皮尔森相关性系数的计算python代码（一）

素颜马尾好姑娘i 2023-09-30 11:30 43阅读 0赞

**部分代码**

from math import sqrt
    import numpy as np
    import pandas as pd
    
    def excel_one_line_to_list():
        def multipl(a, b):
            sumofab = 0.0
            for i in range(len(a)):
                temp = a[i] * b[i]
                sumofab += temp
            return sumofab
    
        def corrcoef(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
    
        df = pd.read_excel("G:\文件夹1\文件夹2\文件夹3\data.xls", usecols=[0], names=None)  # 读取项目名称列,不要列名
        df = np.array(df)
    
        df2 = pd.read_excel("G:\文件夹1\文件夹2\文件夹3\data.xls", usecols=[1], names=None)  # 读取项目名称列,不要列名
        df2 = np.array(df2)
        print(corrcoef(df, df2))
    if __name__ == '__main__':
        excel_one_line_to_list()

**实验结果**  
![在这里插入图片描述][aced0fc86fc649e48c72f2aa5c130104.png]  
**完整代码链接：**[皮尔森相关性系数的计算python代码（一）][python]  
**相关链接**  
1、[皮尔森相关性系数的计算python代码（一）][python 1]  
2、[皮尔森相关性系数的计算python代码（二）][python 2]  
3、[皮尔森相关性系数的计算python代码（三）][python 3]  
4、[皮尔森相关性系数的计算python代码（四）（热力图版）][python 4]  
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[aced0fc86fc649e48c72f2aa5c130104.png]: https://img-blog.csdnimg.cn/aced0fc86fc649e48c72f2aa5c130104.png
[python]: https://download.csdn.net/download/blbyu/85262984
[python 1]: https://blog.csdn.net/blbyu/article/details/123798839
[python 2]: https://blog.csdn.net/blbyu/article/details/123798928
[python 3]: https://blog.csdn.net/blbyu/article/details/124533233?csdn_share_tail=%7B%22type%22:%22blog%22,%22rType%22:%22article%22,%22rId%22:%22124533233%22,%22source%22:%22blbyu%22%7D&ctrtid=xKIV8
[python 4]: https://blog.csdn.net/blbyu/article/details/124541289
[python 5]: https://blog.csdn.net/blbyu/article/details/123798294