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How to Convert Dataframe column into an index in Python-Pandas?

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  • Last Updated : 21 Jul, 2021

Pandas provide a convenient way to handle data and its transformation. Let’s see how can we convert a data frame column to row name or index in Pandas. 
Create a dataframe first with dict of lists. 
 

Python3




# importing pandas as pd
import pandas as pd
 
# Creating a dict of lists
data = {'Name':["Akash", "Geeku", "Pankaj", "Sumitra", "Ramlal"],
       'Branch':["B.Tech", "MBA", "BCA", "B.Tech", "BCA"],
       'Score':["80", "90", "60", "30", "50"],
       'Result': ["Pass", "Pass", "Pass", "Fail", "Fail"]}
 
# creating a dataframe
df = pd.DataFrame(data)
  
df

Output: 
 

Method #1: Using set_index() method.
 

Python3




# importing pandas as pd
import pandas as pd
 
# Creating a dict of lists
data = {'Name':["Akash", "Geeku", "Pankaj", "Sumitra", "Ramlal"],
       'Branch':["B.Tech", "MBA", "BCA", "B.Tech", "BCA"],
       'Score':["80", "90", "60", "30", "50"],
       'Result': ["Pass", "Pass", "Pass", "Fail", "Fail"]}
 
# Creating a dataframe
df = pd.DataFrame(data)
 
# Using set_index() method on 'Name' column
df = df.set_index('Name')
 
df

Output: 
 

Now, set index name as None. 
 

Python3




# set the index to 'None' via its name property
df.index.names = [None]
 
df

Output: 
 

 
Method #2: Using pivot() method.
In order to convert a column to row name or index in dataframe, Pandas has a built-in function Pivot. Now, let’s say we want Result to be the rows/index, and columns be name in our dataframe, to achieve this pandas has provided a method called Pivot. Let us see how it works,
 

Python3




# importing pandas as pd
import pandas as pd
 
# Creating a dict of lists
data = {'name':["Akash", "Geeku", "Pankaj", "Sumitra", "Ramlal"],
       'Branch':["B.Tech", "MBA", "BCA", "B.Tech", "BCA"],
       'Score':["80", "90", "60", "30", "50"],
       'Result': ["Pass", "Pass", "Pass", "Fail", "Fail"]}
 
df = pd.DataFrame(data)
 
# pivoting the dataframe
df.pivot(index ='Result', columns ='name')
 
df

Output: 
 

 


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