SUMIF Function on One Column
Here we are performing sumif operation on one particular column by grouping it with one column
Syntax: dataframe.groupby(‘group_column’)[‘column_name].sum()
where
- dataframe is the input dataframe
- group_column is the column in dataframe to be grouped
- column_name is to get sum of this column 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 internal marks column print(data.groupby('name')['internal marks'].sum()) print("---------------") # find sum of columns group by # name with external marks column print(data.groupby('name')['external marks'].sum()) print("---------------") # find sum of columns group by # subjects with internal marks column print(data.groupby('subjects')['internal marks'].sum()) print("---------------") # find sum of columns group by # subjects with external marks column print(data.groupby('subjects')['external 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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