How to Replace NaN with Mean in pandas DataFrame

Use the fillna() method with the mean value of the column to replace NaN values in a pandas DataFrame. Calculate the mean using df['column'].mean() and then apply df['column'].fillna(mean_value, inplace=True) to update the data.

Syntax

The basic syntax to replace NaN values with the mean in a pandas DataFrame column is:

• df['column'].mean(): Calculates the mean of the specified column, ignoring NaN values.
• df['column'].fillna(value, inplace=True): Replaces NaN values with the given value. Setting inplace=True updates the DataFrame directly.

python

mean_value = df['column'].mean()
df['column'].fillna(mean_value, inplace=True)

Example

This example shows how to replace NaN values in the 'Age' column with the mean age in a pandas DataFrame.

python

import pandas as pd
import numpy as np

data = {'Name': ['Alice', 'Bob', 'Charlie', 'David'],
        'Age': [25, np.nan, 30, np.nan]}
df = pd.DataFrame(data)

mean_age = df['Age'].mean()
df['Age'].fillna(mean_age, inplace=True)

print(df)

Output

      Name   Age
0    Alice  25.0
1      Bob  27.5
2  Charlie  30.0
3    David  27.5

Common Pitfalls

Common mistakes when replacing NaN with mean include:

• Not calculating the mean before filling, which causes errors.
• Forgetting to set inplace=True, so the DataFrame is not updated.
• Applying mean replacement on non-numeric columns, which will fail.

Always ensure the column is numeric and the mean is calculated first.

python

import pandas as pd
import numpy as np

data = {'Score': [10, np.nan, 20]}
df = pd.DataFrame(data)

# Wrong: fillna with mean without calculating mean
# df['Score'].fillna(df['Score'].fillna(), inplace=True)  # This does nothing

# Correct way:
mean_score = df['Score'].mean()
df['Score'].fillna(mean_score, inplace=True)

print(df)

Output

   Score
0   10.0
1   15.0
2   20.0

Quick Reference

Summary tips for replacing NaN with mean in pandas:

• Use df['col'].mean() to get the mean.
• Use fillna(mean_value, inplace=True) to replace NaN.
• Check column data type is numeric before applying.
• Use inplace=True to modify the DataFrame directly.

Key Takeaways

Calculate the mean of the column before replacing NaN values.

Use fillna() with inplace=True to update the DataFrame directly.

Only apply mean replacement on numeric columns to avoid errors.

Always verify the DataFrame after replacement to confirm changes.