How to replace NaN values by Zeroes in a column of a Pandas Dataframe?

You can replace NaN values in a column of a Pandas Dataframe by using the fillna() method and passing in the value you want to replace NaN with. In this case, you can replace NaN with 0 by using the following code snippet:

Replace NaN with 0 in Python's pandas DataFrame

import pandas as pd

# Create a sample dataframe
df = pd.DataFrame({'A': [1, 2, 3, 4, 5, float('nan')],
                   'B': [6, 7, 8, 9, float('nan'), 11],
                   'C': [12, 13, 14, 15, 16, 17]})

# Replace NaN values in column 'A' with 0
df['A'] = df['A'].fillna(0)

print(df)

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You can also replace NaN values in all columns of a Dataframe by using the following code snippet:

Replace NaN values in all columns of a pandas DataFrame in Python

df = df.fillna(0)

This will replace NaN values in all columns with 0.