Pearson Correlation from Scratch

The Pearson correlation coefficient measures how linearly related two variables are, from $-1$ to $1$ :

r = \frac{\sum_i (x_i - \bar x)(y_i - \bar y)}{\sqrt{\sum_i (x_i - \bar x)^2}\,\sqrt{\sum_i (y_i - \bar y)^2}}

Implement pearson(x, y) without using np.corrcoef or any library correlation function. If either input has zero variance, return 0.0.

Example

pearson([1, 2, 3, 4], [2, 4, 6, 8])   # 1.0