Revision of BC100 Fahrgastrechte

1 file changed, 3 insertions, 2 deletions

bc100_fgr.py

			@@ -4,10 +4,11 @@ import re
4	4		from datetime import datetime, date, timedelta
5	5
6	6		BC_START_DATE = date(2025, 3, 6)
	7	+	FGR_AVERAGE_PROCESSING_TIME = timedelta(days=5)
7	8		PRICE = 2988.00
8	9		FILENAME = "Transaktionen.csv"
9	10
10		-	TODAY = date.today()
	11	+	TODAY = date.today() - FGR_AVERAGE_PROCESSING_TIME
11	12		BC_END_DATE = BC_START_DATE + timedelta(days=365)
12	13
13	14		def parse_journey_date(value):
			@@ -34,7 +35,7 @@ df = df[
34	35		]
35	36
36	37		current_amount = df["Betrag"].sum()
37		-	bc_use_percentage= ((BC_END_DATE - TODAY).days / 365)
	38	+	bc_use_percentage= ((TODAY - BC_START_DATE).days / 365)
38	39		max_amount = bc_use_percentage * PRICE * 0.25
39	40
40	41		effective_price = PRICE - (current_amount * (1 / bc_use_percentage))

1 file changed, 10 insertions, 1 deletion

bc100_fgr.py

			@@ -1,4 +1,5 @@
1	1		import pandas as pd
	2	+	import re
2	3
3	4		from datetime import datetime, date, timedelta
4	5
			@@ -9,6 +10,11 @@ FILENAME = "Transaktionen.csv"
9	10		TODAY = date.today()
10	11		BC_END_DATE = BC_START_DATE + timedelta(days=365)
11	12
	13	+	def parse_journey_date(value):
	14	+	match = re.search(r"Bahnreise am (\d{1,2}\.\d{1,2}\.\d{4})", str(value))
	15	+	if match:
	16	+	return datetime.strptime(match.groups()[0], "%d.%m.%Y").date()
	17	+
12	18		df = pd.read_csv(
13	19		FILENAME,
14	20		converters={
			@@ -17,11 +23,14 @@ df = pd.read_csv(
17	23		}
18	24		)
19	25
	26	+	df["Reisedatum"] = df["Verwendungszweck"].map(parse_journey_date)
	27	+
20	28		df = df[
21	29		(df["Zahlungsempfänger"] == "Deutsche Bahn") &
22	30		(df["Verwendungszweck"].str.contains("Fahrgastrechtsfall", case=False)) &
23	31		(df["Betrag"] == 10) &
24		-	(df["Buchungsdatum"] >= BC_START_DATE)
	32	+	(df["Buchungsdatum"] > BC_START_DATE) &
	33	+	(df["Reisedatum"] >= BC_START_DATE)
25	34		]
26	35
27	36		current_amount = df["Betrag"].sum()

1 file changed, 13 insertions, 4 deletions

bc100_fgr.py

			@@ -25,10 +25,19 @@ df = df[
25	25		]
26	26
27	27		current_amount = df["Betrag"].sum()
28		-	max_amount = round(((BC_END_DATE - TODAY).days / 365) * PRICE * 0.25, 2)
	28	+	bc_use_percentage= ((BC_END_DATE - TODAY).days / 365)
	29	+	max_amount = bc_use_percentage * PRICE * 0.25
29	30
30		-	print("{:.2f} € von {:.2f} € ({}%)".format(
31		-	df["Betrag"].sum(),
	31	+	effective_price = PRICE - (current_amount * (1 / bc_use_percentage))
	32	+
	33	+	print("Fahrgastrechte: {:.2f}€ von {:.2f}€ ({:.0f}%)".format(
	34	+	current_amount,
32	35		max_amount,
33		-	round((current_amount / max_amount) * 100)
	36	+	(current_amount / max_amount) * 100
34	37		))
	38	+
	39	+	print("Effektiver Preis der BC100 wird statt {:.2f}€ {:.2f}€ sein ({:.0f}% Rabatt)".format(
	40	+	PRICE,
	41	+	effective_price,
	42	+	(1 - (effective_price / PRICE)) * 100
	43	+	))

1 file changed, 34 insertions

bc100_fgr.py(file created)

		@@ -0,0 +1,34 @@
1	+	import pandas as pd
2	+
3	+	from datetime import datetime, date, timedelta
4	+
5	+	BC_START_DATE = date(2025, 3, 6)
6	+	PRICE = 2988.00
7	+	FILENAME = "Transaktionen.csv"
8	+
9	+	TODAY = date.today()
10	+	BC_END_DATE = BC_START_DATE + timedelta(days=365)
11	+
12	+	df = pd.read_csv(
13	+	FILENAME,
14	+	converters={
15	+	"Betrag": lambda x: float(x.replace(",", ".")),
16	+	"Buchungsdatum": lambda x: datetime.strptime(x, "%d.%m.%Y").date()
17	+	}
18	+	)
19	+
20	+	df = df[
21	+	(df["Zahlungsempfänger"] == "Deutsche Bahn") &
22	+	(df["Verwendungszweck"].str.contains("Fahrgastrechtsfall", case=False)) &
23	+	(df["Betrag"] == 10) &
24	+	(df["Buchungsdatum"] >= BC_START_DATE)
25	+	]
26	+
27	+	current_amount = df["Betrag"].sum()
28	+	max_amount = round(((BC_END_DATE - TODAY).days / 365) * PRICE * 0.25, 2)
29	+
30	+	print("{:.2f} € von {:.2f} € ({}%)".format(
31	+	df["Betrag"].sum(),
32	+	max_amount,
33	+	round((current_amount / max_amount) * 100)
34	+	))

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