# 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]])

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