Python | Pandas Index.to_frame() (original) (raw)

Last Updated : 24 Dec, 2018

Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas **Index.to_frame()** function create a dataFrame from the given index with a column containing the Index. By default, the original Index is reused in the new dataframe. To reinforce a new index for the newly created dataframe, we set the index parameter of the function to be false.

Syntax: Index.to_frame(index=True)Parameters : index : Set the index of the returned DataFrame as the original Index.Returns : DataFrame containing the original Index data.

Example #1: Use Index.to_frame() function to convert the index into a dataframe.

Python3 `

importing pandas as pd

import pandas as pd

Creating the index

idx = pd.Index(['Alice', 'Bob', 'Rachel', 'Tyler', 'Louis'], name ='Winners')

Print the Index

idx

`

Output : Let's convert the index into a dataframe.

Python3 `

convert the index into a dataframe

idx.to_frame()

`

Output : The function has converted the index into a dataframe. By default the function has created the index of the dataframe using the values of the original Index.Example #2: Use Index.to_frame() function to convert the index into a dataframe such that the dataframe created uses new index value.

Python3 `

importing pandas as pd

import pandas as pd

Creating the index

idx = pd.Index([22, 54, 85, 45, 69, 33])

Print the Index

idx

`

Output : Let's convert the index into a dataframe.

Python3 `

convert the index into a dataframe

idx.to_frame(index = False)

`

Output :