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- 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)
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