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- import pandas as pd
- from functools import reduce
- source_csv = 'data\\Kontenrahmen_Import.csv'
- target_csv = 'data\\Kontenrahmen.csv'
- result_csv = 'data\\Kontenrahmen_Ergebnis.csv'
- debug = False
- cols_pkey = ['Konto_Nr']
- def update(d, other):
- d.update(dict(dict(other)))
- return d
- def get_dict(cols, type):
- return dict(dict(zip(cols, [type] * len(cols))))
- # cols_dict = reduce(update, (get_dict(cols_pkey, np.str), get_dict(cols_str, np.str), get_dict(cols_float, np.float)), {})
- df_source = pd.read_csv(source_csv, decimal=",", sep=";", encoding="ansi", converters={i: str for i in range(0, 200)})
- df_source['pkey'] = reduce(lambda x, y: x + "_" + df_source[y], cols_pkey, "")
- df_source = df_source.set_index('pkey')
- df_target = pd.read_csv(target_csv, decimal=",", sep=";", encoding="ansi", converters={i: str for i in range(0, 200)})
- target_columns = df_target.columns
- df_target['pkey'] = reduce(lambda x, y: x + "_" + df_target[y], cols_pkey, "")
- df_target = df_target.set_index('pkey')
- df_join = df_source.join(df_target, rsuffix='_other')[target_columns]
- # df_result = df_join[(df_join['Gesamt'] != 0) & (df_join['Serviceberater'] != "")]
- df_join.to_csv(result_csv, decimal=",", sep=";", encoding="ansi", index=None)
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