Python pandas .isnull() 不适用于对象 dtype 中的 NaT
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Python pandas .isnull() does not work on NaT in object dtype
提问by ragesz
I have this series:
我有这个系列：
ser=pd.Series([11,22,33,np.nan,np.datetime64('nat')],name='my_series')
The series looks like this:
该系列看起来像这样：
0 11
1 22
2 33
3 NaN
4 NaN
Name: my_series, dtype: object
But I get only one Truefor NULL values:
但我只得到一个TrueNULL 值：
ser.isnull()
0 False
1 False
2 False
3 True
4 False
Name: my_series, dtype: bool
Is it a bug or how can I count correctly the NULL values in a pandas series? This does not help:
这是错误还是如何正确计算Pandas系列中的 NULL 值？这没有帮助：
ser=ser.replace('NaN',np.nan)
Thanks!
谢谢！
回答by nck
I ran into a similar issue this morning but in an str series! This worked for me and with your sample data as well:
我今天早上遇到了类似的问题，但在 str 系列中！这对我以及您的示例数据都有效：
pd.isna(ser)
pd.isna(ser)
回答by mirthbottle
To get around this, you can also do
为了解决这个问题，你也可以这样做
series.apply(lambda x: str(x) == "nat")
series.apply(lambda x: str(x) == "nat")
Then you can still use np.datetime if you want
然后你仍然可以使用 np.datetime 如果你愿意
回答by Yogesh
Surprisingly I got following output after execution the code you given:
令人惊讶的是，在执行您给出的代码后，我得到了以下输出：
Alternate way is: count those values which you are able to count.
替代方法是：计算您能够计算的那些值。
calculate length of series object and subtraction will give you the count for null values. As follows:**
计算系列对象的长度，减法将为您提供空值的计数。如下：**
len(ser)-(ser[ser.isnull()==False]).count()
