使用Python查找最相似的行 [英] Find the most similar row using Python

问题描述

我有两个数据帧(df1和df2).在df1中，我将一行存储一组值，并希望在df2中找到最相似的行.

I have two data frames (df1 and df2). In the df1 I store one row with a set of values and I want to find the most similar row in the df2.

import pandas as pd
import numpy as np

# Df1 has only one row and four columns.
df1 = pd.DataFrame(np.array([[30, 60, 70, 40]]), columns=['A', 'B', 'C','D'])

# Df2 has 50 rows and four columns
df2 = pd.DataFrame(np.random.randint(0,100,size=(50, 4)), columns=list('ABCD'))

问题:基于df1，df2中最相似的行是什么?

Question: Based on the df1 what is the most similar row in df2?

推荐答案

如果需要最小距离，我们可以使用 scipy.spatial.distance.cdist

If you want the min distance , we can using scipy.spatial.distance.cdist

import scipy
ary = scipy.spatial.distance.cdist(df2, df1, metric='euclidean')
df2[ary==ary.min()]
Out[894]: 
     A   B   C   D
14  16  66  83  13

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