sort_values() by single column in Pandas - Step-by-Step Execution

Concept Flow - sort_values() by single column

Start with DataFrame

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Choose column to sort

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Call sort_values() on column

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DataFrame rows rearranged

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Sorted DataFrame output

We start with a table, pick one column to sort by, then rearrange rows based on that column's values, producing a sorted table.

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({'Name': ['Bob', 'Alice', 'Eve'], 'Age': [25, 30, 22]})
sorted_df = df.sort_values('Age')
print(sorted_df)

This code sorts the DataFrame rows by the 'Age' column in ascending order.

Execution Table

Step	DataFrame State	Action	Resulting DataFrame
1	{'Name': ['Bob', 'Alice', 'Eve'], 'Age': [25, 30, 22]}	Call df.sort_values('Age')	Name Age 2 Eve 22 0 Bob 25 1 Alice 30
2	Sorted DataFrame ready	Print sorted_df	Name Age 2 Eve 22 0 Bob 25 1 Alice 30
3	End	No further action	Sorting complete

💡 All rows rearranged by ascending 'Age' values, sorting finished

Variable Tracker

Variable	Start	After sort_values()	Final
df	{'Name': ['Bob', 'Alice', 'Eve'], 'Age': [25, 30, 22]}	Unchanged	Unchanged
sorted_df	Not defined	{'Name': ['Eve', 'Bob', 'Alice'], 'Age': [22, 25, 30]}	Same

Key Moments - 2 Insights

Why does the original DataFrame 'df' not change after sort_values()?

Because sort_values() returns a new sorted DataFrame and does not modify 'df' unless you use inplace=True. See execution_table step 1 where 'df' stays the same.

What determines the order of rows after sorting?

The values in the chosen column ('Age' here) determine the new row order, smallest to largest by default, as shown in execution_table step 1.

Visual Quiz - 3 Questions

Look at the execution_table step 1, what is the first row in the sorted DataFrame?

A Bob, Age 25

B Alice, Age 30

C Eve, Age 22

D None of these

💡 Hint

Check the 'Resulting DataFrame' column in step 1 for the first row after sorting.

At which step does the DataFrame get printed?

A Step 2

B Step 1

C Step 3

D It is never printed

💡 Hint

Look at the 'Action' column to find when print(sorted_df) happens.

If we want to sort the original DataFrame 'df' without creating a new one, what should we add?

A by='Age'

B inplace=True

C ascending=False

D axis=1

💡 Hint

Refer to key_moments about why 'df' does not change after sort_values().

Concept Snapshot

sort_values(column_name)
- Sorts DataFrame rows by one column
- Returns a new sorted DataFrame by default
- Use inplace=True to modify original
- Default order is ascending
- Useful to reorder data by values

Full Transcript

We start with a DataFrame containing names and ages. We want to sort rows by the 'Age' column. Calling df.sort_values('Age') returns a new DataFrame with rows ordered from youngest to oldest. The original DataFrame stays the same unless we use inplace=True. We print the sorted DataFrame to see the result. This process helps us organize data by any column's values easily.