Documentary - The Next Big World Economic Crisis

Python Snippet - Pearson Correlation function

Here's the code I wrote in Python to calculate the Pearson Correlation. It works just like the Java version.

def get_Pearson_Correlation(dataseries1, dataseries2):
    result = 0.0
    sum_sq_x = 0.0
    sum_sq_y = 0.0
    sum_coproduct = 0.0
    mean_x = dataseries1[0]
    mean_y = dataseries2[0]

    for i in range(2,len(dataseries1)+1):
        sweep = (i-1)/float(i)
        delta_x = dataseries1[i-1]-mean_x
        delta_y = dataseries2[i-1]-mean_y
        sum_sq_x += delta_x * delta_x * sweep
        sum_sq_y += delta_y * delta_y * sweep
        sum_coproduct += delta_x * delta_y * sweep
        mean_x += delta_x / float(i)
        mean_y += delta_y / float(i)

    pop_sd_x = (sum_sq_x / float(len(dataseries1)))**0.5
    pop_sd_y = (sum_sq_y / float(len(dataseries1)))**0.5
    cov_x_y = sum_coproduct / float(len(dataseries1))

    result = cov_x_y / (pop_sd_x*pop_sd_y)

    return result

Java Snippet - Pearson Correlation function

I am not certain the math is completely correct, regardless, this might serve as a good base to build upon or improve. If you encounter errors feel free to comment!

public class PearsonCorrelation {
   
    public static double getPearsonCorrelation(double[] scores1, double[] scores2){
        double result = 0;
        double sum_sq_x = 0;
        double sum_sq_y = 0;
        double sum_coproduct = 0;
        double mean_x = scores1[0];
        double mean_y = scores2[0];
       
        for(int i=2;i<scores1.length+1;i+=1){
            double sweep = Double.valueOf(i-1)/i;
            double delta_x = scores1[i-1]-mean_x;
            double delta_y = scores2[i-1]-mean_y;
            sum_sq_x += delta_x * delta_x * sweep;
            sum_sq_y += delta_y * delta_y * sweep;
            sum_coproduct += delta_x * delta_y * sweep;
            mean_x += delta_x / i;
            mean_y += delta_y / i;
        }
       
        double pop_sd_x = (double) Math.sqrt(sum_sq_x/scores1.length);
        double pop_sd_y = (double) Math.sqrt(sum_sq_y/scores1.length);
        double cov_x_y = sum_coproduct / scores1.length;
       
        result = cov_x_y / (pop_sd_x*pop_sd_y);
       
        return result;
    }
}