numpy.ma.row_stack¶

numpy.ma.row_stack(tup) = <numpy.ma.extras._fromnxfunction_seq instance at 0x52d1dc8c>¶

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:

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.

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.

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]])