pandas 如何测试变量是否为 pd.NaT？
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how to test if a variable is pd.NaT?
提问by Clément F
I'm trying to test if one of my variables is pd.NaT. I know it is NaT, and still it won't pass the test. As an example, the following code prints nothing :
我正在尝试测试我的变量之一是否是 pd.NaT。我知道它是 NaT，但它仍然无法通过测试。例如，以下代码不打印任何内容：
a=pd.NaT
if a == pd.NaT:
print("a not NaT")
Does anyone have a clue ? Is there a way to effectively test if ais NaT?
有人有线索吗 ？有没有办法有效地测试是否a是 NaT？
回答by user2357112 supports Monica
Pandas NaTbehaves like a floating-point NaN, in that it's not equal to itself. Instead, you can use pandas.isnull:
Pandas 的NaT行为就像一个浮点数NaN，因为它不等于自身。相反，您可以使用pandas.isnull：
In [21]: pandas.isnull(pandas.NaT)
Out[21]: True
This also returns Truefor None and NaN.
这也返回TrueNone 和 NaN。
Technically, you could also check for Pandas NaTwith x != x, following a common pattern used for floating-point NaN. However, this is likely to cause issues with NumPy NaTs, which look very similar and represent the same concept, but are actually a different type with different behavior:
从技术上讲，你也可以检查大熊猫NaT有x != x，以下用于浮点NaN的一种常用模式。但是，这可能会导致 NumPy NaT 出现问题，它们看起来非常相似并代表相同的概念，但实际上是具有不同行为的不同类型：
In [29]: x = pandas.NaT
In [30]: y = numpy.datetime64('NaT')
In [31]: x != x
Out[31]: True
In [32]: y != y
/home/i850228/.local/lib/python3.6/site-packages/IPython/__main__.py:1: FutureWarning: In the future, NAT != NAT will be True rather than False.
# encoding: utf-8
Out[32]: False
numpy.isnat, the function to check for NumPy NaT, also fails with a Pandas NaT:
numpy.isnat，检查 NumPy 的函数NaT，也因 Pandas 失败NaT：
In [33]: numpy.isnat(pandas.NaT)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-33-39a66bbf6513> in <module>()
----> 1 numpy.isnat(pandas.NaT)
TypeError: ufunc 'isnat' is only defined for datetime and timedelta.
pandas.isnullworks for both Pandas and NumPy NaTs, so it's probably the way to go:
pandas.isnull适用于 Pandas 和 NumPy NaTs，所以这可能是要走的路：
In [34]: pandas.isnull(pandas.NaT)
Out[34]: True
In [35]: pandas.isnull(numpy.datetime64('NaT'))
Out[35]: True
回答by Lukas
You can also use pandas.isna() for pandas.NaT, numpy.nan or None:
您还可以将 pandas.isna() 用于 pandas.NaT、numpy.nan 或 None：
import pandas as pd
import numpy as np
x = (pd.NaT, np.nan, None)
[pd.isna(i) for i in x]
Output:
[True, True, True]
回答by Long Bu
pd.NaT is pd.NaT
True
真的
this works for me.
这对我有用。
回答by Max Ghenis
If it's in a Series(e.g. DataFramecolumn) you can also use .isna():
如果它在Series（例如DataFrame列）中，您还可以使用.isna()：
pd.Series(pd.NaT).isna()
# 0 True
# dtype: bool
