我正在尝试弄清楚如何在 Python 中创建与 SUMIF 等效的函数。我目前的解决方案有效，但效率太低，运行需要 20 分钟。

什么是最有效的方法来实现我想要的结果？

这是我目前正在做的事情，归结为一个非常简单的形式。在“实际”代码中，还有更多条件。

**sales_data customer_1**
Transactions   | Product Dimension 4 | Product Dimension 2 | Product Dimension 3 | sum_of_sales
-------------- | ------------------- | ------------------- | --------------------| -------------
1              | 50                  | F80                 | ETQ546              | 80
2              | 50                  | F80                 | SAS978              | 20
3              | 50                  | C36                 | JBH148              | 10
4              | 50                  | F80                 | ETQ546              | 80
5              | 50                  | F80                 | SAS978              | 20
6              | 50                  | C36                 | JBH148              | 10
7              | 20                  | A20                 | OPW269              | 15
8              | 20                  | A20                 | DUW987              | 65
9              | 20                  | v90                 | OWQ897              | 47



**condition_types BEFORE ADDING SUMIF TO TABLE**
Transactions   | Type                | Product Dimensions  |
-------------- | ------------------- | ------------------- | 
customer_1     | ABC                 | 50                  | 
customer_1     | DEF                 | F80                 |
customer_1     | GHI                 | JBH148              | 


**condition_types AFTER ADDING SUMIF TO TABLE**
Transactions   | Type                | Product Dimensions  | sum_of_sales
-------------- | ------------------- | ------------------- | -------------
customer_1     | ABC                 | 50                  | 220
customer_1     | DEF                 | F80                 | 200
customer_1     | GHI                 | JBH148              | 20

定义 sumif 函数

def sumif(row, value_column):
    if row['Type'] == "ABC":
        filtered_data = sales_data.loc[
            (sales_data['Product_dimension_4'] == row['Product Dimensions'])
        ]
    elif row['Type'] == "DEF" and row['Product Dimensions'] in sales_data['Product_dimension_2'].unique():
        filtered_data = sales_data.loc[
            (sales_data['Product_dimension_2'] == row['Product Dimensions'])
        ]

    elif row['Type'] == "GHI" and row['Product Dimensions'] in sales_data['Product_dimension_3'].unique():
        filtered_data = sales_data.loc[
            (sales_data['Product_dimension_3'] == row['Product Dimensions'])
        ]

    else:
        return 0  # Return 0 instead of an empty string for consistency
    
    return filtered_data[value_column].sum()

使用 loc 应用 sumif 函数

condition_types['sum_of_sales'] = condition_types.apply(lambda row: sumif(row, value_column="sum_of_sales"), axis=1)

我希望这足够清楚并且例子不太复杂。