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# numpy.ma.row_stack

`numpy.ma.``row_stack`(tup) = <numpy.ma.extras._fromnxfunction_seq instance>

  > Stack arrays in sequence vertically (row wise).

  > Take a sequence of arrays and stack them vertically to make a single array. Rebuild arrays divided by vsplit.

  > This function continues to be supported for backward compatibility, but you should prefer `np.concatenate` or `np.stack`. The `np.stack` function was added in NumPy 1.10.

  Parameters: | tup : sequence of ndarrays Tuple containing arrays to be stacked. The arrays must have the same shape along all but the first axis.
  Returns: | stacked : ndarray The array formed by stacking the given arrays.

  See also

  `stack`
    Join a sequence of arrays along a new axis.
  `hstack`
    Stack arrays in sequence horizontally (column wise).
  `dstack`
    Stack arrays in sequence depth wise (along third dimension).
  `concatenate`
    Join a sequence of arrays along an existing axis.
  `vsplit`
    Split array into a list of multiple sub-arrays vertically.
  `block`
    Assemble arrays from blocks.

  Notes

  The function is applied to both the _data and the _mask, if any.

  Examples

      >>> a = np.array([1, 2, 3])
      >>> b = np.array([2, 3, 4])
      >>> np.vstack((a,b))
      array([[1, 2, 3],
             [2, 3, 4]])

      >>> a = np.array([[1], [2], [3]])
      >>> b = np.array([[2], [3], [4]])
      >>> np.vstack((a,b))
      array([[1],
             [2],
             [3],
             [2],
             [3],
             [4]])