Question

我的数据框只有一列，该列有1000行。我需要比较所有行并找到所有行的Levenshtein距离。我如何计算python中的比率或距离

我有一个数据框如下：

  #Df 
  StepDescription
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如何计算所有这些的Levenshtein比率

代码我已编写迭代循环但迭代后如何继续。

  import Levenshtein
  import pandas as pd
  data_dist = pd.read_csv('path\Data_TestDescription.csv')
  df = pd.DataFrame(data_dist)
  for index, row in df.iterrows():

Answer 1

正如评论中所要求的那样，百分比是理想的，我会保留已接受的答案并仅添加新部分：

import numpy as np
import pandas as pd
from Levenshtein import distance
from itertools import product

#df = ...

dist = [distance(*x) for x in product(df.StepDescription, repeat=2)]

dist_df = pd.DataFrame(np.array(dist).reshape(df.shape[0], df.shape[0]))
dist_df

    0   1   2   3   4   5   6   7
0   0  23  23  13  29  25  25  28
1  23   0  18  18  23  18  18  23
2  23  18   0  20  25  21  19  24
3  13  18  20   0  27  19  21  26
4  29  23  25  27   0  26  23   5
5  25  18  21  19  26   0  19  25
6  25  18  19  21  23  19   0  21
7  28  23  24  26   5  25  21   0

dist_df_percentage = dist_df // min(x for x in dist if x > 0) * 100

     0    1    2    3    4    5    6    7
0    0  460  460  260  580  500  500  560
1  460    0  360  360  460  360  360  460
2  460  360    0  400  500  420  380  480
3  260  360  400    0  540  380  420  520
4  580  460  500  540    0  520  460  100
5  500  360  420  380  520    0  380  500
6  500  360  380  420  460  380    0  420
7  560  460  480  520  100  500  420    0

Answer 2

最后经过大量的例子我尝试使用fuzzratio获得精确的比率或百分比

from itertools import product
import numpy as np
import difflib
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
import editdistance
dist = np.empty(df.shape[0]**2, dtype=int) 
for i, x in enumerate(product(df.Stepdescription, repeat=2)): 
    dist[i] = fuzz.ratio(*x)
dist_df = pd.DataFrame(dist.reshape(-1, df.shape[0]))
out_csv= dist_df.to_csv('FuzzyRatio.csv', sep='\t')

如何计算python中我的列中行的Levenshtein比率/距离？

2 个答案: