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Add NAF name and NAF code #7

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Add NAF name and NAF code #7

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6 changes: 4 additions & 2 deletions parse.py
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Original file line number Diff line number Diff line change
Expand Up @@ -145,8 +145,8 @@ def save(self, path):
emissions.to_csv(path + 'emissions.csv', index=False, encoding='UTF-8')

assessments = pd.DataFrame(self.collections['assessments'])
assessments = assessments[['id', 'organization_name', 'organization_description', 'organization_type',
'collectivity_type', 'staff', 'population', 'consolidation_method', 'reporting_year',
assessments = assessments[['id', 'organization_name', 'organization_description', 'organization_type', 'collectivity_type',
'naf_name', 'naf_code', 'staff', 'population', 'consolidation_method', 'reporting_year',
'total_scope_1', 'total_scope_2', 'total_scope_3',
'reference_year', 'action_plan',
'reductions_scope_1_2', 'reductions_scope_1', 'reductions_scope_2', 'reductions_scope_3',
Expand Down Expand Up @@ -260,6 +260,8 @@ def save(self):
'legal_unit_id_type': 'SIREN',
'legal_unit_id': match.groups()[0],
})
assessment['naf_name']= match.groups()[1]
assessment['naf_code']= match.groups()[2]
else:
print('ERROR: Invalid legal unit string format "%s".' % line)
del assessment['legal_units']
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2 changes: 2 additions & 0 deletions readme.md
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Expand Up @@ -78,6 +78,8 @@ Le fichier **assessments.csv** (ou l'onglet **assessments** du fichier Excel) d
* `organization_description` : description libre de l'organisation,
* `organization_type` : type d'organisation,
* `collectivity_type` : type de collectivité (pour les collectivités territoriales),
* `naf_name`: nom de l’activité principale exercée selon la nomenclature INSEE
* `naf_code`: code de l’activité principale exercée selon la nomenclature INSEE
* `staff` : effectifs, nombre d'agents ou de salariés de l'organisation,
* `population` : population de la collectivité (pour les collectivités territoriales),
* `consolidation_method` : mode de consolidation du bilan,
Expand Down