我有一个list_of_data_lists包括：
[datetime.datetime(2019, 12, 22, 0, 49, 7), 26.3]
[datetime.datetime(2019, 12, 22, 2, 6, 24), 25.5]
[datetime.datetime(2019, 12, 22, 2, 36, 57), 26.7]
[datetime.datetime(2019, 12, 22, 3, 2, 49), 25.7]
[datetime.datetime(2019, 12, 22, 5, 26, 30), 27.9]
[datetime.datetime(2019, 12, 22, 5, 32, 4), 27.8]
[datetime.datetime(2019, 12, 22, 5, 50, 23), 23.5]
[datetime.datetime(2019, 12, 22, 6, 31, 3), 27.7]
[datetime.datetime(2019, 12, 22, 8, 9, 4), 26.1]
[datetime.datetime(2019, 12, 22, 9, 30, 40), 27.1]
[datetime.datetime(2019, 12, 22, 12, 27, 49), 26.5]
[datetime.datetime(2019, 12, 22, 16, 6, 10), 24.1]
[datetime.datetime(2019, 12, 22, 17, 21, 35), 26.3]
[datetime.datetime(2019, 12, 22, 17, 28, 54), 28.0]
[datetime.datetime(2019, 12, 22, 18, 4, 52), 26.7]
[datetime.datetime(2019, 12, 22, 22, 23, 24), 23.5]
[datetime.datetime(2019, 12, 22, 22, 51, 10), 26.0]
[datetime.datetime(2019, 12, 22, 23, 30, 14), 23.6]
并希望把这个成pandas dataframe，在列date_and_time，并data_value为data_list[0]与data_list[1]在list_of_data_lists对应。如何才能做到这一点？
IIUC，只需传递list_of_data_lists给数据框构造函数
import datetime
list_of_data_lists = [
[datetime.datetime(2019, 12, 22, 0, 49, 7), 26.3],
[datetime.datetime(2019, 12, 22, 2, 6, 24), 25.5],
[datetime.datetime(2019, 12, 22, 2, 36, 57), 26.7],
[datetime.datetime(2019, 12, 22, 3, 2, 49), 25.7],
[datetime.datetime(2019, 12, 22, 5, 26, 30), 27.9],
[datetime.datetime(2019, 12, 22, 5, 32, 4), 27.8],
[datetime.datetime(2019, 12, 22, 5, 50, 23), 23.5],
[datetime.datetime(2019, 12, 22, 6, 31, 3), 27.7],
[datetime.datetime(2019, 12, 22, 8, 9, 4), 26.1],
[datetime.datetime(2019, 12, 22, 9, 30, 40), 27.1],
[datetime.datetime(2019, 12, 22, 12, 27, 49), 26.5],
[datetime.datetime(2019, 12, 22, 16, 6, 10), 24.1],
[datetime.datetime(2019, 12, 22, 17, 21, 35), 26.3],
[datetime.datetime(2019, 12, 22, 17, 28, 54), 28.0],
[datetime.datetime(2019, 12, 22, 18, 4, 52), 26.7],
[datetime.datetime(2019, 12, 22, 22, 23, 24), 23.5],
[datetime.datetime(2019, 12, 22, 22, 51, 10), 26.0],
[datetime.datetime(2019, 12, 22, 23, 30, 14), 23.6],
]
df = pd.DataFrame(list_of_data_lists, columns=['date_and_time', 'data_value'])
Out[155]:
date_and_time data_value
0 2019-12-22 00:49:07 26.3
1 2019-12-22 02:06:24 25.5
2 2019-12-22 02:36:57 26.7
3 2019-12-22 03:02:49 25.7
4 2019-12-22 05:26:30 27.9
5 2019-12-22 05:32:04 27.8
6 2019-12-22 05:50:23 23.5
7 2019-12-22 06:31:03 27.7
8 2019-12-22 08:09:04 26.1
9 2019-12-22 09:30:40 27.1
10 2019-12-22 12:27:49 26.5
11 2019-12-22 16:06:10 24.1
12 2019-12-22 17:21:35 26.3
13 2019-12-22 17:28:54 28.0
14 2019-12-22 18:04:52 26.7
15 2019-12-22 22:23:24 23.5
16 2019-12-22 22:51:10 26.0
17 2019-12-22 23:30:14 23.6
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