我有一个如下所示的数据框:
A B
2014-06-02 09:00:00-04:00 ... ...
2014-06-02 10:00:00-04:00 ... ...
2014-06-02 11:00:00-04:00 ... ...
2014-06-02 12:00:00-04:00 ... ...
2014-06-03 09:00:00-04:00 ... ...
2014-06-03 10:00:00-04:00 ... ...
2014-06-03 11:00:00-04:00 ... ...
2014-06-04 09:00:00-04:00 ... ...
2014-06-04 10:00:00-04:00 ... ...
2014-06-04 11:00:00-04:00 ... ...
2014-06-04 12:00:00-04:00 ... ...
我需要删除没有时间 12:00:00-04:00 的日子:在我的示例中，它将是 2014-06-03。所以最终的数据框看起来像:
A B
2014-06-02 09:00:00-04:00 ... ...
2014-06-02 10:00:00-04:00 ... ...
2014-06-02 11:00:00-04:00 ... ...
2014-06-02 12:00:00-04:00 ... ...
2014-06-04 09:00:00-04:00 ... ...
2014-06-04 10:00:00-04:00 ... ...
2014-06-04 11:00:00-04:00 ... ...
2014-06-04 12:00:00-04:00 ... ...
请注意，索引已本地化 (-04:00)
Pandas 0.24.2
最佳答案
您可以分组和过滤
df.groupby(df.index.date).filter(lambda s: 12 in s.index.hour)
A B
2014-06-02 09:00:00-04:00 ... ...
2014-06-02 10:00:00-04:00 ... ...
2014-06-02 11:00:00-04:00 ... ...
2014-06-02 12:00:00-04:00 ... ...
2014-06-04 09:00:00-04:00 ... ...
2014-06-04 10:00:00-04:00 ... ...
2014-06-04 11:00:00-04:00 ... ...
2014-06-04 12:00:00-04:00 ... ...
关于python - 具有本地化日期时间索引的数据框 : how to drop days not having a given time，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/58918666/