[python] How to get correlation of two vectors in python

In matlab I use

a=[1,4,6]
b=[1,2,3]
corr(a,b)

which returns .9934. I've tried numpy.correlate but it returns something completely different. What is the simplest way to get the correlation of two vectors?

The docs indicate that numpy.correlate is not what you are looking for:

numpy.correlate(a, v, mode='valid', old_behavior=False)[source]
  Cross-correlation of two 1-dimensional sequences.
  This function computes the correlation as generally defined in signal processing texts:
     z[k] = sum_n a[n] * conj(v[n+k])
  with a and v sequences being zero-padded where necessary and conj being the conjugate.

Instead, as the other comments suggested, you are looking for a Pearson correlation coefficient. To do this with scipy try:

from scipy.stats.stats import pearsonr   
a = [1,4,6]
b = [1,2,3]   
print pearsonr(a,b)

This gives

(0.99339926779878274, 0.073186395040328034)

You can also use numpy.corrcoef:

import numpy
print numpy.corrcoef(a,b)

This gives:

[[ 1.          0.99339927]
 [ 0.99339927  1.        ]]