python scipy 斯皮尔曼相关

Question

我正在尝试从数据帧 (df) 中获取列名称，并将它们与 spearmanr 相关函数生成的结果数组相关联。我需要将列名 (a-j) 关联回相关值 (spearman) 和 p 值 (spearman_pvalue)。有没有直观的方法来执行此任务？

from scipy.stats import pearsonr,spearmanr
import numpy as np
import pandas as pd

df=pd.DataFrame(np.random.randint(0,100,size= (100,10)),columns=list('abcdefghij'))

def binary(row):
    if row>=50:
        return 1
    else:
        return 0
df['target']=df.a.apply(binary)

spearman,spearman_pvalue=spearmanr(df.drop(['target'],axis=1),df.target)
print(spearman)
print(spearman_pvalue)

Answer 1

看来您需要：

from scipy.stats import spearmanr

df=pd.DataFrame(np.random.randint(0,100,size= (100,10)),columns=list('abcdefghij'))
#print (df)

#faster for binary df
df['target'] = (df['a'] >= 50).astype(int)
#print (df)

spearman,spearman_pvalue=spearmanr(df.drop(['target'],axis=1),df.target)

df1 = pd.DataFrame(spearman.reshape(-1, 11), columns=df.columns)
#print (df1)

df2 = pd.DataFrame(spearman_pvalue.reshape(-1, 11), columns=df.columns)
#print (df2)

### Kyle, we can assign the index back to the column names for the total matrix:
df2=df2.set_index(df.columns)
df1=df1.set_index(df.columns)

或者：

df1 = pd.DataFrame(spearman.reshape(-1, 11), 
                  columns=df.columns, 
                  index=df.columns)
df2 = pd.DataFrame(spearman_pvalue.reshape(-1, 11), 
                   columns=df.columns, 
                   index=df.columns)

python scipy 斯皮尔曼相关

python scipy spearman correlations

python

scipy

pandas

sklearn-pandas

pearson-correlation