Files
2025-07-30 15:57:48 +02:00

23 lines
804 B
Python

import pandas as pd
def clean_mieten(file_path,cleaned_file_path):
df = pd.read_csv(file_path, delimiter=';', encoding='ISO-8859-1')
df.columns = [
'land', 'mieten_ab_2019', 'mieten_insgesamt'
]
df['land'] = df['land'].str.encode('ISO-8859-1').str.decode('utf-8')
df['mieten_ab_2019'] = pd.to_numeric(df['mieten_ab_2019'], errors='coerce').astype('float')
df['mieten_insgesamt'] = pd.to_numeric(df['mieten_insgesamt'], errors='coerce').astype('float')
df['land'] = df['land'].str.replace('"', '')
df.to_csv(cleaned_file_path, index=False)
return df
mieten_file_path = 'data/source/nettokaltmieten.csv'
mieten_cleaned_file_path = 'data/preprocessed/cleaned_mieten.csv'
cleaned_mieten_df = clean_mieten(mieten_file_path, mieten_cleaned_file_path)