changement-climatique.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "6eee42b8",
   "metadata": {},
   "source": [
    "# Défi open data : Changement climatique"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7020cc47",
   "metadata": {},
   "source": [
    "Dans [son dernier rapport (2023)](https://www.ipcc.ch/report/sixth-assessment-report-cycle/), le Giec estime à 1,1°C l’augmentation de la température moyenne mondiale depuis la fin du XIXe siècle, qu’il attribue largement aux émissions de gaz à effet de serre générées par les activités humaines. Il formule également, à partir de différents scénarios d’émissions, des projections qui prévoient une élévation de température de +1,4°C (scénario le plus optimiste) à +4,4°C (scénario le plus pessimiste) d’ici 2100.\n",
    "\n",
    "Les analyses du Giec sont établies à un niveau mondial, et pour de grandes régions comme l’Europe ou le bassin méditerranéen. **Des études climatiques sur des échelles plus réduites sont encore rares**.\n",
    "\n",
    "**La problématique du défi**\n",
    "\n",
    "Ce projet vous propose d’**analyser le climat passé et de faire des projections sur le climat futur à l’échelle de la France, d’une région ou d’une commune (au choix)**.\n",
    "\n",
    "Beaucoup de données ouvertes sont mises à disposition pour vous permettre de répondre à ce sujet. Plusieurs jeux de données ont déjà été chargés dans cet environnement ([cf. liste](https://defis.data.gouv.fr/defis/65b10beae24f409e31c547a5/)) et vous pouvez bien évidemment en ajouter d’autres selon vos besoins.\n",
    "\n",
    "Une fois vos travaux terminés, partagez-les avec l’ensemble de la communauté [en publiant une réutilisation sur data.gouv.fr](https://guides.data.gouv.fr/guide-data.gouv.fr/reutilisations) !"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5eee062",
   "metadata": {},
   "source": [
    "# Importer des données\n",
    "Nous mettons à disposition une fonction utilitaire qui permet de charger la majorité des ressources de data.gouv.fr à partir de leur identifiant sur le site (exemple : `\"2876a346-d50c-4911-934e-19ee07b0e503\"`). Vous pouvez l'utiliser comme suit :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "132b9993",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LAMBX</th>\n",
       "      <th>LAMBY</th>\n",
       "      <th>DATE</th>\n",
       "      <th>PRENEI_MENS</th>\n",
       "      <th>PRELIQ_MENS</th>\n",
       "      <th>PRETOTM_MENS</th>\n",
       "      <th>T_MENS</th>\n",
       "      <th>EVAP_MENS</th>\n",
       "      <th>ETP_MENS</th>\n",
       "      <th>PE_MENS</th>\n",
       "      <th>...</th>\n",
       "      <th>RUNC_MENS</th>\n",
       "      <th>SPI1_MENS</th>\n",
       "      <th>SPI3_MENS</th>\n",
       "      <th>SPI6_MENS</th>\n",
       "      <th>SPI12_MENS</th>\n",
       "      <th>SSWI1_MENS</th>\n",
       "      <th>SSWI3_MENS</th>\n",
       "      <th>SSWI6_MENS</th>\n",
       "      <th>SSWI12_MENS</th>\n",
       "      <th>ECOULEMENT_MENS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195808</td>\n",
       "      <td>0.0</td>\n",
       "      <td>101.1</td>\n",
       "      <td>101.1</td>\n",
       "      <td>16.2</td>\n",
       "      <td>58.9</td>\n",
       "      <td>74.1</td>\n",
       "      <td>42.2</td>\n",
       "      <td>...</td>\n",
       "      <td>3.4</td>\n",
       "      <td>1.20</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.77</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195809</td>\n",
       "      <td>0.0</td>\n",
       "      <td>87.4</td>\n",
       "      <td>87.4</td>\n",
       "      <td>16.5</td>\n",
       "      <td>59.7</td>\n",
       "      <td>59.5</td>\n",
       "      <td>27.7</td>\n",
       "      <td>...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.82</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.05</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90.4</td>\n",
       "      <td>90.4</td>\n",
       "      <td>12.4</td>\n",
       "      <td>40.8</td>\n",
       "      <td>35.3</td>\n",
       "      <td>49.6</td>\n",
       "      <td>...</td>\n",
       "      <td>6.9</td>\n",
       "      <td>-0.32</td>\n",
       "      <td>0.82</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.69</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195811</td>\n",
       "      <td>0.0</td>\n",
       "      <td>63.8</td>\n",
       "      <td>63.8</td>\n",
       "      <td>9.5</td>\n",
       "      <td>24.9</td>\n",
       "      <td>22.5</td>\n",
       "      <td>38.9</td>\n",
       "      <td>...</td>\n",
       "      <td>5.7</td>\n",
       "      <td>-0.81</td>\n",
       "      <td>-0.38</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.36</td>\n",
       "      <td>0.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195812</td>\n",
       "      <td>0.0</td>\n",
       "      <td>114.1</td>\n",
       "      <td>114.1</td>\n",
       "      <td>8.0</td>\n",
       "      <td>38.7</td>\n",
       "      <td>17.1</td>\n",
       "      <td>75.4</td>\n",
       "      <td>...</td>\n",
       "      <td>10.5</td>\n",
       "      <td>-0.15</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>0.35</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>168159</th>\n",
       "      <td>11960</td>\n",
       "      <td>17450</td>\n",
       "      <td>195908</td>\n",
       "      <td>0.0</td>\n",
       "      <td>128.2</td>\n",
       "      <td>128.2</td>\n",
       "      <td>23.0</td>\n",
       "      <td>50.8</td>\n",
       "      <td>124.7</td>\n",
       "      <td>77.4</td>\n",
       "      <td>...</td>\n",
       "      <td>9.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.40</td>\n",
       "      <td>2.59</td>\n",
       "      <td>0.85</td>\n",
       "      <td>4.31</td>\n",
       "      <td>1.70</td>\n",
       "      <td>1.35</td>\n",
       "      <td>0.79</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>168160</th>\n",
       "      <td>11960</td>\n",
       "      <td>17450</td>\n",
       "      <td>195909</td>\n",
       "      <td>0.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>19.6</td>\n",
       "      <td>72.1</td>\n",
       "      <td>65.7</td>\n",
       "      <td>12.9</td>\n",
       "      <td>...</td>\n",
       "      <td>7.8</td>\n",
       "      <td>0.44</td>\n",
       "      <td>1.93</td>\n",
       "      <td>2.35</td>\n",
       "      <td>1.10</td>\n",
       "      <td>5.53</td>\n",
       "      <td>7.33</td>\n",
       "      <td>3.39</td>\n",
       "      <td>1.33</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168161</th>\n",
       "      <td>11960</td>\n",
       "      <td>17450</td>\n",
       "      <td>195910</td>\n",
       "      <td>0.0</td>\n",
       "      <td>197.5</td>\n",
       "      <td>197.5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>54.8</td>\n",
       "      <td>53.3</td>\n",
       "      <td>142.7</td>\n",
       "      <td>...</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.81</td>\n",
       "      <td>1.77</td>\n",
       "      <td>1.85</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.47</td>\n",
       "      <td>4.45</td>\n",
       "      <td>4.13</td>\n",
       "      <td>1.86</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168162</th>\n",
       "      <td>11960</td>\n",
       "      <td>17450</td>\n",
       "      <td>195911</td>\n",
       "      <td>0.0</td>\n",
       "      <td>92.7</td>\n",
       "      <td>92.7</td>\n",
       "      <td>12.1</td>\n",
       "      <td>32.9</td>\n",
       "      <td>25.9</td>\n",
       "      <td>59.8</td>\n",
       "      <td>...</td>\n",
       "      <td>12.7</td>\n",
       "      <td>-0.16</td>\n",
       "      <td>0.79</td>\n",
       "      <td>1.25</td>\n",
       "      <td>0.87</td>\n",
       "      <td>1.18</td>\n",
       "      <td>2.51</td>\n",
       "      <td>2.97</td>\n",
       "      <td>2.30</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168163</th>\n",
       "      <td>11960</td>\n",
       "      <td>17450</td>\n",
       "      <td>195912</td>\n",
       "      <td>0.0</td>\n",
       "      <td>151.7</td>\n",
       "      <td>151.7</td>\n",
       "      <td>10.8</td>\n",
       "      <td>40.8</td>\n",
       "      <td>30.4</td>\n",
       "      <td>110.9</td>\n",
       "      <td>...</td>\n",
       "      <td>25.4</td>\n",
       "      <td>0.69</td>\n",
       "      <td>1.07</td>\n",
       "      <td>1.52</td>\n",
       "      <td>1.39</td>\n",
       "      <td>1.87</td>\n",
       "      <td>1.84</td>\n",
       "      <td>3.19</td>\n",
       "      <td>2.19</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>168164 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        LAMBX  LAMBY    DATE  PRENEI_MENS  PRELIQ_MENS  PRETOTM_MENS  T_MENS  \\\n",
       "0         600  24010  195808          0.0        101.1         101.1    16.2   \n",
       "1         600  24010  195809          0.0         87.4          87.4    16.5   \n",
       "2         600  24010  195810          0.0         90.4          90.4    12.4   \n",
       "3         600  24010  195811          0.0         63.8          63.8     9.5   \n",
       "4         600  24010  195812          0.0        114.1         114.1     8.0   \n",
       "...       ...    ...     ...          ...          ...           ...     ...   \n",
       "168159  11960  17450  195908          0.0        128.2         128.2    23.0   \n",
       "168160  11960  17450  195909          0.0         85.0          85.0    19.6   \n",
       "168161  11960  17450  195910          0.0        197.5         197.5    15.0   \n",
       "168162  11960  17450  195911          0.0         92.7          92.7    12.1   \n",
       "168163  11960  17450  195912          0.0        151.7         151.7    10.8   \n",
       "\n",
       "        EVAP_MENS  ETP_MENS  PE_MENS  ...  RUNC_MENS  SPI1_MENS  SPI3_MENS  \\\n",
       "0            58.9      74.1     42.2  ...        3.4       1.20        NaN   \n",
       "1            59.7      59.5     27.7  ...        4.0       0.82        NaN   \n",
       "2            40.8      35.3     49.6  ...        6.9      -0.32       0.82   \n",
       "3            24.9      22.5     38.9  ...        5.7      -0.81      -0.38   \n",
       "4            38.7      17.1     75.4  ...       10.5      -0.15      -0.60   \n",
       "...           ...       ...      ...  ...        ...        ...        ...   \n",
       "168159       50.8     124.7     77.4  ...        9.6        NaN       2.40   \n",
       "168160       72.1      65.7     12.9  ...        7.8       0.44       1.93   \n",
       "168161       54.8      53.3    142.7  ...       26.6       0.81       1.77   \n",
       "168162       32.9      25.9     59.8  ...       12.7      -0.16       0.79   \n",
       "168163       40.8      30.4    110.9  ...       25.4       0.69       1.07   \n",
       "\n",
       "        SPI6_MENS  SPI12_MENS  SSWI1_MENS  SSWI3_MENS  SSWI6_MENS  \\\n",
       "0             NaN         NaN       -0.77         NaN         NaN   \n",
       "1             NaN         NaN       -0.05         NaN         NaN   \n",
       "2             NaN         NaN        0.69       -0.01         NaN   \n",
       "3             NaN         NaN        0.36        0.35         NaN   \n",
       "4             NaN         NaN       -0.25        0.35         NaN   \n",
       "...           ...         ...         ...         ...         ...   \n",
       "168159       2.59        0.85        4.31        1.70        1.35   \n",
       "168160       2.35        1.10        5.53        7.33        3.39   \n",
       "168161       1.85        1.30        1.47        4.45        4.13   \n",
       "168162       1.25        0.87        1.18        2.51        2.97   \n",
       "168163       1.52        1.39        1.87        1.84        3.19   \n",
       "\n",
       "        SSWI12_MENS  ECOULEMENT_MENS  \n",
       "0               NaN              0.0  \n",
       "1               NaN              0.0  \n",
       "2               NaN              0.0  \n",
       "3               NaN              0.0  \n",
       "4               NaN              0.0  \n",
       "...             ...              ...  \n",
       "168159         0.79              0.0  \n",
       "168160         1.33              0.0  \n",
       "168161         1.86              0.0  \n",
       "168162         2.30              0.0  \n",
       "168163         2.19              0.0  \n",
       "\n",
       "[168164 rows x 22 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from utils import load_table_from_resource_id, DATAGOUV_URL\n",
    "import requests\n",
    "\n",
    "# on prend une ressource principale d'un jeu de données de Météo France\n",
    "resources = requests.get(DATAGOUV_URL + \"api/1/datasets/65e040c50a5c6872ebebc711/\").json()[\"resources\"]\n",
    "resources = [r for r in resources if r[\"type\"] == \"main\"]\n",
    "\n",
    "df = load_table_from_resource_id(resources[0][\"id\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c9d6176e",
   "metadata": {},
   "source": [
    "# Exemple de réalisation : évolution des températures mensuelles moyennes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2f9f9a28",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests\n",
    "import plotly.express as px"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4fba8c6e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_1958-1959.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_1960-1969.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_1970-1979.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_1980-1989.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_1990-1999.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_2000-2009.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_2010-2019.csv.gz'},\n",
       " {'type': 'main',\n",
       "  'url': 'https://object.files.data.gouv.fr/meteofrance/data/synchro_ftp/REF_CC/SIM_MENS/MENS_SIM2_latest-2020-2024.csv.gz'}]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# on récupère les URLs des ressources de https://defis.data.gouv.fr/datasets/65e040c50a5c6872ebebc711\n",
    "resources = requests.get(\n",
    "    'https://www.data.gouv.fr/api/1/datasets/65e040c50a5c6872ebebc711/',\n",
    "    headers={'X-fields': 'resources{url,type}'}\n",
    ").json()['resources']\n",
    "resources = [r for r in resources if r['type'] == 'main']\n",
    "resources"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a2aa82c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LAMBX</th>\n",
       "      <th>LAMBY</th>\n",
       "      <th>DATE</th>\n",
       "      <th>T_MENS</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195808</td>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195809</td>\n",
       "      <td>16.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195810</td>\n",
       "      <td>12.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195811</td>\n",
       "      <td>9.5</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195812</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>784</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202312</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>785</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202401</td>\n",
       "      <td>7.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202402</td>\n",
       "      <td>10.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>787</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202403</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>788</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202404</td>\n",
       "      <td>11.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>789 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     LAMBX  LAMBY    DATE  T_MENS\n",
       "0      600  24010  195808    16.2\n",
       "1      600  24010  195809    16.5\n",
       "2      600  24010  195810    12.4\n",
       "3      600  24010  195811     9.5\n",
       "4      600  24010  195812     8.0\n",
       "..     ...    ...     ...     ...\n",
       "784    600  24010  202312    10.7\n",
       "785    600  24010  202401     7.6\n",
       "786    600  24010  202402    10.7\n",
       "787    600  24010  202403     9.8\n",
       "788    600  24010  202404    11.2\n",
       "\n",
       "[789 rows x 4 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# import des données qui nous intéressent : coordonnées, mois de relevé, température moyenne mensuelle\n",
    "dfs = []\n",
    "for r in resources:\n",
    "    tmp = pd.read_csv(\n",
    "        r['url'],\n",
    "        compression='gzip',\n",
    "        sep=\";\",\n",
    "        usecols=['LAMBX', 'LAMBY', 'DATE', 'T_MENS'],\n",
    "        dtype={\n",
    "            'LAMBX': int,\n",
    "            'LAMBY': int,\n",
    "            'DATE': str,\n",
    "            'T_MENS': float,\n",
    "        },\n",
    "    )\n",
    "    # on ne garde qu'une station\n",
    "    dfs.append(\n",
    "        tmp.loc[(tmp['LAMBX'] == 600) & (tmp['LAMBY'] == 24010)]\n",
    "    )\n",
    "df = pd.concat(dfs, ignore_index=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "791fb925",
   "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>LAMBX</th>\n",
       "      <th>LAMBY</th>\n",
       "      <th>DATE</th>\n",
       "      <th>T_MENS</th>\n",
       "      <th>annee</th>\n",
       "      <th>mois</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195808</td>\n",
       "      <td>16.2</td>\n",
       "      <td>1958</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195809</td>\n",
       "      <td>16.5</td>\n",
       "      <td>1958</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195810</td>\n",
       "      <td>12.4</td>\n",
       "      <td>1958</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195811</td>\n",
       "      <td>9.5</td>\n",
       "      <td>1958</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>195812</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1958</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>784</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202312</td>\n",
       "      <td>10.7</td>\n",
       "      <td>2023</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>785</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202401</td>\n",
       "      <td>7.6</td>\n",
       "      <td>2024</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>786</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202402</td>\n",
       "      <td>10.7</td>\n",
       "      <td>2024</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>787</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202403</td>\n",
       "      <td>9.8</td>\n",
       "      <td>2024</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>788</th>\n",
       "      <td>600</td>\n",
       "      <td>24010</td>\n",
       "      <td>202404</td>\n",
       "      <td>11.2</td>\n",
       "      <td>2024</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>789 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     LAMBX  LAMBY    DATE  T_MENS  annee  mois\n",
       "0      600  24010  195808    16.2   1958     8\n",
       "1      600  24010  195809    16.5   1958     9\n",
       "2      600  24010  195810    12.4   1958    10\n",
       "3      600  24010  195811     9.5   1958    11\n",
       "4      600  24010  195812     8.0   1958    12\n",
       "..     ...    ...     ...     ...    ...   ...\n",
       "784    600  24010  202312    10.7   2023    12\n",
       "785    600  24010  202401     7.6   2024     1\n",
       "786    600  24010  202402    10.7   2024     2\n",
       "787    600  24010  202403     9.8   2024     3\n",
       "788    600  24010  202404    11.2   2024     4\n",
       "\n",
       "[789 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['annee'] = df['DATE'].str.slice(0, 4).astype(int)\n",
    "df['mois'] = df['DATE'].str.slice(4, 6).astype(int)\n",
    "\n",
    "# on ne garde qu'une année sur 5 pour plus de clarté dans le graphe\n",
    "df_filtered = df.loc[df['annee'].apply(lambda y: y % 5 == 0)]\n",
    "\n",
    "# on construit une échelle de couleur pour les années\n",
    "colors = np.array([(255, 0, 0), (0, 0, 255)])\n",
    "years = sorted(df_filtered['annee'].unique())\n",
    "color_map = {y: f\"rgb{tuple([round(k) for k in idx/len(years)*colors[0] + (len(years)-idx)/len(years)*colors[1]])}\" for idx, y in enumerate(years)}\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "83ce66ee",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{1960: 'rgb(0, 0, 255)',\n",
       " 1965: 'rgb(20, 0, 235)',\n",
       " 1970: 'rgb(39, 0, 216)',\n",
       " 1975: 'rgb(59, 0, 196)',\n",
       " 1980: 'rgb(78, 0, 177)',\n",
       " 1985: 'rgb(98, 0, 157)',\n",
       " 1990: 'rgb(118, 0, 137)',\n",
       " 1995: 'rgb(137, 0, 118)',\n",
       " 2000: 'rgb(157, 0, 98)',\n",
       " 2005: 'rgb(177, 0, 78)',\n",
       " 2010: 'rgb(196, 0, 59)',\n",
       " 2015: 'rgb(216, 0, 39)',\n",
       " 2020: 'rgb(235, 0, 20)'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "color_map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "18244ebc",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = px.line(\n",
    "    df_filtered,\n",
    "    x='mois',\n",
    "    y='T_MENS',\n",
    "    color='annee',\n",
    "    title=\"Evolution des températures mensuelles\",\n",
    "    color_discrete_map=color_map,\n",
    ")\n",
    "# le paramètre renderer permet de garder l'image après fermeture du notebook mais il n'est plus interactible\n",
    "fig.show(\n",
    "#     renderer='png'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ea647ada",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}