Script Python permettant de nettoyer et préparer nos données csv.
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70 lines
2.2 KiB

#Importation des données dont nous aurons besoin
from typing import List
import pandas as pd
import numpy as np
import requests
import csv
import re
#Afficher les tableaux de données
datafram : pd.read_csv("C:\\Users\\luigg\\Data_cleaning\\Table_final.csv")
datafram.head(5)
#Supprimer les colonnes inutilisées ou non pertinentes
to_drop : [''identifiant
','adresse
','commune
','coordonnees_x
','coordonnees_y
','code_epsg
','code_ape
','libelle_ape
','code_eprtr
','libelle_eprtr
','sigleUniteLegale_imp
','activitePrincipaleUniteLegale_imp
','Catégorie_entreprise_imp
','numeroVoieEtablissement_imp
','typeVoieEtablissement_imp
','libelleVoieEtablissement_imp
','libelleCommuneEtablissement_imp
','codeCommuneEtablissement_imp
','adresse_imp
','geo_imp
','com_code_imp
','code_commune_imp
','Code Officiel_EPCI_imp
','Code_Officiel_region_imp
','codenaffix_imp
','Intitule_NAF_imp
','groupe_imp
','division_imp
','nom_etablissement_tndan
','code_operation_eliminatio_valorisation_tndan
','libelle_operation_eliminatio_valorisation_tndan
','code_departement_tndan
','pays_tndan
','pays_pdan
','code_dechet_pdan
','libelle_dechet_pdan
','quantite_pdan
','unite_pdan
','code_operation_eliminatio_valorisation_pndan
','libelle_operation_eliminatio_valorisation_pndan
','code_departement_pndan
','pays_pndan
','code_dechet_pndan
','libelle_dechet_pndan
','quantite_pndan
','unite_pndan
','code_operation_eliminatio_valorisation_tdan
','libelle_operation_eliminatio_valorisation_tdan
','code_departement_tdan
','pays_tdan
','code_dechet_tdan
','libelle_dechet_tdan
']
datafram.drop(to_drop, inplace = True, axis = 1)
datafram.head(5)