与数据框中的文本列匹配的单词列表答案

【问题标题】：List of words matched with text column in dataframe与数据框中的文本列匹配的单词列表
【发布时间】：2021-03-08 06:43:59
【问题描述】：

我有 2 个数据框，第一个是文本数据列（超过 10k 行），第二个是关键字（几乎 100 个列表）

数据帧 1：

           Text
a white house cat plays in garden
cat is a domestic species of small carnivorous mammal
cat is walking in garden behind white house
yellow banana is healthy

数据帧 2：

ID     Keywords
1    ['cat','white']
2    ['garden','white','cat']
3    ['domestic','mammal']

我想在数据框 1 中添加带有 ID 的列，其中最大字数与数据框 2 匹配。此外，如果超过 1 或 2 个 ID 之间存在联系，则将两个 ID 连接在一起。因此，在某些情况下，没有任何单词匹配，在这种情况下添加“不匹配”。

输出：

           Text                                                ID
a white house cat plays in garden                              2
cat is a domestic species of small carnivorous mammal          3
cat is walking in behind white house                           1,2
yellow banana is healthy                                       'No Match'

【问题讨论】：

标签： python-3.x pandas dataframe nlp keyword-search

【解决方案1】：

这会奏效。它创建每个关键字列表的匹配数列表，然后查找该列表中最大值的ID。

import pandas as pd
import ast

df1 = pd.DataFrame(['a white house cat plays in garden', 'cat is a domestic species of small carnivorous mammal', 'cat is walking in behind white house', 'yellow banana is healthy'], columns=['Text'])
df2 = pd.DataFrame([ { "ID": 1, "Keywords": "['cat','white']" }, { "ID": 2, "Keywords": "['garden','white','cat']" }, { "ID": 3, "Keywords": "['domestic','mammal']" } ])
df2['Keywords'] = df2['Keywords'].apply(ast.literal_eval)

def get_ids(text):
    matches = [len(set(text.split(" ")) & set(i)) for i in df2['Keywords']]
    matches_ids = [df2['ID'][index] for index, val in enumerate(matches) if val == max(matches) if max(matches)>0 ]
    return ", ".join(str(x) for x in matches_ids) if matches_ids else "No Match"
    
df1['ID'] = df1['Text'].apply(get_ids)

结果：

	Text	ID
0	a white house cat plays in garden	2
1	cat is a domestic species of small carnivorous mammal	3
2	cat is walking in behind white house	1, 2
3	yellow banana is healthy	No Match

【讨论】：