how to test if a variable is pd.NaT?

怎甘沉沦 提交于 2019-12-18 05:27:41

问题


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 :

a=pd.NaT

if a == pd.NaT:
    print("a not NaT")

Does anyone have a clue ? Is there a way to effectively test if a is NaT?


回答1:


Pandas NaT behaves like a floating-point NaN, in that it's not equal to itself. Instead, you can use pandas.isnull:

In [21]: pandas.isnull(pandas.NaT)
Out[21]: True

This also returns True for None and NaN.

Technically, you could also check for Pandas NaT with 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:

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:

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.isnull works for both Pandas and NumPy NaTs, so it's probably the way to go:

In [34]: pandas.isnull(pandas.NaT)
Out[34]: True

In [35]: pandas.isnull(numpy.datetime64('NaT'))
Out[35]: True



回答2:


You can also use pandas.isna() for pandas.NaT, numpy.nan or 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]


来源:https://stackoverflow.com/questions/49435317/how-to-test-if-a-variable-is-pd-nat

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