How To Convert the Index Of a Pandas Dataframe To A Column – With Examples

Pandas dataframe contains an index that is used to identify rows uniquely.

You can convert the index of a pandas dataframe to a column using the df.reset_index(inplace=True) statement.

Basic Example

• The reset index method resets the existing index of the dataframe by making it a new column
• Uses the default index 0,1,...n as the index.

df.reset_index(inplace=True)

df

Dataframe Will Look Like

The index column is added as a new column of the dataframe, and the default index 0,1,..n is assigned as the index.

	index	First Name	Last Name	Country	Country Code
0	0	Shivam	Pandey	India	1
1	1	Kumar	Ram	US	2
2	2	Felix	John	Germany	3
3	3	Michael	John	India	1

This tutorial explains to you how to convert the index of a pandas dataframe to a column using different methods.

Creating Dataframe

Use the following code to create a Pandas dataframe.

It contains four columns with data.

No index is assigned explicitly. Hence, pandas will use the default index.

import pandas as pd 


users = [ ('Shivam', 'Pandey', 'India', 1),
             ('Kumar', 'Ram' , 'US', 2 ),
         ('Felix','John' , 'Germany', 3 ),
         ('Michael','John' , 'India', 1 ),
              ]


df = pd.DataFrame(  users, 
                    columns = ['First Name' , 'Last Name', 'Country', 'Country Code']
                    ) 

df

Dataframe Will Look Like

	First Name	Last Name	Country	Country Code
0	Shivam	Pandey	India	1
1	Kumar	Ram	US	2
2	Felix	John	Germany	3
3	Michael	John	India	1

Using Reset_index

You can use the reset_index method to convert the index of the pandas dataframe to a column.

The reset index method,

• Converts the existing index to a new column of the dataframe. Uses the name index for the new column
• After converting it, the default index 0,1,2..n is used as the index
• If there are no explicit index, the default index is converted into a column, and again, a default index will be created for the dataframe

inplace=True parameter is used to denote that the reset operation must be performed in the same dataframe instead of creating a new copy as a result.

Code

df.reset_index(inplace=True)

df

Dataframe Will Look Like

The sample dataframe doesn’t contain any explicit index. It has only the default one. Hence, it is converted as a column, and the default index is again used in the dataframe.

	index	First Name	Last Name	Country	Country Code
0	0	Shivam	Pandey	India	1
1	1	Kumar	Ram	US	2
2	2	Felix	John	Germany	3
3	3	Michael	John	India	1

Using Reset_index and New Column Header

This section teaches you how to convert the index of a pandas dataframe to a new column and use a new column header for the new column.

You can

• Convert the index to a new column using the reset_index() method.
• Use the Pandas rename method to use a new column header for the converted index column.

Code

df.reset_index(inplace=True)

df = df.rename(columns = {'index':'S.No.'})

df

Dataframe Will Look Like

The index column has the new name S.No.

	S.No.	First Name	Last Name	Country	Country Code
0	0	Shivam	Pandey	India	1
1	1	Kumar	Ram	US	2
2	2	Felix	John	Germany	3
3	3	Michael	John	India	1

This is how the rename method is used to use a new column header.

Using reset_axis and Reset_index

You can also use the rename_axis() method to rename the index column while converting it into a column.

• It first sets the name for the axis.
• By default, it uses the column axis. Hence, you need not use the axis parameter explicitly.

Code

The following code demonstrates how to rename the column axis.

df.rename_axis('S.No.',inplace=True)

df

Dataframe Will Look Like

The index is renamed as S.No.

	First Name	Last Name	Country	Country Code
S.No.
0	Shivam	Pandey	India	1
1	Kumar	Ram	US	2
2	Felix	John	Germany	3
3	Michael	John	India	1

Code

You can use the reset_index() method to convert the index of a pandas dataframe to a column.

df.reset_index(inplace=True)

df

Dataframe Will Look Like

The index column S.No. is converted to a column and added to the pandas dataframe.

	S.No.	First Name	Last Name	Country	Country Code
0	0	Shivam	Pandey	India	1
1	1	Kumar	Ram	US	2
2	2	Felix	John	Germany	3
3	3	Michael	John	India	1

Using Simple Assignment

You can use the assignment operator = to assign the index values as a new column to the dataframe.

Code

df['index'] = df.index

df

Dataframe Will Look Like

	First Name	Last Name	Country	Country Code	index
0	Shivam	Pandey	India	1	0
1	Kumar	Ram	US	2	1
2	Felix	John	Germany	3	2
3	Michael	John	India	1	3

Creating Multiple Index Dataframe

Pandas dataframe can contain multiple and multi-level indexes.

Create a dataframe with multiple indexes, namely ’Code’, ‘ID’.

Code

index_names = pd.MultiIndex.from_tuples([('A', '1'),
                                       ('B', '2'),
                                       ('C', '3'),
                                       ('D', '4')],
                                       names=['Code', 'ID'])

users = [ ('Shivam', 'Pandey', 'India', 1),
             ('Kumar', 'Ram' , 'US', 2 ),
         ('Felix','John' , 'Germany', 3 ),
         ('Michael','John' , 'India', 1 ),
              ]

df = pd.DataFrame(users,  columns = ['First Name' , 'Last Name', 'Country', 'Country Code'], index=index_names)

df

Dataframe Will Look Like

The sample dataframe contains two column indexes.

		First Name	Last Name	Country	Country Code
Code	ID
A	1	Shivam	Pandey	India	1
B	2	Kumar	Ram	US	2
C	3	Felix	John	Germany	3
D	4	Michael	John	India	1

Now you’ll use this dataframe to learn how to convert the multiple indexes to a column name.

Convert Multiindex to Multiple Columns

You can use the reset_index() method to convert the multiple indexes to multiple columns.

• Converts all the existing indexes into a new column
• Uses the default index as an index.

Code

df.reset_index(inplace=True)

df

Dataframe Will Look Like

	Code	ID	First Name	Last Name	Country	Country Code
0	A	1	Shivam	Pandey	India	1
1	B	2	Kumar	Ram	US	2
2	C	3	Felix	John	Germany	3
3	D	4	Michael	John	India	1

Convert Specific Indexes of Multiple Indexes into a column

You can use the reset_index() method to convert the specific indexes into a new column.

To convert a specific index,

• Use the level parameter.
• Pass the multiple columns as a list to this parameter.

Code

The following code demonstrates how to use the reset_index() method with the level = ['ID'] parameter to convert the index ID into a new column.

df.reset_index(inplace=True, level = ['ID'])

df

Dataframe Will Look Like

The id index is converted into a new column of the dataframe.

	ID	First Name	Last Name	Country	Country Code
Code
A	1	Shivam	Pandey	India	1
B	2	Kumar	Ram	US	2
C	3	Felix	John	Germany	3
D	4	Michael	John	India	1

Additional Resources

• How to Get The Index Of Rows Based On Column Value In Pandas Dataframe
• How to Remove the Index Column in Pandas While Reading from the CSV file