Sängerlust 2023

sandbox/starmoney.py

@@ -2,43 +2,63 @@ import pandas as pd
 import numpy as np
 from pathlib import Path
 
-year = '2022'
-export_dir = f'/home/robert/Dropbox/Jugendchor 2000/Kasse/{year}/Export'
-kst = {'3115532': '0', '3123981': '1', '3124005': '2', '3123999': '3', '3124039': '4', '3123973': '5', '3124013': '6'}
-from_label = ['Buchungstag', 'Internet', 'Verwendungszweckzeile 1', 'Kommentar', 'KST',
-              'Verwendungszweckzeile 3', 'Verwendungszweckzeile 4', 'Verwendungszweckzeile 5',
-              'row_num', 'Einnahmen', 'Ausgaben']
-to_label = ['Datum', 'frei', 'Vorgang', 'Konto', 'KST', 'Nr.', 'Einnahmen_Kasse', 'Ausgaben_Kasse', 'Nr.', 'Einnahmen', 'Ausgaben']
+year = "2023"
+export_dir = f"/home/robert/Nextcloud/Sängerlust Hausen/Kasse/{year}/Export"
+kst = {"3115532": "0", "3123981": "1", "3124005": "2", "3123999": "3", "3124039": "4", "3123973": "5", "3124013": "6"}
+from_label = [
+    "Buchungstag",
+    "Internet",
+    "Verwendungszweckzeile 1",
+    "Kommentar",
+    "KST",
+    "Verwendungszweckzeile 3",
+    "Verwendungszweckzeile 4",
+    "Verwendungszweckzeile 5",
+    "row_num",
+    "Einnahmen",
+    "Ausgaben",
+]
+to_label = [
+    "Datum",
+    "frei",
+    "Vorgang",
+    "Konto",
+    "KST",
+    "Nr.",
+    "Einnahmen_Kasse",
+    "Ausgaben_Kasse",
+    "Nr.",
+    "Einnahmen",
+    "Ausgaben",
+]
 
 
 def import_csv(filename):
-    kto = filename.name.split('_')[0]
-    print(kto + ': ' + kst[kto])
-    df: pd.DataFrame = pd.read_csv(filename, sep=';', decimal=',', encoding='utf-8', index_col=['IBAN', 'Laufende Nummer']).reset_index()
-    df['Einnahmen'] = np.where(df['Betrag'] > 0, df['Betrag'], 0)
-    df['Ausgaben'] = np.where(df['Betrag'] < 0, 0 - df['Betrag'], 0)
-    df['KST'] = kst[kto]
-    first_saldo = df.loc[0]['Saldo'] - df.loc[0]['Betrag']
-    last_saldo = df.loc[len(df) - 1]['Saldo']
-    df = df[df['Betrag'] != 0]
-    df['row_num'] = np.arange(1, len(df) + 1)
+    kto = filename.name.split("_")[0]
+    print(kto + ": " + kst[kto])
+    df: pd.DataFrame = pd.read_csv(
+        filename, sep=";", decimal=",", encoding="utf-8", index_col=["IBAN", "Laufende Nummer"]
+    ).reset_index()
+    df["Einnahmen"] = np.where(df["Betrag"] > 0, df["Betrag"], 0)
+    df["Ausgaben"] = np.where(df["Betrag"] < 0, 0 - df["Betrag"], 0)
+    df["KST"] = kst[kto]
+    first_saldo = df.loc[0]["Saldo"] - df.loc[0]["Betrag"]
+    last_saldo = df.loc[len(df) - 1]["Saldo"]
+    df = df[df["Betrag"] != 0]
+    df["row_num"] = np.arange(1, len(df) + 1)
     df = df[from_label]
     print(df.shape)
-    first_row = [f'01.01.{year}', '', 'Anfangsbestand - SLS ' + kto, 'AB', kst[kto], '', '', '', 0, first_saldo, 0]
-    last_row = [f'31.12.{year}', '', 'Endbestand - SLS ' + kto, 'EB', kst[kto], '', '', '', len(df) + 1, 0, last_saldo]
-    df = pd.concat([
-        pd.DataFrame([first_row], columns=from_label),
-        df,
-        pd.DataFrame([last_row], columns=from_label)
-    ])
+    first_row = [f"01.01.{year}", "", "Anfangsbestand - SLS " + kto, "AB", kst[kto], "", "", "", 0, first_saldo, 0]
+    last_row = [f"31.12.{year}", "", "Endbestand - SLS " + kto, "EB", kst[kto], "", "", "", len(df) + 1, 0, last_saldo]
+    df = pd.concat([pd.DataFrame([first_row], columns=from_label), df, pd.DataFrame([last_row], columns=from_label)])
     print(df.shape)
     return df
 
 
-df = [import_csv(f) for f in Path(export_dir).glob('*.csv')]
+df = [import_csv(f) for f in Path(export_dir).glob("*.csv")]
 df_union: pd.DataFrame = pd.concat(df)
 print(df_union.shape)
 
 
 df_union = df_union.rename(columns=dict(zip(from_label, to_label)))
-df_union.to_csv(export_dir + '/export.csv.txt', sep=';', decimal=',', encoding='latin-1', index=False)
+df_union.to_csv(export_dir + "/export.csv.txt", sep=";", decimal=",", encoding="latin-1", index=False)