UserWarning: X scores are null at iteration
CCA doesn't support sparse matrices. By default, you should assume scikit-learn estimators do not grok sparse matrices and check their docstrings to find out if by chance you found one that does.
(I admit the warning could have been friendlier.)
I am trying to run CCA for a multi label/text classification problem but keep getting following warning and an error which I think are related 

warnings.warn('Maximum number of iterations reached')
  /Library/Python/2.7/site-packages/sklearn/cross_decomposition/pls_.py:290:
  UserWarning: X scores are null at iteration 0   warnings.warn('X
  scores are null at iteration %s' % k)
warnings.warn('Maximum number of iterations reached')
  /Library/Python/2.7/site-packages/sklearn/cross_decomposition/pls_.py:290:
  UserWarning: X scores are null at iteration 1

warnings.warn('X scores are null at iteration %s' % k)
...
for all the 400 iterations and then following error at the end which I think is a side effect of above warning:

Traceback (most recent call last):   File "scikit_fb3.py", line 477,
  in 
      getCCA(shorttestfilepathPreProcessed)   File "scikit_fb3.py", line 318, in getCCA
      X_CCA = cca.fit(x_array, Y_indicator).transform(X)   File "/Library/Python/2.7/site-packages/sklearn/cross_decomposition/pls_.py",
  line 368, in transform
      Xc = (np.asarray(X) - self.x_mean_) / self.x_std_   File "/usr/local/bin/src/scipy/scipy/sparse/compressed.py", line 389, in
  sub
      raise NotImplementedError('adding a nonzero scalar to a ' NotImplementedError: adding a nonzero scalar to a sparse matrix is not
  supported

What could possibly be wrong?