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update code

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This commit is contained in:
Colas Geier 2026-04-28 14:18:17 +02:00
parent 205e55f6f2
commit fd0ddaecc4
4 changed files with 255 additions and 74 deletions
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4
0_FONCIER/grant_table.py
View File

@ -46,7 +46,7 @@ def revoke_all_table(con,sch):
if __name__ == "__main__":
sch_cad = '38_202501'
sch_old = '42_202207'
sch_cad = '26_202504'
sch_old = '38_202501'
grant_all_table(con_cad,sch_cad)
# revoke_all_table(con_cad,sch_old)

27
3_AZALEE/insert_ps.py
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@ -106,7 +106,7 @@ def format_date(df):
df.date = pd.to_datetime(df.date,format='%d%b%Y')
if table == '"PS_BIEVRE_CEN38_2016"':
df.date = df.date.astype(str).replace('\.','',regex=True)
df.date = df.date.astype(str).replace(r'\.','',regex=True)
df.date = df.date.str.rsplit(' ',1).str[0]\
.replace(['avr','mai','juin','juil'],['apr','may','jun','jul'],regex=True)
df.date = pd.to_datetime(df.date,format='%d %b %Y')
@ -541,7 +541,7 @@ def normalize_formatIdsite(id_site):
import re
df = pd.DataFrame({'id_site':id_site})
df['dept'] = '38'
df[['org','num','other']] = [re.split('(\d+)',s) for s in [*df.id_site]]
df[['org','num','other']] = [re.split(r'(\d+)',s) for s in [*df.id_site]]
del df['other']
df.loc[df.num.str.len() == 1,'num'] = '000'+ df.loc[df.num.str.len() == 1,'num']
df.loc[df.num.str.len() == 2,'num'] = '00' + df.loc[df.num.str.len() == 2,'num']
@ -601,7 +601,7 @@ def normalize_pratiques(prat):
p = normalize_paturage(p)
p = p.replace(dic)
p.fillna('N.D', inplace=True)
p[p.str.contains('\?| ou ',na=False)] = 'incertain'
p[p.str.contains(r'\?| ou ',na=False)] = 'incertain'
pp = p.str.split(',',expand=True)
pp.columns = 'p' + pp.columns.astype(str)
for c in pp.columns:
@ -903,7 +903,7 @@ def insert_attrsPS(df,ps_statut='actif'):
del df['pratiques']
for col in params:
df[col] = df[col].astype(str).replace(['\.0'],[''],regex=True)
df[col] = df[col].astype(str).replace([r'\.0'],[''],regex=True)
if 'niv_embrous' in df.columns:
df.niv_embrous.replace(['nan'],['N.D'],inplace=True)
@ -971,9 +971,9 @@ def insert_attrsPS(df,ps_statut='actif'):
def split_codehab(lst_codehab):
lst = lst_codehab.copy()
lst = lst.str.split('x|X|,|&|/|\(|et',expand=True) \
lst = lst.str.split(r'x|X|,|&|/|\(|et',expand=True) \
.stack().str.strip() \
.str.replace('\)','',regex=True)\
.str.replace(r'\)','',regex=True)\
.droplevel(-1).reset_index(drop=False)
return lst
@ -994,7 +994,7 @@ def format_codehab2insert(lst_codehab):
suspect = lst.code_hab.str.split('(',expand=True)
if suspect.shape[1] > 1:
suspect[0] = suspect[0].str.strip()
suspect[1] = suspect[1].str.replace('\)','',regex=True)
suspect[1] = suspect[1].str.replace(r'\)','',regex=True)
suspect.columns = ['code_hab','suspect']
del lst['code_hab']
# raise Exception('habitat suspecté en développement')
@ -1011,7 +1011,7 @@ def insert_cbPS(df):
drop_col = ['auteur','structure']
df = df.copy()
df.date = df.date.astype(str)
df.code_hab = df.code_hab.replace(['\*'],[''],regex=True).str.strip()
df.code_hab = df.code_hab.replace([r'\*'],[''],regex=True).str.strip()
df.code_hab = df.code_hab.replace(['None','nan','0'],[None,None,None])
df.dropna(subset=['code_hab'],inplace=True)
ids = select_ID(df[df.columns.drop(['code_hab',*drop_col])],sch=pycen.ps.schema,tab='r_site_habitat')
@ -1061,7 +1061,7 @@ def insert_habPS(df,ps_statut='actif'):
# df[t] = df[t].astype(str)
df = df.stack().reset_index(-1)
df.columns = ['param','value']
df[['param','index','other']] = [re.split('(\d+)',s) for s in [*df.param]]
df[['param','index','other']] = [re.split(r'(\d+)',s) for s in [*df.param]]
del df['other']
df['index'] = df['index'].astype(int)
df['value'] = df['value'].replace(['-'],[None])
@ -1137,7 +1137,7 @@ def filter_saisierror(df):
tmp.set_index([*cc], inplace=True)
tmp = tmp.stack().reset_index(-1)
tmp.columns = ['param','value']
tmp[['param','index','other']] = [re.split('(\d+)',s) for s in [*tmp.param]]
tmp[['param','index','other']] = [re.split(r'(\d+)',s) for s in [*tmp.param]]
del tmp['other']
tmp['index'] = tmp['index'].astype(int)
tmp['value'] = tmp['value'].replace(['-'],[None])
@ -1180,7 +1180,7 @@ def filter_saisierror(df):
cb = pycen.ref_hab().get_CB()
tmp.code_hab = tmp.code_hab.replace(['\*'],[''],regex=True).str.strip()
tmp.code_hab = tmp.code_hab.replace([r'\*'],[''],regex=True).str.strip()
tmp.code_hab = tmp.code_hab.replace(['0'],[None])
tmp.dropna(subset=['code_hab'], inplace=True)
tmpp = tmp[['id_site','index','code_hab']].copy()
@ -1303,8 +1303,9 @@ if __name__ == "__main__":
]
# from_table = '"cr_ECRIN_habitats_CBNA_2014"'
from_table = None
from_file = 'PS38_modifs_AG_2024.gpkg'
path0 = '/home/colas/Documents/9_PROJETS/2_PS/TO IMPORT/2024/'
from_file = 'PS prioritaire.geojson'
from_tab = 'Tableau_saisie_PS_2026.xlsx'
path0 = '/home/colas/Documents/9_PROJETS/2_PS/TO IMPORT/2026/'
# org = from_file.split('/')[1]
tutu = pd.DataFrame()

142
5_GEONATURE/EXPORT/v_synthese_zones_humides.py
View File

@ -1,9 +1,6 @@
from pycen import con_gn
sql = '''
DROP VIEW IF EXISTS gn_exports.v_synthese_zones_humides;
CREATE VIEW gn_exports.v_synthese_zones_humides AS
sql0 = '''
with habitats as (
SELECT
zh_uuid,
@ -25,8 +22,7 @@ with habitats as (
FROM pr_zh.t_zh
LEFT JOIN pr_zh.cor_zh_lim_fs USING (id_zh)
group by 1 order by 1
), activ_hum AS (
WITH v_activity AS (
), v_activity AS (
SELECT
id_zh,
json_agg(ref_nomenclatures.get_nomenclature_label(cor_impact_types.id_impact)) impacts
@ -34,38 +30,60 @@ with habitats as (
LEFT JOIN pr_zh.cor_impact_list USING (id_impact_list)
LEFT JOIN pr_zh.cor_impact_types USING (id_cor_impact_types)
group by 1 order by 1
)
), activ_hum AS (
SELECT
zh_uuid,
json_agg(json_build_object(
'activite', ref_nomenclatures.get_nomenclature_label(t_activity.id_activity),
'position', ref_nomenclatures.get_nomenclature_label(t_activity.id_position),
'impact', v_activity.impacts,
'rmq_activ', t_activity.remark_activity
)) AS activ_hum
json_agg(CASE WHEN t_activity.id_activity IS NULL
THEN NULL
ELSE json_build_object(
'activite', ref_nomenclatures.get_nomenclature_label(t_activity.id_activity),
'position', ref_nomenclatures.get_nomenclature_label(t_activity.id_position),
'impact', v_activity.impacts,
'rmq_activ', t_activity.remark_activity
)
END) AS activ_hum
FROM pr_zh.t_zh
LEFT JOIN pr_zh.t_activity USING (id_zh)
LEFT JOIN v_activity USING (id_zh)
group by zh_uuid order by 1
--), activ_hum_test AS (
-- SELECT
-- zh_uuid,
-- CASE WHEN t_activity.id_activity IS NOT NULL
-- THEN jsonb_build_object(
-- ref_nomenclatures.get_nomenclature_label(t_activity.id_activity), v_activity.impacts
-- )
-- ELSE NULL
-- END AS activ_hum_test
-- FROM pr_zh.t_zh
-- LEFT JOIN pr_zh.t_activity USING (id_zh)
-- LEFT JOIN v_activity USING (id_zh)
-- --group by zh_uuid order by 1
), inflow as (
SELECT
zh_uuid,
json_agg(json_build_object(
json_agg(CASE WHEN t_inflow.id_inflow IS NULL
THEN NULL
ELSE json_build_object(
'entree_eau', ref_nomenclatures.get_nomenclature_label(t_inflow.id_inflow),
'perm', ref_nomenclatures.get_nomenclature_label(t_inflow.id_permanance),
'topo', t_inflow.topo
)) AS entree_eau
)
END) AS entree_eau
FROM pr_zh.t_zh
LEFT JOIN pr_zh.t_inflow USING (id_zh)
group by zh_uuid
), outflow as (
SELECT
zh_uuid,
json_agg(json_build_object(
'sortie_eau', ref_nomenclatures.get_nomenclature_label(t_outflow.id_outflow),
'perm', ref_nomenclatures.get_nomenclature_label(t_outflow.id_permanance),
'topo', t_outflow.topo
)) AS sortie_eau
json_agg(CASE WHEN t_outflow.id_outflow IS NULL
THEN NULL
ELSE json_build_object(
'sortie_eau', ref_nomenclatures.get_nomenclature_label(t_outflow.id_outflow),
'perm', ref_nomenclatures.get_nomenclature_label(t_outflow.id_permanance),
'topo', t_outflow.topo
)
END) AS sortie_eau
FROM pr_zh.t_zh
LEFT JOIN pr_zh.t_outflow USING (id_zh)
group by zh_uuid
@ -247,11 +265,13 @@ SELECT
zh_uuid,
code,
main_name,
CONCAT(crea_role.nom_role, ' ', crea_role.prenom_role) crea_author,
CONCAT(updt_role.nom_role, ' ', updt_role.prenom_role) updt_author,
bib_org.name organisme,
--concat(crea_role.nom_role, ' ', crea_role.prenom_role) AS crea_author,
--bib_org.name AS organisme,
--concat(updt_role.nom_role, ' ', updt_role.prenom_role) AS updt_author,
bib_org_user_updt.nom_organisme as org_updt,
create_date crea_date,
update_date updt_date,
--ST_TRANSFORM(geom,2154)::geometry(geometry,2154) geom,
geom,
area surface,
rb.river_bassin,
@ -259,27 +279,43 @@ SELECT
zh_area_com.commune,
ref_nomenclatures.get_nomenclature_label(id_sdage) sdage,
ref_nomenclatures.get_nomenclature_label(id_sage) sage,
habitats.habitats,
CASE WHEN habitats.habitats::text = '[null]'
THEN NULL
ELSE habitats.habitats
END AS habitats,
remark_pres descript,
crit_delim.crit_delim,
remark_lim rmq_delilm,
esp_fs.crit_esp_fs,
CASE WHEN esp_fs.crit_esp_fs::text = '[null]'
THEN NULL
ELSE esp_fs.crit_esp_fs
END AS crit_esp_fs,
remark_lim_fs rmq_esp_fs,
ef_area,
v_habref v_hab,
activ_hum.activ_hum,
--ef_area,
--v_habref v_hab,
CASE WHEN activ_hum.activ_hum::text = '[null]'
THEN NULL
ELSE activ_hum.activ_hum::text
END AS activ_hum,
-- activ_hum_test.activ_hum_test,
ref_nomenclatures.get_nomenclature_label(id_thread) bilan_menace,
inflow.entree_eau,
outflow.sortie_eau,
CASE WHEN inflow.entree_eau::text = '[null]'
THEN NULL
ELSE inflow.entree_eau::text
END AS entree_eau,
CASE WHEN outflow.sortie_eau::text = '[null]'
THEN NULL
ELSE outflow.sortie_eau::text
END AS sortie_eau,
ref_nomenclatures.get_nomenclature_label(id_frequency) freq_sub,
ref_nomenclatures.get_nomenclature_label(id_spread) extend_sub,
ref_nomenclatures.get_nomenclature_label(id_connexion) connex,
ref_nomenclatures.get_nomenclature_label(id_diag_hydro) diag_hydro,
ref_nomenclatures.get_nomenclature_label(id_diag_bio) diag_bio,
functions.hydro,
functions.bio,
functions.int_patrim,
functions.val_socio,
functions.hydro::text,
functions.bio::text,
functions.int_patrim::text,
functions.val_socio::text,
remark_eval_functions eval_fcts,
remark_eval_heritage eval_heritage,
remark_eval_thread eval_menace,
@ -293,19 +329,21 @@ SELECT
especes.nb_flora nb_flora_sp,
especes.nb_vertebrates nb_vertebrate_sp,
especes.nb_invertebrates nb_invertebrate_sp,
inventaire.inventaire,
actions.prio_actions,
instrument.instrument,
urba.docs_urba
inventaire.inventaire::text,
actions.prio_actions::text,
instrument.instrument::text,
urba.docs_urba::text
--remark_is_other_inventory
FROM pr_zh.t_zh
JOIN utilisateurs.t_roles crea_role ON t_zh.create_author = crea_role.id_role
LEFT JOIN utilisateurs.t_roles updt_role ON t_zh.update_author = updt_role.id_role
LEFT JOIN utilisateurs.bib_organismes bib_org_user_updt on updt_role.id_organisme = bib_org_user_updt.id_organisme
LEFT JOIN pr_zh.bib_organismes bib_org USING (id_org)
LEFT JOIN habitats USING (zh_uuid)
LEFT JOIN crit_delim USING (zh_uuid)
LEFT JOIN esp_fs USING (zh_uuid)
LEFT JOIN activ_hum USING (zh_uuid)
--LEFT JOIN activ_hum_test USING (zh_uuid)
LEFT JOIN inflow USING (zh_uuid)
LEFT JOIN outflow USING (zh_uuid)
LEFT JOIN functions USING (zh_uuid)
@ -317,11 +355,37 @@ LEFT JOIN actions USING (id_zh)
LEFT JOIN zh_area_com USING (id_zh)
LEFT JOIN dep USING (id_zh)
LEFT JOIN inventaire USING (id_zh)
'''
sql_zh_all = '''
DROP VIEW IF EXISTS gn_exports.v_synthese_zones_humides;
CREATE VIEW gn_exports.v_synthese_zones_humides AS
''' + sql0 + '''
--group BY zh_uuid
WHERE code not like '38CENIS%%'
AND ref_nomenclatures.get_cd_nomenclature(id_sdage)::int > 0
--id_sdage > 0
order by code
;
'''
with con_gn.begin() as cnx:
cnx.execute(sql)
cnx.execute(sql_zh_all)
sql_zh_38 = '''
DROP VIEW IF EXISTS gn_exports.v_synthese_zones_humides_isere;
CREATE VIEW gn_exports.v_synthese_zones_humides_isere AS
''' + sql0 + '''
--group BY zh_uuid
WHERE code not like '38CENIS%%'
AND dep.departement::jsonb @> '"Isère"'
AND ref_nomenclatures.get_cd_nomenclature(id_sdage)::int > 0
order by code
;
'''
with con_gn.begin() as cnx:
cnx.execute(sql_zh_38)

154
5_GEONATURE/pivot_bdc_status_v2.py
View File

@ -24,6 +24,7 @@ def get_status(lst,con):
t.nom_valide,
t.lb_nom,
--s.*
s.cd_sig,
s.rq_statut,
s.code_statut,
s.cd_type_statut,
@ -202,6 +203,54 @@ def get_taxon_status(lst,api):
}
return pd.DataFrame({**phylo,**cd_status})
def filter_bio_geo(df,zone_bio):
idNotBioGeo = []
# Filtre du dommaine biogeographique sur la plaine Rhodanienne et Alpine
test_rhod = df.rq_statut.str.contains('rhodanienne : Non déterminante',na=False)
test_alpi = df.rq_statut.str.contains('Alpine : Non déterminante',na=False)
if zone_bio == 'rhod':
idNotBioGeo = df[test_rhod].index
elif zone_bio == 'alpi':
idNotBioGeo = df[test_alpi].index
elif zone_bio == 'all':
idNotBioGeo = df[test_rhod&test_alpi].index
if not idNotBioGeo.empty:
df.drop(idNotBioGeo, inplace=True)
return df
def form_territoire(df,terr):
is_dep = df.cd_sig.str.contains('INSEED')
dep = (
['38','42','07','26'] if terr == 'platiere' else
['38','69','01'] if terr == 'negria' else ['38']
)
keep_not = df[is_dep&(~df.cd_sig.str[-2:].isin(dep))].index
df.drop(keep_not,inplace=True)
is_dep = df.cd_sig.str.contains('INSEED')
is_38 = df.cd_sig=='INSEED38'
if terr == 'isere':
filter_id = df[is_dep&(~is_38)].index
df.drop(filter_id,inplace=True)
else:
lst_stat = df[is_dep&(~is_38)].cd_type_statut.unique()
# is_lst = df.cd_type_statut.isin(lst_stat)
df.loc[is_dep&(~is_38),'cd_type_statut'] = ( df[is_dep&(~is_38)]
.cd_type_statut + '_' + df[is_dep&(~is_38)].cd_sig.str.strip('INSEED')
)
df.loc[is_38,'cd_type_statut'] = ( df[is_38]
.cd_type_statut + '_38'
)
return df
dict_dep = {
'38':'Isère',
'42':'Loire',
@ -210,6 +259,11 @@ dict_dep = {
}
cols_rename = {
'nom_vernaculaire': 'nom_vern'
}
if __name__ == "__main__":
# Définition de la connection à la bdd GéoNature
from pycen import con_gn
@ -219,19 +273,33 @@ if __name__ == "__main__":
# Paramètres de chargement du fichier des taxons
PATH0 = '/home/cgeier/Téléchargements'
PATH = ''
file = 'CHASS_synthese_observations_2026-01-28.xlsx'
sheet = 'liste sp'
file = 'synthese_observations_2026-04-23.xlsx'
sheet = 'observations'
zone_bio_znieff = 'rhod' # ['rhod', 'alpi', 'all']
territoire = 'negria' # ['isere', 'platiere','negria']
# [GEOMETRY PARAMS]
keep_geomtype = None # ['polygon', 'point', 'ligne', None]
geom_col = 'geometrie_wkt_4326'
# Liste des CD_NOM en entrée
cd_col = 'cd_ref' # Nom de la colonne à utiliser dans le feuillet ``sheet``
cd_col = 'cd_nom' # Nom de la colonne à utiliser dans le feuillet ``sheet``
# Lecture des données
taxlist = pd.read_excel(os.path.join(PATH0,PATH,file),sheet,usecols=[cd_col],header=0)
tab_sp = pd.read_excel(os.path.join(PATH0,PATH,file),sheet,index_col=cd_col)
tab_sp.rename(columns=cols_rename,inplace=True)
# Exclusion d'un type de géométrie
if keep_geomtype is not None:
as_geom = tab_sp[geom_col].str.contains(keep_geomtype.upper(),na=False)
tab_sp = tab_sp[as_geom]
taxlist = taxlist[taxlist.cd_nom.isin(tab_sp.index.tolist())]
lst = taxlist[cd_col]
# Récupération des statuts
df = get_status(taxlist[cd_col].astype(str),con_gn)
df = get_status(taxlist[cd_col].astype(str).unique(),con_gn)
typ = get_type_status(con_gn)
typ = typ[typ.cd_type_statut.isin(df.cd_type_statut.unique())]
@ -241,32 +309,70 @@ if __name__ == "__main__":
df.loc[is_lrr & (df.niveau_admin == 'Ancienne région'),'cd_type_statut'] = 'LRR_RA'
del df['niveau_admin']
for c in ['cd_ref','cd_nom','lb_nom']:
if c in tab_sp.columns:
# if 'cd_nom' not in df.columns and c == 'cd_ref': continue
tab_sp.drop(c,axis=1,inplace=True)
# Filtre du dommaine biogeographique sur la plaine Rhodanienne et Alpine
df = filter_bio_geo(df,zone_bio_znieff)
pivot = pd.pivot_table(
# Filtre des statuts vis à vis du territoire d'intérêts
# Conservation des statuts Adrèche, Drôme et Loire pour la Platière
df = form_territoire(df,territoire)
# for c in ['cd_ref','cd_nom','lb_nom']:
# if c in tab_sp.columns:
# # if 'cd_nom' not in df.columns and c == 'cd_ref': continue
# tab_sp.drop(c,axis=1,inplace=True)
keep_cols = same_col = df.columns[df.columns.isin(tab_sp.reset_index(drop=False).columns)]
as_vern = keep_cols.str.contains('vern').any()
as_numb = keep_cols.str.contains('nombre').any()
if not as_vern:
keep_cols = [*keep_cols,'nom_vern']
if not as_numb:
keep_cols = [*keep_cols,'nombre_min','nombre_max']
else:
same_col = [x for x in keep_cols if x not in ['nombre_min','nombre_max']]
piv = pd.pivot_table(
df,
values='code_statut',
index=['cd_nom', 'cd_ref','lb_nom'#,'niveau_admin','lb_adm_tr'
index=['cd_nom', 'cd_ref','lb_nom','nom_vern'#,'niveau_admin','lb_adm_tr'
],
columns=['cd_type_statut'],
aggfunc=list,fill_value=None)
for c in pivot.columns:
pivot[c] = [x[0] if x is not np.NaN and len(x)==1 else x for x in pivot[c]]
if 'DH' in pivot.columns:
pivot['DH'] = [','.join(x) if (x is not np.NaN) and (len(x)==2) else x for x in pivot['DH']]
pivot.DH.replace({'CDH':''},regex=True,inplace=True)
for c in piv.columns:
piv[c] = [x[0] if x is not np.NaN and len(x)==1 else x for x in piv[c]]
if 'DH' in piv.columns:
piv['DH'] = [','.join(x) if (x is not np.NaN) and (len(x)==2) else x for x in piv['DH']]
piv.DH.replace({'CDH':''},regex=True,inplace=True)
# piv.reset_index(-1, inplace=True)
pivot = tab_sp.merge(pivot,on=[cd_col],how='left')
# tabsp_nb = tab_sp.reset_index(drop=False)[[*same_col,'nombre_min','nombre_max']].groupby([*same_col]).sum()
tabsp_nb = (
tab_sp.reset_index(drop=False)[same_col]
.drop_duplicates()
.merge(
tab_sp.reset_index(drop=False)[[cd_col,'nombre_min','nombre_max','date_debut','date_fin']]
.groupby([cd_col])
.agg({
'nombre_min':'sum',
'nombre_max':'sum',
'date_debut':'min',
'date_fin':'max'
}),
on = cd_col
)
)
tabsp_nb.set_index(cd_col,inplace=True)
tabsp_nb.sort_index(inplace=True)
# pivot = tab_sp.merge(piv,on=[cd_col],how='left')
pivot = tabsp_nb.merge(piv,on=[cd_col],how='left')
pivlib = pd.pivot_table(
df,
values='label_statut',
index=[
'cd_nom', 'cd_ref','lb_nom'#,'niveau_admin','lb_adm_tr'
'cd_nom', 'cd_ref','lb_nom','nom_vern'#,'niveau_admin','lb_adm_tr'
],
columns=['cd_type_statut'],
aggfunc=list,fill_value=None)
@ -276,10 +382,18 @@ if __name__ == "__main__":
pivlib['DH'] = [','.join(x) if (x is not np.NaN) and (len(x)==2) else x for x in pivlib['DH']]
pivlib.DH.replace({'CDH':''},regex=True,inplace=True)
pivlib = tab_sp.merge(pivlib,on=[cd_col],how='left')
# pivlib = tab_sp.merge(pivlib,on=[cd_col],how='left')
pivotlib = tabsp_nb.merge(pivlib,on=[cd_col],how='left')
tx_nb_missing = df[~df.cd_nom.isin(tabsp_nb.index)].shape[0]
if tx_nb_missing > 0:
print('WARNING : %i taxon(s) is MISING !! \n'%tx_nb_missing)
print('INIT writer')
NAME_OUT = os.path.join('~/',sheet+'_status.xlsx')
if keep_geomtype is not None:
NAME_OUT = NAME_OUT[:-5]+' (%s only).xlsx'%keep_geomtype.lower()
with pd.ExcelWriter(NAME_OUT) as writer:
df.to_excel(
writer,sheet_name='v_bdc_status',index=False
@ -291,7 +405,7 @@ if __name__ == "__main__":
)
# writer.save()
print('pivot_table OK !')
pivlib.to_excel(
pivotlib.to_excel(
writer,sheet_name='pivot_libel'
)
# writer.save()
@ -301,3 +415,5 @@ if __name__ == "__main__":
)
# writer.save()
print('dic_type_statut OK !')
print('END writing %s'%NAME_OUT)