我有一个包含搜索词(数字和文本)的 CSV 文件,我想将其与其他词(数字和文本)列表进行比较,以确定是否存在任何匹配项或潜在匹配项。然后我希望将所有结果写入新的 CSV 中以供手动审核。我正在使用 fuzzywuzzy 插件创建一个“分数”来确定术语之间的匹配程度。理想情况下,我能够过滤比率。
我当前的代码将文件行一对一比较,而不是第一个文件中的一行与第二个文件中的所有行进行比较;这就是我需要的。
如何针对 file2 中的所有行对 file1 中的每一行执行模糊查找?
from fuzzywuzzy import fuzz
import csv
from itertools import zip_longest
f = open('FuzzyMatch2.csv', 'wt')
writer = csv.writer(f, lineterminator = '\n')
file1_loc = 'LookUp.csv'
file2_loc = 'Prod.csv'
file1 = csv.DictReader(open(file1_loc, 'r'), delimiter=',', quotechar='"')
file2 = csv.DictReader(open(file2_loc, 'r'), delimiter=',', quotechar='"')
for row in file1:
for l1, l2 in zip_longest(file1, file2):
if all((l1, l2)):
partial_ratio = fuzz.token_sort_ratio(str(l1['SearchTerm']), str(l2['Description']))
a = [l1,l2,partial_ratio]
writer.writerow(a)
f.close()
下面是上述代码的更简洁的版本,但仍然存在问题。代码报错
IndexError: list index out of range
知道如何使列表处于范围内并使代码正常工作吗?
from fuzzywuzzy import process
import csv
save_file = open('FuzzyResults.csv', 'wt')
writer = csv.writer(save_file, lineterminator = '\n')
def parse_csv(path):
with open(path,'r') as f:
for row in f:
row = row.split()
yield row
if __name__ == "__main__":
## Create lookup dictionary by parsing the products csv
data = {}
for row in parse_csv('Prod.csv'):
data[row[0]] = row[1]
## For each row in the lookup compute the partial ratio
for row in parse_csv("LookUp.csv"):
for found, score in process.extract(row, data, limit=100):
if score >= 10:
print('%d%% partial match: "%s" with "%s" ' % (score, row, found))
Digi_Results = [score, row, found]
writer.writerow(Digi_Results)
save_file.close()
最佳答案
下面的代码可以工作。确保安装了最新的 FuzzyWuzzy - 最后更新日期为 2015 年 4 月 28 日。否则您将收到“unicode”错误。希望这有帮助!
from fuzzywuzzy import process
import csv
save_file = open('FuzzyResults3.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('File1.csv'):
data[row[0]] = row[1]
## For each row in the lookup compute the partial ratio
for row in parse_csv("File2.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 = [score, row, found]
writer.writerow(Digi_Results)
save_file.close()
关于python - 模糊比较两列,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/30334510/