56 lines
1.4 KiB
Python
56 lines
1.4 KiB
Python
import pandas as pd
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def parse_above_loc(content):
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row = {}
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try:
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app, loc = content.split("\n")
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except ValueError:
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row["lot"] = ""
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row["type"] = ""
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row["locataire"] = content
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else:
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app_ = app.split(" ")
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row["lot"] = app_[1]
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row["type"] = " ".join(app_[2:])
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row["locataire"] = loc
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return pd.Series(row)
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def extract_situation_loc(table, mois, annee):
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"""From pdfplumber table extract locataire df"""
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try:
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df = pd.DataFrame(table[1:], columns=table[0])
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except IndexError:
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print(table)
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rows = []
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for i, row in df[df["Locataires"] == "Totaux"].iterrows():
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above_row_loc = df.iloc[i - 1]["Locataires"]
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up_row = pd.concat(
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[
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row,
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parse_above_loc(above_row_loc),
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]
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)
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rows.append(up_row)
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df_cleaned = pd.concat(rows, axis=1).T
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df_cleaned.drop(["Locataires", "", "Période"], axis=1, inplace=True)
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df_cleaned = df_cleaned.astype(
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{
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"Loyers": "float64",
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"Taxes": "float64",
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"Provisions": "float64",
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"Divers": "float64",
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"Total": "float64",
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"Réglés": "float64",
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"Impayés": "float64",
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},
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errors="ignore",
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)
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df_cleaned = df_cleaned.assign(mois=mois, annee=annee)
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return df_cleaned
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