how to test if a variable is pd.NaT?

Question

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?

Asked By: Clément F

||

Source

Answer 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

Answered By: user2357112

Answer 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]

Answered By: Lukas

Answer 3

pd.NaT is pd.NaT

True

this works for me.

Answered By: Long Bu

Answer 4

If it’s in a Series (e.g. DataFrame column) you can also use .isna():

pd.Series(pd.NaT).isna()
# 0    True
# dtype: bool

Answered By: Max Ghenis

Answer 5

This is what works for me

>>> a = pandas.NaT
>>> type(a) == pandas._libs.tslibs.nattype.NaTType
>>> True

Answered By: Helton Wernik

how to test if a variable is pd.NaT?

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