pdf_auralia/pdf_oralia/extract_charge.py

import logging

import numpy as np
import pandas as pd


def extract_charge(table):
    """From pdfplumber table extract the charge dataframe"""
    df = (
        pd.DataFrame(table[1:], columns=table[0])
        .replace("", np.nan)
        .dropna(subset=["Débits"])
    )
    drop_index = df[
        df["RECAPITULATIF DES OPERATIONS"].str.contains("TOTAUX", case=False)
        | df["RECAPITULATIF DES OPERATIONS"].str.contains("solde", case=False)
    ].index
    df.drop(drop_index, inplace=True)

    df[""].mask(
        df["RECAPITULATIF DES OPERATIONS"].str.contains("honoraires", case=False),
        "IMI GERANCE",
        inplace=True,
    )

    df = df.astype(
        {
            "Débits": "float64",
            "Crédits": "float64",
            "Dont T.V.A.": "float64",
            "Locatif": "float64",
            "Déductible": "float64",
        }
    )

    return df