SciPy

numpy.vstack

numpy.vstack(tup)[source]

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

Equivalent to np.concatenate(tup, axis=0) if tup contains arrays that are at least 2-dimensional.

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]])

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