NumPy

Previous topic

Indexing routines

Next topic

numpy.r_

numpy.c_

numpy.c_ = <numpy.lib.index_tricks.CClass object>

Translates slice objects to concatenation along the second axis.

This is short-hand for np.r_['-1,2,0', index expression], which is useful because of its common occurrence. In particular, arrays will be stacked along their last axis after being upgraded to at least 2-D with 1’s post-pended to the shape (column vectors made out of 1-D arrays).

See also

column_stack
Stack 1-D arrays as columns into a 2-D array.
r_
For more detailed documentation.

Examples

>>> np.c_[np.array([1,2,3]), np.array([4,5,6])]
array([[1, 4],
       [2, 5],
       [3, 6]])
>>> np.c_[np.array([[1,2,3]]), 0, 0, np.array([[4,5,6]])]
array([[1, 2, 3, ..., 4, 5, 6]])