使用pd.to_datetime处理多种日期时间格式 [英] Handling multiple datetime formats with pd.to_datetime

问题描述

我有一个datatime数据，其格式类似于29062017和01AUG2017. 如您所见，月份位于数据中间.

I have a datatime data, their format is like 29062017 and 01AUG2017. As you can see, the month is in the middle of data.

当我使用pd.to_datetime时，我想将此数据转换为日期时间，但是它不起作用.

I want to convert this data to datetime, when I use pd.to_datetime, but it doesn't work.

您知道解决此问题的好方法吗?

Do you know a good way to solve this problem?

推荐答案

替代方法是使用映射器和replace用数值等效项替换月份代码:

The alternative would be to use a mapper and replace to substitute month codes with their numerical equivalent:

s = pd.Series(["29062017", "01AUG2017"]); s

0     29062017
1    01AUG2017
dtype: object

m = {'JAN' : '01', ..., 'AUG' : '08', ...}  # you fill in the rest

s = s.replace(m, regex=True); s

0    29062017
1    01082017
dtype: object

现在您只需要一个pd.to_datetime呼叫:

Now all you need is a single pd.to_datetime call:

pd.to_datetime(s, format="%d%m%Y", errors="coerce")

0   2017-06-29
1   2017-08-01
dtype: datetime64[ns]

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