Python | Using pandas to detect missing values in python

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Detecting any missing values with .isna().any()

You can use the .isna().any() method to detect any missing values in a Pandas dataframe.

Here's an example:

import pandas as pd

# create a sample dataframe with missing values

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

'age': [30, 25, None, 40],

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

df = pd.DataFrame(data)

# check for missing values in the dataframe

print(df.isna().any())

This will output a boolean series with True values for columns that contain at least one missing value:

name False
age True
gender True
dtype: bool

In this example, we can see that the age and gender columns have at least one missing value, while the name column does not.