Pandas provides 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.
# imporing 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.
# 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.
# 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/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,
# 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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