基于关键词的模糊匹配

Question

I have two tables我有两张桌子

df_1

df_2

Is there any way I could develop a fuzzy match logic (either in Python or in R) to find ID from df_2 for df_1 ?有什么方法可以开发模糊匹配逻辑（在 Python 或 R 中）来从df_2为df_1查找ID ？

The match should be based on fuzzy name match, accurate city , state and zip match.匹配应基于模糊name匹配，准确的city 、 state和zip匹配。 If I couldn't find a match in city_1 , I would look for match in city_2 .如果我在city_1找不到匹配city_1 ，我会在city_2查找匹配city_2 。 If I couldn't find a match in state_1 , I would look for a match in state_2 .如果在state_1找不到匹配state_1 ，我会在state_1查找匹配state_2 。 The same thing for df_2 . df_2 。 If I couldn't find a fuzzy name match in NAME_1 , I would go to find a fuzzy match at NAME_2 .如果我在NAME_1找不到模糊名称匹配，我会在NAME_2找到一个模糊匹配。

The expected output should be like below:预期输出应如下所示：

Answer 1

Checkout fuzzywuzzy library.结帐fuzzywuzzy库。 It uses Lavenstein distance to compare matches.它使用 Lavenstein 距离来比较匹配。 If you are not convinced by the results, you can use n gram analysis .如果您不相信结果，您可以使用n gram analysis 。

基于关键词的模糊匹配

问题描述

1 个解决方案

解决方案1
0 2020-09-17 20:02:05

基于关键词的模糊匹配

问题描述

1 个解决方案

解决方案1 0 2020-09-17 20:02:05

解决方案1
0 2020-09-17 20:02:05