import pandas as pd
import os

# Preprocess data
vote_counter = -1
data = pd.DataFrame()

name_column = 'Bezeichnung'

column_to_filename = {}

voting_features = ['ja', 'nein', 'Enthaltung', 'ungültig']
for dirname, _, filenames in os.walk('./de/csv'):
    for filename in filenames:
        vote_counter += 1
        print(os.path.join(dirname, filename))
        df = pd.read_csv(os.path.join(dirname, filename))
        
        # Give each voting behaviour type an identifier from 0 to len(voting_features) - 1
        for i, feature in enumerate(voting_features):
            df[feature] *= i
        vote_column_name = f'vote_{vote_counter}'
        # Map column name of vote to filename -> allows retrieving what the vote was about
        column_to_filename[vote_column_name] = filename
        
        # add feature for the vote
        df[vote_column_name] = df[voting_features].sum(axis=1)
        
        if data.empty:
            # if first file that is loaded set data equal to data from first file
            data = df[[name_column, vote_column_name]]
        else:
            # merge data with already loaded data 
            data = data.merge(df[[name_column, vote_column_name]], on=name_column)

print(column_to_filename)
print(data)