Reputation: 3955
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?
Upvotes: 167
Views: 226567
Reputation: 303
This is what works for me
>>> a = pandas.NaT
>>> type(a) == pandas._libs.tslibs.nattype.NaTType
>>> True
Upvotes: 1
Reputation: 15803
If it's in a Series
(e.g. DataFrame
column) you can also use .isna()
:
pd.Series(pd.NaT).isna()
# 0 True
# dtype: bool
Upvotes: 10
Reputation: 2312
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]
Upvotes: 22
Reputation: 280778
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
Upvotes: 240