How to Sort a Pandas Pivot Table and Add a Total Row in Python

Introduction: The author received a question in a Python community about sorting a Pandas pivot table by its values before exporting.

Implementation

The provided solution sorts the pivot table in ascending order:

# Sort pivot table by value (ascending)
sorted_pivot_df = pivot_df.sort_values(by='Value')

A follow‑up request asked to add a row that contains the sum of each column. The complete example creates a sample DataFrame, builds a pivot table, sorts it, and then appends a “total” row with the column sums:

import pandas as pd

# Create example DataFrame
df = pd.DataFrame({
    'Category': ['A', 'A', 'B', 'B', 'C', 'C'],
    'Value': [1, 2, 3, 4, 5, 6]
})

# Generate pivot table
pivot_df = df.pivot_table(index='Category', values='Value', aggfunc='sum')

# Sort pivot table by value (ascending)
sorted_pivot_df = pivot_df.sort_values(by='Value')

# Add a row to calculate the total of each column
sorted_pivot_df.loc['total'] = sorted_pivot_df.sum()

sorted_pivot_df

The result shows the data sorted by the summed values and includes an additional row named “total” that contains the column sums.

Conclusion

The article demonstrates a concise method to sort a Pandas pivot table and append a summary row, helping readers solve similar data‑analysis tasks.