我正在使用巨大的数据框架:

reader = pd.read_csv("D:/...path.../test.csv", names=["id_easy","ordinal", "latitude", "longitude","epoch",'weekday'],
                 parse_dates=['epoch'], chunksize=n_rows, error_bad_lines=False)

day_names = (('0:00', '1:00'),('1:00', '2:00'),('2:00', '3:00'),('3:00', '4:00'),('4:00', '5:00'),('5:00', '6:00'),
             ('6:00', '7:00'),('7:00', '8:00'),('8:00', '9:00'),('9:00', '10:00'),('10:00', '11:00'),('11:00', '12:00'),
             ('12:00', '13:00'),('13:00', '14:00'),('14:00', '15:00'),('15:00', '16:00'),('16:00', '17:00'),('17:00', '18:00'),
             ('18:00', '19:00'),('19:00', '20:00'),('20:00', '21:00'),('21:00', '22:00'),('22:00', '23:00'),('23:00', '00:00'))

for df in reader:
    if not df.empty:
        df['epoch'] = pd.to_datetime(df.epoch,unit = 's')
        df.index = pd.to_datetime(df.epoch)
        for day in day_names:
            day_df = df.between_time[day] # ERROR IS HERE
            if not day_df.empty:
                day_df.to_csv(f'{day}.csv', index=False, header=False, mode='a')





  TypeError:“方法”对象不可下标




所需的输出是24个.csv文件,例如:final1,final2,...,final24



样本数据:

e35f652a    68  11.9125 3.7432  1465084811  Sunday
e35f652a    69  11.8992 3.7412  1465084870  Sunday
e35f652a    70  11.8866 3.7342  1465084930  Sunday
e35f652a    71  11.8755 3.7321  1465084990  Sunday
e35f652a    72  11.8675 3.7247  1465085050  Sunday




this问题多少有些相似

最佳答案

将用于索引的[]更改为(),因为DataFrame.between_time()并通过索引选择元组的第一个和第二个值:

for day in day_names:
    day_df = df.between_time(day[0], day[1])


或更改循环以打开元组:

for s, e in day_names:
    day_df = df.between_time(s, e)

关于python - TypeError,“方法”对象在迭代时不可下标,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/58626896/

10-12 22:00