更快地计算距离矩阵

Question

我有一个数据框

import numpy as np
from fuzzywuzzy import fuzz
from fuzzywuzzy import process
import pandas as pd
a = {'b':['cat','bat','cat','cat','bat','No Data','bat','No Data']}
df11 = pd.DataFrame(a,index=['x1','x2','x3','x4','x5','x6','x7','x8'])

我有一个距离函数

def distancemetric(x):
    list1 = x['b'].tolist()
    result11 =[]
    sortlist11 = [process.extract(ele, list1, limit=11000000, scorer=fuzz.token_set_ratio) for ele in list1]
    d11 = [dict(element) for element in sortlist11]
    finale11 = [(k, element123[k]) for k in list1 for element123 in d11]
    result11.extend([x[1] for x in finale11])
    final_result11=np.reshape(result11, (len(x.index),len(x.index)))
    return final_result11

我将功能称为

values1 = distancemetric(df11)

此处token_set_ratio方法仅比较两个字符串。当我传递字符串数组时，它会给我我不需要的平均值。

此代码有效，但速度较慢。有什么方法可以使其运行更快