基于列表计算DataFrame中的匹配值

您需要将所有内容转换为小写，然后计算 TYPE 是搜索历史项的子字符串的次数，反之亦然

import pandas as pd

ratings_dict = {
    "TYPE": ["Testing","Headphone","Iphone","AC","Laptop","Monitor"],
}
df = pd.DataFrame(ratings_dict)

Search_history=['test','phone','lap','testing','tes','iphone','Headphone','head','Monitor','ac']

# convert everything to lower case
Search_history = [ x.lower() for x in Search_history]
df['TYPE'] = [ x.lower() for x in df.TYPE]

# count up the number of times one of the TYPEs is a substring of a Search_history or a Search_history is a substring of a TYPE
df['count'] = [ sum( x in y or y in x for y in Search_history) for x in df.TYPE]