Pandas provide a convenient way to handle data and its transformation. Let’s see how can we convert a column to row name/index in Pandas.
Create a dataframe first with dict of lists.
Python3
# importing pandas as pdimport pandas as pd# Creating a dict of listsdata = {'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 dataframedf = pd.DataFrame(data) df |
Output:
Method #1: Using set_index() method.
Python3
# importing pandas as pdimport pandas as pd# Creating a dict of listsdata = {'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 dataframedf = pd.DataFrame(data)# Using set_index() method on 'Name' columndf = df.set_index('Name')df |
Output:
Now, set index name as None.
Python3
# set the index to 'None' via its name propertydf.index.names = [None]df |
Output:
Method #2: Using pivot() method.
In order to convert a column to row name/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 pdimport pandas as pd# Creating a dict of listsdata = {'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 dataframedf.pivot(index ='Result', columns ='name')df |
Output:
