def main(args): # road_to_area = {} # func_road_to_area(args, road_to_area) df = pd.read_csv(env.get_full_path(read_dir_name, args), names=env.get_col_names(), encoding='Shift_JISx0213') # df = df.dropna(how='all') df = df.apply(lambda x: extract_only_area(x), axis=1) # df.iloc[:, 3:] = df.iloc[:, 3:].applymap(lambda x: road_to_area[x]) # df = df[df.loc[:, 'c03'] >= 0] # dfT = df.T # dfT = dfT.apply(remove_and_fill_none_area) # df = dfT.T # df.reset_index(drop=True, inplace=True) # # df = pd.concat([df_id, df], axis=1) # df = df.rename(columns={'c00': 'id'}) # df = df.sort_values(['id']) # df = df.drop(['c01', 'c02'], axis=1) # # df.replace(' ', np.NaN, inplace=True) # df.dropna(how='all', axis=1, inplace=True) df = df.applymap(lambda x: (x.split('(census)')[0]) if (type(x) is str) and ('(census)' in x) else x) for _area in env.get_area_list(): df_area = create_next_move_area(df.copy(), _area) df_area.to_csv(env.get_full_path(write_dir_name, args, any=_area), index=False)
def main(args): df = pd.read_csv(env.get_full_path(read_dir_name, args), encoding='Shift_JISx0213') for _area in env.get_area_list(): df_area = create_next_move_area(df, _area) df_area.to_csv(env.get_full_path(write_dir_name, args, any=_area), index=False)
def main(args): df = pd.read_csv(env.get_full_path(read_dir_name, args), names=env.get_col_names(), encoding='Shift_JISx0213') df = df.apply(lambda x: extract_only_area(x), axis=1) df = df.applymap(lambda x: (x.split('(census)')[0]) if (type(x) is str) and ('(census)' in x) else x) for _area in env.get_area_list(): df_area = create_next_move_area(df.copy(), _area) df_area.to_csv(env.get_full_path(write_dir_name, args, any=_area), index=False)
def main(args): start = time.time() col_names = ['c{0:02d}'.format(i) for i in range(30)] df = pd.read_csv(env.get_full_path('Origin', args), names=col_names, encoding='Shift_JISx0213') df.replace(' ', np.NaN, inplace=True) df.dropna(how='all', axis=1, inplace=True) distribute(df.copy(), args) df_base[args.dir][args.ratio][args.seed][args.csv].to_csv( env.get_full_path('2D', args), index=False) print(env.get_file_name(args)) elapsed_time = time.time() - start print("elapsed_time:{0}".format(elapsed_time) + "[sec]")
def func_road_to_area(args): df = pd.read_csv(env.get_full_path('include_area_-1', args), encoding='Shift_JISx0213') df = df.loc[:, ['road', 'area']] for row in np.asanyarray(df): create_road_to_area(row[0], row[1]) road_to_area[np.nan] = np.nan
def main(args, array): df = pd.read_csv(env.get_full_path(read_dir_name, args), encoding='Shift_JISx0213') df = df.loc[:, ['id', 'time', 'area']] group_list = df.groupby(['id'], sort=True) for _id, _group in group_list: _group = _group.sort_values(['time']) # array[args.dir][args.ratio][args.seed][args.csv][_id] = [] array[args.dir][args.ratio][args.seed][args.csv][_id] = [] for area in np.asanyarray(_group.loc[:, 'area']): array[args.dir][args.ratio][args.seed][args.csv][_id].append(area) df = pd.DataFrame() df_main = array[args.dir][args.ratio][args.seed][args.csv].copy() for _id in df_main: df_main[_id].insert(0, _id) tmp = pd.DataFrame(df_main[_id]).T df = pd.concat([df, tmp]) df.to_csv(env.get_full_path(write_dir_name, args), index=False)