尝试sub模式"-\\d+$"

> setDT(df)[, identifier_edited := sub("-\\d+$", "", identifier)][]
     identifier number identifier_edited
1:      cat-123      5               cat
2: green-489743     25             green
3: orange-fish5     77      orange-fish5
4:  red-blue123     90       red-blue123
5:       dog-23     34               dog
6:      orange5     17           orange5
7:      reptile      9           reptile
8:     purple-2     11            purple

数据

> dput(df)
structure(list(identifier = c("cat-123", "green-489743", "orange-fish5",
"red-blue123", "dog-23", "orange5", "reptile", "purple-2"), number = c(5L,
25L, 77L, 90L, 34L, 17L, 9L, 11L)), class = "data.frame", row.names = c(NA,
-8L))

要识别以破折号结尾的字符串，后跟一个或多个数字，可以使用Regex。

import pandas as pd
import re

data = {
    'identifier': ['cat-123','example-2 , 'example-3'],
    'number': [5,25,77,1,2,3]
}
df = pd.DataFrame(data)

# Define a regular expression pattern
pattern = r'-\d+$'

# Function to extract the edited identifier
def extract_identifier(identifier):
    if re.search(pattern, identifier):
        return re.sub(pattern, '', identifier)
    return identifier

# Apply the function to create the new column
df['identifier_edited'] = df['identifier'].apply(extract_identifier)

# Display the resulting DataFrame
print(df)