Change the order of a Pandas DataFrame columns in Python
Let us see how to change the order of a DatFrame’s columns.
Algorithm :
- Create a DatFrame.
- Reassign the same DataFrame with the order of the columns changed.
- Print the DataFame.
Example 1 :
# importing the modules import pandas as pd import numpy as np # creating the DataFrame my_data = { 'Sr.no' : [ 1 , 2 , 3 , 4 , 5 ], 'Name' : [ 'Ram' , 'Sham' , 'Sonu' , 'Tinu' , 'Monu' ], 'Maths Score' : [ 45 , 67 , 89 , 74 , 56 ]} df = pd.DataFrame(data = my_data) # printing the original DataFrame print ( "My Original DataFrame" ) print (df) # altering the DataFrame df = df[[ 'Sr.no' , 'Maths Score' , 'Name' ]] # printing the altered DataFrame print ( 'After altering Name and Maths Score' ) print (df) |
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Output:
Example 2 :
# importing the modules import pandas as pd # creating the DataFrame l1 = [ "Amar" , "Barsha" , "Carlos" , "Tanmay" , "Misbah" ] l2 = [ "Alpha" , "Bravo" , "Charlie" , "Tango" , "Mike" ] l3 = [ 23 , 25 , 22 , 27 , 29 ] l4 = [ 69 , 54 , 73 , 70 , 74 ] df = pd.DataFrame( list ( zip (l1, l2, l3, l4))) df.columns = [ 'Name' , 'Code' , 'Age' , 'Weight' ] # printing the original DataFrame print ( "My Original DataFrame" ) print (df) # altering the DataFrame df = df[[ 'Name' , 'Code' , 'Weight' , 'Age' ]] # printing the altered DataFrame print ( 'After altering Weight and Age' ) print (df) |
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Output :
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