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Python | Pandas dataframe.isna ()

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The Pandas function dataframe.isna() is used to detect missing values. It returns a boolean of the same size indicating whether the values ​​are NA. NA values ​​such as None or numpy.NaN are mapped to True values. Everything else is matched against false values. Characters such as blank lines "or numpy.inf are not considered NA values ​​(unless you set pandas.options.mode.use_inf_as_na = True).

Syntax: DataFrame.isna ()

Returns: Mask of bool values ​​for each element in DataFrame that indicates whether an element is not an NA value.

To link to the CSV file used in the example, click here

Example # 1: Use the isna () function to detect missing values ​​in a data frame.

# import pandas as pd

import pandas as pd

 
# Create a data frame

df = pd.read_csv ( "nba.csv" )

  
# Print the data frame
df

Let’s use the isna () function to detect missing values.

# detect missing values ​​
df.isna ()

Output:

In the output, cells corresponding to missing values ​​contain a value true, false otherwise.

Example # 2: Use the isna () function to find missing values ​​in a panda series object

# pandas import as pd

import pandas as pd

 
# Create a series

sr = pd.Series ([ 12 , 5 , None , 5 , None , 11 ])

 
# Print series
sr

Let’s find all missing values ​​in the series.

# to detect missing values ​​
sr.isna ()

Output:

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