Pandas 按 DataFrame 中的日期排序未正确排序

Question

以下代码段将 sample_data.csv 读入 DataFrame 并按观察时间排序。排序例程没有正确排序日期/时间。

df = pd.read_csv('C:/data/sample_data.csv')
df = df.sort(['observation_time'])
df.to_csv('C:/data/outfile.csv')

[从 Anaconda 32 位窗口使用 Pandas 0.12]

输入：sample_data.csv：

latitude    longitude   vessel_name observation_time
1.031000018 -79.68883514    aqasi           12/28/2012 10:40
1.032833338 -79.71916199    aqasi           12/29/2012 14:06
1.486500025 -80.1906662     aqasi           12/31/2012 4:41
1.466999888 -80.16249847    aqasi           12/31/2012 4:30
2.342833519 -81.46682739    aqasi           12/31/2012 13:40
2.360000134 -81.4936676     aqasi           12/31/2012 13:51
3.816000223 -83.68183899    aqasi           1/1/2013 5:20
3.730499983 -83.55400085    aqasi           1/1/2013 4:24
3.714666843 -83.53016663    aqasi           1/1/2013 4:14
4.986999989 -85.45566559    aqasi           1/1/2013 19:04
6.884333134 -88.21949768    aqasi           1/2/2013 13:11
6.885833263 -88.22200012    aqasi           1/2/2013 13:12
6.886833191 -88.22383881    aqasi           1/2/2013 13:12
6.887333393 -88.22450256    aqasi           1/2/2013 13:13
6.889333248 -88.22800446    aqasi           1/2/2013 13:14

输出：outfile.csv：

    latitude    longitude   vessel_name observation_time
9   4.986999989 -85.45566559    aqasi           1/1/2013 19:04
8   3.714666843 -83.53016663    aqasi           1/1/2013 4:14
7   3.730499983 -83.55400085    aqasi           1/1/2013 4:24
6   3.816000223 -83.68183899    aqasi           1/1/2013 5:20
10  6.884333134 -88.21949768    aqasi           1/2/2013 13:11
12  6.886833191 -88.22383881    aqasi           1/2/2013 13:12
11  6.885833263 -88.22200012    aqasi           1/2/2013 13:12
13  6.887333393 -88.22450256    aqasi           1/2/2013 13:13
14  6.889333248 -88.22800446    aqasi           1/2/2013 13:14
0   1.031000018 -79.68883514    aqasi           12/28/2012 10:40
1   1.032833338 -79.71916199    aqasi           12/29/2012 14:06
4   2.342833519 -81.46682739    aqasi           12/31/2012 13:40
5   2.360000134 -81.4936676     aqasi           12/31/2012 13:51
3   1.466999888 -80.16249847    aqasi           12/31/2012 4:30
2   1.486500025 -80.1906662     aqasi           12/31/2012 4:41

Answer 1

“错误”排序的原因是该observation_time列是string类型列，因此实际上它被正确排序为string。

在排序之前将其转换为datetime类型将产生所需的结果：

df['observation_time'] = pd.to_datetime(df['observation_time'])