Pandas: Reorder DataFrame rows based on Index List

# Table of Contents

# Pandas: Reorder DataFrame rows based on Index List

Use the DataFrame.reindex() method to reorder the rows of a Pandas DataFrame based on an index list.

The DataFrame.reindex() method takes a labels argument that is used to determine the row order.

main.py

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import pandas as pd

df = pd.DataFrame({
    'name': ['Alice', 'Bobby', 'Carl', 'Dan', 'Ethan'],
    'experience': [1, 1, 5, 7, 7],
    'salary': [175.1, 180.2, 190.3, 205.4, 210.5],
}, index=['A', 'B', 'C', 'D', 'E'])

print(df)

print('-' * 50)

index_list = ['C', 'D', 'E', 'B', 'A']

new_df = df.reindex(labels=index_list)
print(new_df)

The code for this article is available on GitHub

Running the code sample produces the following output.

shell

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    name  experience  salary
A  Alice           1   175.1
B  Bobby           1   180.2
C   Carl           5   190.3
D    Dan           7   205.4
E  Ethan           7   210.5
--------------------------------------------------
    name  experience  salary
C   Carl           5   190.3
D    Dan           7   205.4
E  Ethan           7   210.5
B  Bobby           1   180.2
A  Alice           1   175.1

pandas reorder rows based on index list

The index_list variable stores a list with the indices in which we want to sort the DataFrame rows.

main.py

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index_list = ['C', 'D', 'E', 'B', 'A']

new_df = df.reindex(labels=index_list)

The DataFrame.reindex() method conforms a DataFrame to a new index with optional filling logic.

The only argument we passed to the method is labels - the new index to conform the row axis to.

# Sorting the `DataFrame` rows with `sort_index()`

If you need to sort the DataFrame rows by the index in ascending order, use the DataFrame.sort_index() method.

main.py

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import pandas as pd

df = pd.DataFrame({
    'name': ['Alice', 'Bobby', 'Carl', 'Dan', 'Ethan'],
    'experience': [1, 1, 5, 7, 7],
    'salary': [175.1, 180.2, 190.3, 205.4, 210.5],
}, index=['C', 'D', 'E', 'B', 'A'])

print(df)

print('-' * 50)

df = df.sort_index(ascending=True)
print(df)

The code for this article is available on GitHub

Running the code sample produces the following output.

shell

Copied!
    name  experience  salary
C  Alice           1   175.1
D  Bobby           1   180.2
E   Carl           5   190.3
B    Dan           7   205.4
A  Ethan           7   210.5
--------------------------------------------------
    name  experience  salary
A  Ethan           7   210.5
B    Dan           7   205.4
C  Alice           1   175.1
D  Bobby           1   180.2
E   Carl           5   190.3

sort dataframe rows with sort index

If you want to sort the DataFrame rows by the index in descending order, set the ascending argument to False.

main.py

Copied!
import pandas as pd

df = pd.DataFrame({
    'name': ['Alice', 'Bobby', 'Carl', 'Dan', 'Ethan'],
    'experience': [1, 1, 5, 7, 7],
    'salary': [175.1, 180.2, 190.3, 205.4, 210.5],
}, index=['C', 'D', 'E', 'B', 'A'])

print(df)

print('-' * 50)

df = df.sort_index(ascending=False)
print(df)

Running the code sample produces the following output.

shell

Copied!
    name  experience  salary
C  Alice           1   175.1
D  Bobby           1   180.2
E   Carl           5   190.3
B    Dan           7   205.4
A  Ethan           7   210.5
--------------------------------------------------
    name  experience  salary
E   Carl           5   190.3
D  Bobby           1   180.2
C  Alice           1   175.1
B    Dan           7   205.4
A  Ethan           7   210.5

sort dataframe rows by index in descending order

The DataFrame.sort_index() method sorts the DataFrame by its index.

The method returns a new DataFrame sorted by the index.

The sort_index() method takes an optional axis argument which determines the axis along which to sort.

By default, the axis argument is set to 0 (the rows axis).