根据列表计算DataFrame中的匹配值

Question

我有一个数据框，例如有一些项目标题

ratings_dict = {
    "TYPE": ["Testing","Headphone","Iphone","AC","Laptop","Monitor"],
}

df = pd.DataFrame(ratings_dict)

想要根据给定列表计算值：

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

预期输出：

注意：在这种情况下，单词“phone”与数据帧“Headphone”和“Iphone”中的 2 个值匹配，然后两者的计数都会递增.

任何建议或代码片段都会有所帮助。

Answer 1

由你来定义什么条件是有意义的，你的问题有点太笼统了。您可以检查值是否匹配，也可以在检查之前将一些列表值转换为默认值

Answer 2

您需要将所有内容都转换为小写，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]

根据列表计算DataFrame中的匹配值

Count Match value in DataFrame based on list

python

list

string-matching

dataframe

python-3.x