Python模糊匹配（FuzzyWuzzy）-仅保留最佳匹配

Question

我试图模糊匹配两个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

该脚本工作正常。输出是预期的。但是我所寻找的只是最佳的匹配。

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

因此，我需要基于第2列中的最大值，以某种方式删除第1列中的重复名称。这应该相当简单，但是我似乎无法弄清楚。任何帮助，将不胜感激。

Answer 1

Fuzzywuzzy会process.extract()以反向排序的顺序返回列表，最佳匹配排在最前面。

因此，要找到最佳匹配项，可以将limit参数设置为1，以便它仅返回最佳匹配项；如果大于60，则可以像现在一样将其写入csv。

范例-

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)