Python 模糊匹配(FuzzyWuzzy)——只保留最佳匹配

Question

我正在尝试模糊匹配两个 csv 文件，每个文件包含一列名称，它们相似但不相同。

到目前为止我的代码如下:

import pandas as pd
from pandas import DataFrame
from fuzzywuzzy import process
import csv

save_file = open('fuzzy_match_results.csv', 'w')
writer = csv.writer(save_file, lineterminator = '\n')

def parse_csv(path):

with open(path,'r') as f:
    reader = csv.reader(f, delimiter=',')
    for row in reader:
        yield row


if __name__ == "__main__":
## Create lookup dictionary by parsing the products csv
data = {}
for row in parse_csv('names_1.csv'):
    data[row[0]] = row[0]

## For each row in the lookup compute the partial ratio
for row in parse_csv("names_2.csv"):
    #print(process.extract(row,data, limit = 100))
    for found, score, matchrow in process.extract(row, data, limit=100):
        if score >= 60:
            print('%d%% partial match: "%s" with "%s" ' % (score, row, found))
            Digi_Results = [row, score, found]
            writer.writerow(Digi_Results)


save_file.close()

输出如下:

Name11 , 90 , Name25 
Name11 , 85 , Name24 
Name11 , 65 , Name29

脚本运行良好。输出符合预期。但我要找的只是最佳匹配。

Name11 , 90 , Name25
Name12 , 95 , Name21
Name13 , 98 , Name22

所以我需要根据第 2 列中的最大值以某种方式删除第 1 列中的重复名称。它应该相当简单，但我似乎无法弄清楚。任何帮助将不胜感激。

Answer 1

fuzzywuzzy 的 process.extract() 以倒序返回列表，最匹配的排在最前面。

所以要找到最佳匹配，您可以将限制参数设置为 1 ，这样它只返回最佳匹配，如果大于 60 ，您可以将它写入csv，就像你现在做的那样。

例子-

from fuzzywuzzy import process
## For each row in the lookup compute the partial ratio
for row in parse_csv("names_2.csv"):

    for found, score, matchrow in process.extract(row, data, limit=1):
        if score >= 60:
            print('%d%% partial match: "%s" with "%s" ' % (score, row, found))
            Digi_Results = [row, score, found]
            writer.writerow(Digi_Results)