meteo.data MENS LATEST - Télécharge-Visualise-Extrait les données Mensuelles LATEST_23-12-27.ipynb

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    "### Portail meteo.data.gouv.fr - Téléchargement-affichage-Extraction des données MENSUELLES LATEST de Météo-France (Métropole & outre-mer)\n",
    "Une connexion internet est nécessaire pour le téléchargement automatique des archives de données.\n",
    "1) Téléchargement des fichiers et décompression automatique, pour différents postes dans plusieurs départements si besoin\n",
    "2) Tracé du graphique chronologique pour le paramètre Précipitations RR des postes choisis par l'utilisateur\n",
    "3) Sauvegarde des données intégrales et du graphique dans un fichier Excel (tous paramètres de la période \"Latest\" pour tous les postes des départements concernés).\n",
    "\n",
    "data : https://meteo.data.gouv.fr/ (6 min, horaire, quotidien, mensuel)<br>\n",
    "Fiche PDF des postes : https://www.data.gouv.fr/fr/datasets/r/bee4b0c7-260a-40fe-b463-ed5631d6dc39 (paramètres et périodes de mesure)<br>\n",
    "Fichier CSV descriptif champs: https://www.data.gouv.fr/fr/datasets/r/6d4ac560-8f7c-477f-9a3f-3c33137fc04e\n",
    "\n",
    "Utilisez mon autre script pour visualiser sous forme de carte la liste des postes météorologiques fournie par Météo-France sous forme de fichier JSON https://meteo.data.gouv.fr/https://www.data.gouv.fr/fr/datasets/r/1fe544d8-4615-4642-a307-5956a7d90922\n",
    "\n",
    "NB:\n",
    "- Les données LATEST correspondent aux DERNIERS fichiers mis à jour quotidiennement, et qui vont du mois de janvier de l'année précédente au mois en cours même partiel.\n",
    "- Les données MENSUELLES ne sont pas simplement équivalentes à des données QUOTIDIENNE agrégées (les paramètres ne sont pas strictement les mêmes. Par exemple, il existe des des NOMBRES DE JOURS DE PLUIE/GELEE/CHALEUR/etc.., ainsi que des précipitations MENSUELLES ESTIMEES 'RR_ME' plus anciennes que les mesures)\n",
    "\n",
    "Auteur: https://github.com/loicduffar"
   ]
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    "##### 1) Lecture après téléchargement automatique des archives GZ et décompression des fichiers CSV LATEST (dernière période disponible)\n",
    "\n",
    "- Définir les chemins d'enregistrement pour les archives GZ et pour les fichier CSV décompressés\n",
    "- Définir les postes à interroger par leur code (voir fichier \"fiches.json\" sur https://www.data.gouv.fr/fr/datasets/r/1fe544d8-4615-4642-a307-5956a7d90922)\n",
    "- On peut choisir d'éviter de télécharger-décompresser les archives GZ si les fichiers CSV ont déjà été téléchargés dans le mois en cours\n",
    "\n",
    "Les archives LATEST sont automatiquement téléchargées-décompressées, et les fichiers CSV sont lus\n"
   ]
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      "2023-12-27 19:57\n",
      "Départements concernés:  ['04', '05', '06', '13', '83', '84']\n",
      "Lecture:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\MENSQ_04_latest-2022-2023.csv\n",
      "Lecture:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\MENSQ_05_latest-2022-2023.csv\n",
      "Lecture:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\MENSQ_06_latest-2022-2023.csv\n",
      "Lecture:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\MENSQ_13_latest-2022-2023.csv\n",
      "Lecture:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\MENSQ_83_latest-2022-2023.csv\n",
      "Lecture:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\MENSQ_84_latest-2022-2023.csv\n"
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       "      <th></th>\n",
       "      <th>NUM_POSTE</th>\n",
       "      <th>NOM_USUEL</th>\n",
       "      <th>LAT</th>\n",
       "      <th>LON</th>\n",
       "      <th>ALTI</th>\n",
       "      <th>DATE</th>\n",
       "      <th>RR</th>\n",
       "      <th>QRR</th>\n",
       "      <th>NBRR</th>\n",
       "      <th>RR_ME</th>\n",
       "      <th>...</th>\n",
       "      <th>QNEIGETOTM</th>\n",
       "      <th>NEIGETOTAB</th>\n",
       "      <th>QNEIGETOTAB</th>\n",
       "      <th>NEIGETOTABDAT</th>\n",
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       "      <th>NBJNEIGETOT10</th>\n",
       "      <th>NBJNEIGETOT30</th>\n",
       "      <th>NBJGREL</th>\n",
       "      <th>NBJORAG</th>\n",
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       "      <td>6.625333</td>\n",
       "      <td>1400</td>\n",
       "      <td>2022-01-01</td>\n",
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       "      <td>1400</td>\n",
       "      <td>2022-02-01</td>\n",
       "      <td>29.4</td>\n",
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       "      <td>28.0</td>\n",
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       "      <th>2</th>\n",
       "      <td>04006005</td>\n",
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       "      <td>44.242500</td>\n",
       "      <td>6.625333</td>\n",
       "      <td>1400</td>\n",
       "      <td>2022-03-01</td>\n",
       "      <td>13.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>04006005</td>\n",
       "      <td>ALLOS_SAPC</td>\n",
       "      <td>44.242500</td>\n",
       "      <td>6.625333</td>\n",
       "      <td>1400</td>\n",
       "      <td>2022-04-01</td>\n",
       "      <td>53.6</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>04006005</td>\n",
       "      <td>ALLOS_SAPC</td>\n",
       "      <td>44.242500</td>\n",
       "      <td>6.625333</td>\n",
       "      <td>1400</td>\n",
       "      <td>2022-05-01</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>31.0</td>\n",
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       "      <td>84150001</td>\n",
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       "      <td>44.336667</td>\n",
       "      <td>4.905500</td>\n",
       "      <td>141</td>\n",
       "      <td>2023-08-01</td>\n",
       "      <td>49.0</td>\n",
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       "      <td>84150001</td>\n",
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       "      <td>44.336667</td>\n",
       "      <td>4.905500</td>\n",
       "      <td>141</td>\n",
       "      <td>2023-09-01</td>\n",
       "      <td>56.9</td>\n",
       "      <td>1.0</td>\n",
       "      <td>30.0</td>\n",
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       "      <td>84150001</td>\n",
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       "      <td>44.336667</td>\n",
       "      <td>4.905500</td>\n",
       "      <td>141</td>\n",
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       "      <td>131.1</td>\n",
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       "      <td>141</td>\n",
       "      <td>2023-11-01</td>\n",
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       "      <td>84150001</td>\n",
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       "      <td>4.905500</td>\n",
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       "    NUM_POSTE   NOM_USUEL        LAT       LON  ALTI       DATE     RR  QRR  \\\n",
       "0    04006005  ALLOS_SAPC  44.242500  6.625333  1400 2022-01-01    4.2  1.0   \n",
       "1    04006005  ALLOS_SAPC  44.242500  6.625333  1400 2022-02-01   29.4  1.0   \n",
       "2    04006005  ALLOS_SAPC  44.242500  6.625333  1400 2022-03-01   13.0  1.0   \n",
       "3    04006005  ALLOS_SAPC  44.242500  6.625333  1400 2022-04-01   53.6  1.0   \n",
       "4    04006005  ALLOS_SAPC  44.242500  6.625333  1400 2022-05-01   38.0  1.0   \n",
       "..        ...         ...        ...       ...   ...        ...    ...  ...   \n",
       "427  84150001       VISAN  44.336667  4.905500   141 2023-08-01   49.0  1.0   \n",
       "428  84150001       VISAN  44.336667  4.905500   141 2023-09-01   56.9  1.0   \n",
       "429  84150001       VISAN  44.336667  4.905500   141 2023-10-01  131.1  1.0   \n",
       "430  84150001       VISAN  44.336667  4.905500   141 2023-11-01   44.6  1.0   \n",
       "431  84150001       VISAN  44.336667  4.905500   141 2023-12-01   33.8  1.0   \n",
       "\n",
       "     NBRR  RR_ME  ...  QNEIGETOTM  NEIGETOTAB  QNEIGETOTAB  NEIGETOTABDAT  \\\n",
       "0    31.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "1    28.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "2    31.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "3    30.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "4    31.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "..    ...    ...  ...         ...         ...          ...            ...   \n",
       "427  31.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "428  30.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "429  31.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "430  30.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "431  19.0    NaN  ...         NaN         NaN          NaN            NaN   \n",
       "\n",
       "     NBJNEIGETOT1  NBJNEIGETOT10  NBJNEIGETOT30  NBJGREL  NBJORAG  NBJBROU  \n",
       "0             NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "1             NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "2             NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "3             NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "4             NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "..            ...            ...            ...      ...      ...      ...  \n",
       "427           NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "428           NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "429           NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "430           NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "431           NaN            NaN            NaN      NaN      NaN      NaN  \n",
       "\n",
       "[4478 rows x 162 columns]"
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     "text": [
      "Postes absents de la liste JSON: ['04006400' '04019404' '04088001' '04112010' '04205001' '04219001'\n",
      " '04226001' '05001001' '05001400' '05004001' '05013003' '05026400'\n",
      " '05027001' '05032002' '05061400' '05063001' '05063410' '05064403'\n",
      " '05079400' '05085403' '05098402' '05101400' '05110001' '05110400'\n",
      " '05114402' '05119402' '05127001' '05133400' '05139405' '05157400'\n",
      " '05166001' '06073405' '06094400' '06120400' '06163400'] ['La Foux d Allos' 'Pra Loup' 'FORCALQUIER' 'MANOSQUE-PIMARLET' 'SEYNE'\n",
      " 'THORAME HAUTE' 'UVERNET FOURS' 'ABRIES' 'ABRIES RM' 'ANCELLE'\n",
      " 'BARCILLONNETTE' 'CEILLAC_NIVO' 'CERVIERES' 'CHAMPOLEON' 'GAP-BAYARD'\n",
      " 'LA GRAVE' 'LA GRAVE 3200 M' 'Les Portes en Valgaudemar' 'Le Monetier'\n",
      " 'MONTGENEVRE-LE CHALVET' 'LES ORRES FONTAINES' 'PELVOUX ST ANTOINE'\n",
      " 'PUY-ST-VINCENT' 'PUY ST VINCENT 1600' 'REALLON _NIVO' 'RISOUL' 'ROUSSET'\n",
      " 'Serre Chevalier' 'Super_Devoluy' 'ST VERAN RM' 'SERRES' 'ISOLA'\n",
      " 'Valberg' 'Auron' 'Val Casterino']\n"
     ]
    }
   ],
   "source": [
    "############ Auteur: L. Duffar ###########\n",
    "############ Décembre 2023 ###########\n",
    "# python 3.8.12\n",
    "# Télécharge les les archives ZIP & et décompresse les fichiers CSV LATEST (DERNIERE PERIODE DISPONIBLE)\n",
    "import os\n",
    "import requests\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import datetime\n",
    "import time\n",
    "import sys\n",
    "import gzip\n",
    "\n",
    "# ================ Personalisation ====================\n",
    "# Chemin d'enregistrement des archives gz et des fichiers CSV décompressés\n",
    "folder_gz= r\"X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\archives\\2023 Déc\\base\\M\"\n",
    "folder_csv= r\"X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\"\n",
    "\n",
    "# Numéro des Postes météo souhaités (chaine de 8 caractères) - voir fichier \"fiches.json\" sur https://www.data.gouv.fr/fr/datasets/r/1fe544d8-4615-4642-a307-5956a7d90922\n",
    "# LES DEPARTEMENTS CORRESPONDANTS DOIVENT ËTRE PRESENTS DANS LA LISTE DES URLS (voir ======= Initialisation ==========)\n",
    "postes= [\n",
    "        '04088001', '04039001', '04230001',                  # Forcalquier, Castellane, Valensole \\\n",
    "        '05046001',                                           # Embrun \\\n",
    "        '06088001', '06029001',                               # Nice, Cannes \\\n",
    "        '13001009', '13111002', '13103001','13055001',        # Aix en Provence, Vauvenargue, Salon, Marseille, \\\n",
    "        '83031001', '83061001', '83137001',                   # Le Luc, Fréjus, Toulon \\\n",
    "        '84003002', '84009002',                                # Apt-Viton, Bastide des Jourdans \\\n",
    "        # '97411132', '97411150',                                  # La REUNION: Chaudron, Saint-François \\\n",
    "        ]                               \n",
    "# Choisir d'éviter le téléchargement/décompression\n",
    "# non recommandé, sauf pour test ou à moins que le dernier téléchargement date du mois en cours\n",
    "download= False\n",
    "\n",
    "# ================ Extrait du fichier data CSV ============= (les colonnes sont en réalité séparées par des points-virgules)\n",
    "# NUM_POSTE\tNOM_USUEL\tLAT\tLON\tALTI\tAAAAMM\tRR\tQRR\tNBRR\tRR_ME\tRRAB\tQRRAB\tRRABDAT\tNBJRR1\tNBJRR5\tNBJRR10\tNBJRR30\n",
    "# 13001009\tAIX EN PROVENCE\t43.5295\t5.4245\t173\t202201\t3.6\t1\t31\t\t1.4\t1\t4\t1\t0\t0\t0\n",
    "# 13001009\tAIX EN PROVENCE\t43.5295\t5.4245\t173\t202202\t26.1\t28\t\t24.7\t1\t14\t2\t1\t1\t0\n",
    "# 13001009\tAIX EN PROVENCE\t43.5295\t5.4245\t173\t202203\t6.6\t1\t31\t\t3.6\t1\t30\t2\t0\t0\t0\n",
    "# 13001009\tAIX EN PROVENCE\t43.5295\t5.4245\t173\t202204\t27\t1\t30\t\t17.6\t1\t23\t4\t2\t1\t0\n",
    "# 13001009\tAIX EN PROVENCE\t43.5295\t5.4245\t173\t202205\t26\t1\t31\t\t16.8\t1\t8\t3\t2\t1\t0\n",
    "\n",
    "# ================ Extrait du fichier CSV Descriptif de quelques paramètres (les plus souvent utiles, précipitations et températures) =============(les colonnes sont en réalité séparées par \":\")\n",
    "# NUM_POSTE       \t numéro Météo-France du poste sur 8 chiffres\n",
    "# NOM_USUEL       \t nom usuel du poste\n",
    "# LAT             \t latitude, négative au sud (en degrés et millionièmes de degré)\n",
    "# LON             \t longitude, négative à l’ouest de GREENWICH (en degrés et millionièmes de degré)\n",
    "# ALTI            \t altitude du pied de l'abri ou du pluviomètre si pas d'abri (en m)\n",
    "# AAAAMM          \t mois\n",
    "# RR              \t cumul mensuel des hauteurs de précipitation (en mm et 1/10)\n",
    "# QRR             \t code qualité de RR\n",
    "# NBRR            \t nombre de valeurs présentes de hauteur de précipitation quotidienne\n",
    "# RR_ME           \t cumul mensuel estimé des hauteurs de précipitation (en mm et 1/10)\n",
    "# RRAB            \t précipitation maximale tombée en 24 heures au cours du mois\n",
    "# QRRAB           \t code qualite de RRAB\n",
    "# NBJRR1          \t nombre de jours avec RR ≥ 1.0 mm\n",
    "# TX              \t moyenne mensuelle des températures maximales (TX) quotidiennes (en °C et 1/10)\n",
    "# QTX             \t code qualité de TX\n",
    "# TN              \t moyenne mensuelle des températures minimales (TN) quotidiennes (en °C et 1/10)\n",
    "# QTN             \t code qualité de TN\n",
    "# TM              \t moyenne mensuelle des (TN+TX)/2 quotidiennes (en °C et 1/10)\n",
    "# QTM             \t code qualité de TM\n",
    "# TMM             \t moyenne mensuelle des températures moyennes (TM) quotidiennes (en °C et 1/10)\n",
    "# QTMM            \t code qualité du TMM\n",
    "# TMMIN           \t minimum mensuel des moyennes (TN+TX)/2 quotidiennes (en °C et 1/10)\n",
    "# QTMMIN          \t code qualité de TMMIN\n",
    "# TMMAX           \t maximum mensuel des moyennes (TN+TX)/2 quotidiennes (en °C et 1/10) \n",
    "# QTMMAX          \t code qualité du TMMAX\n",
    "# NBJGELEE        \t nombre de jours avec gelée\n",
    "\n",
    "# ================ Initialisation ====================\n",
    "now= datetime.datetime.now()\n",
    "print(now.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "# Structure du nom des fichiers de données mensuelles (1 fichier par département dont le numéro sera ajouté automatiquement au début et à la fin du template ci-dessous)\n",
    "template_start= 'MENSQ_'\n",
    "# Fin du nom dépendant de l'année en cours\n",
    "template_end= '_latest-' + str(now.year-1) + '-' + str(now.year) + '.csv'\n",
    "\n",
    "# ---------------- urls de téléchargement des archives des dernières données depuis janvier de l'année précédente https://meteo.data.gouv.fr/ (Ajouter d'autres départements si besoin)\n",
    "url_liste_postes= \"https://www.data.gouv.fr/fr/datasets/r/1fe544d8-4615-4642-a307-5956a7d90922\"\n",
    "url_desc_m = \"https://www.data.gouv.fr/fr/datasets/r/6d4ac560-8f7c-477f-9a3f-3c33137fc04e\"\n",
    "urls= dict()\n",
    "urls['04']= \"https://www.data.gouv.fr/fr/datasets/r/5c2d6f73-4162-4f36-bb41-98d7bc3e2ee1\" \n",
    "urls['05']= 'https://www.data.gouv.fr/fr/datasets/r/589b53fd-adef-44a4-b306-1dee1500d2d2'\n",
    "urls['06']= 'https://www.data.gouv.fr/fr/datasets/r/f8bdc686-8c37-4ced-8c36-407148bca194'\n",
    "urls['13']= 'https://www.data.gouv.fr/fr/datasets/r/78fe3a8a-7f32-44dd-a1b5-8acb841d6cc1'\n",
    "urls['83']= 'https://www.data.gouv.fr/fr/datasets/r/dc5ee912-e84a-4f15-bd08-7f326795ce41'\n",
    "urls['84']= 'https://www.data.gouv.fr/fr/datasets/r/75526d6c-81d5-4aad-8961-e9fc2a43f7b5'\n",
    "urls['974']= 'https://www.data.gouv.fr/fr/datasets/r/50a0d0fb-d97c-4ca3-b308-def80d69416d'\n",
    "\n",
    "# ---------------- Définition des fonctions\n",
    "def convert_to_date(aaaamm):\n",
    "    return pd.to_datetime(str(aaaamm), format='%Y%m', errors='coerce')\n",
    "\n",
    "def download_file(url, filename):\n",
    "    file= os.path.join(folder_gz, filename) + '.gz'\n",
    "    print('Téléchargement: ', file)\n",
    "    response = requests.get(url)\n",
    "    if response.status_code == 200:\n",
    "        with open(file, 'wb') as f:\n",
    "            f.write(response.content)\n",
    "    else:\n",
    "        print(\"Fichier d'archive non présent à l'url habituelle: \", file)\n",
    "\n",
    "def decompress_gz(filename):\n",
    "    file= os.path.join(folder_gz, filename) + '.gz'\n",
    "    \n",
    "    if os.path.exists(file):\n",
    "        with gzip.open(file, 'rb') as f_in:\n",
    "            file= os.path.join(folder_csv, filename) \n",
    "            print('Décompression', file)\n",
    "            with open(file, 'wb') as f_out:\n",
    "                f_out.write(f_in.read())\n",
    "    else:\n",
    "        print(\"Fichier d'archive non trouvé: \", file)\n",
    "\n",
    "def read_csv(filename):\n",
    "    file= os.path.join(folder_csv, filename)\n",
    "    if os.path.exists(file):\n",
    "        print('Lecture: ', file)\n",
    "        df= pd.read_csv(file, header=0, sep=\";\", dtype={\"NUM_POSTE\":str, 'AAAAMM':str}, parse_dates=['AAAAMM'], date_parser= convert_to_date)\n",
    "    else:\n",
    "        print(\"Fichier CSV non trouvé: \", file)\n",
    "    return df\n",
    "\n",
    "# ================ Traitement ====================\n",
    "# Lecture en ligne du fichier JSON de la liste des postes\n",
    "req= requests.get(url_liste_postes)\n",
    "if req.status_code == 200:\n",
    "    data_json= req.json()\n",
    "else:\n",
    "    print('la requête a échoué avec le code : ', req.status_codes)\n",
    "    sys.exit() # interrompt le script\n",
    "df_liste_postes = pd.DataFrame(data_json['features']).T\n",
    "# Ajout de colonnes avec les champs de properties\n",
    "df_liste_postes['lat'] = df_liste_postes['geometry'].apply(lambda x: x['coordinates'][1]).astype(float)\n",
    "df_liste_postes['lon'] = df_liste_postes['geometry'].apply(lambda x: x['coordinates'][0]).astype(float)\n",
    "df_liste_postes['nom_usuel']= df_liste_postes['properties'].apply(lambda x: x['NOM_USUEL'].strip())\n",
    "df_liste_postes['num_poste']= df_liste_postes['properties'].apply(lambda x: x['NUM_POSTE'].strip())\n",
    "df_liste_postes['commune'] = df_liste_postes['properties'].apply(lambda x: x['COMMUNE'].strip())\n",
    "df_liste_postes['ficheClimComplete'] = df_liste_postes['properties'].apply(lambda x: x['ficheClimComplete']).astype(float)\n",
    "df_liste_postes['ficheClimReduite'] = df_liste_postes['properties'].apply(lambda x: x['ficheClimReduite']).astype(float)\n",
    "df_liste_postes['alti'] = df_liste_postes['properties'].apply(lambda x: x['ALTI'])\n",
    "# supprime les colonnes inutiles et classe par numéro de poste (donc par département)\n",
    "df_liste_postes.drop(['type', 'geometry', 'properties'], axis=1, inplace=True)\n",
    "df_liste_postes.sort_values(by= ['num_poste'], inplace=True)\n",
    "\n",
    "# Lit en ligne le fichier \"MENSQ_descriptif_champs.csv\" de description des champs et le stocke dans un dataframe pandas\n",
    "# définit le dataframe pandas avec les 2 colonnes \"param\" et \"name_long\" pour la description des champs \n",
    "df_desc_m = pd.read_csv(url_desc_m, sep=\":\", header= None, index_col=0, names= [\"param\", \"name_long\", 'complement'], dtype={\"param\":str, \"name_long\":str, 'complement':str}, encoding= 'utf-8')\n",
    "df_desc_m.index= df_desc_m.index.str.strip()\n",
    "df_desc_m['name_long']= df_desc_m['name_long'].str.strip()\n",
    "\n",
    "# fait la liste des départements concernés et garde les 2 premiers chiffres uniques\n",
    "departements = []\n",
    "for poste in postes:\n",
    "    if float(poste[:2]) > 95:\n",
    "        departements.append(poste[:3])\n",
    "    else:\n",
    "        departements.append(poste[:2])\n",
    "\n",
    "# On ne garde que départements uniques\n",
    "departements = list(set(departements)) # set() ignore automatiquement les doublons (ce qui évite de passer par array numpy pour utiliser la fonction np.unique() )\n",
    "# On trie la liste\n",
    "departements.sort()\n",
    "# On affiche la liste\n",
    "print('Départements concernés: ', departements)\n",
    "\n",
    "# Téléchargement/décompression/lecture des fichiers dans une boucle sur les départements (urls tirées du dictionnaire 'urls')\n",
    "for i, departement in enumerate(departements):\n",
    "    # On récupère l'url\n",
    "    url = urls[departement]\n",
    "    # Formation du nom du fichier à partir du template et du numéro de département\n",
    "    filename = f\"{template_start}{departement}{template_end}\"\n",
    "    if download:\n",
    "        download_file(url, filename)\n",
    "        decompress_gz(filename)\n",
    "    # Lecture du fichier CSV dans un dataframe pandas\n",
    "    df_departement= read_csv(filename)\n",
    "    if i== 0:\n",
    "        # initialisation du dataframe final df avec les données du premier département        \n",
    "        df= df_departement\n",
    "    else:\n",
    "        df= pd.concat([df, df_departement])        \n",
    "\n",
    "# supprime les espaces avant et après le numéro de poste\n",
    "df['NUM_POSTE'] = df['NUM_POSTE'].str.strip()\n",
    "# renome la colonne \"AAAMM\" en \"DATE\"\n",
    "df.rename(columns={'AAAAMM':'DATE'}, inplace=True)\n",
    "# supprime les espaces dans les noms de colonnes\n",
    "df.columns= df.columns.str.strip()\n",
    "display(df)\n",
    "\n",
    "# Détection des postes manquants dans la liste JSON\n",
    "postes_mesures= df['NUM_POSTE'].unique()\n",
    "postes_json= df_liste_postes['num_poste'].unique()\n",
    "# trouvrer les postes_mesures absents de la liste JSON\n",
    "postes_absents= np.setdiff1d(postes_mesures, postes_json)\n",
    "if len(postes_absents) > 0:\n",
    "    # trouver le NOM_USEL des postes absents\n",
    "    print(\"Postes absents de la liste JSON:\", postes_absents, df[df['NUM_POSTE'].isin(postes_absents)]['NOM_USUEL'].unique())\n",
    "else:\n",
    "    print(\"Aucun postes absent de la liste JSON\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 2) Affichage des données mensuelles & graphique des précipitations\n",
    "\n",
    "- Définir les dates de début et de fin du graphique comme suit:\n",
    "    - None pour prendre le début et la fin du fichier LATEST (premier jour de l'année précédente et veille du téléchargement)\n",
    "    - ou définir la date de début et de fin\n",
    "- Définir le ou les paramètres à extraire (au minimum les précipitations RR car le graphique est uniquement prévu pour cela)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-12-27 19:46\n",
      "Données mensuelles des 2 derniers mois pour les paramètres choisis: Attention le cumul du dernier mois est incomplet à ce jour\n",
      "- RR: cumul mensuel des hauteurs de précipitation (en mm et 1/10)\n",
      "- TM: moyenne mensuelle des (TN+TX)/2 quotidiennes (en °C et 1/10)\n",
      "- FXYAB: maximum absolu mensuel de la force maximale quotidienne du vent moyenné sur 10 mn (FXY), à 10 m (en m/s et 1/10)\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>NOM_USUEL</th>\n",
       "      <th>AIX EN PROVENCE</th>\n",
       "      <th>APT-VITON</th>\n",
       "      <th>CANNES</th>\n",
       "      <th>CASTELLANE</th>\n",
       "      <th>EMBRUN</th>\n",
       "      <th>FORCALQUIER</th>\n",
       "      <th>FREJUS</th>\n",
       "      <th>LA BASTIDE DES JOURDANS</th>\n",
       "      <th>LE LUC</th>\n",
       "      <th>MARSEILLE-OBS</th>\n",
       "      <th>NICE</th>\n",
       "      <th>SALON DE PROVENCE</th>\n",
       "      <th>TOULON</th>\n",
       "      <th>VALENSOLE</th>\n",
       "      <th>VAUVENARGUES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>parametre</th>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">RR</th>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>30.2</td>\n",
       "      <td>37.6</td>\n",
       "      <td>20.7</td>\n",
       "      <td>102.2</td>\n",
       "      <td>214.2</td>\n",
       "      <td>63.1</td>\n",
       "      <td>20.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>21.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>29.0</td>\n",
       "      <td>30.8</td>\n",
       "      <td>25.8</td>\n",
       "      <td>36.4</td>\n",
       "      <td>41.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-01</th>\n",
       "      <td>42.6</td>\n",
       "      <td>60.4</td>\n",
       "      <td>41.5</td>\n",
       "      <td>76.3</td>\n",
       "      <td>125.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>50.6</td>\n",
       "      <td>42.6</td>\n",
       "      <td>53.8</td>\n",
       "      <td>28.3</td>\n",
       "      <td>48.9</td>\n",
       "      <td>35.4</td>\n",
       "      <td>65.2</td>\n",
       "      <td>56.8</td>\n",
       "      <td>71.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">TM</th>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>10.2</td>\n",
       "      <td>9.1</td>\n",
       "      <td>13.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>5.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.3</td>\n",
       "      <td>9.0</td>\n",
       "      <td>12.7</td>\n",
       "      <td>12.9</td>\n",
       "      <td>13.5</td>\n",
       "      <td>10.5</td>\n",
       "      <td>13.6</td>\n",
       "      <td>9.0</td>\n",
       "      <td>8.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-01</th>\n",
       "      <td>7.9</td>\n",
       "      <td>6.8</td>\n",
       "      <td>10.8</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.5</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.2</td>\n",
       "      <td>10.5</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>10.7</td>\n",
       "      <td>6.8</td>\n",
       "      <td>6.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">FXYAB</th>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>9.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.2</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>10.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>10.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-01</th>\n",
       "      <td>7.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>15.1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>19.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.7</td>\n",
       "      <td>18.4</td>\n",
       "      <td>12.1</td>\n",
       "      <td>11.2</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
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       "NOM_USUEL             AIX EN PROVENCE  APT-VITON  CANNES  CASTELLANE  EMBRUN  \\\n",
       "parametre DATE                                                                 \n",
       "RR        2023-11-01             30.2       37.6    20.7       102.2   214.2   \n",
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       "FXYAB     2023-11-01              9.2        NaN    12.5         NaN    13.8   \n",
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       "NOM_USUEL             FORCALQUIER  FREJUS  LA BASTIDE DES JOURDANS  LE LUC  \\\n",
       "parametre DATE                                                               \n",
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       "NOM_USUEL             MARSEILLE-OBS  NICE  SALON DE PROVENCE  TOULON  \\\n",
       "parametre DATE                                                         \n",
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       "\n",
       "NOM_USUEL             VALENSOLE  VAUVENARGUES  \n",
       "parametre DATE                                 \n",
       "RR        2023-11-01       36.4          41.8  \n",
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    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Données mensuelles LATEST (depuis le début de l'année précédente) pour les paramètres choisis: \n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NOM_USUEL</th>\n",
       "      <th>AIX EN PROVENCE</th>\n",
       "      <th>APT-VITON</th>\n",
       "      <th>CANNES</th>\n",
       "      <th>CASTELLANE</th>\n",
       "      <th>EMBRUN</th>\n",
       "      <th>FORCALQUIER</th>\n",
       "      <th>FREJUS</th>\n",
       "      <th>LA BASTIDE DES JOURDANS</th>\n",
       "      <th>LE LUC</th>\n",
       "      <th>MARSEILLE-OBS</th>\n",
       "      <th>NICE</th>\n",
       "      <th>SALON DE PROVENCE</th>\n",
       "      <th>TOULON</th>\n",
       "      <th>VALENSOLE</th>\n",
       "      <th>VAUVENARGUES</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>parametre</th>\n",
       "      <th>DATE</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">RR</th>\n",
       "      <th>2022-01-01</th>\n",
       "      <td>3.6</td>\n",
       "      <td>1.8</td>\n",
       "      <td>7.6</td>\n",
       "      <td>5.6</td>\n",
       "      <td>9.2</td>\n",
       "      <td>3.5</td>\n",
       "      <td>2.4</td>\n",
       "      <td>3.4</td>\n",
       "      <td>0.8</td>\n",
       "      <td>0.4</td>\n",
       "      <td>11.3</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-02-01</th>\n",
       "      <td>26.1</td>\n",
       "      <td>23.7</td>\n",
       "      <td>47.6</td>\n",
       "      <td>35.4</td>\n",
       "      <td>15.4</td>\n",
       "      <td>24.8</td>\n",
       "      <td>36.2</td>\n",
       "      <td>18.4</td>\n",
       "      <td>31.9</td>\n",
       "      <td>19.9</td>\n",
       "      <td>26.8</td>\n",
       "      <td>38.2</td>\n",
       "      <td>27.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>24.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-03-01</th>\n",
       "      <td>6.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>31.9</td>\n",
       "      <td>13.4</td>\n",
       "      <td>9.4</td>\n",
       "      <td>6.6</td>\n",
       "      <td>30.4</td>\n",
       "      <td>6.4</td>\n",
       "      <td>28.2</td>\n",
       "      <td>9.4</td>\n",
       "      <td>18.9</td>\n",
       "      <td>6.6</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8.4</td>\n",
       "      <td>10.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-04-01</th>\n",
       "      <td>27.0</td>\n",
       "      <td>53.7</td>\n",
       "      <td>50.9</td>\n",
       "      <td>65.6</td>\n",
       "      <td>48.6</td>\n",
       "      <td>44.4</td>\n",
       "      <td>40.4</td>\n",
       "      <td>41.5</td>\n",
       "      <td>45.8</td>\n",
       "      <td>19.3</td>\n",
       "      <td>26.1</td>\n",
       "      <td>25.6</td>\n",
       "      <td>26.2</td>\n",
       "      <td>32.6</td>\n",
       "      <td>38.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2022-05-01</th>\n",
       "      <td>26.0</td>\n",
       "      <td>47.3</td>\n",
       "      <td>3.8</td>\n",
       "      <td>29.4</td>\n",
       "      <td>33.6</td>\n",
       "      <td>28.5</td>\n",
       "      <td>3.8</td>\n",
       "      <td>24.5</td>\n",
       "      <td>38.1</td>\n",
       "      <td>29.5</td>\n",
       "      <td>2.2</td>\n",
       "      <td>7.6</td>\n",
       "      <td>28.6</td>\n",
       "      <td>29.0</td>\n",
       "      <td>44.7</td>\n",
       "    </tr>\n",
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       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">FXYAB</th>\n",
       "      <th>2023-08-01</th>\n",
       "      <td>11.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.1</td>\n",
       "      <td>13.3</td>\n",
       "      <td>17.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.4</td>\n",
       "      <td>16.6</td>\n",
       "      <td>11.0</td>\n",
       "      <td>13.9</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-01</th>\n",
       "      <td>8.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>9.6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.3</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.7</td>\n",
       "      <td>9.2</td>\n",
       "      <td>11.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "      <td>11.8</td>\n",
       "      <td>9.2</td>\n",
       "      <td>10.1</td>\n",
       "      <td>6.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-01</th>\n",
       "      <td>9.4</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.9</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>11.3</td>\n",
       "      <td>10.2</td>\n",
       "      <td>12.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.8</td>\n",
       "      <td>12.0</td>\n",
       "      <td>11.9</td>\n",
       "      <td>10.7</td>\n",
       "      <td>8.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-01</th>\n",
       "      <td>9.2</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.2</td>\n",
       "      <td>15.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>NaN</td>\n",
       "      <td>14.1</td>\n",
       "      <td>19.0</td>\n",
       "      <td>10.6</td>\n",
       "      <td>11.6</td>\n",
       "      <td>10.0</td>\n",
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       "    <tr>\n",
       "      <th>2023-12-01</th>\n",
       "      <td>7.8</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.5</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>15.1</td>\n",
       "      <td>10.0</td>\n",
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       "      <td>12.7</td>\n",
       "      <td>18.4</td>\n",
       "      <td>12.1</td>\n",
       "      <td>11.2</td>\n",
       "      <td>8.3</td>\n",
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      ],
      "text/plain": [
       "NOM_USUEL             AIX EN PROVENCE  APT-VITON  CANNES  CASTELLANE  EMBRUN  \\\n",
       "parametre DATE                                                                 \n",
       "RR        2022-01-01              3.6        1.8     7.6         5.6     9.2   \n",
       "          2022-02-01             26.1       23.7    47.6        35.4    15.4   \n",
       "          2022-03-01              6.6       11.6    31.9        13.4     9.4   \n",
       "          2022-04-01             27.0       53.7    50.9        65.6    48.6   \n",
       "          2022-05-01             26.0       47.3     3.8        29.4    33.6   \n",
       "...                               ...        ...     ...         ...     ...   \n",
       "FXYAB     2023-08-01             11.3        NaN    10.2         NaN     9.9   \n",
       "          2023-09-01              8.5        NaN     9.6         NaN     8.3   \n",
       "          2023-10-01              9.4        NaN    13.9         NaN     8.5   \n",
       "          2023-11-01              9.2        NaN    12.5         NaN    13.8   \n",
       "          2023-12-01              7.8        NaN    12.5         NaN     7.6   \n",
       "\n",
       "NOM_USUEL             FORCALQUIER  FREJUS  LA BASTIDE DES JOURDANS  LE LUC  \\\n",
       "parametre DATE                                                               \n",
       "RR        2022-01-01          3.5     2.4                      3.4     0.8   \n",
       "          2022-02-01         24.8    36.2                     18.4    31.9   \n",
       "          2022-03-01          6.6    30.4                      6.4    28.2   \n",
       "          2022-04-01         44.4    40.4                     41.5    45.8   \n",
       "          2022-05-01         28.5     3.8                     24.5    38.1   \n",
       "...                           ...     ...                      ...     ...   \n",
       "FXYAB     2023-08-01          NaN    13.1                     13.3    17.1   \n",
       "          2023-09-01          NaN    10.7                      9.2    11.8   \n",
       "          2023-10-01          NaN    11.3                     10.2    12.1   \n",
       "          2023-11-01          NaN    14.2                     15.0    19.5   \n",
       "          2023-12-01          NaN    15.1                     10.0    19.9   \n",
       "\n",
       "NOM_USUEL             MARSEILLE-OBS  NICE  SALON DE PROVENCE  TOULON  \\\n",
       "parametre DATE                                                         \n",
       "RR        2022-01-01            0.4  11.3                2.0     2.8   \n",
       "          2022-02-01           19.9  26.8               38.2    27.0   \n",
       "          2022-03-01            9.4  18.9                6.6    16.4   \n",
       "          2022-04-01           19.3  26.1               25.6    26.2   \n",
       "          2022-05-01           29.5   2.2                7.6    28.6   \n",
       "...                             ...   ...                ...     ...   \n",
       "FXYAB     2023-08-01            NaN  14.4               16.6    11.0   \n",
       "          2023-09-01            NaN  12.5               11.8     9.2   \n",
       "          2023-10-01            NaN  13.8               12.0    11.9   \n",
       "          2023-11-01            NaN  14.1               19.0    10.6   \n",
       "          2023-12-01            NaN  12.7               18.4    12.1   \n",
       "\n",
       "NOM_USUEL             VALENSOLE  VAUVENARGUES  \n",
       "parametre DATE                                 \n",
       "RR        2022-01-01        4.8           1.0  \n",
       "          2022-02-01       15.0          24.7  \n",
       "          2022-03-01        8.4          10.4  \n",
       "          2022-04-01       32.6          38.9  \n",
       "          2022-05-01       29.0          44.7  \n",
       "...                         ...           ...  \n",
       "FXYAB     2023-08-01       13.9           8.3  \n",
       "          2023-09-01       10.1           6.7  \n",
       "          2023-10-01       10.7           8.3  \n",
       "          2023-11-01       11.6          10.0  \n",
       "          2023-12-01       11.2           8.3  \n",
       "\n",
       "[72 rows x 15 columns]"
      ]
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   ],
   "source": [
    "# trace un graphique plotly des précipitations avec la colonne 'DATE' en abscisse et la colonne 'RR' en ordonnée\n",
    "# chaque poste de la colonnee 'NUM_POSTE' est représenté dans un subplot séparé\n",
    "import plotly.graph_objects as go\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly\n",
    "\n",
    "#-------------- Personalisation du graphique \n",
    "# Paramètres à représenter: 'RR' obligatoire en premier, pour le graphique dont la présentation actuelle est spécialement adaptée aux précipitations\n",
    "param_list= ['RR', 'TM', 'FXYAB']\n",
    "\n",
    "# Période à représenter (None pour le début ou la fin du fichier par défaut)\n",
    "start_date= None\n",
    "# start_date= datetime.datetime(2022, 5, 1)\n",
    "\n",
    "end_date= None\n",
    "# end_date= datetime.datetime(now.year, now.month, now.day)\n",
    "\n",
    "#-------------- initialisation des paramètres du graphique\n",
    "param_RR= 'RR'\n",
    "# Période par défaut if start_date= None ou  end_date= None\n",
    "if start_date is None:\n",
    "    start_date= df['DATE'].min()\n",
    "if end_date is None:\n",
    "    end_date= df['DATE'].max()\n",
    "\n",
    "# filtre le dataframe sur les postes choisis\n",
    "df_postes= df[df['NUM_POSTE'].isin(postes)]\n",
    "# filtre le dataframe sur la période souhaitée\n",
    "df_postes= df_postes[(df_postes['DATE'] >= start_date) & (df_postes['DATE'] <= end_date)]\n",
    "\n",
    "#  Couleurs des courbes\n",
    "color_sequence_bar = plotly.colors.qualitative.Set3\n",
    "color_sequence_scatter = plotly.colors.qualitative.Pastel\n",
    "\n",
    "# Axe des ordonnées secondaire (cumulé)\n",
    "specs= [[{'secondary_y': True}]]*len(postes)\n",
    "\n",
    "#-------------- Graphique\n",
    "fig = make_subplots(rows= len(postes), cols= 1,# shared_xaxes= True, # shared_xaxes= True inutile grâce à  matches='x' dans update_xaxes qui fait la même chose sans supprimer la graduation des dates des subplots \n",
    "                    subplot_titles= [f\"{poste} - {df_postes[df_postes['NUM_POSTE'] == poste]['NOM_USUEL'].iloc[0]}\" for poste in postes], specs= specs)\n",
    "\n",
    "for i, poste in enumerate(postes):\n",
    "    df_poste = df_postes[df_postes['NUM_POSTE'] == poste]\n",
    "    fig.add_trace(go.Bar(x= df_poste['DATE'], y= df_poste[param_RR], \n",
    "                          # name= poste\n",
    "                         name= df_postes[df_postes['NUM_POSTE'] == poste]['NOM_USUEL'].iloc[0],\n",
    "                         marker= dict(color=color_sequence_bar[i % len(color_sequence_bar)]),  # Utilisez la couleur correspondante de la séquence\n",
    "                         ),\n",
    "                row= i+1, col= 1)\n",
    "    fig.add_trace(go.Scatter(x= df_poste['DATE'], y= df_poste[param_RR].cumsum(), \n",
    "                             name= f\"Cumulé {poste}\", yaxis= \"y2\",\n",
    "                             line= dict(color= 'gray'),\n",
    "                            #  line= dict(color= color_sequence_scatter[i % len(color_sequence_scatter)]), # sinon l'incrémentation dans la séquence de couleurs est de +2 à cause de la trace Bar\n",
    "                             mode='lines' \n",
    "                             ), \n",
    "                 row=i+1, col=1, secondary_y= True)\n",
    "\n",
    "fig.update_layout(title_text= 'meteo.data.gouv.fr - ' + \"Précipitations mensuelles (mm) - \" + now.strftime(\"%Y-%m-%d\") , title_x= 0.5, \n",
    "                  height= 133.*(len(postes)+1), width= 1000,\n",
    "                  hovermode= 'x unified', hoverlabel= dict(bgcolor='rgba(255,255,255,0.6)'),\n",
    "                  )\n",
    "\n",
    "# Survol par la souris : ligne verticale à travers tous les subplots matérialisant l'abscisse \n",
    "xlast= 'x' + str(len(postes))\n",
    "# fig.update_traces(xaxis= xlast)  # xlast est le nom de l'axe des abscisses du dernier subplot\n",
    "\n",
    "# Définition générale des axes\n",
    "max_value= df_postes[param_RR].max()\n",
    "max_value_cum= df_postes.groupby(['NUM_POSTE']).sum()[param_RR].max()\n",
    "fig.update_yaxes(secondary_y= False, range= [0, max_value])  # Axe principale: Replace max_value with the desired maximum coordinate\n",
    "fig.update_yaxes(secondary_y= True, title_text= \"Cumulé\", range= [0, max_value_cum]) # Axe secondaire: Replace max_value with the desired maximum coordinate\n",
    "\n",
    "# Graduations de l'axe des DATES ...............................................................\n",
    "if end_date - start_date > datetime.timedelta(days= 365): # Plus d'un an\n",
    "    tickformat= '%b\\n%Y'\n",
    "    dtick= 'M6'\n",
    "    showgrid_x= True\n",
    "else: # Moins d'un an\n",
    "    tickformat= '%b %Y'\n",
    "    dtick= 'M1'\n",
    "    showgrid_x= False\n",
    "# ...............................Premiers subplots\n",
    "# ................................................ en fonction de la longueur de la période\n",
    "for i in range(1, len(postes) + 1):\n",
    "    fig.update_xaxes(tickformat= tickformat, tickmode= 'linear', dtick= dtick, row=i, col=1, matches='x')\n",
    "# ...............................Dernier subplot\n",
    "# ................................................ en fonction de la longueur de la période\n",
    "fig.update_xaxes(tickformat= tickformat, tickmode= 'linear', dtick= dtick, row=len(postes), col=1, matches='x')\n",
    "#                                                SANS tenir compte de la longueur de la période\n",
    "# fig.update_xaxes(tickformat= '%b\\n%Y', tickmode= 'linear', dtick= 'M1', row=len(postes), col=1, matches='x')\n",
    "\n",
    "# GRILLE .............................................................................\n",
    "# .................. verticales...\n",
    "fig.update_xaxes(showgrid= showgrid_x, gridwidth= 1, gridcolor= 'white')\n",
    "# .................. horizontales\n",
    "#                                Axe secondaire:\n",
    "fig.update_yaxes(secondary_y=True, showgrid=False) # pas de grille\n",
    "\n",
    "#-------------- sauvegarde le graphique\n",
    "file_graph= \"meteo.data MENS\"\n",
    "fig.write_html(os.path.join(folder_csv, file_graph + template_end[:-4] + \".html\"))\n",
    "# sauvegarde le graphique dans un fichier png\n",
    "fig.write_image(os.path.join(folder_csv, file_graph + template_end[:-4] + \".png\"))\n",
    "\n",
    "#-------------- Valeurs quotidiennes pivotée pour la présentation avec les postes en colonnes\n",
    "#               pour les postes et les paramètres SELECTIONNES, SUR la durée COMPLETE\n",
    "for i, par in enumerate(param_list):\n",
    "    if i==0:\n",
    "        df_m = df[df['NUM_POSTE'].isin(postes)].pivot(index='DATE', columns='NOM_USUEL', values= param_list[i]) \\\n",
    "            .assign(parametre= par)\n",
    "    else:\n",
    "        # append des lignes à df_m\n",
    "        df_m = pd.concat([df_m,\n",
    "                        df[df['NUM_POSTE'].isin(postes)].pivot(index='DATE', columns='NOM_USUEL', values= param_list[i]) \\\n",
    "                        .assign(parametre= par)]\n",
    "                        )\n",
    "df_m= df_m.reset_index().set_index(['parametre', 'DATE'], drop= True)\n",
    "\n",
    "#-------------- Affichage\n",
    "print(datetime.datetime.now().strftime(\"%Y-%m-%d %H:%M\"))\n",
    "# imprimer un avertissement si la dernière date du dataframe est antérieure au dernier jour du mois en cours\n",
    "\n",
    "titre= 'Données mensuelles des 2 derniers mois pour les paramètres choisis: '\n",
    "titre= titre + 'Attention le cumul du dernier mois est incomplet à ce jour'\n",
    "print(titre)\n",
    "for i, par in enumerate(param_list):\n",
    "    titre= '- ' + par + ': ' + df_desc_m.loc[par]['name_long']\n",
    "    print(titre)\n",
    "month_before_now= datetime.datetime(now.year, now.month, 1) - datetime.timedelta(days= 30)\n",
    "display(df_m[(df_m.index.get_level_values(1) >= month_before_now) & (df_m.index.get_level_values(1) <= end_date)])\n",
    "\n",
    "fig.show()\n",
    "\n",
    "titre_m= \"Données mensuelles LATEST (depuis le début de l'année précédente) pour les paramètres choisis: \"\n",
    "print(titre_m)\n",
    "display(df_m)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 3) Sauvegarde les données intégrales dans un fichier Excel (tous les paramètres pour tous les postes des départements concernés)\n",
    "Le fichier est sauvegardé dans le même dossier local que les fichiers CSV décompressés"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2023-12-27 19:06\n",
      "Sauvegarde en cours, patientez...\n",
      "2023-12-27 19:06\n",
      "Ficher Excel sauvegardé:  X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat France\\Météo-France\\meteo.data\\base\\M\\meteo.data MENS_04-05-06-13-83-84_latest-2022-2023.xlsx\n"
     ]
    }
   ],
   "source": [
    "# Sauvegarde toutes les informations dans un fichier Excel\n",
    "print(now.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "print('Sauvegarde en cours, patientez...')\n",
    "file= os.path.join(folder_csv, \"meteo.data MENS\" + '_' + '-'.join(departements) + template_end[:-4] + \".xlsx\")\n",
    "writer = pd.ExcelWriter(file, engine='xlsxwriter')\n",
    "workbook  = writer.book\n",
    "#======================== Sauvegarde la liste des postes dans le fichier excel\n",
    "\n",
    "# sauvegarde dans un fichier excel plus lisible que le JSON après suppression des colonnes type, geometry et properties\n",
    "sheet= 'liste_postes'\n",
    "df_liste_postes.to_excel(writer, sheet_name= sheet, index= False, startrow= 0)\n",
    "\n",
    "#======================== Sauvegarde la liste des champs dans le fichier Excel\n",
    "sheet= 'MENSQ_descriptif_champs'\n",
    "df_desc_m.to_excel(writer, sheet_name= sheet, index= True, startrow= 1)\n",
    "worksheet = writer.sheets[sheet]\n",
    "worksheet.write('A1', sheet + '.csv')\n",
    "                \n",
    "sheet= 'donnée complètes'\n",
    "df.to_excel(writer, sheet_name= sheet, index=False, startrow= 2)\n",
    "worksheet = writer.sheets[sheet]\n",
    "worksheet.write('A1', now.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "worksheet.write('A2', 'Données LATEST quotidiennes au format original, complètes pour tous les départements concernés: ')\n",
    "\n",
    "#======================== Sauvegarde les dataframes dans le fichier Excel\n",
    "sheet= 'donnée complètes'\n",
    "df.to_excel(writer, sheet_name= sheet, index=False, startrow= 2)\n",
    "worksheet = writer.sheets[sheet]\n",
    "worksheet.write('A1', now.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "worksheet.write('A2', \"Données mensuelles LATEST (depuis le début de l'année précédente) au format original, complètes pour tous les départements concernés: \")\n",
    "\n",
    "# ajoute un onglet exel avec df_m\n",
    "n_param= len(param_list)\n",
    "sheet= 'MENS Sélection'\n",
    "df_m.to_excel(writer, sheet_name= sheet, index=True, startrow= n_param + 2)\n",
    "worksheet = writer.sheets[sheet]\n",
    "worksheet.write('A1', now.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "worksheet.write('A2', titre_m)\n",
    "for i, par in enumerate(param_list):\n",
    "    titre= '- ' + par + ': ' + df_desc_m.loc[par]['name_long']\n",
    "    worksheet.write('A' + str(i+3), titre)\n",
    "\n",
    "# ajoute un onglet excel et enregistre une image statique du graphique\n",
    "sheet= 'graph'\n",
    "worksheet = workbook.add_worksheet(sheet)\n",
    "worksheet.insert_image('A1', os.path.join(folder_csv, file_graph + template_end[:-4] + \".png\"))\n",
    "\n",
    "writer.save()\n",
    "\n",
    "print(now.strftime(\"%Y-%m-%d %H:%M\"))\n",
    "print('Ficher Excel sauvegardé: ', file)"
   ]
  }
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