比较csv的两列，并在另一个csv中输出字符串相似性比率 [英] Comparing two columns of a csv and outputting string similarity ratio in another csv

问题描述

我对python编程很新。我试图采取一个csv文件，它有两列字符串值，并希望比较两列之间的字符串的相似比。然后我想取值并在另一个文件中输出比率。

I am very new to python programming. I am trying to take a csv file that has two columns of string values and want to compare the similarity ratio of the string between both columns. Then I want to take the values and output the ratio in another file.

csv可能如下所示：

The csv may look like this:

Column 1|Column 2 
tomato|tomatoe 
potato|potatao 
apple|appel 

我想要为每一行显示输出文件，列1中的字符串与列2的相似程度。我使用difflib输出比率分数。

I want the output file to show for each row, how similar the string in Column 1 is to Column 2. I am using difflib to output the ratio score.

是我到目前为止的代码：

This is the code I have so far:

import csv
import difflib

f = open('test.csv')

csf_f = csv.reader(f)

row_a = []
row_b = []

for row in csf_f:
    row_a.append(row[0])
    row_b.append(row[1])

a = row_a
b = row_b

def similar(a, b):
    return difflib.SequenceMatcher(a, b).ratio()

match_ratio = similar(a, b)

match_list = []
for row in match_ratio:
    match_list.append(row)

with open("output.csv", "wb") as f:
    writer = csv.writer(f, delimiter=',')
    writer.writerows(match_list)

f.close()

我得到错误：

Traceback (most recent call last):
  File "comparison.py", line 24, in <module>
    for row in match_ratio:
TypeError: 'float' object is not iterable

我觉得我不是正确地导入列列表，并对sequencematcher函数运行它。

I feel like I am not importing the column list correctly and running it against the sequencematcher function.

推荐答案

使用 pandas / a>：

Here is another way to get this done using pandas:

考虑您的csv数据如下：

Column 1,Column 2 
tomato,tomatoe 
potato,potatao 
apple,appel

CODE

import pandas as pd
import difflib as diff
#Read the CSV
df = pd.read_csv('datac.csv')
#Create a new column 'diff' and get the result of comparision to it
df['diff'] = df.apply(lambda x: diff.SequenceMatcher(None, x[0].strip(), x[1].strip()).ratio(), axis=1) 
#Save the dataframe to CSV and you could also save it in other formats like excel, html etc
df.to_csv('outdata.csv',index=False)

结果

Column 1,Column 2 ,diff
tomato,tomatoe ,0.923076923077
potato,potatao ,0.923076923077
apple,appel ,0.8

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