SUMIF Operation on multiple columns
Here we will use sumif operation on multiple columns.
Syntax: dataframe.groupby(‘group_column’)[[‘column_names’]].sum()
where,
- dataframe is the input dataframe
- group_column is the column in dataframe to be grouped
- column_names are to get sum of these columns with respect to grouped column
- sum() function is to perform the sum operation
Python3
# import pandas module import pandas as pd # create dataframe with 4 columns data = pd.DataFrame({ "name" : [ 'sravan' , 'jyothika' , 'harsha' , 'ramya' , 'sravan' , 'jyothika' , 'harsha' , 'ramya' , 'sravan' , 'jyothika' , 'harsha' , 'ramya' ], "subjects" : [ 'java' , 'java' , 'java' , 'python' , 'python' , 'python' , 'html/php' , 'html/php' , 'html/php' , 'php/js' , 'php/js' , 'php/js' ], "internal marks" : [ 98 , 79 , 89 , 97 , 82 , 98 , 90 , 87 , 78 , 89 , 93 , 94 ], "external marks" : [ 88 , 71 , 89 , 97 , 82 , 98 , 80 , 87 , 71 , 89 , 92 , 64 ], }) # find sum of columns group by name with # external marks and internal marks column print (data.groupby( 'name' )[[ 'external marks' , 'internal marks' ]]. sum ()) print ( "---------------" ) # find sum of columns group by subjects # with external marks and internal marks column print (data.groupby( 'subjects' )[[ 'external marks' , 'internal marks' ]]. sum ()) |
Output:
How to Perform a SUMIF Function in Pandas?
sumif() function is used to perform sum operation by a group of items in the dataframe, It can be applied on single and multiple columns and we can also use this function with groupby function.
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