如何将字符串转换为日期时间格式在熊猫 python?

在一个名为 train 的数据框中,有一个类型为 string (object)的 I _ DATE 列,如下所示。

I_DATE
28-03-2012  2:15:00 PM
28-03-2012  2:17:28 PM
28-03-2012  2:50:50 PM

如何将 I _ DATE 从字符串转换为数据时间格式并指定输入字符串的格式。我看到了一些答案,但这不是 AM/PM 格式。

另外,如何根据大熊猫中的日期范围过滤行?

256838 次浏览

Use to_datetime. There is no need for a format string since the parser is able to handle it:

In [51]:
pd.to_datetime(df['I_DATE'])


Out[51]:
0   2012-03-28 14:15:00
1   2012-03-28 14:17:28
2   2012-03-28 14:50:50
Name: I_DATE, dtype: datetime64[ns]

To access the date/day/time component use the dt accessor:

In [54]:
df['I_DATE'].dt.date


Out[54]:
0    2012-03-28
1    2012-03-28
2    2012-03-28
dtype: object


In [56]:
df['I_DATE'].dt.time


Out[56]:
0    14:15:00
1    14:17:28
2    14:50:50
dtype: object

You can use strings to filter as an example:

In [59]:
df = pd.DataFrame({'date':pd.date_range(start = dt.datetime(2015,1,1), end = dt.datetime.now())})
df[(df['date'] > '2015-02-04') & (df['date'] < '2015-02-10')]


Out[59]:
date
35 2015-02-05
36 2015-02-06
37 2015-02-07
38 2015-02-08
39 2015-02-09

Approach: 1

Given original string format: 2019/03/04 00:08:48

you can use

updated_df = df['timestamp'].astype('datetime64[ns]')

The result will be in this datetime format: 2019-03-04 00:08:48

Approach: 2

updated_df = df.astype({'timestamp':'datetime64[ns]'})