例如，给定以下数据框（请注意，此列的原始数据是dtype（'0 '））

df = pd.DataFrame({'product_description': ["CUTLERY HVY DUTY FORKS", "XYZ DISP LQD SOAP", "ABCD FOOD STRG CNTNR"]})

如何有效地识别和分离缩写并产生类似的结果

product_description            abbreviations
0  CUTLERY HVY DUTY FORKS        [HVY]

1  XYZ DISP LQD SOAP             [XYZ,DISP,LQD]

2  ABCD FOOD STRG CNTNR          [ABCD,STRG,CNTNR]

所以我把这些缩写转换成完整的单词。
我试过这个：

import pandas as pd
import re

df = pd.DataFrame({'product_description': ["CUTLERY HVY DUTY FORKS", "XYZ DISP LQD SOAP", "ABCD FOOD STRG CNTNR"]})

def extract_abbreviations(description):
    abbreviation_pattern = r'\b[A-Z]{2,}(?![a-z])'  # Updated regular expression pattern to match abbreviations
    abbreviations = re.findall(abbreviation_pattern, description)
    return abbreviations

df['abbreviations'] = df['product_description'].apply(extract_abbreviations)
print(df)

但我得到的是

product_description            abbreviations
0  CUTLERY HVY DUTY FORKS        [CUTLERY,HVY,DUTY,FORKS]

1  XYZ DISP LQD SOAP             [XYZ,DISP,LQD,SOAP]

2  ABCD FOOD STRG CNTNR          [ABCD,FOOD,STRG,CNTNR]

非常感谢你的帮助。谢谢你