Python | Counting null values in python

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Counting missing values

In Python, you can count the number of missing values (NaN or null values) in a Pandas dataframe using the isna() method to create a boolean mask and then using the sum() method to count the number of True values.

Here's an example:

import pandas as pd

# create a sample dataframe with missing values

data = {'name': ['John', 'Jane', 'Mike', 'Susan'],

'age': [30, None, None, 40],

'gender': ['M', 'F', None, 'F']}

df = pd.DataFrame(data)

# count the number of missing values in the dataframe

missing_values_count = df.isna().sum().sum()

print("Number of missing values in the dataframe:", missing_values_count)

This will output:

Number of missing values in the dataframe: 3

In this example, we have a total of 3 missing values in the age and gender columns of the dataframe.