Python 为凌乱的数据替换部分字符串（以更快的方式代替字符串替换）？

我想替换产品变体的许多值

Big Ben Personalized Products AVENGERS – Stark / 2 set                                                2
BigBen Personalized Products Expendables – Statham / 2 set                                            2
BigBen Personalized Toy 20.00% Off Auto renew Adults Toy / 5 set                                      2
BigBen Personalized Toy 20.00% Off Auto renew Adults Toy / 3 set                                       1
Personalized Toy 5 set                                                                                  1
BIG BEN Personalized  Machine 20.00% Off Auto renew (Versand jeden 3 Monate) Kids Toy / 3 set    1
BigBen Personalized Toy 20.00% Off Auto renew (Versand jeden 2 Monate) Kids Toy / 5 set            1
BigBen Personalized Toy 20.00% Off Auto renew (Versand jeden 2 Monate) Adults Toy / 5 set              1
BigBen Personalized Products 20.00% Off Auto renew (Versand jeden 5 Monate) Adults Toy / 5 set                   

有许多产品变体实际上具有相同的值

我想知道是否有比使用更快捷的方法：

df["product_variant"]= df["product_variant"].str.replace('BigBen Personalized', '',case = False) 
df["product_variant"]= df["product_variant"].str.replace('Big Ben Personalized ', '',case = False)
df["product_variant"]= df["product_variant"].str.replace('BigBen Personalized', '',case = False)
df["product_variant"]= df["product_variant"].str.replace('Auto renew', '',case = False) 

---

一个选项是为这些示例创建一个带有2个捕获组的特定模式

对于大多数项目，在

产品

之后或

成人

或

儿童

• 在组1中捕获

  /

  之前的零件（如果存在）
• 在第2组中捕获1或数字后接

  set

示例模式

^(?:big\s*ben personalized (?:products\s+)?(?:.*?(?=Adult|Kids))?|personalized\s+)(\w+(?: \w+)*(?: – \w+(?: \w+)*)?)(?: /)? (\d+ set)\b.*

在替换中使用2个捕获组

\1（\2）

输出

                 product_variant
0       AVENGERS – Stark (2 set)
1  Expendables – Statham (2 set)
2             Adults Toy (5 set)
3             Adults Toy (3 set)
4                    Toy (5 set)
5               Kids Toy (3 set)
6               Kids Toy (5 set)
7             Adults Toy (5 set)
8             Adults Toy (5 set)

---

答案出来了吗？

import pandas as pd

regex = r"^Event:\s+Task_(\d+)Error:(NO_ERROR|ERROR_(?:MINOR|\d+))(?:\w+:(\w+))?"

items = [
    "Big Ben Personalized Products AVENGERS – Stark / 2 set                                                2",
    "BigBen Personalized Products Expendables – Statham / 2 set                                            2",
    "BigBen Personalized Toy 20.00% Off Auto renew Adults Toy / 5 set                                      2",
    "BigBen Personalized Toy 20.00% Off Auto renew Adults Toy / 3 set                                       1",
    "Personalized Toy 5 set                                                                                  1",
    "BIG BEN Personalized  Machine 20.00% Off Auto renew (Versand jeden 3 Monate) Kids Toy / 3 set    1",
    "BigBen Personalized Toy 20.00% Off Auto renew (Versand jeden 2 Monate) Kids Toy / 5 set            1",
    "BigBen Personalized Toy 20.00% Off Auto renew (Versand jeden 2 Monate) Adults Toy / 5 set              1",
    "BigBen Personalized Products 20.00% Off Auto renew (Versand jeden 5 Monate) Adults Toy / 5 set                   "
]


df = pd.DataFrame(items, columns=["product_variant"])
df["product_variant"] = df["product_variant"].replace(
    r'(?i)^(?:big\s*ben personalized (?:products\s+)?(?:.*?(?=Adult|Kids))?|personalized\s+)(\w+(?: \w+)*(?: – \w+(?: \w+)*)?)(?: /)? (\d+ set)\b.*',
    r'\1 (\2)',
    regex=True
)
print(df)

                 product_variant
0       AVENGERS – Stark (2 set)
1  Expendables – Statham (2 set)
2             Adults Toy (5 set)
3             Adults Toy (3 set)
4                    Toy (5 set)
5               Kids Toy (3 set)
6               Kids Toy (5 set)
7             Adults Toy (5 set)
8             Adults Toy (5 set)