import pandas as pd
import os
import numpy as np
from tqdm import tqdm

# def get_rank(stat, week, name, df_group):
#     df_group_name_list = df_group.loc[df_group['week'] == week][name].tolist()
#     df_group_name_list = sorted(df_group_name_list, reverse=True)
#     # return [round(df_group_name_list.index(stat)/len(df_group_name_list), 3) , df_group_name_list.index(stat)+1, len(df_group_name_list)]
#     if len(df_group_name_list) == 0:
#         return [np.nan, np.nan, np.nan]
#     if stat == 0:
#         return [round(0/len(df_group_name_list), 3) , 0, len(df_group_name_list)]
#     for i, v in enumerate(df_group_name_list):
#         if stat >= v:
#             return [round(i/len(df_group_name_list), 3) , i+1, len(df_group_name_list)]


if __name__ == '__main__':
    vin_list = os.listdir('./dataframes/')
    for name in ['charge', 'drive']:
        df_stats = pd.DataFrame()
        for vin in tqdm(vin_list):
            group_list = os.listdir(f'./dataframes/{vin}/{name}/')
            # df_charge_vin = pd.read_csv(f'./dataframes/{vin}/{name}/{vin}.csv')
            df_group = pd.DataFrame()
            for group in group_list:
                # df_group = pd.read_csv(f'./dataframes/{vin}/charge/{group}')
                df_group = pd.concat([df_group, pd.read_csv(f'./dataframes/{vin}/{name}/{group}')])
            
            df_group_week_list = list(df_group.groupby('week'))
            df_group = pd.DataFrame()
            for week, df_group_week in df_group_week_list:
                # check if df_group_week has zero values, if so, replace them with np.nan
                df_group_week_0 = df_group_week[df_group_week.columns[3:]].replace(0, np.nan)
                df_group_week_rank = df_group_week_0.rank(axis=0, method='min', ascending=False).fillna(0).astype(int)
                # rename the columns of df_group_week_rank by adding '_rank' to the original column names
                df_group_week_rank.columns = [f'{col}_rank' for col in df_group_week_rank.columns]

                # merge df_group_week and df_group_week_rank                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    
                df_group_week = pd.concat([df_group_week, df_group_week_rank], axis=1)
                df_group = pd.concat([df_group, df_group_week])
            
            
            df_group.to_csv(f'./{name}/group_{vin}.csv', index=False)
        #     df_stats = pd.concat([df_stats, df_charge_vin])
        # df_stats.to_csv(f'./{name}_rank.csv', index=False)