I'm trying to find distance correlation between columns, look at the code below. Most of time it returns higher than 1 result, which is not possible, because distance correlation is between 0 and 1. You can read about scipy's distance correlation here.
import numpy as np
from scipy.spatial import distance
x = np.random.uniform(-1, 1, 10000)
print distance.correlation(x, x**2)
1.00210811815
What is wrong here or how can I measure it?
upd1: Link to issue on github
Correlational distance is the inverse of correlation and only looks at the angle/similarity among patterns (sort of like normalization). Correlational distance goes from 0 - 2, with 0 being PERFECT correlation, 1 being no correlation, and 2 being PERFECT ANTICORRELATION. So a small correlational distance value means close together in correlational space (small angular difference). Corr = 1 – dist; Corr dist = 1 – corr; so while a high correlation = high relationship; LOW CORR DISTINANCE = high relationship