Ascending and descending order in Pandas

Introduction

Sorting data helps us see information clearly by putting it in order. We can arrange data from smallest to largest or largest to smallest.

When you want to see the highest or lowest values in a list of numbers.

When you need to organize names or dates alphabetically or by time.

When preparing data for reports to show trends or rankings.

When cleaning data to find duplicates or errors by sorting.

When comparing different groups by sorting their values.

Syntax

Pandas

DataFrame.sort_values(by='column_name', ascending=True)

by is the column name you want to sort.

ascending=True sorts from smallest to largest; False sorts from largest to smallest.

Examples

Sorts the DataFrame by the 'Age' column from youngest to oldest.

Pandas

df.sort_values(by='Age', ascending=True)

Sorts the DataFrame by the 'Score' column from highest to lowest.

Pandas

df.sort_values(by='Score', ascending=False)

Sorts first by 'City' alphabetically, then by 'Age' descending within each city.

Pandas

df.sort_values(by=['City', 'Age'], ascending=[True, False])

Sample Program

This code creates a small table of people with their ages and scores. It first sorts the table by age from youngest to oldest, then sorts by score from highest to lowest.

Pandas

import pandas as pd

data = {'Name': ['Anna', 'Bob', 'Charlie', 'Diana'],
        'Age': [28, 24, 35, 30],
        'Score': [88, 92, 85, 90]}
df = pd.DataFrame(data)

# Sort by Age ascending
sorted_by_age = df.sort_values(by='Age', ascending=True)
print('Sorted by Age (ascending):')
print(sorted_by_age)

# Sort by Score descending
sorted_by_score = df.sort_values(by='Score', ascending=False)
print('\nSorted by Score (descending):')
print(sorted_by_score)

Important Notes

If you want to sort the original DataFrame without creating a new one, use inplace=True.

You can sort by multiple columns by passing a list to by and a list of booleans to ascending.

Summary

Sorting helps organize data to understand it better.

Use ascending=True for smallest to largest, False for largest to smallest.

You can sort by one or more columns easily with pandas.