从 Pandas 数据框中删除 NaT 值
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Get rid of NaT values from pandas dataframe
提问by user3527975
I have a dataframe that looks like shown below
我有一个如下所示的数据框
mean
comp_name date
Appdynamics 2012-05-01 00:18:15.910000
2012-05-01 NaT
2012-05-01 NaT
2012-05-02 00:20:12.145200
2012-05-02 NaT
2012-05-02 NaT
Here the comp_name and date form multiindex. I want to get rid of the NaT values and obtain only those rows where the mean(timedelta64) is not NaT.
这里的 comp_name 和 date 构成多索引。我想去掉 NaT 值，只获取那些均值（timedelta64）不是 NaT 的行。
mean
comp_name date
Appdynamics 2012-05-01 00:18:15.910000
2012-05-02 00:20:12.145200
Any ideas on this?
对此有何想法？
回答by exp1orer
pandas.notnull()takes a series and returns a Boolean series which is True where the input series is not null (None, np.NaN, np.NaT). Then you can slice a dataframe by the Boolean series:
pandas.notnull()接受一个系列并返回一个布尔系列，该系列为 True，其中输入系列不为空（无、np.NaN、np.NaT）。然后您可以通过布尔系列对数据帧进行切片：
df[pandas.notnull(df['mean'])]
