1、皮尔逊相关系数在统计学中,皮尔逊相关系数( Pearson correlation coefficient),又称皮尔逊积矩相关系数(Pearson product-moment correlation coefficient,简称 PPMCC或PCCs)。用于衡量两个变量X和Y之间的线性相关相关关系,值域在-1与1之间。
2、根据公式手写
import numpy as np
import pandas as pdfrom math import *
def multipl(a,b):
sumofab=0.0
for i in range(len(a)):
temp=a[i]*b[i]
sumofab+=temp
return sumofab
def cal_pccs(x,y):
n=len(x)
#求和
sum1=sum(x)
sum2=sum(y)
#求乘积之和
sumofxy=multipl(x,y)
#求平方和
sumofx2 = sum([pow(i,2) for i in x])
sumofy2 = sum([pow(j,2) for j in y])
num=sumofxy-(float(sum1)*float(sum2)/n)
#计算皮尔逊相关系数
den=sqrt((sumofx2-float(sum1**2)/n)*(sumofy2-float(sum2**2)/n))
return num/den
pct_chg = pd.Series({'000001.SZ':-1.7391, '000002.SZ':0.6250,'000004.SZ':1.1378,'002600.SZ':0.0000,'000010.SZ':-1.0013})
vol = pd.Series({'000001.SZ':249326.31,'000002.SZ':338224.97,'000004.SZ':211876.00,'000010.SZ':222782.00,'002600.SZ':342096.76})
print(cal_pccs(pct_chg, vol))
3、talib的函数
import talib as ta
import pandas as pdpct_chg = pd.Series({'000001.SZ':-1.7391, '000002.SZ':0.6250,'000004.SZ':1.1378,'002600.SZ':0.0000,'000010.SZ':-1.0013})
vol = pd.Series({'000001.SZ':249326.31,'000002.SZ':338224.97,'000004.SZ':211876.00,'000010.SZ':222782.00,'002600.SZ':342096.76})
print(ta.CORREL(pct_chg,vol,5)[-1])
4、numpy的函数
import numpy as np
import pandas as pd
pct_chg = pd.Series({'000001.SZ':-1.7391, '000002.SZ':0.6250,'000004.SZ':1.1378,'002600.SZ':0.0000,'000010.SZ':-1.0013})
vol = pd.Series({'000001.SZ':249326.31,'000002.SZ':338224.97,'000004.SZ':211876.00,'000010.SZ':222782.00,'002600.SZ':342096.76})
pccs = np.corrcoef(pct_chg, vol)
print(pccs[0][1])
5、scipy的函数
import numpy as np
import pandas as pd
from scipy.stats import pearsonr
pct_chg = pd.Series({'000001.SZ':-1.7391, '000002.SZ':0.6250,'000004.SZ':1.1378,'002600.SZ':0.0000,'000010.SZ':-1.0013})
vol = pd.Series({'000001.SZ':249326.31,'000002.SZ':338224.97,'000004.SZ':211876.00,'000010.SZ':222782.00,'002600.SZ':342096.76})
pccs = pearsonr(pct_chg, vol)
print(pccs[0])
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