How to Sort a Pandas DataFrame by Both Index and Column?

In this article, we will discuss how to sort a Pandas dataframe by both index and columns.

Sort DataFrame based on Index

We can sort a Pandas DataFrame based on Index and column using sort_index method.

• To sort the DataFrame based on the index we need to pass axis=0 as a parameter to sort_index method.
• To sort the DataFrame based on the column name then we need to pass axis=1 as a parameter to sort_index method.

Syntax

DataFrame_Name.sort_index(axis=0, ascending=True, inplace=False, kind='quicksort')

Parameters

• axis- Specifies on which basis to sort whether based on index or column. By default, it sorts based on index i.e. axis=0.
• ascending- Specifies on which order to sort whether in ascending or descending order. It accepts True or False. By default it is True.
• inplace- It specifies that the changes to the DataFrame is Temporary or Permanent. inplace=False indicates temporary and True indicates permanent.
• kind- Specifies which sorting algorithm to use. It accepts quicksort, mergesort, heapsort, etc. By default, it is quicksort if not mentioned.

DataFrame

This was the DataFrame we are using in the below codes for sorting. By specifying axis=0 in sort_index method we can sort the DataFrame. Even if we don't specify axis parameter in sort_index  by default it sorts the DataFrame based on row.

Example:

 In this example, the DataFrame is a sorted DataFrame based on index labels and this was temporarily sorted in python language.

Output

original DataFrame
 col2 col1
3 150 70
2 170 55
1 160 60
Sorted by index col2 col1
1 160 60
2 170 55
3 150 70

Sort DataFrame based on columns

To sort the data in the DataFrame on the basis of column names, then we need to pass axis=1 as a parameter to sort_index method in python language.

Output

original DataFrame
 col2 col1
3 150 70
2 170 55
1 160 60
Sorted by column name col1 col2
3 70 150
2 55 170
1 60 160

Example Code to sort the DataFrame & save changes permanently on original DataFrame:

Here the sort operation is performed directly on the original DataFrame and changes are saved permanently because of inplace=True argument.

Output

original DataFrame
 col2 col1
3 150 70
2 170 55
1 160 60
Modified Original DataFrame
 col1 col2
3 70 150
2 55 170
1 60 160