Feat: rename first column of charges
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1153931b7f
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@ -22,6 +22,7 @@ def extract_charge(table):
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.replace("", np.nan)
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.replace("", np.nan)
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.dropna(subset=["Débits", "Crédits"], how="all")
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.dropna(subset=["Débits", "Crédits"], how="all")
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)
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)
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drop_index = df[
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drop_index = df[
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df["RECAPITULATIF DES OPERATIONS"].str.contains("TOTAUX", case=False)
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df["RECAPITULATIF DES OPERATIONS"].str.contains("TOTAUX", case=False)
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| df["RECAPITULATIF DES OPERATIONS"].str.contains("Solde créditeur", case=False)
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| df["RECAPITULATIF DES OPERATIONS"].str.contains("Solde créditeur", case=False)
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@ -50,14 +51,18 @@ def extract_charge(table):
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}
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}
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)
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)
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df.columns.values[0] = "Fournisseur"
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return df
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return df
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def extract_remise_com(table):
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def extract_remise_com(table):
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"""Extract "remise commercial" from first page"""
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"""Extract "remise commercial" from first page"""
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df = pd.DataFrame(table[1:], columns=table[0]).replace("", np.nan)
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df = pd.DataFrame(table[1:], columns=table[0]).replace("", np.nan)
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return df[
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df = df[
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df["RECAPITULATIF DES OPERATIONS"].str.contains(
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df["RECAPITULATIF DES OPERATIONS"].str.contains(
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"Remise commerciale gérance", case=False, na=False
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"Remise commerciale gérance", case=False, na=False
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)
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)
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]
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]
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df.columns.values[0] = "Fournisseur"
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return df
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