From e957b821a0538d4fce4715b41911b1fd011e133b Mon Sep 17 00:00:00 2001
From: patha <patha99@yahoo.de>
Date: Sun, 1 Dec 2024 17:49:02 +0100
Subject: [PATCH] Erstellung

---
 ghostfolio_conversion.py | 118 +++++++++++++++++++++++++++++++++++++++
 1 file changed, 118 insertions(+)
 create mode 100644 ghostfolio_conversion.py

diff --git a/ghostfolio_conversion.py b/ghostfolio_conversion.py
new file mode 100644
index 0000000..11f7b11
--- /dev/null
+++ b/ghostfolio_conversion.py
@@ -0,0 +1,118 @@
+# Dieses Skript liest die von Easybank exportierten .csv-Dateien ein und konvertiert sie zu Ghostfolio-kompatiblen .csv-Dateien
+
+import pandas
+import csv
+
+# Datei einlesen
+file = input('Name of Input-File (without .csv): ') + ".csv"
+
+# Header und Datenzeile für Ghostfolio.csv anlegen
+header = ['Date','Code','DataSource','Currency','Price','Quantity','Action','Fee','accountId']
+data = [None,None,'YAHOO','EUR',None,'1','dividend','0.00','3054673f-165a-4302-b340-8133a1667e80']
+
+# Bankauszug (ohne Header) in Dataframe schreiben
+raw_df = pandas.read_csv(file, sep=';', header=None)
+
+# Nichtbenötigte Spalten entfernen
+df = raw_df.drop(raw_df.columns[[0,3,5]], axis=1)
+
+# Header für Importfile schreiben
+with open('ghostfolio_import.csv', 'a', encoding='UTF8', newline='') as f:
+        writer = csv.writer(f)
+        writer.writerow(header)
+
+# Durch alle Zeilen der Ausgangsdatei durchiterieren und dann Zeile passend in Importfile schreiben
+for i in range(df.shape[0]):
+    # Aktiencode feststellen
+    # Altlasten
+    if 'TELENOR' in str((df.iloc[i, 0])):
+        data[1] = "TEQ.F"
+    elif 'WOODSIDE' in str((df.iloc[i, 0])):
+        data[1] = "WOP0.F" 
+    elif 'SHELL' in str((df.iloc[i, 0])):
+        data[1] = "R6C0.F"
+    elif 'HSBC' in str((df.iloc[i, 0])):
+        data[1] = "HBC2.F"
+    elif 'CIBC' in str((df.iloc[i, 0])):
+        data[1] = "CAI.F"
+    elif 'SCOTIA' in str((df.iloc[i, 0])):
+        data[1] = "BKN.F"
+    elif 'BARRATT' in str((df.iloc[i, 0])):
+        data[1] = "3BA.F"
+    elif 'WOODSIDE' in str((df.iloc[i, 0])):
+        data[1] = "WOP0.F"
+    elif 'CNOOC' in str((df.iloc[i, 0])):
+        data[1] = "NC2B.F"
+    elif 'VOEST' in str((df.iloc[i, 0])):
+        data[1] = "VAS.F"
+    elif 'STARBUCKS' in str((df.iloc[i, 0])):
+        data[1] = "SRB.F"
+    elif 'SOUTH' in str((df.iloc[i, 0])):
+        data[1] = "32Z.F"
+    elif 'PHILIPS' in str((df.iloc[i, 0])):
+        data[1] = "PHIA.F"                 
+    # Portfolio
+    elif 'ABBVIE' in str((df.iloc[i, 0])):
+        data[1] = "4AB.F"
+    elif 'RTX' in str((df.iloc[i, 0])):
+        data[1] = "5UR.F"
+    elif 'MERCK' in str((df.iloc[i, 0])):
+        data[1] = "6MK.F"
+    elif 'ORGANON' in str((df.iloc[i, 0])):
+        data[1] = "7XP.F"
+    elif 'AIRBUS' in str((df.iloc[i, 0])):
+        data[1] = "AIR.F"
+    elif 'BHP' in str((df.iloc[i, 0])):
+        data[1] = "BHP1.F"
+    elif 'CATERPILLAR' in str((df.iloc[i, 0])):
+        data[1] = "CAT1.F"
+    elif 'COCA-COLA' in str((df.iloc[i, 0])):
+        data[1] = "CCC3.F"
+    elif 'CISCO' in str((df.iloc[i, 0])):
+        data[1] = "CIS.F"
+    elif 'DEUTSCHE POST' in str((df.iloc[i, 0])):
+        data[1] = "DHL.F"
+    elif 'JOHNSON + JOHNSON' in str((df.iloc[i, 0])):
+        data[1] = "JNJ.F"
+    elif 'KRAFT HEINZ' in str((df.iloc[i, 0])):
+        data[1] = "KHNZ.F"
+    elif 'LEGAL' in str((df.iloc[i, 0])):
+        data[1] = "LGI.F"
+    elif 'LOCKHEED MARTIN' in str((df.iloc[i, 0])):
+        data[1] = "LOM.F"
+    elif 'MERCEDES-BENZ' in str((df.iloc[i, 0])):
+        data[1] = "MBG.F"
+    elif 'MCDONALDS' in str((df.iloc[i, 0])):
+        data[1] = "MDO.F"
+    elif '3M' in str((df.iloc[i, 0])):
+        data[1] = "MMM.F"
+    elif 'PFIZER' in str((df.iloc[i, 0])):
+        data[1] = "PFE.F"
+    elif 'RHEINMETALL' in str((df.iloc[i, 0])):
+        data[1] = "RHM.F"
+    elif 'DISTRI' in str((df.iloc[i, 0])):
+        data[1] = "RYE.F"
+    elif 'ROYAL' in str((df.iloc[i, 0])):
+        data[1] = "RYE.F"
+    elif 'SIEMENS' in str((df.iloc[i, 0])):
+        data[1] = "SIE.F"
+    elif 'AT + T' in str((df.iloc[i, 0])):
+        data[1] = "SOBA.F"
+    elif 'UNILEVER' in str((df.iloc[i, 0])):
+        data[1] = "UNVA.F"
+    elif 'BANK OF CHINA' in str((df.iloc[i, 0])):
+        data[1] = "W8V.F"
+    else:
+        data[1] = "MISSING"
+    
+    # Datum feststellen
+    data[0] = str((df.iloc[i, 1]))
+    #Dividende feststellen
+    dividend = str(df.iloc[i, 2]).replace('+', '').replace(',', '.')
+    data[4] = float(dividend)
+
+    # Daten-Zeile in Import-File schreiben
+    with open('ghostfolio_import.csv', 'a', encoding='UTF8', newline='') as f:
+        writer = csv.writer(f)
+        writer.writerow(data)
+