Question

I have a list of values and a 1-d numpy array, and I would like to calculate the correlation coefficient using numpy.corrcoef(x,y,rowvar=0). I get the following error:

Traceback (most recent call last):
File "testLearner.py", line 25, in <module>
corr = np.corrcoef(valuesToCompare,queryOutput,rowvar=0)
File "/usr/local/lib/python2.6/site-packages/numpy/lib/function_base.py", line 2003,  in corrcoef
c = cov(x, y, rowvar, bias, ddof)
File "/usr/local/lib/python2.6/site-packages/numpy/lib/function_base.py", line 1935, in cov
X = concatenate((X,y), axis)
ValueError: array dimensions must agree except for d_0

I printed out the shape for my numpy array and got (400,1). When I convert my list to an array with numpy.asarray(y) I get (400,)!

I believe this is the problem. I did an array.reshape to (400,1) and printed out the shape, and I still get (400,). What am I missing?

Thanks in advance.

Answer 1

I think you might have assumed that reshape modifies the value of the original array. It doesn’t:

>>> a = np.random.randn(5)
>>> a.shape
(5,)
>>> b = a.reshape(5,1)
>>> b.shape
(5, 1)
>>> a.shape
(5,)

---

np.asarray treats a regular list as a 1d array, but your original numpy array that you said was 1d is actually 2d (because its shape is (400,1)). If you want to use your list like a 2d array, there are two easy approaches:

• np.asarray(lst).reshape((-1, 1)) – -1 means “however many it needs” for that dimension”.
• np.asarray([lst]).T – .T means array transpose, which switches from (1,5) to (5,1).-

You could also reshape your original array to 1d via ary.reshape((-1,)).