根據 pandas 數據幀中的 15 分鍾時間間隔將一行分成多行 6 小時數據

Question

我想根據 pandas 數據幀中的 15 分鍾時間間隔將一行分成多行 6 小時數據

    start_time          end_time    
0   2022-08-22 00:15:00 2022-08-22 06:15:00

我嘗試了一個小時的時間分割並使用了下面的代碼

result['start_time'] = result.apply(lambda d: pd.date_range(d['start_time'],
                                                    d['end_time'], 
                                                    freq='h')[:-1], 
                            axis=1) 

這對我有用

   result["start_time"][0]

Output：

DatetimeIndex(['2022-08-22 00:15:00', '2022-08-22 01:15:00',
               '2022-08-22 02:15:00', '2022-08-22 03:15:00',
               '2022-08-22 04:15:00', '2022-08-22 05:15:00'],
              dtype='datetime64[ns]', freq='H')

現在我想要 15 分鍾時間間隔的頻率，所以它應該給我 24 個時間戳

Answer 1

嘗試： 15T而不是h

result['start_time'] = result.apply(lambda d: pd.date_range(d['start_time'],
                                                    d['end_time'], 
                                                    freq='15T')[:-1], 
                            axis=1) 

OUTPUT：

DatetimeIndex(['2022-08-22 00:15:00', '2022-08-22 00:30:00',
               '2022-08-22 00:45:00', '2022-08-22 01:00:00',
               '2022-08-22 01:15:00', '2022-08-22 01:30:00',
               '2022-08-22 01:45:00', '2022-08-22 02:00:00',
               '2022-08-22 02:15:00', '2022-08-22 02:30:00',
               '2022-08-22 02:45:00', '2022-08-22 03:00:00',
               '2022-08-22 03:15:00', '2022-08-22 03:30:00',
               '2022-08-22 03:45:00', '2022-08-22 04:00:00',
               '2022-08-22 04:15:00', '2022-08-22 04:30:00',
               '2022-08-22 04:45:00', '2022-08-22 05:00:00',
               '2022-08-22 05:15:00', '2022-08-22 05:30:00',
               '2022-08-22 05:45:00', '2022-08-22 06:00:00'],
              dtype='datetime64[ns]', freq='15T')

正如預期的那樣——你得到了24 個時間戳

Answer 2

from datetime import timedelta

df = pd.DataFrame({'start_time': ['2022-08-22 00:15:00'],'end_time': ['2022-08-22 06:15:00']})
df['start_time'] = pd.to_datetime(df['start_time'])
df['end_time'] = pd.to_datetime(df['end_time'])
df['start_time'] = df['start_time'].dt.strftime('%Y-%m-%d %H:%M:%S')
df['end_time'] = df['end_time'].dt.strftime('%Y-%m-%d %H:%M:%S')

#             start_time             end_time
# 0  2022-08-22 00:15:00  2022-08-22 06:15:00

new_df = pd.date_range(start=df['start_time'][0], end=df['end_time'][0], freq='15min')[:-1]
result_df = pd.DataFrame({'start_time': new_df, 'end_time': new_df + timedelta(minutes=15)})

output：

> result_df

      start_time            end_time
0  2022-08-22 00:15:00 2022-08-22 00:30:00
1  2022-08-22 00:30:00 2022-08-22 00:45:00
2  2022-08-22 00:45:00 2022-08-22 01:00:00
3  2022-08-22 01:00:00 2022-08-22 01:15:00
4  2022-08-22 01:15:00 2022-08-22 01:30:00
5  2022-08-22 01:30:00 2022-08-22 01:45:00
6  2022-08-22 01:45:00 2022-08-22 02:00:00
7  2022-08-22 02:00:00 2022-08-22 02:15:00
8  2022-08-22 02:15:00 2022-08-22 02:30:00
9  2022-08-22 02:30:00 2022-08-22 02:45:00
10 2022-08-22 02:45:00 2022-08-22 03:00:00
11 2022-08-22 03:00:00 2022-08-22 03:15:00
12 2022-08-22 03:15:00 2022-08-22 03:30:00
13 2022-08-22 03:30:00 2022-08-22 03:45:00
14 2022-08-22 03:45:00 2022-08-22 04:00:00
15 2022-08-22 04:00:00 2022-08-22 04:15:00
16 2022-08-22 04:15:00 2022-08-22 04:30:00
17 2022-08-22 04:30:00 2022-08-22 04:45:00
18 2022-08-22 04:45:00 2022-08-22 05:00:00
19 2022-08-22 05:00:00 2022-08-22 05:15:00
20 2022-08-22 05:15:00 2022-08-22 05:30:00
21 2022-08-22 05:30:00 2022-08-22 05:45:00
22 2022-08-22 05:45:00 2022-08-22 06:00:00
23 2022-08-22 06:00:00 2022-08-22 06:15:00