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Python | Pandas Index.to_frame()
  • 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.




# 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.




# 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.




# 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.




# convert the index into a dataframe
idx.to_frame(index = False)

Output :

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