Print the mean of a Pandas series

The mean() function in the Pandas library can be used to find the arithmetic mean (average) of a series. This function calculates the sum of all values divided by the number of values.

Syntax

Series.mean(axis=None, skipna=True, level=None, numeric_only=None)

Parameters

The key parameters are:

• skipna: If True (default), excludes NaN values from calculation
• numeric_only: Include only numeric columns

Example

Here's how to calculate the mean of a Pandas series ?

import pandas as pd

series = pd.Series([10, 20, 30, 40, 50])
print("Pandas Series:")
print(series)

series_mean = series.mean()
print("Mean of the Pandas series:", series_mean)

Pandas Series:
0    10
1    20
2    30
3    40
4    50
dtype: int64
Mean of the Pandas series: 30.0

Handling Missing Values

The mean() function automatically excludes NaN values by default ?

import pandas as pd
import numpy as np

series_with_nan = pd.Series([10, 20, np.nan, 40, 50])
print("Series with NaN:")
print(series_with_nan)

mean_value = series_with_nan.mean()
print("Mean (excluding NaN):", mean_value)

Series with NaN:
0    10.0
1    20.0
2     NaN
3    40.0
4    50.0
dtype: float64
Mean (excluding NaN): 30.0

Conclusion

The mean() function provides a simple way to calculate the average of a Pandas series. It automatically handles missing values by excluding them from the calculation, making it robust for real-world data analysis.