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.

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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