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Pandas | isnull method
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schedule Jul 1, 2022
Last updated Pandas●Python
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expand_more Pandas isnull(~)
method returns a boolean mask where True
is set for NaN
(missing values) and False
for non-NaN
.
Parameters
1. obj
| array-like
or object
The array-like (e.g. Series, DataFrames, Numpy arrays, lists and so on) in which to check for NaN
.
Return Value
If a single scalar object (e.g. a string and a numeric) is provided, then a single
boolean
is returned.Otherwise, a boolean mask where
True
represents non-NaN
values, andFalse
representingNaN
, is returned.
Examples
Scalars
pd.isnull("A")
False
pd.isnull(np.NaN)
True
pd.isnull(None)
True
Array-likes
Series
pd.isnull(s)
0 False1 True2 Falsedtype: bool
The return type is a Series
of booleans.
DataFrame
Consider the following DataFrame:
df
A B0 NaN 3.01 2.0 NaN
To check for existing values (non-NaN
values):
pd.isnull(df)
A B0 True False1 False True
The return type is a DataFrame
of booleans.
NOTE
Series and DataFrames have the method isnull()
, so you can call df.isnull()
directly.
Published by Isshin Inada
Edited by 0 others
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Official Pandas Documentation
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.isnull.html
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