init file

5_GEONATURE/tmp/manip_IPA_from_synthese.py

@@ -0,0 +1,66 @@
+
+import pandas as pd
+import json
+import uuid
+
+df = pd.read_csv(
+    '/home/cgeier/Téléchargements/IPA/Extraction/synthese_observations_2026-10-13T10_10_43.127Z.csv',
+    sep=';', 
+    converters={'champs_additionnels':eval}
+)
+
+rename_columns = {
+    'date_debut' : 'date_visit',
+    'nombre_min': 'effectif',
+    'jdd_uuid': 'id_dataset',
+
+}
+
+df.loc[df.comment_releve.str.contains('IPA'),'nom_point_ecoute'] = 'NDM - ' + (
+    df[df.comment_releve.str.contains('IPA')].comment_releve
+    .str.split('\n')
+    .str[0]
+    .str.strip()
+)
+df.loc[df.comment_releve.str.contains('IPA'),'heure_debut'] = (
+    df[df.comment_releve.str.contains('IPA')].comment_releve
+    .str.split('\n')
+    .str[1]
+    .str.split('-')
+    .str[0]
+    .str.strip()
+)
+df.loc[df.comment_releve.str.contains('IPA'),'meteo_ciel'] = (
+    df[df.comment_releve.str.contains('IPA')].comment_releve
+    .str.split('\n')
+    .str[2]
+    .str.strip()
+)
+
+
+df['code_atlas'] = df.champs_additionnels.map(lambda x: x['code_atlas'])
+df['uuid_observation'] = [str(uuid.uuid4()) for x in df.iterrows()]
+df['uuid_site'] = None
+df['uuid_visit'] = None
+df['date_site'] = None
+
+for s in df.nom_point_ecoute.unique():
+    t1 = df.nom_point_ecoute == s
+    df.loc[t1,'uuid_site'] = str(uuid.uuid4())
+    if df[t1].date_debut.unique().any():
+        df.loc[t1,'date_site'] = df[t1].date_debut.sort_values().unique()[0]
+
+    for v in df[t1].date_debut.unique():
+        t2 = df.date_debut == v
+        df.loc[t1&t2,'uuid_visit'] = str(uuid.uuid4())
+
+df.rename(columns=rename_columns, inplace=True)
+
+res = df[
+    ['cd_nom','nom_valide', 'nom_vernaculaire',*rename_columns.values(),
+    'code_atlas','comportement','technique_observation','uuid_observation','uuid_site','uuid_visit','date_site'
+    ,'nom_point_ecoute','heure_debut','meteo_ciel'
+    ]
+].copy()
+
+res.to_excel('/home/cgeier/Téléchargements/IPA/Extraction/ipa_ndm.xlsx')