如何在 Pandas 中执行 SUMIF函数？

sumif()函数用于对数据框中的一组项目进行求和运算，它可以应用于单列和多列，我们也可以将此函数与 groupby函数一起使用。

方法 1：使用 groupby() 对所有列进行 SUMIF

此函数用于显示所有列相对于分组列的总和

Syntax: dataframe.groupby(‘group_column’).sum()

where

• dataframe is the input dataframe
• group_column is the column in dataframe to be grouped
• sum() function is to perform the sum operation

创建包含 4 列的学生数据框

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],
})
  
# display dataframe
print(data)

输出：

通过对特定列进行分组来执行所有列的总和

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 all columns group by name
print(data.groupby('name').sum())
  
  
# find sum of all columns group by subjects
print(data.groupby('subjects').sum())

输出：

方法 2：一列上的 SUMIF函数

在这里，我们通过将某一列与一列分组来对某一列执行 sumif 操作

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())

输出：

方法3：多列SUMIF操作

这里我们将在多列上使用 sumif 操作。

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())

输出：