Difference of two columns in Pandas dataframe (original) (raw)

Last Updated : 24 Dec, 2018

Difference of two columns in pandas dataframe in Python is carried out by using following methods :

Method #1 : Using ” -” operator.

import pandas as pd

df1 = { 'Name' :[ 'George' , 'Andrea' , 'micheal' ,

`` 'maggie' , 'Ravi' , 'Xien' , 'Jalpa' ],

`` 'score1' :[ 62 , 47 , 55 , 74 , 32 , 77 , 86 ],

`` 'score2' :[ 45 , 78 , 44 , 89 , 66 , 49 , 72 ]}

df1 = pd.DataFrame(df1,columns = [ 'Name' , 'score1' , 'score2' ])

print ( "Given Dataframe :\n" , df1)

df1[ 'Score_diff' ] = df1[ 'score1' ] - df1[ 'score2' ]

print ( "\nDifference of score1 and score2 :\n" , df1)

Output:

Given Dataframe : Name score1 score2 0 George 62 45 1 Andrea 47 78 2 micheal 55 44 3 maggie 74 89 4 Ravi 32 66 5 Xien 77 49 6 Jalpa 86 72

Difference of score1 and score2 : Name score1 score2 Score_diff 0 George 62 45 17 1 Andrea 47 78 -31 2 micheal 55 44 11 3 maggie 74 89 -15 4 Ravi 32 66 -34 5 Xien 77 49 28 6 Jalpa 86 72 14

Method #2 : Using sub() method of the Dataframe.

import pandas as pd

df1 = { 'Name' :[ 'George' , 'Andrea' , 'micheal' ,

`` 'maggie' , 'Ravi' , 'Xien' , 'Jalpa' ],

`` 'score1' :[ 62 , 47 , 55 , 74 , 32 , 77 , 86 ],

`` 'score2' :[ 45 , 78 , 44 , 89 , 66 , 49 , 72 ]}

df1 = pd.DataFrame(df1,columns = [ 'Name' , 'score1' , 'score2' ])

print ( "Given Dataframe :\n" , df1)

df1[ 'Score_diff' ] = df1[ 'score1' ].sub(df1[ 'score2' ], axis = 0 )

print ( "\nDifference of score1 and score2 :\n" , df1)

Output:

Given Dataframe : Name score1 score2 0 George 62 45 1 Andrea 47 78 2 micheal 55 44 3 maggie 74 89 4 Ravi 32 66 5 Xien 77 49 6 Jalpa 86 72

Difference of score1 and score2 : Name score1 score2 Score_diff 0 George 62 45 17 1 Andrea 47 78 -31 2 micheal 55 44 11 3 maggie 74 89 -15 4 Ravi 32 66 -34 5 Xien 77 49 28 6 Jalpa 86 72 14

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