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Pandas | isnull method

Pandas
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Documentation
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General Functions
schedule Jul 1, 2022
Last updated
local_offer PandasPython
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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, and False representing NaN, is returned.

Examples

Scalars

pd.isnull("A")
False
pd.isnull(np.NaN)
True
pd.isnull(None)
True

Array-likes

Series

s = pd.Series([1,np.NaN,3])
pd.isnull(s)
0 False
1 True
2 False
dtype: bool

The return type is a Series of booleans.

DataFrame

Consider the following DataFrame:

df = pd.DataFrame({"A":[np.NaN,2], "B":[3,np.NaN]})
df
   A    B
0  NaN  3.0
1  2.0  NaN

To check for existing values (non-NaN values):

pd.isnull(df)
   A      B
0  True   False
1  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.

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Published by Isshin Inada
Edited by 0 others
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