diff --git a/5_GEONATURE/pivot_bdc_status_v2.py b/5_GEONATURE/pivot_bdc_status_v2.py
index fb0d8a1..ba7c068 100644
--- a/5_GEONATURE/pivot_bdc_status_v2.py
+++ b/5_GEONATURE/pivot_bdc_status_v2.py
@@ -20,26 +20,42 @@ def get_status(lst):
             t.nom_valide,
             t.lb_nom,
             --s.*
+            s.rq_statut,
             s.code_statut,
             s.cd_type_statut,
-            s.label_statut
-        FROM taxonomie.v_taxref_all_listes t
+            s.label_statut,
+            s.full_citation,
+            s.doc_url
+        FROM taxonomie.taxref t
         JOIN taxonomie.v_bdc_status s USING (cd_nom)
         WHERE t.cd_nom IN {cd_nom}
     ;""".format(cd_nom = tuple(lst))
     return pd.read_sql_query(sql,con_gn)
+
+dict_dep = {
+    '38':'Isère',
+    '42':'Loire',
+    '07':'Ardèche',
+    '26':'Drôme',
+}
     
 
 if __name__ == "__main__":
 
-    PATH = '/media/colas/Disk2/tmp/NICO'
-    file = 'MAIR_FAUNE&FLORE_PG2024_V0.xlsx'
-    sheet = 'MAIR_FLORE'
+    PATH = '/media/colas/SRV/FICHIERS/SITES/SITES GERES/ROLA_ROLANDE-MAUPAS/ROLA_PPI/ROLA_2025-2034_PG/donneesnaturalistes'
+    file = 'liste sp_ROLA.xlsx'
+    sheet = 'liste sp'
 
     # Liste des CD_NOM en entrée
-    taxlist = pd.read_excel(os.path.join(PATH,file),sheet,usecols=['cd_nom'],header=1)
-    df = get_status(taxlist.cd_nom.astype(str))
+    cd_col = 'cd_ref'
+    taxlist = pd.read_excel(os.path.join(PATH,file),sheet,usecols=[cd_col],header=0)
+    tab_sp = pd.read_excel(os.path.join(PATH,file),sheet,index_col=cd_col)
+    df = get_status(taxlist[cd_col].astype(str))
 
+    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)
 
     # df.to_csv('/media/colas/SRV/FICHIERS/TRANSFERTS-EQUIPE/LC/BOCA_CD_NOM_STATUS.csv')
 
@@ -57,6 +73,8 @@ if __name__ == "__main__":
         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)
 
+    pivot = tab_sp.merge(pivot,on=[cd_col],how='left')
+
 
     pivlib = pd.pivot_table(
         df,
@@ -71,12 +89,13 @@ 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')
 
     print('INIT writer')
     NAME_OUT = os.path.join(PATH,sheet+'_status.xlsx')
     with pd.ExcelWriter(NAME_OUT) as writer:
         df.to_excel(
-            writer,sheet_name='v_bdc_status'
+            writer,sheet_name='v_bdc_status',index=False
             )
         # writer.save()
         print('v_bdc_status OK !')