Sorting by index in Pandas - Step-by-Step Execution

Concept Flow - Sorting by index

Start with DataFrame

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Choose sort order: ascending or descending

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Apply sort_index() method

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DataFrame rows rearranged by index

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Return sorted DataFrame

The DataFrame is sorted by its index labels in ascending or descending order using sort_index().

Execution Sample

Pandas

import pandas as pd

df = pd.DataFrame({'A': [10, 20, 30]}, index=[2, 0, 1])
sorted_df = df.sort_index()

This code sorts the DataFrame rows by their index in ascending order.

Execution Table

Step	DataFrame Index Before	Action	Sort Order	DataFrame Index After
1	[2, 0, 1]	Call sort_index()	ascending (default)	[0, 1, 2]
2	[0, 1, 2]	Return sorted DataFrame	N/A	[0, 1, 2]
3	N/A	End of operation	N/A	N/A

💡 Sorting completes after rearranging rows by index in ascending order.

Variable Tracker

Variable	Start	After sort_index()	Final
df.index	[2, 0, 1]	[2, 0, 1]	[2, 0, 1]
sorted_df.index	N/A	[0, 1, 2]	[0, 1, 2]

Key Moments - 2 Insights

Why does the original DataFrame 'df' keep its index order after sort_index()?

Because sort_index() returns a new sorted DataFrame and does not modify 'df' in place unless inplace=True is used, as shown in execution_table row 1 and variable_tracker.

What happens if we set ascending=False in sort_index()?

The DataFrame rows will be sorted by index in descending order, reversing the index order, which changes the 'DataFrame Index After' in execution_table row 1.

Visual Quiz - 3 Questions

Look at the execution table, what is the index order of 'sorted_df' after step 1?

A [1, 2, 0]

B [0, 1, 2]

C [2, 0, 1]

D [2, 1, 0]

💡 Hint

Check the 'DataFrame Index After' column in execution_table row 1.

At which step does the sorting operation complete according to the execution table?

A Step 2

B Step 1

C Step 3

D Sorting never completes

💡 Hint

Look at the 'Action' column describing 'Return sorted DataFrame' in execution_table.

If we want to sort the original DataFrame 'df' in place, what should we do?

A Assign the result of sort_index() back to df

B Use df.sort_values() instead

C Use df.sort_index(inplace=True)

D Nothing, df is sorted automatically

💡 Hint

Refer to key_moments explanation about inplace parameter.

Concept Snapshot

sort_index() sorts DataFrame rows by their index labels.
Default is ascending order.
Returns a new sorted DataFrame unless inplace=True.
Use ascending=False for descending order.
Does not change original DataFrame unless inplace=True.

Full Transcript

Sorting by index in pandas means rearranging the rows of a DataFrame based on their index labels. The method sort_index() is called on the DataFrame. By default, it sorts in ascending order and returns a new DataFrame with rows reordered. The original DataFrame remains unchanged unless you specify inplace=True. You can also sort in descending order by setting ascending=False. The execution table shows the index order before and after sorting, and the variable tracker shows how the index values change in the new sorted DataFrame. Remember to assign the result back or use inplace=True to modify the original DataFrame.