12a73ee95786c34825e6b2b75c88e.setContent(html_d11a10168d3bb6e475f164d2eb476f55);\n",
       "        \n",
       "\n",
       "        marker_3bb266d70d413915708501c53db9ea03.bindPopup(popup_efc12a73ee95786c34825e6b2b75c88e)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_8de9643e66c4d6282f6f51ff7ce92ddd = L.marker(\n",
       "                [48.82636, 2.30303],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_0df9f2c997c7c6fb12177b95ac776049 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_f80ed7a49f9bfbd3a86a0a90ac9527f0 = $(`&lt;div id=&quot;html_f80ed7a49f9bfbd3a86a0a90ac9527f0&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;6 rue Julia Bartet SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_0df9f2c997c7c6fb12177b95ac776049.setContent(html_f80ed7a49f9bfbd3a86a0a90ac9527f0);\n",
       "        \n",
       "\n",
       "        marker_8de9643e66c4d6282f6f51ff7ce92ddd.bindPopup(popup_0df9f2c997c7c6fb12177b95ac776049)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_da75b1c099936888f749af92167897d4 = L.marker(\n",
       "                [48.89141, 2.38482],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_18f025d2b46a71133f6b0a990c7d46a8 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_3657d35e88be39179fdacb1794db773a = $(`&lt;div id=&quot;html_3657d35e88be39179fdacb1794db773a&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 25 quai de l&#x27;Oise NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_18f025d2b46a71133f6b0a990c7d46a8.setContent(html_3657d35e88be39179fdacb1794db773a);\n",
       "        \n",
       "\n",
       "        marker_da75b1c099936888f749af92167897d4.bindPopup(popup_18f025d2b46a71133f6b0a990c7d46a8)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_587508790246cf854a03772eb2ebad1e = L.marker(\n",
       "                [48.89141, 2.38482],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_80cb160f01cab1d9842f6c2e65171c7c = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_415a009461a81650ae9a85f592383e9c = $(`&lt;div id=&quot;html_415a009461a81650ae9a85f592383e9c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 25 quai de l&#x27;Oise SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_80cb160f01cab1d9842f6c2e65171c7c.setContent(html_415a009461a81650ae9a85f592383e9c);\n",
       "        \n",
       "\n",
       "        marker_587508790246cf854a03772eb2ebad1e.bindPopup(popup_80cb160f01cab1d9842f6c2e65171c7c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_a9e15b3e5898a75c252d804410e83188 = L.marker(\n",
       "                [48.840801, 2.333233],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_564d7dbad9cbea0ee336399e7b597484 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_8d03a33f12a59f3918c2ce4ffa98f62f = $(`&lt;div id=&quot;html_8d03a33f12a59f3918c2ce4ffa98f62f&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;152 boulevard du Montparnasse E-O&lt;/div&gt;`)[0];\n",
       "            popup_564d7dbad9cbea0ee336399e7b597484.setContent(html_8d03a33f12a59f3918c2ce4ffa98f62f);\n",
       "        \n",
       "\n",
       "        marker_a9e15b3e5898a75c252d804410e83188.bindPopup(popup_564d7dbad9cbea0ee336399e7b597484)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_18ed90d3bb28e63ea4abb61815025692 = L.marker(\n",
       "                [48.840801, 2.333233],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_65acca4e51998529cece873cf5f879ad = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_20c335f1adda834cce9faebb0c5ebbfc = $(`&lt;div id=&quot;html_20c335f1adda834cce9faebb0c5ebbfc&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;152 boulevard du Montparnasse O-E&lt;/div&gt;`)[0];\n",
       "            popup_65acca4e51998529cece873cf5f879ad.setContent(html_20c335f1adda834cce9faebb0c5ebbfc);\n",
       "        \n",
       "\n",
       "        marker_18ed90d3bb28e63ea4abb61815025692.bindPopup(popup_65acca4e51998529cece873cf5f879ad)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_c5ace1e32ecdf0d8f50b9dffac16a830 = L.marker(\n",
       "                [48.85735, 2.35211],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_6c2667c30c2f237f272e456ee41ca306 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_e2b2d89e401a3087987216dd779f93e2 = $(`&lt;div id=&quot;html_e2b2d89e401a3087987216dd779f93e2&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem 64 Rue de Rivoli E-O&lt;/div&gt;`)[0];\n",
       "            popup_6c2667c30c2f237f272e456ee41ca306.setContent(html_e2b2d89e401a3087987216dd779f93e2);\n",
       "        \n",
       "\n",
       "        marker_c5ace1e32ecdf0d8f50b9dffac16a830.bindPopup(popup_6c2667c30c2f237f272e456ee41ca306)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_863002964f91d05d76b36157d9488e66 = L.marker(\n",
       "                [48.85735, 2.35211],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_b50c4919bf60aea1e9b375b80376f9ee = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_6f855b0269d310173583f92c9ce880f5 = $(`&lt;div id=&quot;html_6f855b0269d310173583f92c9ce880f5&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem 64 Rue de Rivoli O-E&lt;/div&gt;`)[0];\n",
       "            popup_b50c4919bf60aea1e9b375b80376f9ee.setContent(html_6f855b0269d310173583f92c9ce880f5);\n",
       "        \n",
       "\n",
       "        marker_863002964f91d05d76b36157d9488e66.bindPopup(popup_b50c4919bf60aea1e9b375b80376f9ee)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_c6a3a3362d32a9ce9fe0742f6b4f34cc = L.marker(\n",
       "                [48.86282, 2.31061],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_eb67cf0c91488b584d7606f9ca6ee95b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_415cb6a1bc713dd2ae20df37d7de8e7d = $(`&lt;div id=&quot;html_415cb6a1bc713dd2ae20df37d7de8e7d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont des Invalides S-N&lt;/div&gt;`)[0];\n",
       "            popup_eb67cf0c91488b584d7606f9ca6ee95b.setContent(html_415cb6a1bc713dd2ae20df37d7de8e7d);\n",
       "        \n",
       "\n",
       "        marker_c6a3a3362d32a9ce9fe0742f6b4f34cc.bindPopup(popup_eb67cf0c91488b584d7606f9ca6ee95b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2904852e2a84687c5ace647078a8867b = L.marker(\n",
       "                [48.86378, 2.32003],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_5fd3e9c024a2e5ec1dcf09438136e052 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_9dc2dea38b8328a481a54e6c184248f7 = $(`&lt;div id=&quot;html_9dc2dea38b8328a481a54e6c184248f7&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont de la Concorde S-N&lt;/div&gt;`)[0];\n",
       "            popup_5fd3e9c024a2e5ec1dcf09438136e052.setContent(html_9dc2dea38b8328a481a54e6c184248f7);\n",
       "        \n",
       "\n",
       "        marker_2904852e2a84687c5ace647078a8867b.bindPopup(popup_5fd3e9c024a2e5ec1dcf09438136e052)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_a9b9732448d21841bc084775ab737d80 = L.marker(\n",
       "                [48.86284, 2.310345],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_394f988f75129526874f8b4a5346a1c6 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_69d2daea3b7fbbecc589821cf9b9020c = $(`&lt;div id=&quot;html_69d2daea3b7fbbecc589821cf9b9020c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont des Invalides N-S&lt;/div&gt;`)[0];\n",
       "            popup_394f988f75129526874f8b4a5346a1c6.setContent(html_69d2daea3b7fbbecc589821cf9b9020c);\n",
       "        \n",
       "\n",
       "        marker_a9b9732448d21841bc084775ab737d80.bindPopup(popup_394f988f75129526874f8b4a5346a1c6)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_6818c13d51513fc0597163f2b61bdebd = L.marker(\n",
       "                [48.830331, 2.400551],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_17432b291763f18a81ca31f127716fcf = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_83ae0a4bd4e0a71472f03f4909f84651 = $(`&lt;div id=&quot;html_83ae0a4bd4e0a71472f03f4909f84651&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 8 avenue de la porte de Charenton NO-SE&lt;/div&gt;`)[0];\n",
       "            popup_17432b291763f18a81ca31f127716fcf.setContent(html_83ae0a4bd4e0a71472f03f4909f84651);\n",
       "        \n",
       "\n",
       "        marker_6818c13d51513fc0597163f2b61bdebd.bindPopup(popup_17432b291763f18a81ca31f127716fcf)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_f7c23a7511d0ba243819c1e3e6a21437 = L.marker(\n",
       "                [48.830331, 2.400551],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_807f20ae6f449a8dadcfe7e326aeeeb1 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_44aed62bd4848abe6a5dc316c5ff8f1d = $(`&lt;div id=&quot;html_44aed62bd4848abe6a5dc316c5ff8f1d&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 8 avenue de la porte de Charenton SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_807f20ae6f449a8dadcfe7e326aeeeb1.setContent(html_44aed62bd4848abe6a5dc316c5ff8f1d);\n",
       "        \n",
       "\n",
       "        marker_f7c23a7511d0ba243819c1e3e6a21437.bindPopup(popup_807f20ae6f449a8dadcfe7e326aeeeb1)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_1434b9b9d619c700cd0eba7987ffae22 = L.marker(\n",
       "                [48.86461, 2.40969],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_47a3d811718d0627ad678c15983056c5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_1b47aa22a2e4f6401d546034b5d93957 = $(`&lt;div id=&quot;html_1b47aa22a2e4f6401d546034b5d93957&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 4 avenue de la porte de Bagnolet E-O&lt;/div&gt;`)[0];\n",
       "            popup_47a3d811718d0627ad678c15983056c5.setContent(html_1b47aa22a2e4f6401d546034b5d93957);\n",
       "        \n",
       "\n",
       "        marker_1434b9b9d619c700cd0eba7987ffae22.bindPopup(popup_47a3d811718d0627ad678c15983056c5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_c65d64cb37cecc0cb32fef7ed7c7d5a0 = L.marker(\n",
       "                [48.86461, 2.40969],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_dd55e214edc119f84d29e20beef5cc45 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_363ca9e53ae2b9fa7121a2cdb12c8eb7 = $(`&lt;div id=&quot;html_363ca9e53ae2b9fa7121a2cdb12c8eb7&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 4 avenue de la porte de Bagnolet O-E&lt;/div&gt;`)[0];\n",
       "            popup_dd55e214edc119f84d29e20beef5cc45.setContent(html_363ca9e53ae2b9fa7121a2cdb12c8eb7);\n",
       "        \n",
       "\n",
       "        marker_c65d64cb37cecc0cb32fef7ed7c7d5a0.bindPopup(popup_dd55e214edc119f84d29e20beef5cc45)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_28664c1de11009d61838c29d0e7bf613 = L.marker(\n",
       "                [48.84223, 2.36811],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_2cdec24d63786b08b7f5f0236746b633 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_b6cf4032eeb9dd0c2f8318bfaf8c819b = $(`&lt;div id=&quot;html_b6cf4032eeb9dd0c2f8318bfaf8c819b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont Charles De Gaulle NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_2cdec24d63786b08b7f5f0236746b633.setContent(html_b6cf4032eeb9dd0c2f8318bfaf8c819b);\n",
       "        \n",
       "\n",
       "        marker_28664c1de11009d61838c29d0e7bf613.bindPopup(popup_2cdec24d63786b08b7f5f0236746b633)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_403b6215d2ec676b8f20721dbfe134d0 = L.marker(\n",
       "                [48.84223, 2.36811],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_429cd9fb2d6b9d820ae71b01bceff4a7 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_4e9c07073c81716b297f2d5998777530 = $(`&lt;div id=&quot;html_4e9c07073c81716b297f2d5998777530&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont Charles De Gaulle SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_429cd9fb2d6b9d820ae71b01bceff4a7.setContent(html_4e9c07073c81716b297f2d5998777530);\n",
       "        \n",
       "\n",
       "        marker_403b6215d2ec676b8f20721dbfe134d0.bindPopup(popup_429cd9fb2d6b9d820ae71b01bceff4a7)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_6cf76f776fd69cbecce2c23e7d092416 = L.marker(\n",
       "                [48.85209, 2.28508],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_59d72b0bc8e20b4548bc5834e52132c5 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_b30708da74033f192b8fa0bbbf1d544a = $(`&lt;div id=&quot;html_b30708da74033f192b8fa0bbbf1d544a&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;36 quai de Grenelle NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_59d72b0bc8e20b4548bc5834e52132c5.setContent(html_b30708da74033f192b8fa0bbbf1d544a);\n",
       "        \n",
       "\n",
       "        marker_6cf76f776fd69cbecce2c23e7d092416.bindPopup(popup_59d72b0bc8e20b4548bc5834e52132c5)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_3df88a9440053fc7fa1b608b94073a37 = L.marker(\n",
       "                [48.85209, 2.28508],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_560c641705a4b92076515273680e38de = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_e9891170b4f9bf3f6db1c111d1d1138e = $(`&lt;div id=&quot;html_e9891170b4f9bf3f6db1c111d1d1138e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;36 quai de Grenelle SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_560c641705a4b92076515273680e38de.setContent(html_e9891170b4f9bf3f6db1c111d1d1138e);\n",
       "        \n",
       "\n",
       "        marker_3df88a9440053fc7fa1b608b94073a37.bindPopup(popup_560c641705a4b92076515273680e38de)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_705db4fc15c2c414a79e977b5861cafc = L.marker(\n",
       "                [48.83421, 2.26542],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_90562fc1f3be97dc0c6d88530081a6ee = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_24d3d440f50d977cabddea7d563cc957 = $(`&lt;div id=&quot;html_24d3d440f50d977cabddea7d563cc957&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 40 quai D&#x27;Issy NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_90562fc1f3be97dc0c6d88530081a6ee.setContent(html_24d3d440f50d977cabddea7d563cc957);\n",
       "        \n",
       "\n",
       "        marker_705db4fc15c2c414a79e977b5861cafc.bindPopup(popup_90562fc1f3be97dc0c6d88530081a6ee)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_fa01caa7b1e8fc6c16fe8bc3ef706eb9 = L.marker(\n",
       "                [48.83421, 2.26542],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_75ad9490e7bb87053a85be9df286107d = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_2034dc96e9dd7d33bd033b028f46404f = $(`&lt;div id=&quot;html_2034dc96e9dd7d33bd033b028f46404f&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Face au 40 quai D&#x27;Issy SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_75ad9490e7bb87053a85be9df286107d.setContent(html_2034dc96e9dd7d33bd033b028f46404f);\n",
       "        \n",
       "\n",
       "        marker_fa01caa7b1e8fc6c16fe8bc3ef706eb9.bindPopup(popup_75ad9490e7bb87053a85be9df286107d)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_3cf256073fe6b9b9fc32bf293f7ec6d5 = L.marker(\n",
       "                [48.83848, 2.37587],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_986ed9c9f602700aa7d5d90f05c8da02 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_059230672615c58f0ecb2db68392514e = $(`&lt;div id=&quot;html_059230672615c58f0ecb2db68392514e&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont de Bercy NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_986ed9c9f602700aa7d5d90f05c8da02.setContent(html_059230672615c58f0ecb2db68392514e);\n",
       "        \n",
       "\n",
       "        marker_3cf256073fe6b9b9fc32bf293f7ec6d5.bindPopup(popup_986ed9c9f602700aa7d5d90f05c8da02)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_0e90faecd9f7b10ad7f03f4b226c0350 = L.marker(\n",
       "                [48.83848, 2.37587],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_35e5c10a9c23dba8cff0707b56b9878b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_9db2ba0008cbdbd21a59e6d0a1ab7b59 = $(`&lt;div id=&quot;html_9db2ba0008cbdbd21a59e6d0a1ab7b59&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Pont de Bercy SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_35e5c10a9c23dba8cff0707b56b9878b.setContent(html_9db2ba0008cbdbd21a59e6d0a1ab7b59);\n",
       "        \n",
       "\n",
       "        marker_0e90faecd9f7b10ad7f03f4b226c0350.bindPopup(popup_35e5c10a9c23dba8cff0707b56b9878b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_153f25c2ffdf9cde78a8d82b997b84a6 = L.marker(\n",
       "                [48.86502, 2.35387],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_b8f1446851312ba3a93ae6cecf32c421 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_58944ff23b9977b4ac6b5138e5914aab = $(`&lt;div id=&quot;html_58944ff23b9977b4ac6b5138e5914aab&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;38 rue Turbigo NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_b8f1446851312ba3a93ae6cecf32c421.setContent(html_58944ff23b9977b4ac6b5138e5914aab);\n",
       "        \n",
       "\n",
       "        marker_153f25c2ffdf9cde78a8d82b997b84a6.bindPopup(popup_b8f1446851312ba3a93ae6cecf32c421)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_5f8dd0150c0963b278bf29bd3f2d1f3f = L.marker(\n",
       "                [48.86502, 2.35387],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_5576135eb51824e7c8dfc9f90c5979d1 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_8a647651f6366ab9f81bf5c556e6c11c = $(`&lt;div id=&quot;html_8a647651f6366ab9f81bf5c556e6c11c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;38 rue Turbigo SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_5576135eb51824e7c8dfc9f90c5979d1.setContent(html_8a647651f6366ab9f81bf5c556e6c11c);\n",
       "        \n",
       "\n",
       "        marker_5f8dd0150c0963b278bf29bd3f2d1f3f.bindPopup(popup_5576135eb51824e7c8dfc9f90c5979d1)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_36d17c67550a4e30267d85dd985e1c34 = L.marker(\n",
       "                [48.86288, 2.31179],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_f4894c426e9ceea174c3367d14c2d79b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_8da90a13e13a94b68807287063c1369b = $(`&lt;div id=&quot;html_8da90a13e13a94b68807287063c1369b&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Quai d&#x27;Orsay E-O&lt;/div&gt;`)[0];\n",
       "            popup_f4894c426e9ceea174c3367d14c2d79b.setContent(html_8da90a13e13a94b68807287063c1369b);\n",
       "        \n",
       "\n",
       "        marker_36d17c67550a4e30267d85dd985e1c34.bindPopup(popup_f4894c426e9ceea174c3367d14c2d79b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_d9de5eaf61efc2866482fc9a23a417c9 = L.marker(\n",
       "                [48.86288, 2.31179],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_897f8ac977d5858ebef7b58c9f6683a3 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_853fd6cc499ffadeb039dc9ee5bdab5c = $(`&lt;div id=&quot;html_853fd6cc499ffadeb039dc9ee5bdab5c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Quai d&#x27;Orsay O-E&lt;/div&gt;`)[0];\n",
       "            popup_897f8ac977d5858ebef7b58c9f6683a3.setContent(html_853fd6cc499ffadeb039dc9ee5bdab5c);\n",
       "        \n",
       "\n",
       "        marker_d9de5eaf61efc2866482fc9a23a417c9.bindPopup(popup_897f8ac977d5858ebef7b58c9f6683a3)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_b9cafa398e67b4420a35dede0af3d258 = L.marker(\n",
       "                [48.85013, 2.35423],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_024c920269afa06e7af474edf8d73ccc = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_be895a6e3d6ad205696e0e3dca033c41 = $(`&lt;div id=&quot;html_be895a6e3d6ad205696e0e3dca033c41&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;27 quai de la Tournelle NO-SE&lt;/div&gt;`)[0];\n",
       "            popup_024c920269afa06e7af474edf8d73ccc.setContent(html_be895a6e3d6ad205696e0e3dca033c41);\n",
       "        \n",
       "\n",
       "        marker_b9cafa398e67b4420a35dede0af3d258.bindPopup(popup_024c920269afa06e7af474edf8d73ccc)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_775a12e88e60795994a77c21293be864 = L.marker(\n",
       "                [48.85013, 2.35423],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_da631419e80154edcdcaec34f971450d = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_4ecf6084fbaa91b1a37cacece13cbd95 = $(`&lt;div id=&quot;html_4ecf6084fbaa91b1a37cacece13cbd95&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;27 quai de la Tournelle SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_da631419e80154edcdcaec34f971450d.setContent(html_4ecf6084fbaa91b1a37cacece13cbd95);\n",
       "        \n",
       "\n",
       "        marker_775a12e88e60795994a77c21293be864.bindPopup(popup_da631419e80154edcdcaec34f971450d)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_e41fd865271823d171722506cbe5535a = L.marker(\n",
       "                [48.84201, 2.36729],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_581d39e375f545ac01f42e51a83a7943 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_110acb8d8b9a375dd0f8fdb9d5cf7c19 = $(`&lt;div id=&quot;html_110acb8d8b9a375dd0f8fdb9d5cf7c19&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem 85 quai d&#x27;Austerlitz NO-SE&lt;/div&gt;`)[0];\n",
       "            popup_581d39e375f545ac01f42e51a83a7943.setContent(html_110acb8d8b9a375dd0f8fdb9d5cf7c19);\n",
       "        \n",
       "\n",
       "        marker_e41fd865271823d171722506cbe5535a.bindPopup(popup_581d39e375f545ac01f42e51a83a7943)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_1cbf93b18b0f95b37e11e6e76cdd98da = L.marker(\n",
       "                [48.84201, 2.36729],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_3836a53f8bb366b5e23a2b3fcbde176b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_fc8b18ce7e17b6f4f1200264a738707c = $(`&lt;div id=&quot;html_fc8b18ce7e17b6f4f1200264a738707c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem 85 quai d&#x27;Austerlitz SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_3836a53f8bb366b5e23a2b3fcbde176b.setContent(html_fc8b18ce7e17b6f4f1200264a738707c);\n",
       "        \n",
       "\n",
       "        marker_1cbf93b18b0f95b37e11e6e76cdd98da.bindPopup(popup_3836a53f8bb366b5e23a2b3fcbde176b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_2405e6b0dd3f4709cd84db2e0228f2d1 = L.marker(\n",
       "                [48.86462, 2.31444],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_94c71c6990ce963b1c9ae64b4eb5638b = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_6a063dfe2c69b7e4cdb2b739f1f38852 = $(`&lt;div id=&quot;html_6a063dfe2c69b7e4cdb2b739f1f38852&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem Cours la Reine E-O&lt;/div&gt;`)[0];\n",
       "            popup_94c71c6990ce963b1c9ae64b4eb5638b.setContent(html_6a063dfe2c69b7e4cdb2b739f1f38852);\n",
       "        \n",
       "\n",
       "        marker_2405e6b0dd3f4709cd84db2e0228f2d1.bindPopup(popup_94c71c6990ce963b1c9ae64b4eb5638b)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_74a21008819d8c5e662bb8a1cef792fc = L.marker(\n",
       "                [48.86462, 2.31444],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_a775a417b73be75f097c42aa21674755 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_d093c105cb43175b8ff4d58b3c3a9c68 = $(`&lt;div id=&quot;html_d093c105cb43175b8ff4d58b3c3a9c68&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem Cours la Reine O-E&lt;/div&gt;`)[0];\n",
       "            popup_a775a417b73be75f097c42aa21674755.setContent(html_d093c105cb43175b8ff4d58b3c3a9c68);\n",
       "        \n",
       "\n",
       "        marker_74a21008819d8c5e662bb8a1cef792fc.bindPopup(popup_a775a417b73be75f097c42aa21674755)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_7bab91d7c016749f5dd2f208344837a8 = L.marker(\n",
       "                [48.86377, 2.35096],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_6e7771365bb266ecacf97ad028035d62 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_52d86c884237b383736bd9dba7a96474 = $(`&lt;div id=&quot;html_52d86c884237b383736bd9dba7a96474&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem 73 boulevard de Sébastopol N-S&lt;/div&gt;`)[0];\n",
       "            popup_6e7771365bb266ecacf97ad028035d62.setContent(html_52d86c884237b383736bd9dba7a96474);\n",
       "        \n",
       "\n",
       "        marker_7bab91d7c016749f5dd2f208344837a8.bindPopup(popup_6e7771365bb266ecacf97ad028035d62)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_832dca11ea55ddcfdc750034e939a367 = L.marker(\n",
       "                [48.86377, 2.35096],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_db0421fa4a1b10d8d320b9743d84982c = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_cd96c2a0e8cc07c7fd39384fc631a8dc = $(`&lt;div id=&quot;html_cd96c2a0e8cc07c7fd39384fc631a8dc&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;Totem 73 boulevard de Sébastopol S-N&lt;/div&gt;`)[0];\n",
       "            popup_db0421fa4a1b10d8d320b9743d84982c.setContent(html_cd96c2a0e8cc07c7fd39384fc631a8dc);\n",
       "        \n",
       "\n",
       "        marker_832dca11ea55ddcfdc750034e939a367.bindPopup(popup_db0421fa4a1b10d8d320b9743d84982c)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_4343d239536161f7684c2db69a539ae2 = L.marker(\n",
       "                [48.84638, 2.31529],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_f511ac337ba0215519f59c8ea1d7a2c8 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_4740ff23aee2c4f0116c79fbda06f59c = $(`&lt;div id=&quot;html_4740ff23aee2c4f0116c79fbda06f59c&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;90 Rue De Sèvres NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_f511ac337ba0215519f59c8ea1d7a2c8.setContent(html_4740ff23aee2c4f0116c79fbda06f59c);\n",
       "        \n",
       "\n",
       "        marker_4343d239536161f7684c2db69a539ae2.bindPopup(popup_f511ac337ba0215519f59c8ea1d7a2c8)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_1c189fafafb22354e39040265d3665e5 = L.marker(\n",
       "                [48.84638, 2.31529],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_31fd56ba00b8b24adb2df8e1644ad641 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_6241d002980e8b8537a7a0c1737d27f7 = $(`&lt;div id=&quot;html_6241d002980e8b8537a7a0c1737d27f7&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;90 Rue De Sèvres SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_31fd56ba00b8b24adb2df8e1644ad641.setContent(html_6241d002980e8b8537a7a0c1737d27f7);\n",
       "        \n",
       "\n",
       "        marker_1c189fafafb22354e39040265d3665e5.bindPopup(popup_31fd56ba00b8b24adb2df8e1644ad641)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_4239437aebf0d847f53d52d0f433fc23 = L.marker(\n",
       "                [48.88529, 2.32666],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_954eb7d2dee4ad88af0a101ee253b844 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_dd199f0cf0f01b4d9e089aa7477b7e68 = $(`&lt;div id=&quot;html_dd199f0cf0f01b4d9e089aa7477b7e68&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;20 Avenue de Clichy NO-SE&lt;/div&gt;`)[0];\n",
       "            popup_954eb7d2dee4ad88af0a101ee253b844.setContent(html_dd199f0cf0f01b4d9e089aa7477b7e68);\n",
       "        \n",
       "\n",
       "        marker_4239437aebf0d847f53d52d0f433fc23.bindPopup(popup_954eb7d2dee4ad88af0a101ee253b844)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_d2f9bd8412c5d2cf16e5451e4edf76ef = L.marker(\n",
       "                [48.88529, 2.32666],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_381633c734e0fa031ddedcb0f1d827ac = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_18570997a674d7e0f8ce06e37927e2b8 = $(`&lt;div id=&quot;html_18570997a674d7e0f8ce06e37927e2b8&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;20 Avenue de Clichy SE-NO&lt;/div&gt;`)[0];\n",
       "            popup_381633c734e0fa031ddedcb0f1d827ac.setContent(html_18570997a674d7e0f8ce06e37927e2b8);\n",
       "        \n",
       "\n",
       "        marker_d2f9bd8412c5d2cf16e5451e4edf76ef.bindPopup(popup_381633c734e0fa031ddedcb0f1d827ac)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_fb502d73480622d0906394c2cc6cb758 = L.marker(\n",
       "                [48.83977, 2.30198],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_bf989cf84f0b9df89725663084340245 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_2fcd23d66c7c175fe823c64a92ac4786 = $(`&lt;div id=&quot;html_2fcd23d66c7c175fe823c64a92ac4786&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;254 rue de Vaugirard NE-SO&lt;/div&gt;`)[0];\n",
       "            popup_bf989cf84f0b9df89725663084340245.setContent(html_2fcd23d66c7c175fe823c64a92ac4786);\n",
       "        \n",
       "\n",
       "        marker_fb502d73480622d0906394c2cc6cb758.bindPopup(popup_bf989cf84f0b9df89725663084340245)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "    \n",
       "            var marker_c2d1f687a022ec9572bef147b2d0771b = L.marker(\n",
       "                [48.83977, 2.30198],\n",
       "                {}\n",
       "            ).addTo(map_f698baac49ed6868bf812dbcd7e6fad8);\n",
       "        \n",
       "    \n",
       "        var popup_1ffe17961de1782c3ac611b391893c72 = L.popup({&quot;maxWidth&quot;: &quot;100%&quot;});\n",
       "\n",
       "        \n",
       "            var html_2337cbe5429e4bbf47bdc75337b57468 = $(`&lt;div id=&quot;html_2337cbe5429e4bbf47bdc75337b57468&quot; style=&quot;width: 100.0%; height: 100.0%;&quot;&gt;254 rue de Vaugirard SO-NE&lt;/div&gt;`)[0];\n",
       "            popup_1ffe17961de1782c3ac611b391893c72.setContent(html_2337cbe5429e4bbf47bdc75337b57468);\n",
       "        \n",
       "\n",
       "        marker_c2d1f687a022ec9572bef147b2d0771b.bindPopup(popup_1ffe17961de1782c3ac611b391893c72)\n",
       "        ;\n",
       "\n",
       "        \n",
       "    \n",
       "&lt;/script&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x7f5e967237c0>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import folium\n",
    "\n",
    "m = folium.Map(location=data[[\"latitude\", \"longitude\"]].mean(axis=0), zoom_start=13)\n",
    "\n",
    "for _, row in (\n",
    "    data[[\"counter_name\", \"latitude\", \"longitude\"]]\n",
    "    .drop_duplicates(\"counter_name\")\n",
    "    .iterrows()\n",
    "):\n",
    "    folium.Marker(\n",
    "        row[[\"latitude\", \"longitude\"]].values.tolist(), popup=row[\"counter_name\"]\n",
    "    ).add_to(m)\n",
    "\n",
    "m"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83a58f27-b2c3-4eee-8991-b206471eb723",
   "metadata": {},
   "source": [
    "Note that in this RAMP problem we consider only the 30 most frequented counting sites, to limit data size.\n",
    "\n",
    "\n",
    "Next we will look into the temporal distribution of the most frequented bike counter. If we plot it directly we will not see much because there are half a million data points,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8fe0c1a0-e661-4dd9-bf14-be1ac5a1a34c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='date'>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = data[\"counter_name\"] == \"Totem 73 boulevard de Sébastopol S-N\"\n",
    "\n",
    "data[mask].plot(x=\"date\", y=\"bike_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6782d258-580c-4db4-9b96-fa1e16d89b2f",
   "metadata": {},
   "source": [
    "Instead we aggregate the data, for instance, by week to have a clearer overall picture,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "349fbd40-c57e-40cc-bd99-608d9e2e89ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='date'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IQpwdeZzUPJVK1a4dHAmDnIs4WSyVj9t3XAUAXSIC8cfRczh+jsnHRESOpFAorNIfPMXiTZn4Mv0MSmpFvHX7Je5eDjXgoeZF5LQxJweA3BCQvXKIiDqG9BxLN/4NRwpRb+JxmqdgkNOMitp6FFVatkPbtJPDMnIiog6juNIo/1FbWlWHXTml7l0QyRjkNEMa5xAWqEaw1v7SNWknJ6e4ihE9EZGP292wiyNZfyj/IleSqzHIaUbjOAf7d3EAIFanhValQJ1JxKmSakcujYiIPMyuhiAnIsjSMuQXBjkeg0FOM+Qgpw35OACgUAhIlsY7FPDIiojIl6WftAQ5D47qCj+FgOOFlchmQ1iPwCCnGVK340Q7BnOeT87LYYUVEZHPqjOZsfdUGQDgyp6RGJZsaRvC3RzPwCCnGe3dyQGajHdghRURkc86nFuO6joT9P4qdIkIwtje0QCA9YcKWnlPcgUGOc1ob04OAHSVK6wY5BAR+ar0k8UAgEsSQ6BQCBjXOwoAsDO7GGXVdS29K7kAg5zz1NabkFtmSRZObEeQ0yVCGtTJ4yoiIl+V3lAuPjgxFACQFB6IblFBqDeL+P1IoRtXRgCDnAucLqmGWQQC1EpEBmnafJ/khp2ccxVGRvNERD5qV0PS8eCkUPltYxt2c1hK7n4Mcs7TtNNxc0PBbBWk8UO0zhIksSkgEZHvyS2rxpnSaigEYEBCiPz2sb0seTm/ZbL7sbsxyDmP1AiwPfk4EvnIink5REQ+Z9fJUgBA71gdAjWNoyAHJYYgJECFsuo6ubyc3INBznkaB3O2vXxcwjJyIiLfld7MURUA+CkVGN2z4cjqMKus3IlBznnaM5jzfBzUSUTku6ShnOcHOUBjXg775bgXg5zzNO7kOCLIYRk5EZEvqqkzIeOMpQngoMQLg5wrekTCTyHgRGElstj92G0Y5DRhNovIkYKcsPYfV3VtyMnJKqqEySy2+35EROQZ9p8pQ71ZRFSwBvGh/hc8rtOqMLyLpfsxq6zch0FOE3mGGhjrzfBTCIgL0bb7fp1C/aH2U8BYb8YZDuokIvIZUj7OoMTQi1biSlVW7H7sPgxympA6HceH+sNP2f5PjVIhILkhgfk4k4+JiHzGxZKOmxrXMOKB3Y/dh0FOE44YzHk+5uUQEfkWURTlJoCDWghyEsMD0L2h+/FGdj92CwY5TThiMOf5GoMc7uQQEfmCk0VVKKo0Qq1UoG8nXYvXjmH3Y7dikNOEIyurJGwISETkW6Sjqn7xemj8lC1eKx1ZbWD3Y7dgkNOE1O3YET1yJGwISETkW1rqj3O+QYmhCG3ofvwnux+7HIOcBqIoysdVnSMcmZNj2cnJN9SiorbeYfclIiL32NWksqo1SoXQ2P2YR1YuxyCnQWlVHcprLEGII3dy9P4qRASpAQBZPLIiIvJqhpo6ZOaXAwAGJYXY9D5jG46sOOLB9RjkNJDycaJ1GmhVLZ+x2kvOy+GRFRGRV9uTUwpRtPwxHBVsWz+1K3pEQKVk92N3YJDTQJ4+7oBOx+eT8nKOFzDIISLyZo1NAENsfp9grQrDk8MB8MjK1RjkNJAHczqwskoiBzmM4ImIvNouO5KOm+LATvdgkNMg2wk9ciQsIyci8n4ms4g9OaUAWm4C2BxpxMPO7BKUVbH7saswyGnQ2O3YeTs5WecqYOagTiIir3S0oBzltfUIVCvRMzrYrveVuh+bzCI2HGECsqswyGkgl487cKSDJCEsACqlgJo6M3INNQ6/PxEROZ+UjzMwMaRN8w3lKisO7HQZBjkAqo0mFJTXAnBst2OJSqmQy9I53oGIyDvJQzlt6I/TnHENeTkbMgtQx+7HLsEgB8DpEssujk7rh5AAtVOeQ2oKyLwcIiLvZMtQzpZckhiKsEA1DDX1csBEzsUgB0COPLPK8UdVEg7qJCLyXucqauUClUvauJOjVAi4smckAGDdQVZZuQKDHACnip1XPi7pKjcE5E4OEZG3kXZxekQHQe+vavN9ru4bCwD4etdp1NSZHLI2ujgGOQBOlTivfFzSuJPDIIeIyNtIQzltmVfVkjG9ohAf6o/Sqjp8t+eMI5ZGLWCQAyCnuBqAcyqrJFJOzpnSalQbGb0TEXmT9ubjSJQKAVNTOwMAlm7OhiiyrYgzMchBY+KxM4+rwgLVCAmwbHFyhhURkfcw1pux93QZAPs7HTfn1iEJ8FcpcTivHNuzitt9P7o4BjkAckstvWucUT7eVJcIHlkREXmbjLNlMNabERKgkn+Ot4c+QIWbBnUCACzdnNXu+9HFMcgBUG8WofZTINrGibJtxTJyIiLv07Q/jiAIDrnn3Zd2BmCpspKKX8jxGOQ0SAwLgELhmC/ei5GTj3lcRUTkNXa3cV5VS7pHB2NktwiYReCTbScddl+yxiCngTMrqyRduZNDRORVRFHEnycteTOOyMdp6p7LOgMAVu7IQZWx3qH3JgsGOQ2c2QhQ0rVJQ0Bm1BMReb6zZTXIN9RCqRAwID7Eofce3TMKSeEBMNTU45vdLCd3BgY5DZyddAwAiWGBUCoEVDaZlUVERJ5LysfpE6eDv1rp0HsrFALuaignX8ZycqdgkNPAmeXjErWfAgmh/gCA4xzvQETk8dKzLUdV7W0CeDG3DIlHgFqJowUV2HK8yCnP0ZExyGngipwcgBVWRETe5I+j5wAAw5LDnHJ/nVaFmwfHA7A0ByTHsivImTdvHgRBsHrp1auX/HhNTQ1mzJiB8PBwBAUFYdKkScjPtx5ClpOTg4kTJyIgIABRUVF4/PHHUV9vnXC1YcMGDBo0CBqNBt26dcOyZcsuWMvChQvRuXNnaLVaDB8+HDt27LDnQ7GiEID4UBcFOeyVQ0TkFU4UVuDEuUr4KQRc3j3Cac8ztaGcfP3hfOQUsZzckezeyenTpw9yc3Pll02bNsmPzZo1Cz/88AO+/PJLbNy4EWfPnsVNN90kP24ymTBx4kQYjUZs2bIFy5cvx7JlyzB37lz5mqysLEycOBGjR4/Gnj178Nhjj+G+++7DTz/9JF/z+eefY/bs2Xjuueewa9cuDBgwAGlpaSgoKGjTJyFap4XazzWbWvJODsvIiYg82q+HLb9ThncJQ7C27UM5W9M1MgijekRCFIHlW7Od9jwdkd2/2f38/BATEyO/RERYotuysjIsWbIEb7zxBsaMGYPBgwdj6dKl2LJlC7Zt2wYA+Pnnn3Hw4EF88sknGDhwIK6++mq8+OKLWLhwIYxGIwBg8eLFSE5Oxuuvv47evXtj5syZuPnmm/Hmm2/Ka3jjjTdw//3345577kFKSgoWL16MgIAAfPTRR236JCS66KgKaOyVw5wcIiLPtv6QJcgZ2yva6c91d0M5+Rc7T6Gy1jnl5GZzx0tstjvIOXr0KOLi4tClSxdMmTIFOTk5AID09HTU1dVh3Lhx8rW9evVCYmIitm7dCgDYunUr+vXrh+joxi+YtLQ0GAwGZGRkyNc0vYd0jXQPo9GI9PR0q2sUCgXGjRsnX2OvBBcGOd2iLDs5p0uqYaipc9nzEhGR7cqq67CzIel4bO8opz/fqO6RSI4IRHltPf6363Sb71NvMuNkUSU2ZBZg+ZZsPP9DBu5dthNjXt+Ans/+iNve29qhqrj87Ll4+PDhWLZsGXr27Inc3Fw8//zzuPzyy3HgwAHk5eVBrVYjJCTE6n2io6ORl5cHAMjLy7MKcKTHpcdausZgMKC6uholJSUwmUzNXnP48OEW119bW4va2sbSbYPBAABICPO38TPQfhFBGnSJCMSJc5XYdrwIV/WJcdlzExGRbX4/Uoh6s4iukYEu6aOmUAiYmpqEeT8cxLIt2ZgyPMmmLvxl1XVYsikLe0+V4mRRJU6XVKO+hR2b7VnFKCyvRZTOuWOMPIVdQc7VV18t/3///v0xfPhwJCUl4YsvvoC/v+sChbaaP38+nn/++QvenuiipGPJZd0icOJcJTYdO8cgh4jIA0n5OON6O/+oSnLzkAT8++cjOF5YiT+OncOoHpEXvVYURXyz+wxeWnMY5yqs+65p/BToHB6IpPAAdI5o+G94IGZ/sQf5hlqcLq1mkGOLkJAQ9OjRA8eOHcP48eNhNBpRWlpqtZuTn5+PmBjLL/KYmJgLqqCk6qum15xfkZWfnw+dTgd/f38olUoolcpmr5HucTFz5szB7Nmz5dcNBgMSEhIQ78KdHAAY2T0CH287iU3Hzrn0eYmIqHUms4jfMi1Bzphezj+qkgRp/HDLkHgs3ZyNZZuzLhrkHM4zYO63GdjRcJzWJTIQ916WjK6RQegcEYDoYG2zu0BJYYGWIKek2ml9fzxNu0qKKioqcPz4ccTGxmLw4MFQqVRYv369/HhmZiZycnKQmpoKAEhNTcX+/futqqDWrVsHnU6HlJQU+Zqm95Cuke6hVqsxePBgq2vMZjPWr18vX3MxGo0GOp3O6gUAEsKcvxXZ1Igu4VAIljLys6XVLn1uIiJq2a6cEpRW1UHvr3L4vKrWTE3tDEEAfsssRNY561Yj5TV1eHHVQUxcsAk7sovhr1LiiQk9sfbRK/CXEUlI7RqOWL3/RY+54hua0Z4u6Thl6nYFOX//+9+xceNGZGdnY8uWLbjxxhuhVCoxefJk6PV6TJs2DbNnz8Zvv/2G9PR03HPPPUhNTcWIESMAAFdddRVSUlJw5513Yu/evfjpp5/wzDPPYMaMGdBoNACABx98ECdOnMATTzyBw4cPY9GiRfjiiy8wa9YseR2zZ8/GBx98gOXLl+PQoUOYPn06Kisrcc8997TpkxCkadeGlt30/ioMSAgBAO7mEBF5GKmq6sqekfBTurZnbueIQIzuadk9Wr4lG4DlaOq7PWcw9vWNWLIpCyaziKv7xuCXv43CQ1d2s7kFSmOQ03H+uLbrt/vp06cxefJkFBUVITIyEiNHjsS2bdsQGWnZUnvzzTehUCgwadIk1NbWIi0tDYsWLZLfX6lUYtWqVZg+fTpSU1MRGBiIqVOn4oUXXpCvSU5OxurVqzFr1iy8/fbbiI+Px4cffoi0tDT5mttuuw2FhYWYO3cu8vLyMHDgQKxdu/aCZGRPNrJbBHbnlGLT0XO4dUiCu5dDREQNfj1sSYdw5VFVU3df2hm/Hi7AV+mncf3AOLy6NhNbT1hGPnQOD8C8/+uDK3vavzap6W1HCnIEsSPVkp3HYDBAr9ejrKxMPrpyle0ninDb+9sQHqjGzqfH2ZRFT0REznWquAqXv/oblAoBu54ZD32A85oAXowoihj/5u84VtDYT03jp8DM0d1w/xVdoFW1bVDolmPncMeH29ElMhC//u1KB63WPWz9/c3ZVW5ySWIo/FVKFFUakZlf7u7lEBERgPWHLLs4Q5JC3RLgAIAgCPKoB8BS4fXL7FF4eGz3Ngc4QONOzpmS6g7TK8e1ySgkU/spMLxLGDZkFmLT0XPoHevanSQiIrrQ+obScVc0AGzJHcMSUW8yo0vDyAdHiNFrIQhAbb0Z5yqMiAzWOOS+now7OW40sptlJAaTj4mI3K+ith7bT1jKsse4YJRDS5QKAfdcluywAAew/HEd09Afp6NUWDHIcaORDVNtt2cVobbe5ObVEBF1bJuOFsJoMqNzeAC6Rrq2tYirdLQKKwY5btQzOhgRQRrU1Jmx62Sp059vd04J5v94CFVG5wx/IyLyZlLp+Jhe0RAE3ywG6WgVVgxy3EgQBIzsFg4A2HSs0KnPlZlXjjuX7MB7G0/gf7vOOPW5iIi8jblJl2N35+M4U0drCMggx81Gdrect246VuS05ygsr8W9y3aiotayg7PvdKnTnouIyBvtPV2KcxVGBGv8MLRzmLuX4zRSkHOmg3TbZ5DjZlLy8f7TpSirqnP4/WvqTHjg4z9xprQaWpXln3vf6TKHPw8RkTeTBnJe0SPS5g7C3qhTCI+ryIVi9Fp0iwqCWQS2nnBslZUoinjiq33YnVMKvb8KH909FABwtKACNXVMdCYikvxyyPePqgDr46qO0CuHQY4HcFYp+dvrj+L7vWfhpxDw7l8GIbVLOCKCNDCZRRzMNTj0uYiIvNXZ0mocyjVAENCmcQneJDbE0iunps6Mokqju5fjdAxyPMBlUpBz1HFBznd7zuCtX44CAP55Q19c2jUCgiCgf7weALCfR1ZERAAaj6oGJYYiLFDt5tU4l8ZPiehgqVeO7x9ZMcjxACO6hEGpEJBdVIVTxe3PeE8/WYLHv9oHAHjgii64fVii/Fi/TpYgh3k5REQW0igHXz+qknSkCisGOR4gWKvCwIQQAMDmdh5ZnSquwgP//RPGejPGp0TjyQm9rB6Xd3LOlLbreYiIfEGVsR6bj1uqW8e6ucuxq8gVVu3cyTlVXIWNR5zb/qS9GOR4CEfk5ZTX1GHa8p0oqjQiJVaHt24bCOV5082lnZxjBRVsCkhEHd6WY0Uw1pvRKcQfPaKD3L0cl+jkoK7Hs7/Yg6kf7UD6yRJHLMspGOR4CGnEw5bjRTCb7c94rzeZ8fDK3TiSX4GoYA2W3D0EgZoL569G6bSI1mlgFoGDZ5l8TEQdmzSQc1zvKJ/tcny+xq7HbT+uMplF7G1Ie9idwyCHWjEwIQSBaiWKK41tqnz65+pD2JBZCK1KgSVThyJW73/Ra/t1CgHAvBwi6thEUcSvhy35OGN6d4yjKsAx86tyiqtgrDcDAA7lljtkXc7AIMdDqJQKjOhiGfFgb17Ox1uzsWxLNgDgrdsGol9D3s3FNOblMMghoo4r46wB+YZaBKiVGJ7su12Oz9d0flVbe+UcyW8MbA7nee6pAIMcDyIdWdmTl/NndjGe/+EgAOCJCT0xoW9sq+8jBUEc70BEHZk0kPPy7hHQqpRuXo3rxIVYSsir60wobmOvnGMFFfL/H82vQL3J7JC1ORqDHA8iJR/vyCq2qSNxQXkNHvp0F+rNIq4bEIfpo7ra9DxS8vGJc5XyPCsioo5mfcNRVUepqpJo/JSI1mkAtH2GVdOdHKPJjKxzlQ5Zm6MxyPEg3aKCEK3ToLbe3Gq2ep3JjJkrdqOgvBbdo4Lw8k39bE6aiwjSIE6vhSgCGTyyIqIOqMBQI+clXtkr0s2rcb1OIe3LyzmSb9nJkQp4D+V5Zl4OgxwPIghCY/fjVo6sXvnxMHZkFSNI44fFdw5utpKqJf2Yl0NEHdhvmZajqgEJIYhq6ADckbSnwspkFnG80BLkSL+zDnvoqCAGOR5GOrJqKfl49b5cfLgpCwDw71v6o2uk/b0d+seHAGCFFRF1TPJAzl4do8vx+dpTYSVVVmn8FBjXUJV2mDs5ZAspyNl/pgwlzSSEHSsox+Nf7QUA/HVUF5sSjZsj5eVwJ4eIOpqK2nq5U++4DlQ63lTTCit7HW3Ix+kWFYQ+cToA3MkhG0XptOgRHQRRBLaeKLJ6rKK2Hn/9OB1VRhNSu4Tj8at6tvl5pCAn61wlDDV17VozEZE3+eVgPoz1ZnSJDETv2GB3L8ct2jO/6mhDZVWP6GD0iLF8/s6W1aCsyvN+lzDI8UAju1mS4P5oMpVcFEU88dVeHC+sRIxOi//ccQn8lG3/5wsNVMtf5Ae4m0NEHciqfbkAgGv7xXaYLsfnazq/yt5eOUea7OTotCo5idkT++UwyPFAI7tf2BTwwz+ysGZ/HlRKAQunDEJEkKbdzyM3BWReDhF1EIaaOvzecFQ1sX+cm1fjPnENgUml0YRSO3dgjuY37uQAkHfDPDEvh0GOBxqeHA4/hYCc4irkFFVh6/EivLz2MADg2WtTMDgp1CHPI4934E4OEXUQ6zLyYTSZ0T0qCD1jOuZRFQBoVUpEBlv+WLYnL6dpZVX3KEvRS6+YhrwcBjlki0CNHwYlWgKZr3adxsMrd8FkFnHjJZ1w54gkhz2PnHzMnRwi6iBW77ccVU3s37aiDV/SlrycU8VVqG2orEoIsyQv95J3cnhcRTaSRjwsWH8U5yqM6BUTjJdutL3hny2kICenuAqlVW1r7U1E5C3Kqurwx1HLUdW1DHLaVGHVNB9H2dAJUNrJycwrh9nctllYzsIgx0NJDZYAIFjrh8V/GQx/tWNnq+gDVEgKt3yRHzjjeRE4EZEj/XQwD3UmEb1igtEtquMeVUnk5GM7RjtIlVXSURUAdA4PgMZPgSqjCafaUK3lTAxyPNSAeD0igtQAgDduHYjOEYFOeR5pN2ffmVKn3J+IyFOsbqiqmtiPuzhA246rpB453aMbg0Q/pUJOQj6U61l5OQxyPJSfUoHPHkjF19MvxfgU5zWrYoUVEXUEJZVGuWKV+TgWbZlfJc2sarqTAwC9YjwzL8e+gUfkUt2i7B/XYK++0k4Ogxwi8mE/ZeSh3iwiJVaHLm0YheOLmubkiKLYas5n08qqHtHWx329YqXOx9zJIQ8iBTlnSqtR3MwYCSIiX8CqqgtJx1UVtfUoq269V05zlVWS3h66k8Mgp4PTaVXo0pDvwzlWROSLiipqseW4ZUwOq6oaaVVKubGsLUdWUmVV18jGyiqJ1HPoZHEVKmvrHbzStmOQQ+gn5+WUunchREROsDYjDyaziH6d9EgKd04Rh7eyZxp548yqC4/7woM0iArWQBQbgyFPwCCHGiusmJdDRD5IrqriLs4FOtlRYdVcZVVTPWM8b7wDgxxq7HzM4yoi8jGF5bXYdsJyVMXS8QvZs5NzscoqSW85+dhz8nIY5BD6dNJDEIDcshoUlte6ezlERA6z9kAuzCIwICHkgmRZsr3rcUuVVRKpjPwQd3LIkwRp/NC1oaTyAHdziMiH/NBwVHUtd3GaZWtDwJYqqyRNxzuIomeMd2CQQwCA/szLISIfk2+owc7sYgDANczHaVaCNNqhlZ0cKem4ucoqSdeoQPgpBJRV1yHPUOPYhbYRgxwC0NgvZz/HOxCRj/hxfy5EERiUGCJ39yVrnUIsuzLlrfTKkSqmmquskmj8lPKpgKc0BWSQQwAaxztwJ4eIfMUq6aiqf5ybV+K5/NVKhAda5iS2dGTVWmWVpFeslJfjGcnHDHIIAJASp4NCAArKa5HvIduMRERtlVtWjT9PlgAArmE+TotsqbBqbvp4c6S8HO7kkEcJUPuhe5QlAuewTiLydlJvnKGdQxGj17p5NZ6ttQork1nEMSnIsXEnx1PGOzDIIZk8rJMVVkTk5aRZVTyqal1rFVanSxorqxJbKcPv3bCTc7ywErX1JscutA0Y5JCsP8c7EJEPOF1Shd05pRAE4Oq+Me5ejsdr7bhKagLYUmWVJFqnQUiAymr3x53aFeS8/PLLEAQBjz32mPy2mpoazJgxA+Hh4QgKCsKkSZOQn59v9X45OTmYOHEiAgICEBUVhccffxz19dYDvTZs2IBBgwZBo9GgW7duWLZs2QXPv3DhQnTu3BlarRbDhw/Hjh072vPhdHjyDKszZR7T44CIyF5rGnZxhnUOQ5SOR1WtkY6rLlZGfkROOm45HwcABEGQmwJ6Ql5Om4OcnTt34r333kP//v2t3j5r1iz88MMP+PLLL7Fx40acPXsWN910k/y4yWTCxIkTYTQasWXLFixfvhzLli3D3Llz5WuysrIwceJEjB49Gnv27MFjjz2G++67Dz/99JN8zeeff47Zs2fjueeew65duzBgwACkpaWhoKCgrR9Sh5cSq4NSIeBchRG5ZUw+JiLvJOXjXDuAR1W2aG1+1bGCljsdn09OPvaAvJw2BTkVFRWYMmUKPvjgA4SGhspvLysrw5IlS/DGG29gzJgxGDx4MJYuXYotW7Zg27ZtAICff/4ZBw8exCeffIKBAwfi6quvxosvvoiFCxfCaDQCABYvXozk5GS8/vrr6N27N2bOnImbb74Zb775pvxcb7zxBu6//37cc889SElJweLFixEQEICPPvqoPZ+PDk2rUspfxJxjRUTe6FRxFfaeLoNCACb04VGVLaQeQoaa5nvlSDs53VqprJL08qBBnW0KcmbMmIGJEydi3LhxVm9PT09HXV2d1dt79eqFxMREbN26FQCwdetW9OvXD9HR0fI1aWlpMBgMyMjIkK85/95paWnyPYxGI9LT062uUSgUGDdunHwNtU2/TpYInBVWROSNpN44I7qEIzJY4+bVeIdAjR/CGnrlnH9k1TS3xuadnIZBnYe88bjqs88+w65duzB//vwLHsvLy4NarUZISIjV26Ojo5GXlydf0zTAkR6XHmvpGoPBgOrqapw7dw4mk6nZa6R7NKe2thYGg8Hqhaz1iw8BwAorIvJOa1hV1SYXq7CSKqvUNlRWSXpEB0EQgHMVtThX4d6hz3YFOadOncKjjz6KTz/9FFqt9yVzzZ8/H3q9Xn5JSEhw95I8jjTDav/pUiYfE5FXqTOZcTDX8sfrqJ6Rbl6Nd7lYhZU9lVWSALUfOocHArAM63Qnu4Kc9PR0FBQUYNCgQfDz84Ofnx82btyIBQsWwM/PD9HR0TAajSgtLbV6v/z8fMTEWM5GY2JiLqi2kl5v7RqdTgd/f39ERERAqVQ2e410j+bMmTMHZWVl8supU6fs+fA7hF6xwVApBZRU1bXY/ZKIyNOcLqmGySzCX6VELKuq7CJXWJVa/9w/WtD6zKrmSHk5h3Lde2JiV5AzduxY7N+/H3v27JFfhgwZgilTpsj/r1KpsH79evl9MjMzkZOTg9TUVABAamoq9u/fb1UFtW7dOuh0OqSkpMjXNL2HdI10D7VajcGDB1tdYzabsX79evma5mg0Guh0OqsXsqbxU6JnwxfnAR5ZEZEXyTpn2XVICg+AwsZdB7KQko/PP646mm/bOIfzNVZYuXcnx8+ei4ODg9G3b1+rtwUGBiI8PFx++7Rp0zB79myEhYVBp9Ph4YcfRmpqKkaMGAEAuOqqq5CSkoI777wTr776KvLy8vDMM89gxowZ0GgsSWIPPvgg3nnnHTzxxBO499578euvv+KLL77A6tWr5eedPXs2pk6diiFDhmDYsGF46623UFlZiXvuuaddnxAC+nXS48AZA/aeLsPVnPlC5HHqTGaUVBkRFczdiqayzll+QXeJDHTzSrzPxY6rpJ2c1sY5nM9TxjvYFeTY4s0334RCocCkSZNQW1uLtLQ0LFq0SH5cqVRi1apVmD59OlJTUxEYGIipU6fihRdekK9JTk7G6tWrMWvWLLz99tuIj4/Hhx9+iLS0NPma2267DYWFhZg7dy7y8vIwcOBArF279oJkZLJf//gQrNxxCvvY+ZjII03/ZBd+PZyPNY9eLv/FTI07OVI+CNmuuflV5jZUVkmk8Q5H8itQbzLDT+meAQvtDnI2bNhg9bpWq8XChQuxcOHCi75PUlIS1qxZ0+J9r7zySuzevbvFa2bOnImZM2favFayTeN4hzKYzSK3fYk8yJbj5/DLIUs+4s6sYgY5TWQ37OQkRzDIsZfUELCsug6GmjrotCqcKqlCTZ19lVWS+FB/BKqVqDSakF1UiW5R9gVJjsLZVXSBHtHB0KoUKK+tx4lzle5eDhE1EEURr/98RH79ZFHzHWo7qqyGn1cMcuwXpPFDaIAKQGOvnKNtqKySKBSCnN/pzn45DHLoAiqlAn3iGiaS88iKyGNsOFKI9JMl8usnixnkSGrqTDhbZvnlzCCnbc6fYXVEysexM+lYIjUFdGdeDoMcapZ0ZLWPnY+pgzlXUYvr/rMJb/1ypPWLXciyi5MJwDJnDgByuJMjO1lUBVEEgrWN3XvJPudXWEk7OfaWj0t6e8CgTgY51KyBCSEAgD2nSt26DiJX+/LP09h/pgwf/H4CdSazu5cj+ykjDwfOGBCoVuLFG/oAAHKKq9i0s4F0VNUlIhCCwDzCtji/wqqtlVWSxp0cBjnkYfo3jHc4mGuAsd5zftATOduqfWcBAJVGE3bnlLp3MQ1MZhFvrLPsLN07Mhn9OoVAIQDVdSYUlru3bb6nkIKczjyqarOmQU7Tyqq2HldJFVlnSqubHfzpCgxyqFmdwwOg0/rBWG+WJ9AS+bqsc5XIONuYP7DpaKEbV9No1b6zOJJfAZ3WD/dd3gVqPwVi9ZZfSMzLschm0nG7yWXkpVU4XVLd5soqid5fJR+BuWu8A4McapYgCBjQcGS1l8nH1EGsbtjFUftZfjT+ceycO5cDAKg3mfFmwy7OX0d1hd7fUgGTFG75xcMKKwtWVrVffFjjTo70x22XiMB29biRxju4K/mYQQ5dlJR8vJd5OdRBrNpnmWA9fVRXAJavfXdts0u+3nUa2UVVCAtU4+5LO8tvl4KcnCK2eQCArCIGOe0l7bqUVtXJ+Zj2NgE8X2PnY+7kkIeR8nJYYUUdwbGCchzOK4efQsA9l3VGl8hAmEVg6/Eit62ptt6EBeuPAQAeurIrAjWN/VsTwyy/zHlcBZTX1Mm5SczJabtgrUreKfwt0zJfsq2VVRJ5hpWbBnUyyKGLkiqsjuSXo8pY797FEDmZtItzefcIhASocXm3CADApmPuy8v5fOcpnCmtRrROg7+MSLJ6jMdVjaTPQUSQGjqtys2r8W5S8rGUm9beTsW9G3ZyMvPKYTa7vhKQQQ5dVLROi2idBmYROHDGvUPWiJxJFEU5yJnYPw4AMLJ7JABg01H35OVUG034z6+WXZyZY7pDq1JaPS4lg+ZwJ0fuzM6ZVe0nBTmS9u7kdA4PhNpPgUqj6YLhn67AIIda1HhkVerWdRA505H8ChwrqIBaqcBVfSxDfkd0CYNSISC7qAqn3BBIfLwtG4XltegU4o/bhiRc8Li0k1NcaUR5jevyhjLOluGUh/XnYWWV40gVVgDaVVkl8VMq5EDpoBuOrBw+hZx8y4B4PdYdzMde5uWQD5N641zRI1I+7gjWqnBJQgj+PFmCTcfOYfKwRJetp6K2Hu9uOA4AeHRcd7naq6lgrQphgWoUVxpxsqgKfTvpnb6uJZuy8OKqg5bn1/ihV2wwesfq0CtGh96xwegZE4wAtet/rbBHjuM03clpb2WVpG+cHgfOGLDnVCkm9I1p9/3swSCHWiSXkbPCinxU06Oq6wbEWj02snuEJcg56togZ+mmLJRU1aFLRCBuuqTTRa9LDAtAcaUROcXOD3IyzpbhlR8PAwCUCgHltfXYmV2CndmNs7QEwXI80Ts2GL1idLi6b0ybu+Xao2m3Y2qfpjs57a2skgxKCsVnO08h/WSxQ+5nDwY51KL+nUIAWM79SyqNCOVMGPIxB3MNyDpXCY2fAmN7R1s9dnn3CLz1y1FsPn4OJrNo9yTmtiirqsP7f5wAADw2vkeLf0knhQdgz6lSpycfVxtNeGTlbhhNZoxPicbCOwbhxLkKHMo14HBuOQ7mGnA4rxyF5bXIOleJrHOVWLM/D2/9cgRThidh1vgeTp0nxZ0cx5HKyIG2dzo+39DOYQCAvafLUFtvgsZP2cp7OA6DHGqRPkCFzuEByC6qwr4zZRjVI9LdSyJyKGkXZ3TPKARprH8kDogPQbDGD6VVdcg4WybnqDnT+38cR3lNPXrFBOPafrEtXpskJx87t1fOP1cfxPHCSkQFa/DKpP5Q+ynQK8ZyTIVLGq87V1GLw7nlOJRrwNYTRfj1cAE+3nYS3+05g8fG9cCdqUlQOeD4o6mSSqPcy4iJx+3XqclxlaN24TqHByA8UI2iSiMOnDFgcFKoQ+5rCyYeU6ukI6t9PLIiH2M5qrLk41w74MKAwk+pwIiu4QCAP1xQZXWuohZLN2cDAGaP7wFFKztHiQ2/1J25k/NzRh4+3Z4DAHj91gEt7shEBGkwsnsE7r+iCz66eyhW3j8CvWN1MNTU44VVBzHhrd+xoaH/iqNIlVWxei381a7bIfBVen8VonUaCALQJ07nkHsKgiAHNn9mu/bIikEOtUr665XjHcjX7D9ThlPF1fBXKTGmV1Sz11zevaFfjguCnMUbjqPKaEL/eD3Gp0S3er2ze+XkG2rw5Nf7AAD3X56My7vbt5Ob2jUcqx4eiZdu7IfwQDWOF1bi7qU7cc/SHTheWOGQNbKyyvGWTB2Kj+4eioR2VlY1NaRzQ5BzsqSVKx2LQQ61aoA03uF0mUeVjRK1l3RUNaZ31EWrgkY2NAVMP1mCaqPJaWspqTTik+0nAVh2cQSh9fwf6bgqt6waxnqzQ9djNov4+5d7UVJVh5RYHf6e1rNN91EqBNwxPBG/PX4l7r88GX4KAb9lFiLtzd/xwg8HUVbVvvJ35uM4Xt9Oeozu2XzQ31aDkyx5ObtOlrj09wiDHGpVnzg9lAoBheW1yDPUuHs5RA4hiiJWS1VV/S+e+5IcEYhOIf4wmszYnuW8EQ+fbDuJmjoz+nbS2Zz7Fhmsgb9KCbMInC5x7G7OR5uz8MfRc9CqFFgw+ZJ2J4vqtCo8PTEFP8+6AmN7RaHeLOKjzVm48t+/4aeMvDbfV5pZxcoqz9a3kw4aPwWKKo1yYOoKDHKoVf5qpVxKyFJy8hW7T5XiTGk1AtVKXNnCX62CIMi7Oc46sqqpM2H51mwAwP2Xd7FpF0dam9SszZEzrDLOluHVtZkAgGevTUE3B1XZAECXyCAsuXso/nvvMHSPCkJJVR3+/sVe1JvathOVVchux95A46fEgIbUhz+zXXdkxSCHbNL0yIrIF6zaa9nFGZcSfcHIhPONlPJyjjknyPluzxmcqzAiTq/FNa1UVJ0vUZ5G7pgg5/xy8Tuc1B/oih6RWPPo5dBp/VBeW9+mbriiKCJbmj4eySDH0w2W83Jcl3zMIIdsIldYMfmYfIDZLGLNfkuQc23DrKqWXNYtAoIAHM4rR0G5Y49szWYRH/yRBQC4d2Sy3SXWUl6Oo5KPzy8Xt3VXqS1USgWGNPRQ2dmGv+4LymtRZTRBIQAJoY5LkiXnGJLk+uRjBjlkk/4NOzn7Tpe5ZZIskSOl55Qgz1CDYK0frugR0er1YYFquZx2s4N3czYcKcCxggoEa/xw29ALZ1S1RqqwckSvHHvKxR1FahS3M8v+v+6l3I6EsIBmR1+QZ5HKyE8UVqK40uiS5+RXBdmkR3QwNH4KlNfUy4l+RN5q1V5Lb5yrUmJsTqgd2c2SDOzofjkf/G7ZxZk8PBHBDXOz7OGoXjntLRdvq6ENRxg7s4vtrrrJ4vRxrxISoJa7KKe7aDeHQQ7ZRKVUyLNxeGRF3sxkFrHmgKWa59oWqqrO17RfjqNKYPefLsPWE0XwUwi4+9LObbpHY9fjqjbvsprNIv72RfvLxduiX7we6oaqmxN2Vt2wR473kfvluKgpIIMcspl0ZLX3FJOPyXvtyCpGYXkt9P4qXNat9aMqyeCkUGj8FCgor8XRAsc0svugYUbVtf1jEddkZpA9OoX6Q6kQUFtvRkF5bZvu8dWu09h0zHHl4vbQ+CkxsCHnz95ffCcY5HgdqV+Oq/JyGOSQzQaw8zH5AGmMw4Q+MXblcWhVSgxLtvyAdsSR1ZnSaqxuSH6+7/Iubb6PSqlAXIgWAHCyjUfJvx22jFr46xVdHVoubqthDXk5O7Ls+8XHnRzvIx1P7j9dhpo65zXXlDDIIZtJOzkHzxpQ18aeFkTuVG8yY23DUdVEO46qJI1HVoXtXsvSTVkwmUVc2jVcPgpuq6SwhrycNvTKEUURu3IswcWlDXO6XG1Ik7wcW5nMopyHxCDHeySGBSAiSAOjyYwDZ5x/KsAgh2zWOTwQOq0fauvNyMwrd/dyPNrZ0mos/O2YPB2ZPMO2E8UoqjQiLFDdpl/oUvLx9qzido1RMNTU4bOdpwAA91/R9l0cSXt65eSW1SDfUAulQnDJlPXmDE4KhUKw5BXl29hV/WxpNYwmM9RKRZuP+sj1BEGQS8nb0jbAXgxyyGaKJj8EeWR1cfUmM+5b/ide+ykTn+3IcfdyqAn5qKpvDPzs7EcDAL1ighERpEaV0STvfrTFZztyUFFbj+5RQbjSxhEOLUlqR9dj6ePoHRvstinewVoVesdaSvRt3c2RKqsSwwOgbGVaO3kWaecu3QVNARnkkF3kfjlMPr6o5VtPyt1bz5RWu3k1JKkzmbE2w/6qqqYUCkFOVm7riIc6kxlLN2cDsG+EQ0vkXjltyMnZnVMKABiUGNrudbSHvf1y5E7HPKryOlK/nHQXDOtkkEN2kTofcyenebll1Xjj50z59XMVbat2IcfbdPQcSqvqEBGkwfDktueeSHOs/mhjU8DV+3KRW1aDiCANrr+k9W7LtkgKb3tOjrSTc0liiEPW0lZSkLPDxiOME4UMcrxVnzg9tCoFSqrqcLzQuX3XGOSQXaQKq6MFFagy1rt3MR7o+e8PotJogn/DLKTCNpb0kuOtaDg6vG5AbLuON6QmeftPl6Ksyr6cK1EU8f7vlrLxuy9NcliptjSks7Sqzq48sNp6EzLOWHYd3b6Tk2x5/sN5BhhqWv8YuJPjvdR+iibDOp17ZMUgh+wSo9ciKlgDk1lExln7B+r5svWH8rE2Iw9KhYB/XNMLAIMcT3G2tBrrD+UDAKYMT2rXvWL0WnSLCoJZBLYct283Z8vxIhzMNcBfpWz3OpoK1PghIkgDwL7k44yzBhhNZoQFquVAyV2igrXoHB4AUbStGy67HXs3uSmgk/vlMMghu8lHVqdK3boOT1JlrMfc7zIAAPeNTJbzNhjkeIaVO3JgFoHULuEO6QPT1iMrqfnfrUPiEerguVBSXs5JO2ZYNebjhDh1EKethtiYl2OsN+N0iSXfrQunj3ulIQ1NAZ093oFBDtltQJNhnWSxYP0xnCmtRqcQfzw6rjsigy1/VVcaTais5bGeO9WZzHK59l9GOGb3pOmIB1sdyS/HhsxCCIJl2rijtWUaeWM+jnuPqiTD5InkLQc5p0qqYDKLCFArEdXwvUbeZVBiKATBsiPnzNxFBjlkN5aRW8vMK8eHDX+hP/9/fRCg9kOQxg9aleXbi8nH7vVzRj4Ky2sRGazBVX2iHXLP4V3C4acQkFNcZfPxkPQ1MqFPjJwo7Eht6ZWzp2En55KG3Vl3G9rQUXrvqZa74WY3OaryhB0osp8+QIUeUcEAgD+d2C+HQQ7ZTSojP1lUhdIqo5tX415ms4inv9mPerOItD7RGJdi+SUqCIK8m8Mgx70+3pYNAJg8NAGqNvTGaU6Qxk+uRvrjWOvdjwsMNfh2t6VHT3tGOLTE3uOqfEMNzpRWQyEA/T0kyOkc3tgNd38L3XCzOM7BJwx2Qb8cP6fdmXxWSIAancMDkF1UhX2ny3CFA5qZeasv00/hz5MlCFQr8dx1faweiwzS4FRxNfNy3OhYQTm2nSiGUiFg8vBEh957ZLdI7Mwuwbe7zyBArYRSoYBKIUCpEOCnFOCnUMBPIcBPqcB3e87AaDJjcFKo3CPE0RIbRjvYupOzu+Goqkd0MII0nvGrQBAEDO0cih8P5GFHVrFcVn4+Dub0DUOSQrFie45Tk4894yubvE7/+JCGIKe0wwY5RRW1mP/jYQDArPE9LmgtL+3kMMhxn0+2WcrGx/aKQqzesa3/L+8RgTd/OYKd2SU2t6e/30m7OEDjTk6uoQa19aZWy9N3SUnHTgq62mpo5zD8eCCvxdJi+biKQY5Xk5KPD5yxHE9qVY7vuM0gh9qkf7we3+89iz0duPPxS2sOo7SqDr1jdbj70s4XPC6V9DLIcY8qYz2+Tj8NALgz1XHl2pJLEkLw0JVdcSjXgHqziHqTCJNZRJ3ZDFPD6/VmM+rNlrf37aTH+BTH5AQ1JzxQjUC1EpVGE04VV7daRSbt5HhKPo5EmvT+58kSmMxisz2NeFzlGxLC/BEVrEFBeS32nS6T/+0diUEOtcnAhh+M+zpo8vHW40X4etdpCALw0o19m52DJO/kMCfHLb7bcxbltfXoHB6Ay7pGOPz+giDgiQm9HH7fthIEAYnhgTiUa0BOcWWLQY6x3ixXR3raTk6vGMvxWXlNPTLzypESp7N6vNpoQm6ZZYgngxzvJggChnQOxZr9ediZXeyUIIeJx9QmfeL0UCoEFJTXIq/MtqnBvqK23oSnv90PAJgyPPGi5beNx1UdOznbHURRxMdbTwKwlI0rOsgAR1vLyA/nGVBbb4beX4VkD2um56dUyEndzZWSS52O9f4qhAaoXLk0coLBTu6XwyCH2sRfrUT3hr8U93SwpoAf/H4CJworERGkweNpF/9LPjKIOznusvtUKQ7mGqDxU+DmwfHuXo7LyBVWrQQ5UhPASxJDPDIAbKlfTtN8HJaPe78hTYZ1ms2OH9bJIIfarKMdWZnNIg6cKcN/fj0GAHj22t7Q+1/8L0m5hJw5OS73yTbLLs61/eMQEuDYzsKeTO6V08qgTrkJYIJnHVVJpH45O7OLL5hSLVVWdeFRlU9IidPBX6VEWXUdjhdWOPz+zMmhNhuQEILPdp6S/yr0FVXGepworMSJc5U4XlAh/zfrXCWqGxqUjewWgf8b0PIE6abVVaIo8q9OFympNGLVvlwAzkk49mRJDWXkJ4ta7pUjj3NICnHyitpmYEIIVEoB+YZanCquloM3wLoRIHk/lVKBgQkh2HqiCDuzS9A9Otih97cryHn33Xfx7rvvIjs7GwDQp08fzJ07F1dffTUAoKamBn/729/w2Wefoba2FmlpaVi0aBGioxsrCnJycjB9+nT89ttvCAoKwtSpUzF//nz4+TUuZcOGDZg9ezYyMjKQkJCAZ555BnfffbfVWhYuXIjXXnsNeXl5GDBgAP7zn/9g2LBhbfw0UFtIU4v3ni5FvcncbPKtu8397gA2HT3X0LtEAZVSkHuXSP9VNfQ1qTKacKKwEmdKqy96P5VSQP/4EMy/qV+rQYtUXWU0mWGoroee+QMu8WX6KRjrzejbSSePIOkopOOqUyXVMJvFZo+izlXUIqe4CoLQOIfO02hVSvTrpMeunFLsyC62CnLkyirOrPIZQzqHYuuJIvx5shh3OLiflV1BTnx8PF5++WV0794doihi+fLluP7667F792706dMHs2bNwurVq/Hll19Cr9dj5syZuOmmm7B582YAgMlkwsSJExETE4MtW7YgNzcXd911F1QqFV566SUAQFZWFiZOnIgHH3wQn376KdavX4/77rsPsbGxSEtLAwB8/vnnmD17NhYvXozhw4fjrbfeQlpaGjIzMxEVFeXQTxBdXPeoIARr/FBeW4/DeeXo28mzfqFsO1GE/zYkn9orLFCNLhGB6BoZhK5RgegSEYSuUUFICPW3OZjTqpQI1lqqRAorahjkuIDZLOLT7ZbeOHeOSOpwu2exei38FAKM9WbkGWou6N0ENO7idI8Kgk7ruV+TQ5PDsCunFH9mF1vlVUmJx56WME1tN7hJXo6j2RXkXHfddVav/+tf/8K7776Lbdu2IT4+HkuWLMGKFSswZswYAMDSpUvRu3dvbNu2DSNGjMDPP/+MgwcP4pdffkF0dDQGDhyIF198EU8++STmzZsHtVqNxYsXIzk5Ga+//joAoHfv3ti0aRPefPNNOch54403cP/99+Oee+4BACxevBirV6/GRx99hKeeeqrdnxSyjUIhYGBiCP44eg67c0o8LshZsP4oAOD6gXG4bUgC6swiTGYz6kyNPUws/29GnVmExk+BrpGWgMZRE6IjgzWWIKfciG6Mv53uj2PncLKoCsFaP1zXynGiL/JTKhAf6o/soiqcLKpqNsjx9HwcybDOYXhv4wnsaJJ8bKipw7kKS7Vi54iAi70reZlBSZZhnSeLqlBQXoOoYK3D7t3m8wWTyYTPPvsMlZWVSE1NRXp6Ourq6jBu3Dj5ml69eiExMRFbt24FAGzduhX9+vWzOr5KS0uDwWBARkaGfE3Te0jXSPcwGo1IT0+3ukahUGDcuHHyNRdTW1sLg8Fg9ULt48wIvD3STxZjy/EiqJSWXiaXdovAqB6RGNMrGml9YjCxfyyuH9gJNw+Ox+3DEnHniCTcOiQBg5PCHBbgAK6vsKozmfHEV3vxxZ+nXPJ8nkZKOL55cDwC1B0z5TCxYYcj5yIzrOQmgA1l2p5K+tlyorBxSrWUjxMZrEGwB+9CkX10WhV6NuTipDt4WKfdQc7+/fsRFBQEjUaDBx98EN988w1SUlKQl5cHtVqNkJAQq+ujo6ORl5cHAMjLy7MKcKTHpcdausZgMKC6uhrnzp2DyWRq9hrpHhczf/586PV6+SUhIcHeD5/OI+Xl7PKw5OMF6y0VUJMGxaNTM3/NuoqrRztsP1GML/48jae+3if/xe4K5TV1WLzxOJ777gC2nyi6oCLGFc6UVmP9oXwAwJThHSvhuKmWeuXUm8zYe8ozmwCeLyRALf/ik0Y8yPk4PKryOUMahnU6eo6V3UFOz549sWfPHmzfvh3Tp0/H1KlTcfDgQYcuylnmzJmDsrIy+eXUqY75164jDUwMgSBYSlY9ZXzB3lOl2HikEEqFgIeu7ObWtbg6yDlbZkmaNovA37/ci5qGajBnKa+pwzu/HsXIV37Dyz8exvKtJ3Hb+9sw/s3fsWRTlkun1H+2IwdmEUjtEt7qSANf1jiN/MIgJzO/HNV1JgRr/NAt0vM/R0OTLb/4pNlgHOfgu6Q5Vm4PctRqNbp164bBgwdj/vz5GDBgAN5++23ExMTAaDSitLTU6vr8/HzExMQAAGJiYpCfn3/B49JjLV2j0+ng7++PiIgIKJXKZq+R7nExGo0GOp3O6oXaR6dVoUeU5a8tV+4ctOQ/vzbm4jStynAHV8+vym/SffpEYSXeWHfEKc9TUVuPhb8dw+Wv/oZ//3wEZdV16BoZiJsGdYK/SoljBRV4cdVBDH9pPWZ/vgd/NtPvxJGM9Was3GH5o6WjlY2fL7FhJ6e5aeTSjutAD20CeL6h5zUFzOJgTp8lHU9mnClDtdFxf5y1u+bXbDajtrYWgwcPhkqlwvr16+XHMjMzkZOTg9TUVABAamoq9u/fj4KCAvmadevWQafTISUlRb6m6T2ka6R7qNVqDB482Ooas9mM9evXy9eQa0nb3p4Q5GScLcMvhwqgEIAZo927iwM0aQjoopycPIMlyJEaNX7wxwmkn7z4NGd7ScHNyFd+xWs/ZaK0qg5dIgPx9u0D8fOsUXjj1oHY8fRYvHhDX/SO1aG23oz/7T6DmxdvxYS3/sDyLdkoq65z2HokPx/Mw7mKWkQFa5w6BNMbJIVfvFeOpw7lvBgpyMk4a0Blbb2ck8OdHN8TH+qPGJ0W9WbRoV307Qpy5syZg99//x3Z2dnYv38/5syZgw0bNmDKlCnQ6/WYNm0aZs+ejd9++w3p6em45557kJqaihEjRgAArrrqKqSkpODOO+/E3r178dNPP+GZZ57BjBkzoNFYfhk8+OCDOHHiBJ544gkcPnwYixYtwhdffIFZs2bJ65g9ezY++OADLF++HIcOHcL06dNRWVkpV1uRaw1qSGDc5QHJx+80dCO+tn8cunrAdryrj6ukOWK3DInHpEHxEEXg71/ua/dfRpW19Vi04RgubxrcRATirdsGYt2sUbh+YCd5WnSwVoU7RyRhzSMj8b+HLsXNg+OhVSmQmV+O577PwPCXfsGc/7V/TU1Jc6puH5YIlQf2a3IlaSfHUFN/wXGhPM7Bw/NxJHEh/ugU4g+TWcSunBK52zGDHN8jCAIGN+Tl7D7luN8ldpUfFBQU4K677kJubi70ej369++Pn376CePHjwcAvPnmm1AoFJg0aZJVM0CJUqnEqlWrMH36dKSmpiIwMBBTp07FCy+8IF+TnJyM1atXY9asWXj77bcRHx+PDz/8UC4fB4DbbrsNhYWFmDt3LvLy8jBw4ECsXbv2gmRkcg1pJ2ff6TIY681Q+7nnl0xmXjl+PGBJPp85xv27OIDrq6uknZwYnRZzr0vBpmOFyDpXiX//nIlnr02x+36iKOK/W0/irV+OoKTKsgOTHBGIR8Z2w3X941rsGSQIAgYlhmJQYiievTYF3+w6jRU7cnAkvwIrd5zCoMRQ3DKk/cn/R/PLsT2rGEqFgMnDWEzgr1YiKliDgvJanCyqksdalFQa5eMeb9nJAYBhyWH4ZvcZ/JSRh/KaeghCY94R+RYpab7A4Lifl3YFOUuWLGnxca1Wi4ULF2LhwoUXvSYpKQlr1qxp8T5XXnkldu/e3eI1M2fOxMyZM1u8hlyjS0QgQgJUKK2qw8Fcg3xU4mrv/GbZxbm6bwx6OLg1eFtFNezkFFXUwmQW5d0OZ8mXghy9Fnp/FV6+qT/uWbYTH23OwoS+MfL2vy3qTWbM/T4DKxqa63UOD8AjY7vj/wa0HNw0R++vwt2XJWPqpZ3xwqqDWLo5G9tOFDskyPlm9xkAwNheUYjVu6+SzpMkhQdYgpziKrmrsfTXcZfIQK+a5zW0syXI+W7PWQBAnN4fWpXSzasiZwhpaJjqyCPtjr2vSw4h/cUOuO/I6nhhBVbts/wQ9JRdHMDSOVkQLNVOxZXOrTQy1pvlRmkxOkszrdG9onDLYMux1eNf7rX5iKjKWI+/fpyOFdtzIAjAMxN745fZo3DToPh2je8QBAGje1q6Im47UdTm+zS15bjlPml9Wi486EgSG2ZY5TTJy5GPqjy8CeD5hjYcYZTX1APgUZUvkwYeO7Iqk0EOOYTcFNBNyccLfzsGUQTG9Y5GnzjP6bzsp1QgrOGvZmfn5RSUW3Zx1EoFwpo0NHzm2hTE6rXILqrCqz8dbvU+5ypqMfmD7Vh/uAAaPwXenTIY913exWGzyQYnhUKpEHCmtBqnS1qelt2aitp67D9j6fsyomu4I5bnE+Qy8iYVVlJhgKcO5byYblFBCG0yEoWdjn2X3t/yc4s7OeRxpO6pu92wk3OyqFLeyn5krOfs4khcVWElHVVF6TRWM5v0/iq8PKk/AGDp5mxsb2EHJftcJSa9uwV7T5UiJECFFfcPx4S+jt0hCdT4oV/DCJDtJ9pX+bUzqxgms4jEsAC3Nn30NOf3yjGZRbkJoLft5AiCgCFNjlmTI9xfUEDOIe/kMMghTzMgPgRKhYCzZTXILbv4FG9nWPTbcZjMIq7sGYn+8SEufW5buKrCKq/Mcn/pqKqpUT0icftQS/7L41/tQ5Wx/oJrdueU4KZ3t+BkURUSwvzx9fRLMTjJ9hweewzvYrnv9qz2HVltbQjYUrtwF6ep83vlHC0oR0VtPQLUSvSM8Yx8NXtIR1YAkMydHJ8l5eQYGOSQpwnU+KFXww/PXSdLXfa8p0uq8PWu0wCAh8d0d9nz2sNVFVZScBmtb3643dMTeyNOr0VOcRVe+dH62GrdwXxM/mAbiiuN6NdJj6+nX+rUEvwRyZagZHtW+3Zytjbk46TyqMqK1Csnz1CDmjqTnI8j/THibYZyJ6dDaMzJqXNY81AGOeQwg93QFHDxxuOoN4u4rFu4/PyexlU7OdJxVWwzOzmApX/NKzdbjq2Wbz0pBwifbDuJv378J2rqzBjVIxKfPTDCoVOAmzOkcygUDVOH85p0abZHWXUdMs5ajmAY5FgLDVAhWGMpnj1VXOU1Qzkvpm8nPbpFBaFrZCASQnks6auknZx6s4gqB/XRYpBDDiNVWLlqInleWQ2+2OnZuziA60Y75DX0loi5yE4OAFzePRJ3DE8EADzx9V7MX3MIz3x7AGYRuHVIPD6cOgSBGudP7w7WquQE8bYeWe3MKoZZtLQwiL5IYNdRCYIgjzQ5WVQlj3OQvke9jUqpwKqHR+LHR69wWAI8eR5/lRIqpWWn0VF5OfxqIYeRfoBmnC1z+mBIwLKLYzSZMSw5DCM8OCfDZTs5DTsirf3C/8c1vdEpxB+niqvx3u8nAACPjeuOVyb1d2m34OHJliOIbW1MPpbycYZ78L+9O0nJx/vPlOFYQQUAy8wqb6VVKd3WaJRcQxCExgqrKgY55GESwvwREaRBnUnEgYayXmcpKK/Byh2WJnWPePAuDuC66qq8Jo0AWxKk8cOrDcdWSoWAVyf1x2PjelhVZLmCFJy0dSeH+Tgtk3rl/LDXUnmYFB4g7yoSeSq9v2UnubTaMb1ynL8vTR2GpSlgCH4+mI9dOSVWZZ+O9uEfWaitN+OSxBBc1s2zf8nJOzlODHJEUbQa6dCay7pF4OvplyJQo0SvGJ3T1tWSYZ3DIAiWaekF5TV25QGVVhlxKM8AABjRxXlfZ95M2sk54YWjHKjjsnTjrnRYhRV3csih5KaATszLKauqkwcyPjKmu8t3IOwlVVeVVtWhtt45x3glVXUw1psBWPrk2GJwUqjbAhwA0Aeo5OffYWeV1bYTxRBFS6M4ZydJeytpDpBkkIcm5hM11bTCyhEY5JBDDZIrrEodVgJ4vm92n0Z1nQm9YoJxZc9IpzyHI+n9VXIyXVGFc0Y7SBVKYYFqaPy8Z66PlJdjb1PAbeyP06rE84ZYelsTQOqYQvwdO7+KQQ45VL9OeqiUAgrLa3G6xPFNAUVRxGc7TwEAJg9L9PhdHABQKASEBzo3+TjfjqMqTzKijU0B5SCH+TgXFav3l4NrrUqBXrHe1wSQOh59gGO7HjPIIYfSqpRIaSgNdka/nD2nSnE4rxwaPwVuGNjJ4fd3FmcnH9uadOxphjU0BTySX2HzANOiiloczisH0LgTRBdSKgQkhFp2c/p3CnFp5RxRW+m5k0OebrATJ5J/tsOyizOxX6wc8XsDZ5eR59lYPu5pwgLV6BFt6WC7w8bdHKlLcs/oYISzWqhF0pHVJV42lJM6Lvm4ijk55KmkKceOnkheUVuPH/ZZymFvH5bo0Hs7W6STGwJ663EVALnHka39clg6brupl3bG4KRQ3OFl3y/UcUl/vHInhzyW1BTwUG55s4Mg2+r7PWdRZTSha2Sg1cA+b+DsMvLG4yrv29kYbuccK6kJoCc3gPQUo3tG4evpl8qzrIg8XUhDM0BH9clhkEMOFxfij1i9FiaziL2nHNcU8LOdluZ/tw/1joTjpnhcdXHDGvJqDucZUFrV8g+2gvIaHCuogCCwPw6RL9IxJ4e8gbSb46jk44yzZdh3ugwqpYCbBnlPwrHE2fOrpJ2cWL33DS+MDNaga2QgRLH1fjlSqXnvGF1D0zAi8iXSkE72ySGPJvfLcVDysZRwfFWfGK9MNnVmdVVNnUn+geCNOTlA0xEPLQc5PKoi8m1SdVV5TT1M5vb3WmOQQ04xqGEQ4K6cknY3Bawy1uPb3WcAwGsTKJ15XCUlHWtVCuj8vXNSi9wUsJUKq21MOibyaVKQA8Ahox0Y5JBT9InTQ+2nQElVHbIaZue01ep9uSivrUdiWIDXdriVgpxKowmVtY5LxgYa83FidFqvy1WSSDszB88aYKhp/gdbvqEGJ85VQiE05vEQkW9RKRUIVFu6tjuiISCDHHIKtZ8C/TtJTQFL23UvqcPxbUMToFB45y/xQLUS/irLN66jj6ykfBxvTDqWROu06BweALMI/Jnd/JGVVDreJ05v9dceEfkWKd/OEcnHDHLIaQYntT/5+Eh+OdJPlkCpEHDL4HhHLc3lBEFw2pGVvJPjZd2OzyeXkl+kXw774xB1DDp5SGf7y8gZ5JDTXOKAzsdSwvHYXlGI8uKdCgCICLL8deKsnRyvD3IaSsK3XST5eCuHchJ1CI4c0skgh5xG6nycmV+O8ovkWbSkps6E/+0+DcAyjNPbOWsnx5u7HTclVVgdOFOGivPyls6UViOnuApKhYAhXtYIkojs48j5VQxyyGmigrVICPOHKFoGa9rrp4w8lFbVIU6vxRU9Ih2/QBdz+nGVlwc5nUL8ER/qD5NZRPp5u39SVVXfTnoEa5mPQ+TLpF45jphfxSCHnEpuCniy1O73lY6qbhmSAKWXJhw3FRlkCUIcPdoh32C5X7SXH1cBTfNyrEvJeVRF1HFIOzmsriKPJyUf2zusM/tcJbaeKIIgALcOTXDG0lzOGTs5ZrPoM8dVQGNezvlNAZl0TNRxOHJIJ4MccippJ2d3TgnMdnSvlMrGR/WIRKcQ7xtV0Bwp8diRQU5RpRH1ZhGC0BhEebMRDTs5+06XotpoAgCcKq7CmdJq+CkEDEliPg6Rr5N3cnhcRZ6uV0ww/FVKlNfU41hhhU3vU2cy46t030k4ljSOdnDMdF2gMR8nIkgDldL7v50TwizDXetMotx6QNrFGZAQgkCNd3Z0JiLbSZPI2fGYPJ6fUoEBCQ1NAW0sJV9/KB/nKmoRGazBmF5RzlyeSzU9rmrvqAtJ42BO7z+qAiz9hKTux1JeTuO8KnY5JuoIGnNy2CeHvICUl/PxtpNYvS8XVcaWxxqskBKOB8f7xO6ERJpEbjSZYah2zGgHX+h2fD5pjtW2rGKIoohtctJxhDuXRUQuEsKcHPImo3pYdmMyzhowY8UuDHpxHaZ/ko7v9569YI7TqeIq/HG0EIBljIMv0aqU0Gktxy2FFTUOuWe+j5SPNyX1y9lzqhRH8iuQW1YDlVKQg2Ui8m2OzMnhATc53bDkMKx+ZCR+2JuLNftzkVNchR8P5OHHA3nQ+CkwqkckJvaPxZheUfjyz1MQReCybuFICg9099IdLjJYA0NNPQrKa9EtKrjd9/OVbsdNdQ4PQFSwBgXltVi88TgA4JKEUPg3DO0jIt8mVVfV1ptRU2eCVtX2730GOeQSfeL06BOnx5MTeiLjrAFr9lsCnuyiKvx8MB8/H8yHWqmAn9LSD+f2ob6TcNxURJAGxwsrHVZhle+Dx1WCIGB4l3D8sPcsvttzBgAwgqXjRB1GkNoPCgEwi5YjKwY55DUEQUDfTnr07aTH42k9cSi3HD8eyMXq/bk4UVgJowkIC1Tjqj7R7l6qUzi6wirXB4+rAEtezg97z0LqOsAmgEQdh0IhQO+vQklVHcqq69r1RxyDHHIbQRCQEqdDSpwOs8f3wJH8Cmw8UoAhncOg8fPNowlHNwTM95EJ5OdrWkml9lPgksQQ9y2GiFxOCnLam5fDIIc8giAI6BkTjJ4x7c9T8WSODHIqa+tR3pC47WtBTtfIIEQEqXGuwohBiSHt2q4mIu+jD1ADRVXtrrBidRWRC0U2lJE7Yn6VlHQcpPFDkI81yRMEAaldLSXjI7uxdJyoo2mssGrf0b5v/WQk8nCO3MmRjqqidd4/zqE5T1/TG/066XBXamd3L4WIXCzE3zG9chjkELmQ1BDwnAN3cnztqEoSo9figSu6unsZROQGegcFOTyuInKhqIadnKKKWpjsGFjaHF/sdkxEBDiu6zGDHCIXCgtUQ2jo/1Bc2b6zZmk4p6/MrSIikjiq6zGDHCIX8lMqEB5ombDb3rycPB/tkUNExOMqIi8V4aAKK1/sdkxEBDSdRM4gh8irOKrCytcTj4mo4woJsOx4G1wZ5MyfPx9Dhw5FcHAwoqKicMMNNyAzM9PqmpqaGsyYMQPh4eEICgrCpEmTkJ+fb3VNTk4OJk6ciICAAERFReHxxx9Hfb31NOoNGzZg0KBB0Gg06NatG5YtW3bBehYuXIjOnTtDq9Vi+PDh2LFjhz0fDpFbRDqgwqreZJaDJB5XEZGvkRKP29snx64gZ+PGjZgxYwa2bduGdevWoa6uDldddRUqKyvla2bNmoUffvgBX375JTZu3IizZ8/ipptukh83mUyYOHEijEYjtmzZguXLl2PZsmWYO3eufE1WVhYmTpyI0aNHY8+ePXjsscdw33334aeffpKv+fzzzzF79mw899xz2LVrFwYMGIC0tDQUFBS05/NB5HSO2Mk5V2GEWQSUCgHhQb7ZJ4eIOq6mOTnm9lSiiu1QUFAgAhA3btwoiqIolpaWiiqVSvzyyy/law4dOiQCELdu3SqKoiiuWbNGVCgUYl5ennzNu+++K+p0OrG2tlYURVF84oknxD59+lg912233SampaXJrw8bNkycMWOG/LrJZBLj4uLE+fPn27z+srIyEYBYVlZmx0dN1D4f/H5cTHpylfjwil1tvseuk8Vi0pOrxNSXfnHgyoiIPEO1sV5MenKVmPTkKrGs2njB47b+/m5XTk5ZWRkAICzMMkwvPT0ddXV1GDdunHxNr169kJiYiK1btwIAtm7din79+iE6unHKdFpaGgwGAzIyMuRrmt5Duka6h9FoRHp6utU1CoUC48aNk69pTm1tLQwGg9ULkas5YidHTjpmPg4R+SCtSgmNnyVEKWtHGXmbgxyz2YzHHnsMl112Gfr27QsAyMvLg1qtRkhIiNW10dHRyMvLk69pGuBIj0uPtXSNwWBAdXU1zp07B5PJ1Ow10j2aM3/+fOj1evklISHB/g+cqJ0cMb+K5eNE5Osc0RCwzUHOjBkzcODAAXz22WdtfnJXmzNnDsrKyuSXU6dOuXtJ1AFJOzntSTzOM1jel+XjROSrHNErp02zq2bOnIlVq1bh999/R3x8vPz2mJgYGI1GlJaWWu3m5OfnIyYmRr7m/Cooqfqq6TXnV2Tl5+dDp9PB398fSqUSSqWy2WukezRHo9FAo2GSJrmX1CentKoOtfUmaPyUdt8jn+XjROTjQvwtZeTt6Xps106OKIqYOXMmvvnmG/z6669ITk62enzw4MFQqVRYv369/LbMzEzk5OQgNTUVAJCamor9+/dbVUGtW7cOOp0OKSkp8jVN7yFdI91DrVZj8ODBVteYzWasX79evobIU+n9VVApBQBAUUXbyiN5XEVEvk7n6p2cGTNmYMWKFfjuu+8QHBws57/o9Xr4+/tDr9dj2rRpmD17NsLCwqDT6fDwww8jNTUVI0aMAABcddVVSElJwZ133olXX30VeXl5eOaZZzBjxgx5l+XBBx/EO++8gyeeeAL33nsvfv31V3zxxRdYvXq1vJbZs2dj6tSpGDJkCIYNG4a33noLlZWVuOeee9r8ySByBYVCQESQBrllNSgsr0VciL/d92C3YyLydXKvnOq298qxK8h59913AQBXXnml1duXLl2Ku+++GwDw5ptvQqFQYNKkSaitrUVaWhoWLVokX6tUKrFq1SpMnz4dqampCAwMxNSpU/HCCy/I1yQnJ2P16tWYNWsW3n77bcTHx+PDDz9EWlqafM1tt92GwsJCzJ07F3l5eRg4cCDWrl17QTIykSeKDG4McuwliiJyOZyTiHycy3NyRLH1hjxarRYLFy7EwoULL3pNUlIS1qxZ0+J9rrzySuzevbvFa2bOnImZM2e2uiYiT9OeCitDTT2q60wAmJNDRL4rRApy3FFCTkRtJyUfn2vDTo50VKX3V0Grsj9pmYjIG+jdWUJORG0nNwRsw04Ok46JqCOQJ5FzJ4fIu7Sn63Eeux0TUQcgBzncySHyLu0JcvLlnRz2fCIi3xUSYOmTY2CQQ+Rd2nNclSs3ArS/9JyIyFs0Hle1vYScQQ6RG8jVVe3ayeFxFRH5Lqm6qtJoQp3J3KZ7MMghcoOIhp2cKqMJlbX1dr1vnryTw+MqIvJdUsdjoO0VVgxyiNwgUK2Ef0P5t72DOtntmIg6AqVCQLDW0s6PQQ6RFxEEoU3Jx8Z6M841zLvicRUR+br2lpEzyCFyk7YEOQXlll0ctVKBsEC1U9ZFROQppPlVba2wYpBD5CZtGe0gH1XpNRAEwSnrIiLyFI29ctpWYcUgh8hNpJ0ce0Y75LKyiog6kBB/y451W+dXMcghcpOINuzkSCMdmHRMRB2Brp1djxnkELlJW3JypOMq7uQQUUcQ0s4hnQxyiNykLUFOnsFybQznVhFRByDl5PC4isjLtGknh8dVRNSBSF2PuZND5GXkxOMKI0RRtOl9GrsdM8ghIt/X3knkDHKI3CQiyFI1YDSZYahufbSDKIqNQQ53coioA9AzJ4fIO2n8lNA1tCwvrKhp9fqSqjoY6y1D6nhcRUQdATseE3kx6ciqwIa8HKl8PDxQDbUfv3WJyPeFBFh2vA3VdTYf6zfFn5REbmRP8jEHcxJRRyPt5BhNZlTXmex+fwY5RG4UGWwJWGwJcph0TEQdTaBaCT+FZYRNW/JyGOQQuZE0v+p4YUWr17LbMRF1NIIgtCsvh0EOkRv17aQDAKzccQqzv9iDytqLV1lJx1Wx3Mkhog6kPRVWDHKI3OiGgZ3wt/E9oBCA/+06g+ve2YSDZw3NXsvhnETUEYVwJ4fIOykUAh4e2x2fPZCKGJ0WJworccOizfh4a/YFlQRy4jF3coioA5GOqwzcySHyTsOSw/Djo5djbK8oGOvNePa7DEz/ZJfVvBY2AiSijkgqIy+tNtr9vgxyiDxEaKAaH04dgmevTYFKKWBtRh6uWfAH0k+WoKbOJG/VMsghoo5E3475VX6OXgwRtZ0gCJg2MhlDO4fi4ZW7cbKoCre+txV3jkgCAGhVCuj8+W1LRB0Hq6uIfEz/+BCsengkrhsQB5NZxLIt2QCAWL0/BEFw7+KIiFyoPTs5DHKIPFSwVoUFtw/Eyzf1g1Zl+VblURURdTQh7Sgh5743kQcTBAG3D0vEoKRQLPztGG4ZnODuJRERuRRzcoh8XI/oYLx9+yXuXgYRkctJOznMySEiIiKfwpwcIiIi8kl6f0ufHENNHcxmsZWrrTHIISIiIo8l7eSIIlBec/H5fs1hkENEREQeS+2nQIBaCcD+rscMcoiIiMijtTUvh0EOERERebS2dj1mkENEREQejTs5RERE5JPkXjkMcoiIiMiXSDs5BgY5RERE5EtCAiy9ckqrWF1FREREPoQ5OUREROSTWF1FREREPkkOcriTQ0RERL5Eqq5yeuLx77//juuuuw5xcXEQBAHffvut1eOiKGLu3LmIjY2Fv78/xo0bh6NHj1pdU1xcjClTpkCn0yEkJATTpk1DRUWF1TX79u3D5ZdfDq1Wi4SEBLz66qsXrOXLL79Er169oNVq0a9fP6xZs8beD4eIiIg8nMuOqyorKzFgwAAsXLiw2cdfffVVLFiwAIsXL8b27dsRGBiItLQ01NTUyNdMmTIFGRkZWLduHVatWoXff/8dDzzwgPy4wWDAVVddhaSkJKSnp+O1117DvHnz8P7778vXbNmyBZMnT8a0adOwe/du3HDDDbjhhhtw4MABez8kIiIi8mAhDZPI7U08htgOAMRvvvlGft1sNosxMTHia6+9Jr+ttLRU1Gg04sqVK0VRFMWDBw+KAMSdO3fK1/z444+iIAjimTNnRFEUxUWLFomhoaFibW2tfM2TTz4p9uzZU3791ltvFSdOnGi1nuHDh4t//etfbV5/WVmZCEAsKyuz+X2IiIjItUorjWLSk6vEpCdXiTV19Tb//nZoTk5WVhby8vIwbtw4+W16vR7Dhw/H1q1bAQBbt25FSEgIhgwZIl8zbtw4KBQKbN++Xb7miiuugFqtlq9JS0tDZmYmSkpK5GuaPo90jfQ8zamtrYXBYLB6ISIiIs8WrPWDIFj+357dHIcGOXl5eQCA6Ohoq7dHR0fLj+Xl5SEqKsrqcT8/P4SFhVld09w9mj7Hxa6RHm/O/Pnzodfr5ZeEhAR7P0QiIiJyMYVCgE7b0CvHjrycDlVdNWfOHJSVlckvp06dcveSiIiIyAZShZXbdnJiYmIAAPn5+VZvz8/Plx+LiYlBQUGB1eP19fUoLi62uqa5ezR9jotdIz3eHI1GA51OZ/VCREREnq8tFVYODXKSk5MRExOD9evXy28zGAzYvn07UlNTAQCpqakoLS1Fenq6fM2vv/4Ks9mM4cOHy9f8/vvvqKtr/EDWrVuHnj17IjQ0VL6m6fNI10jPQ0RERL6jLaMd7A5yKioqsGfPHuzZsweAJdl4z549yMnJgSAIeOyxx/DPf/4T33//Pfbv34+77roLcXFxuOGGGwAAvXv3xoQJE3D//fdjx44d2Lx5M2bOnInbb78dcXFxAIA77rgDarUa06ZNQ0ZGBj7//HO8/fbbmD17tryORx99FGvXrsXrr7+Ow4cPY968efjzzz8xc+ZMez8kIiIi8nBt6npsbxnXb7/9JgK44GXq1KmiKFrKyJ999lkxOjpa1Gg04tixY8XMzEyrexQVFYmTJ08Wg4KCRJ1OJ95zzz1ieXm51TV79+4VR44cKWo0GrFTp07iyy+/fMFavvjiC7FHjx6iWq0W+/TpI65evdquj4Ul5ERERN7h6W/2iUlPrhJf/znT5t/fgiiKoqOjLW9hMBig1+tRVlbG/BwiIiIP9tpPh7Hwt+OYmpqEv41OtOn3d4eqriIiIiLv1JauxwxyiIiIyOPpA+zPyWGQQ0RERB7PJdVVRERERK4W4s+Ox0REROSD9O7ueExERETkDFLicWl1HWwtDGeQQ0RERB5PyskxmUVUGk02vQ+DHCIiIvJ4WpUCaj9L2FJWZbTpfRjkEBERkccTBEHezTHU2JaXwyCHiIiIvIJUYWWoqrfpegY5RERE5BW4k0NEREQ+KcTOrscMcoiIiMgr6LiTQ0RERL6ocUgnc3KIiIjIh8g5OTyuIiIiIl8i5eQYqtknh4iIiHxIY3UVj6uIiIjIh+hZXUVERES+iDk5RERE5JNCGOQQERGRL5J2cipqOYWciIiIfIgU5NiKQQ4RERF5BT+lAkEaP5uvZ5BDREREXsOe3RwGOUREROQ1GOQQERGRT5K6HtuCQQ4RERF5De7kEBERkU/iTg4RERH5JB13coiIiMgXhfirbb6WQQ4RERF5jaTwAAyI19t0rSCKoujk9Xgsg8EAvV6PsrIy6HQ6dy+HiIiIbGDr72/u5BAREZFPYpBDREREPolBDhEREfkkBjlERETkkxjkEBERkU9ikENEREQ+iUEOERER+SQGOUREROSTGOQQERGRT2KQQ0RERD6JQQ4RERH5JAY5RERE5JMY5BAREZFPYpBDREREPsnP3QtwJ1EUAVhGthMREZF3kH5vS7/HL6ZDBzlFRUUAgISEBDevhIiIiOxVVFQEvV5/0cc7dJATFhYGAMjJyWnxkwQAQ4cOxc6dO1u9pyOvMxgMSEhIwKlTp6DT6Txufd6yRk//XHvDGj39c+0Na/T09XnDGvm5dt0aPX19ZWVlSExMlH+PX0yHDnIUCktKkl6vb/UTr1QqW73GGdcBgE6n8+j1efoaPf1z7Q1r9PTPtTes0dPX5w1r5OfadWv09PVJpN/jF33c5jt1cDNmzHDLdbby9PU547l95XNt77WOvJ+vfK7tudZXPte24uew/dfZip/r9nP0/QSxtawdH2YwGKDX61FWVmZX5Ogqnr4+wDvWaAtv+Di8YY228IaPw9PX6OnrA7xjjbbwho/D09fojPXZes8OvZOj0Wjw3HPPQaPRuHspzfL09QHesUZbeMPH4Q1rtIU3fByevkZPXx/gHWu0hTd8HJ6+Rmesz9Z7duidHCIiIvJdHXonh4iIiHwXgxwiIiLySQxyiMjtBEHAt99+6+5lEPkUfl/5YJBTWFiI6dOnIzExERqNBjExMUhLS8PmzZvdvbQLnDp1Cvfeey/i4uKgVquRlJSERx99VO7E3JoNGzZAEASUlpY6bE133303BEHAyy+/bPX2b7/9FoIgOOx5XEH6WARBgEqlQnR0NMaPH4+PPvoIZrPZ3cuzcvfdd+OGG25w9zLapennu+nLsWPH3L00AI3re/DBBy94bMaMGRAEAXfffbfrF9aMrVu3QqlUYuLEie5eisybPn/28KbvPU9cqyd+rTblc0HOpEmTsHv3bixfvhxHjhzB999/jyuvvNLmwMFVTpw4gSFDhuDo0aNYuXIljh07hsWLF2P9+vVITU1FcXGx29am1WrxyiuvoKSkxG1rcJQJEyYgNzcX2dnZ+PHHHzF69Gg8+uijuPbaa1FfX+/u5fkc6fPd9CU5Odndy5IlJCTgs88+Q3V1tfy2mpoarFixAomJie26d11dXXuXJ1uyZAkefvhh/P777zh79my77mUymRwW1Dvz80feyZFfq87gU0FOaWkp/vjjD7zyyisYPXo0kpKSMGzYMMyZMwf/93//J19z3333ITIyEjqdDmPGjMHevXvle8ybNw8DBw7Ee++9h4SEBAQEBODWW29FWVmZQ9c6Y8YMqNVq/Pzzzxg1ahQSExNx9dVX45dffsGZM2fw9NNPAwBqa2vx5JNPIiEhARqNBt26dcOSJUuQnZ2N0aNHAwBCQ0Md+lfUuHHjEBMTg/nz51/0mq+//hp9+vSBRqNB586d8frrr8uP/eMf/8Dw4cMveJ8BAwbghRdecMgabSXt5nXq1AmDBg3CP/7xD3z33Xf48ccfsWzZMgCtf00AwA8//IChQ4dCq9UiIiICN954o9PWvHbtWowcORIhISEIDw/Htddei+PHj8uPZ2dnQxAE/O9//8Po0aMREBCAAQMGYOvWrU5bk62kz3fTF6VSie+++w6DBg2CVqtFly5d8Pzzz18QZObm5uLqq6+Gv78/unTpgq+++srh6xs0aBASEhLwv//9T37b//73PyQmJuKSSy6R32brv8Hnn3+OUaNGQavV4tNPP3XIGisqKvD5559j+vTpmDhxovx1CjTu3q5evRr9+/eHVqvFiBEjcODAAfmaZcuWISQkBN9//z1SUlKg0WiQk5PjkLU56vM3ZswYzJw50+rehYWFUKvVWL9+vUPW2hadO3fGW2+9ZfW2gQMHYt68efLrgiDgww8/xI033oiAgAB0794d33//vWsXCtvW6mwtfa1KX4dNNXci8M9//hNRUVEIDg7Gfffdh6eeegoDBw502Bp9KsgJCgpCUFAQvv32W9TW1jZ7zS233IKCggL8+OOPSE9Px6BBgzB27FirnZNjx47hiy++wA8//IC1a9di9+7deOihhxy2zuLiYvz000946KGH4O/vb/VYTEwMpkyZgs8//xyiKOKuu+7CypUrsWDBAhw6dAjvvfcegoKCkJCQgK+//hoAkJmZidzcXLz99tsOWZ9SqcRLL72E//znPzh9+vQFj6enp+PWW2/F7bffjv3792PevHl49tln5S/wKVOmYMeOHVY/1DIyMrBv3z7ccccdDllje4wZMwYDBgyQf1C39jWxevVq3Hjjjbjmmmuwe/durF+/HsOGDXPa+iorKzF79mz8+eefWL9+PRQKBW688cYL/hp/+umn8fe//x179uxBjx49MHnyZI/cnfrjjz9w11134dFHH8XBgwfx3nvvYdmyZfjXv/5ldd2zzz6LSZMmYe/evZgyZQpuv/12HDp0yOHruffee7F06VL59Y8++gj33HOP1TW2/hs89dRTePTRR3Ho0CGkpaU5ZH1ffPEFevXqhZ49e+Ivf/kLPvroowsmLT/++ON4/fXXsXPnTkRGRuK6666z2kmqqqrCK6+8gg8//BAZGRmIiopyyNoAx3z+7rvvPqxYscLq5/Qnn3yCTp06YcyYMQ5bq7M8//zzuPXWW7Fv3z5cc801mDJlilt3393Flq/Vlnz66af417/+hVdeeQXp6elITEzEu+++69hFij7mq6++EkNDQ0WtViteeuml4pw5c8S9e/eKoiiKf/zxh6jT6cSamhqr9+natav43nvviaIois8995yoVCrF06dPy4//+OOPokKhEHNzcx2yxm3btokAxG+++abZx9944w0RgLh9+3YRgLhu3bpmr/vtt99EAGJJSYlD1iWKojh16lTx+uuvF0VRFEeMGCHee++9oiiK4jfffCNKXy533HGHOH78eKv3e/zxx8WUlBT59QEDBogvvPCC/PqcOXPE4cOHO2ydtmj6sZzvtttuE3v37m3T10Rqaqo4ZcoUt621sLBQBCDu379fFEVRzMrKEgGIH374oXxNRkaGCEA8dOiQU9fZkqlTp4pKpVIMDAyUX26++WZx7Nix4ksvvWR17ccffyzGxsbKrwMQH3zwQatrhg8fLk6fPt2h67v++uvFgoICUaPRiNnZ2WJ2drao1WrFwsJC8frrrxenTp3a7Pte7N/grbfectj6JJdeeql837q6OjEiIkL87bffRFFs/J7/7LPP5OuLiopEf39/8fPPPxdFURSXLl0qAhD37Nnj0HU58vNXXV0thoaGymsWRVHs37+/OG/ePIeu2RZNv/eSkpLEN9980+rxAQMGiM8995z8OgDxmWeekV+vqKgQAYg//vijR671Yr9nHKGlr9WlS5eKer3e6vqmv0dE0fI9PmPGDKtrLrvsMnHAgAEOW6NP7eQAlpycs2fP4vvvv8eECROwYcMGDBo0CMuWLcPevXtRUVGB8PBwedcnKCgIWVlZVrsOiYmJ6NSpk/x6amoqzGYzMjMzHbpWsZWINzs7G0qlEqNGjXLo89rqlVdewfLlyy/4a/rQoUO47LLLrN522WWX4ejRozCZTAAsuzkrVqwAYPk4V65ciSlTprhm4TYQRRGCINj0NbFnzx6MHTvWZWs7evQoJk+ejC5dukCn06Fz584AcMGRQ//+/eX/j42NBQAUFBS4bJ3NGT16NPbs2SO/LFiwAHv37sULL7xg9fm9//77kZubi6qqKvl9U1NTre6VmprqlJ2cyMhIeWt96dKlmDhxIiIiIqyusfXfYMiQIQ5dW2ZmJnbs2IHJkycDAPz8/HDbbbdhyZIlVtc1/VyFhYWhZ8+eVp8rtVpt9fXhSI74/Gm1Wtx555346KOPAAC7du3CgQMHvCZxuennNjAwEDqdzu3fe65m69dqa/c4f1fc0bvkPjmFXKvVYvz48Rg/fjyeffZZ3HfffXjuuefw0EMPITY2Fhs2bLjgfc4/O3Smbt26QRAEHDp0qNncjkOHDiE0NPSCoyxXu+KKK5CWloY5c+bY/cNn8uTJePLJJ7Fr1y5UV1fj1KlTuO2225yz0DY4dOgQkpOTUVFR0erXhKv/Ha677jokJSXhgw8+QFxcHMxmM/r27Quj0Wh1nUqlkv9fOud2d9VYYGAgunXrZvW2iooKPP/887jpppsuuF6r1bpqaVbuvfdeOSdk4cKFFzxu679BYGCgQ9e1ZMkS1NfXIy4uTn6bKIrQaDR45513bL6Pv7+/U6shHfH5u++++zBw4ECcPn0aS5cuxZgxY5CUlOS0NdtCoVBc8MdncwnlTb/3AMv3n6u/92xdq7O09rXq7vVJfDLIOV9KSgq+/fZbDBo0CHl5efDz85P/smhOTk4Ozp49K//jbdu2DQqFAj179nTIesLDwzF+/HgsWrQIs2bNsvolmpeXh08//RR33XUX+vXrB7PZjI0bN2LcuHEX3EetVgOAvHviDC+//DIGDhxo9bH37t37gpL8zZs3o0ePHlAqlQCA+Ph4jBo1Cp9++imqq6sxfvx4h+YFtMevv/6K/fv3Y9asWYiPj2/1a6J///5Yv379BXkHzlBUVITMzEx88MEHuPzyywEAmzZtcvrzOtOgQYOQmZl5QfBzvm3btuGuu+6yer1pMqsjTZgwAUajEYIgXJBL465/g/r6evz3v//F66+/jquuusrqsRtuuAErV65Er169AFg+N1I1U0lJCY4cOYLevXs7fY0SR3z++vXrhyFDhuCDDz7AihUr7ArinCUyMhK5ubny6waDAVlZWW5c0cW5c622fK0mJSWhvLwclZWV8h8De/bssbq2Z8+e2Llzp9X3/c6dOx26Vp8KcoqKinDLLbfg3nvvRf/+/REcHIw///wTr776Kq6//nqMGzcOqampuOGGG/Dqq6+iR48eOHv2rJxYKm09a7VaTJ06Ff/+979hMBjwyCOP4NZbb0VMTIzD1vrOO+/g0ksvRVpaGv75z38iOTkZGRkZePzxx9GpUyf861//QlhYGKZOnYp7770XCxYswIABA3Dy5EkUFBTg1ltvRVJSEgRBwKpVq3DNNdfA398fQUFBDlsjYPlBNGXKFCxYsEB+29/+9jcMHToUL774Im677TZs3boV77zzDhYtWmT1vlOmTMFzzz0Ho9GIN99806HrslVtbS3y8vJgMpmQn5+PtWvXYv78+bj22mtx1113QaFQtPo18dxzz2Hs2LHo2rUrbr/9dtTX12PNmjV48sknHb7e0NBQhIeH4/3330dsbCxycnLw1FNPOfx5XGnu3Lm49tprkZiYiJtvvhkKhQJ79+7FgQMH8M9//lO+7ssvv8SQIUMwcuRIfPrpp9ixY4ddW9/2UCqV8vGOFJhL3PVvsGrVKpSUlGDatGnQ6/VWj02aNAlLlizBa6+9BgB44YUXEB4ejujoaDz99NOIiIhwaf8UR33+7rvvPsycOROBgYFOrVi01ZgxY7Bs2TJcd911CAkJwdy5cy/4+DyFO9dqy9fqTz/9hICAAPzjH//AI488gu3bt1tVXwHAww8/jPvvvx9DhgzBpZdeis8//xz79u1Dly5dHLdYh2X3eICamhrxqaeeEgcNGiTq9XoxICBA7Nmzp/jMM8+IVVVVoiiKosFgEB9++GExLi5OVKlUYkJCgjhlyhQxJydHFEVL4vGAAQPERYsWiXFxcaJWqxVvvvlmsbi42OHrzc7OFqdOnSpGR0fLa3n44YfFc+fOyddUV1eLs2bNEmNjY0W1Wi1269ZN/Oijj+THX3jhBTEmJkYUBOGiSX/2aC4BNisrS1Sr1VYJY1999ZWYkpIiqlQqMTExUXzttdcuuFdJSYmo0WjEgIAAsby8vN1rs9fUqVNFACIA0c/PT4yMjBTHjRsnfvTRR6LJZJKva+1rQhRF8euvvxYHDhwoqtVqMSIiQrzpppscutY777xTnDRpkiiKorhu3Tqxd+/eokajEfv37y9u2LDBKoFQSnrdvXu3/P4lJSUiADnpzx1aSp5eu3ateOmll4r+/v6iTqcThw0bJr7//vvy4wDEhQsXiuPHjxc1Go3YuXNnq6RUZ69PFEWrxNm2/Bu017XXXitec801zT4mFSG8/fbbIgDxhx9+EPv06SOq1Wpx2LBhcnGFKDaf8OkIjvz8ScrLy8WAgADxoYcecvh6bdX0e6+srEy87bbbRJ1OJyYkJIjLli2zKZlXr9eLS5cu9Yq1OoItX6t79+4Vv/nmG7Fbt26iv7+/eO2114rvv/++eH7Y8cILL4gRERFiUFCQeO+994qPPPKIOGLECIetlVPIzzNv3jx8++23F2yrETnThAkT0K1bN4/YsifPtWHDBowePRolJSUuzSN0luzsbHTt2hU7d+7EoEGD3LIGb/re86a1ttX48eMRExODjz/+2CH386njKiJvU1JSgs2bN2PDhg3Ntssn8kV1dXUoKirCM888gxEjRrglwPGm7z1vWqs9qqqqsHjxYqSlpUGpVGLlypX45ZdfsG7dOoc9B4McIje69957sXPnTvztb3/D9ddf7+7lELnE5s2bMXr0aPTo0cMpna1t4U3fe960VnsIgoA1a9bgX//6F2pqatCzZ098/fXXzRbatPk5eFxFREREvsjnmgESERERAQxyiIiIyEcxyCEiIiKfxCCHyEXmz5+PoUOHIjg4GFFRUbjhhhsumIdWU1ODGTNmyLO0Jk2ahPz8fPnxvXv3YvLkyUhISIC/vz969+59wfT53Nxc3HHHHejRowcUCgUee+wxV3x4REQeh0EOkYts3LgRM2bMwLZt27Bu3TrU1dXhqquuQmVlpXzNrFmz8MMPP+DLL7/Exo0bcfbsWauZT+np6YiKisInn3yCjIwMPP3005gzZ45V34za2lpERkbimWeewYABA1z6MRIReRJWVxG5SWFhIaKiorBx40ZcccUVKCsrQ2RkJFasWIGbb74ZAHD48GH07t0bW7duxYgRI5q9z4wZM3Do0CH8+uuvFzx25ZVXYuDAgXjrrbec+aEQEXkk7uQQuUlZWRkAICwsDIBll6aurs6qR0SvXr2QmJiIrVu3tngf6R5ERNSIzQCJ3MBsNuOxxx7DZZddhr59+wKwTKBXq9UXtOuPjo5GXl5es/fZsmULPv/8c6xevdrZSyYi8joMcojcYMaMGThw4AA2bdrU5nscOHAA119/PZ577jlcddVVDlwdEZFv4HEVkYvNnDkTq1atwm+//Yb4+Hj57TExMTAajSgtLbW6Pj8/HzExMVZvO3jwIMaOHYsHHngAzzzzjCuWTUTkdRjkELmIKIqYOXMmvvnmG/z6669ITk62enzw4MFQqVRYv369/LbMzEzk5OQgNTVVfltGRgZGjx6NqVOn4l//+pfL1k9E5G14XEXkIjNmzMCKFSvw3XffITg4WM6z0ev18Pf3h16vx7Rp0zB79myEhYVBp9Ph4YcfRmpqqlxZdeDAAYwZMwZpaWmYPXu2fA+lUonIyEj5ufbs2QMAqKioQGFhIfbs2QO1Wo2UlBTXftBERG7EEnIiFxEEodm3L126FHfffTcASzPAv/3tb1i5ciVqa2uRlpaGRYsWycdV8+bNw/PPP3/BPZKSkpCdnd3ic51/DRGRr2OQQ0RERD6JOTlERETkkxjkEBERkU9ikENEREQ+iUEOERER+SQGOUREROSTGOQQERGRT2KQQ0RERD6JQQ4ReaUrr7wSjz32mLuXQUQejEEOEfm8DRs2QBCEC4afEpFvY5BDREREPolBDhF5vMrKStx1110ICgpCbGwsXn/9davHP/74YwwZMgTBwcGIiYnBHXfcgYKCAgBAdnY2Ro8eDQAIDQ2FIAjyrDCz2Yz58+cjOTkZ/v7+GDBgAL766iuXfmxE5DwMcojI4z3++OPYuHEjvvvuO/z888/YsGEDdu3aJT9eV1eHF198EXv37sW3336L7OxsOZBJSEjA119/DQDIzMxEbm4u3n77bQDA/Pnz8d///heLFy9GRkYGZs2ahb/85S/YuHGjyz9GInI8DugkIo9WUVGB8PBwfPLJJ7jlllsAAMXFxYiPj8cDDzyAt95664L3+fPPPzF06FCUl5cjKCgIGzZswOjRo1FSUoKQkBAAQG1tLcLCwvDLL78gNTVVft/77rsPVVVVWLFihSs+PCJyIj93L4CIqCXHjx+H0WjE8OHD5beFhYWhZ8+e8uvp6emYN28e9u7di5KSEpjNZgBATk4OUlJSmr3vsWPHUFVVhfHjx1u93Wg04pJLLnHCR0JErsYgh4i8WmVlJdLS0pCWloZPP/0UkZGRyMnJQVpaGoxG40Xfr6KiAgCwevVqdOrUyeoxjUbj1DUTkWswyCEij9a1a1eoVCps374diYmJAICSkhIcOXIEo0aNwuHDh1FUVISXX34ZCQkJACzHVU2p1WoAgMlkkt+WkpICjUaDnJwcjBo1ykUfDRG5EoMcIvJoQUFBmDZtGh5//HGEh4cjKioKTz/9NBQKS91EYmIi1Go1/vOf/+DBBx/EgQMH8OKLL1rdIykpCYIgYNWqVbjmmmvg7++P4OBg/P3vf8esWbNgNpsxcuRIlJWVYfPmzdDpdJg6dao7PlwiciBWVxGRx3vttddw+eWX47rrrsO4ceMwcuRIDB48GAAQGRmJZcuW4csvv0RKSgpefvll/Pvf/7Z6/06dOuH555/HU089hejoaMycORMA8OKLL+LZZ5/F/Pnz0bt3b0yYMAGrV69GcnKyyz9GInI8VlcRERGRT+JODhEREfkkBjlERETkkxjkEBERkU9ikENEREQ+iUEOERER+SQGOUREROSTGOQQERGRT2KQQ0RERD6JQQ4RERH5JAY5RERE5JMY5BAREZFPYpBDREREPun/AU4l2sPSPF2/AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mask = data[\"counter_name\"] == \"Totem 73 boulevard de Sébastopol S-N\"\n",
    "\n",
    "data[mask].groupby(pd.Grouper(freq=\"1w\", key=\"date\"))[[\"bike_count\"]].sum().plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c262f5c5-3a54-4017-a99b-fed24eee385f",
   "metadata": {},
   "source": [
    "While at the same time, we can zoom on a week in particular for a more short-term visualization,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6f8b5840-53ba-43ca-8966-f594975696c9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='date'>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 4))\n",
    "\n",
    "mask = (\n",
    "    (data[\"counter_name\"] == \"Totem 73 boulevard de Sébastopol S-N\")\n",
    "    & (data[\"date\"] > pd.to_datetime(\"2021/03/01\"))\n",
    "    & (data[\"date\"] < pd.to_datetime(\"2021/03/08\"))\n",
    ")\n",
    "\n",
    "data[mask].plot(x=\"date\", y=\"bike_count\", ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca56052b-51f7-4c67-b135-2cc14698448f",
   "metadata": {},
   "source": [
    "The hourly pattern has a clear variation between work days and weekends (7 and 8 March 2021).\n",
    "\n",
    "If we look at the distribution of the target variable it skewed and non normal, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "99893b87-cc1c-4c3e-b0cc-2069eb0e6874",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "\n",
    "ax = sns.histplot(data, x=\"bike_count\", kde=True, bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e0055ae-ea52-4198-bc31-5089e73aaf9e",
   "metadata": {},
   "source": [
    "Least square loss would not be appropriate to model it since it is designed for normal error distributions. One way to precede would be to transform the variable with a logarithmic transformation,\n",
    "```py\n",
    "data['log_bike_count'] = np.log(1 + data['bike_count'])\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6414fb09-93e7-431a-ac04-237ca8ccea2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = sns.histplot(data, x=\"log_bike_count\", kde=True, bins=50)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7ce873c-aa3d-40a8-9f07-ef1692df281d",
   "metadata": {},
   "source": [
    "which has a more pronounced central mode, but is still non symmetric. In the following, **we use `log_bike_count` as the target variable** as otherwise `bike_count` ranges over 3 orders of magnitude and least square loss would be dominated by the few large values. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c51fc59f-e77f-4c82-bfe8-35a93ef2db09",
   "metadata": {},
   "source": [
    "## Feature extraction\n",
    "\n",
    "To account for the temporal aspects of the data, we cannot input the `date` field directly into the model. Instead we extract the features on different time-scales from the `date` field, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d13d9bfd-7852-4206-b16f-e09e7c83d6d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def _encode_dates(X):\n",
    "    X = X.copy()  # modify a copy of X\n",
    "    # Encode the date information from the DateOfDeparture columns\n",
    "    X.loc[:, \"year\"] = X[\"date\"].dt.year\n",
    "    X.loc[:, \"month\"] = X[\"date\"].dt.month\n",
    "    X.loc[:, \"day\"] = X[\"date\"].dt.day\n",
    "    X.loc[:, \"weekday\"] = X[\"date\"].dt.weekday\n",
    "    X.loc[:, \"hour\"] = X[\"date\"].dt.hour\n",
    "\n",
    "    # Finally we can drop the original columns from the dataframe\n",
    "    return X.drop(columns=[\"date\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "df5a9c16-69fb-4d05-aa77-5ef1bc28fe78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48321   2020-09-01 02:00:00\n",
       "48324   2020-09-01 03:00:00\n",
       "48327   2020-09-01 04:00:00\n",
       "48330   2020-09-01 15:00:00\n",
       "48333   2020-09-01 18:00:00\n",
       "Name: date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[\"date\"].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8dd6cfea-6fc8-4707-a0c9-404b62a7833d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>weekday</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>48321</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48324</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48327</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48330</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48333</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  month  day  weekday  hour\n",
       "48321  2020      9    1        1     2\n",
       "48324  2020      9    1        1     3\n",
       "48327  2020      9    1        1     4\n",
       "48330  2020      9    1        1    15\n",
       "48333  2020      9    1        1    18"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_encode_dates(data[[\"date\"]].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4eb15a9-421b-4f2a-a913-26df51449092",
   "metadata": {},
   "source": [
    "To use this function with scikit-learn estimators we wrap it with [FunctionTransformer](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html),"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "c4676f76-1bdb-4fdd-94b3-061a9a7c691e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>day</th>\n",
       "      <th>weekday</th>\n",
       "      <th>hour</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>48321</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48324</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48327</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48330</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48333</th>\n",
       "      <td>2020</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       year  month  day  weekday  hour\n",
       "48321  2020      9    1        1     2\n",
       "48324  2020      9    1        1     3\n",
       "48327  2020      9    1        1     4\n",
       "48330  2020      9    1        1    15\n",
       "48333  2020      9    1        1    18"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import FunctionTransformer\n",
    "\n",
    "date_encoder = FunctionTransformer(_encode_dates, validate=False)\n",
    "date_encoder.fit_transform(data[[\"date\"]]).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6c85678-2403-4a31-90ae-ac68f9565859",
   "metadata": {},
   "source": [
    "Since it is unlikely that, for instance, that `hour` is linearly correlated with the target variable, we would need to additionally encode categorical features for linear models. This is classically done with [OneHotEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html), though other encoding strategies exist."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "46e5f3cd-e177-4b73-8058-1472a46bb34b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 0., 0., 0., 0.],\n",
       "       [0., 1., 0., 0., 0.],\n",
       "       [0., 0., 1., 0., 0.],\n",
       "       [0., 0., 0., 1., 0.],\n",
       "       [0., 0., 0., 0., 1.]])"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import OneHotEncoder\n",
    "\n",
    "enc = OneHotEncoder(sparse=False)\n",
    "\n",
    "enc.fit_transform(_encode_dates(data[[\"date\"]])[[\"hour\"]].head())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5feb47c-c05f-442b-8009-4b7272bdf84f",
   "metadata": {},
   "source": [
    "## Linear model"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e8fb001e-3446-492c-b887-6ed485448495",
   "metadata": {},
   "source": [
    "Let's now construct our first linear model with [Ridge](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Ridge.html). We use a few helper functions defined in `problem.py` of the starting kit to load the public train and test data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "809fa5fa-099f-4b98-b47c-98f4e11ea0f7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import problem\n",
    "\n",
    "X_train, y_train = problem.get_train_data()\n",
    "X_test, y_test = problem.get_test_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6e579d41-9f7a-4b50-b07d-31866168a67e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>counter_id</th>\n",
       "      <th>counter_name</th>\n",
       "      <th>site_id</th>\n",
       "      <th>site_name</th>\n",
       "      <th>date</th>\n",
       "      <th>counter_installation_date</th>\n",
       "      <th>counter_technical_id</th>\n",
       "      <th>latitude</th>\n",
       "      <th>longitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>400125</th>\n",
       "      <td>100049407-353255860</td>\n",
       "      <td>152 boulevard du Montparnasse E-O</td>\n",
       "      <td>100049407</td>\n",
       "      <td>152 boulevard du Montparnasse</td>\n",
       "      <td>2020-09-01 01:00:00</td>\n",
       "      <td>2018-12-07</td>\n",
       "      <td>Y2H19070373</td>\n",
       "      <td>48.840801</td>\n",
       "      <td>2.333233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>408305</th>\n",
       "      <td>100049407-353255859</td>\n",
       "      <td>152 boulevard du Montparnasse O-E</td>\n",
       "      <td>100049407</td>\n",
       "      <td>152 boulevard du Montparnasse</td>\n",
       "      <td>2020-09-01 01:00:00</td>\n",
       "      <td>2018-12-07</td>\n",
       "      <td>Y2H19070373</td>\n",
       "      <td>48.840801</td>\n",
       "      <td>2.333233</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 counter_id                       counter_name    site_id  \\\n",
       "400125  100049407-353255860  152 boulevard du Montparnasse E-O  100049407   \n",
       "408305  100049407-353255859  152 boulevard du Montparnasse O-E  100049407   \n",
       "\n",
       "                            site_name                date  \\\n",
       "400125  152 boulevard du Montparnasse 2020-09-01 01:00:00   \n",
       "408305  152 boulevard du Montparnasse 2020-09-01 01:00:00   \n",
       "\n",
       "       counter_installation_date counter_technical_id   latitude  longitude  \n",
       "400125                2018-12-07          Y2H19070373  48.840801   2.333233  \n",
       "408305                2018-12-07          Y2H19070373  48.840801   2.333233  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_train.head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d3ea2f21-1d7b-48d0-87ce-e55440a99360",
   "metadata": {},
   "source": [
    "and"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8c396114-de58-40b4-bfd3-10c0c7f4f83a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.60943791, 1.38629436, 0.        , ..., 2.48490665, 1.60943791,\n",
       "       1.38629436])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "937ebcf8-8769-46b4-93f8-d54a30194f87",
   "metadata": {},
   "source": [
    "Where `y` contains the `log_bike_count` variable. \n",
    "\n",
    "The test set is in the future as compared to the train set,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "252bf7ea-2def-46e1-b4fd-583c0e2c3f8b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: n_samples=455163,  2020-09-01 01:00:00 to 2021-08-09 23:00:00\n",
      "Test: n_samples=41608,  2021-08-10 01:00:00 to 2021-09-09 23:00:00\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    f'Train: n_samples={X_train.shape[0]},  {X_train[\"date\"].min()} to {X_train[\"date\"].max()}'\n",
    ")\n",
    "print(\n",
    "    f'Test: n_samples={X_test.shape[0]},  {X_test[\"date\"].min()} to {X_test[\"date\"].max()}'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b3d1c151-da75-4dae-bbe6-07bf06e2b1c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['year', 'month', 'day', 'weekday', 'hour']"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_encode_dates(X_train[[\"date\"]]).columns.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "413e7450-5529-47e5-a311-c78e364048ea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;functiontransformer&#x27;,\n",
       "                 FunctionTransformer(func=&lt;function _encode_dates at 0x7f5e41c58550&gt;)),\n",
       "                (&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;date&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;year&#x27;, &#x27;month&#x27;, &#x27;day&#x27;,\n",
       "                                                   &#x27;weekday&#x27;, &#x27;hour&#x27;]),\n",
       "                                                 (&#x27;cat&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;counter_name&#x27;,\n",
       "                                                   &#x27;site_name&#x27;])])),\n",
       "                (&#x27;ridge&#x27;, Ridge())])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Pipeline</label><div class=\"sk-toggleable__content\"><pre>Pipeline(steps=[(&#x27;functiontransformer&#x27;,\n",
       "                 FunctionTransformer(func=&lt;function _encode_dates at 0x7f5e41c58550&gt;)),\n",
       "                (&#x27;columntransformer&#x27;,\n",
       "                 ColumnTransformer(transformers=[(&#x27;date&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;year&#x27;, &#x27;month&#x27;, &#x27;day&#x27;,\n",
       "                                                   &#x27;weekday&#x27;, &#x27;hour&#x27;]),\n",
       "                                                 (&#x27;cat&#x27;,\n",
       "                                                  OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),\n",
       "                                                  [&#x27;counter_name&#x27;,\n",
       "                                                   &#x27;site_name&#x27;])])),\n",
       "                (&#x27;ridge&#x27;, Ridge())])</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">FunctionTransformer</label><div class=\"sk-toggleable__content\"><pre>FunctionTransformer(func=&lt;function _encode_dates at 0x7f5e41c58550&gt;)</pre></div></div></div><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">columntransformer: ColumnTransformer</label><div class=\"sk-toggleable__content\"><pre>ColumnTransformer(transformers=[(&#x27;date&#x27;, OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;year&#x27;, &#x27;month&#x27;, &#x27;day&#x27;, &#x27;weekday&#x27;, &#x27;hour&#x27;]),\n",
       "                                (&#x27;cat&#x27;, OneHotEncoder(handle_unknown=&#x27;ignore&#x27;),\n",
       "                                 [&#x27;counter_name&#x27;, &#x27;site_name&#x27;])])</pre></div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">date</label><div class=\"sk-toggleable__content\"><pre>[&#x27;year&#x27;, &#x27;month&#x27;, &#x27;day&#x27;, &#x27;weekday&#x27;, &#x27;hour&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">OneHotEncoder</label><div class=\"sk-toggleable__content\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div></div></div></div></div></div><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">cat</label><div class=\"sk-toggleable__content\"><pre>[&#x27;counter_name&#x27;, &#x27;site_name&#x27;]</pre></div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">OneHotEncoder</label><div class=\"sk-toggleable__content\"><pre>OneHotEncoder(handle_unknown=&#x27;ignore&#x27;)</pre></div></div></div></div></div></div></div></div><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">Ridge</label><div class=\"sk-toggleable__content\"><pre>Ridge()</pre></div></div></div></div></div></div></div>"
      ],
      "text/plain": [
       "Pipeline(steps=[('functiontransformer',\n",
       "                 FunctionTransformer(func=<function _encode_dates at 0x7f5e41c58550>)),\n",
       "                ('columntransformer',\n",
       "                 ColumnTransformer(transformers=[('date',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore'),\n",
       "                                                  ['year', 'month', 'day',\n",
       "                                                   'weekday', 'hour']),\n",
       "                                                 ('cat',\n",
       "                                                  OneHotEncoder(handle_unknown='ignore'),\n",
       "                                                  ['counter_name',\n",
       "                                                   'site_name'])])),\n",
       "                ('ridge', Ridge())])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.compose import ColumnTransformer\n",
    "from sklearn.linear_model import Ridge\n",
    "from sklearn.pipeline import make_pipeline\n",
    "\n",
    "date_encoder = FunctionTransformer(_encode_dates)\n",
    "date_cols = _encode_dates(X_train[[\"date\"]]).columns.tolist()\n",
    "\n",
    "categorical_encoder = OneHotEncoder(handle_unknown=\"ignore\")\n",
    "categorical_cols = [\"counter_name\", \"site_name\"]\n",
    "\n",
    "preprocessor = ColumnTransformer(\n",
    "    [\n",
    "        (\"date\", OneHotEncoder(handle_unknown=\"ignore\"), date_cols),\n",
    "        (\"cat\", categorical_encoder, categorical_cols),\n",
    "    ]\n",
    ")\n",
    "\n",
    "regressor = Ridge()\n",
    "\n",
    "pipe = make_pipeline(date_encoder, preprocessor, regressor)\n",
    "pipe.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "772e16fe-50fd-4229-af39-a6ebefad0a1e",
   "metadata": {},
   "source": [
    "We then evaluate this model with the RMSE metric,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "4d4d803c-80ea-4423-af83-5666c799838e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train set, RMSE=0.80\n",
      "Test set, RMSE=0.73\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_squared_error\n",
    "\n",
    "print(\n",
    "    f\"Train set, RMSE={mean_squared_error(y_train, pipe.predict(X_train), squared=False):.2f}\"\n",
    ")\n",
    "print(\n",
    "    f\"Test set, RMSE={mean_squared_error(y_test, pipe.predict(X_test), squared=False):.2f}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2298cbed-ff41-49f4-9e51-6925410fc083",
   "metadata": {},
   "source": [
    "The model doesn't have enough capacity to generalize on the train set, since we have lots of data with relatively few parameters. However it happened to work somewhat better on the test set. We can compare these results with the baseline predicting the mean value,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "f20e09d6-cbe8-4911-bfe1-ef5e939cacb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Baseline mean prediction.\n",
      "Train set, RMSE=1.68\n",
      "Test set, RMSE=1.44\n"
     ]
    }
   ],
   "source": [
    "print(\"Baseline mean prediction.\")\n",
    "print(\n",
    "    f\"Train set, RMSE={mean_squared_error(y_train, np.full(y_train.shape, y_train.mean()), squared=False):.2f}\"\n",
    ")\n",
    "print(\n",
    "    f\"Test set, RMSE={mean_squared_error(y_test, np.full(y_test.shape, y_test.mean()), squared=False):.2f}\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c753fe34-a94b-4d18-9497-e516c1ccc4e2",
   "metadata": {},
   "source": [
    "which illustrates that we are performing better than the baseline.\n",
    "\n",
    "Let's visualize the predictions for one of the stations,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3a2509f6-7cba-4671-8363-d4abda33ef30",
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = (\n",
    "    (X_test[\"counter_name\"] == \"Totem 73 boulevard de Sébastopol S-N\")\n",
    "    & (X_test[\"date\"] > pd.to_datetime(\"2021/09/01\"))\n",
    "    & (X_test[\"date\"] < pd.to_datetime(\"2021/09/08\"))\n",
    ")\n",
    "\n",
    "df_viz = X_test.loc[mask].copy()\n",
    "df_viz[\"bike_count\"] = np.exp(y_test[mask.values]) - 1\n",
    "df_viz[\"bike_count (predicted)\"] = np.exp(pipe.predict(X_test[mask])) - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "3fab3196-90bd-4918-a509-01cd38b1adfa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'bike_count')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 4))\n",
    "\n",
    "df_viz.plot(x=\"date\", y=\"bike_count\", ax=ax)\n",
    "df_viz.plot(x=\"date\", y=\"bike_count (predicted)\", ax=ax, ls=\"--\")\n",
    "ax.set_title(\"Predictions with Ridge\")\n",
    "ax.set_ylabel(\"bike_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "187d342e-ba15-4741-a457-d4ae31d07c9a",
   "metadata": {},
   "source": [
    "So we start to see the daily trend, and some of the week day differences are accounted for, however we still miss the details and the spikes in the evening are under-estimated.\n",
    "\n",
    "A useful way to visualize the error is to plot `y_pred` as a function of `y_true`,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "9ef6c8cd-56ce-4294-8d98-da217262aa22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='y_true', ylabel='y_pred'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "\n",
    "df_viz = pd.DataFrame({\"y_true\": y_test, \"y_pred\": pipe.predict(X_test)}).sample(\n",
    "    10000, random_state=0\n",
    ")\n",
    "\n",
    "df_viz.plot.scatter(x=\"y_true\", y=\"y_pred\", s=8, alpha=0.1, ax=ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3d82e36-4033-4d96-a501-d2f56578c894",
   "metadata": {},
   "source": [
    "It is recommended to use cross-validation for hyper-parameter tuning with [GridSearchCV](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.GridSearchCV.html) or more reliable model evaluation with [cross_val_score](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_score.html#sklearn.model_selection.cross_val_score). In this case, because we want the test data to always be in the future as compared to the train data, we can use [TimeSeriesSplit](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html),\n",
    "\n",
    "<img src=\"https://i.stack.imgur.com/Q37Bn.png\" />\n",
    "\n",
    "The disadvantage, is that we can either have the training set size be different for each fold which is not ideal for hyper-parameter tuning (current figure), or have constant sized small training set which is also not ideal given the data periodicity. This explains that generally we will have worse cross-validation scores than test scores, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "4781077b-9da4-4db4-af9a-c130cb9b2182",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE:  [-0.96320864 -0.87311411 -0.85383867 -0.87000261 -1.0607788  -0.97297134]\n",
      "RMSE (all folds): 0.932 ± 0.0738\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import TimeSeriesSplit, cross_val_score\n",
    "\n",
    "cv = TimeSeriesSplit(n_splits=6)\n",
    "\n",
    "# When using a scorer in scikit-learn it always needs to be better when smaller, hence the minus sign.\n",
    "scores = cross_val_score(\n",
    "    pipe, X_train, y_train, cv=cv, scoring=\"neg_root_mean_squared_error\"\n",
    ")\n",
    "print(\"RMSE: \", scores)\n",
    "print(f\"RMSE (all folds): {-scores.mean():.3} ± {(-scores).std():.3}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8a5aaf05-1e68-49ab-891f-289430545c20",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
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