Previous topic

numpy.dstack

Next topic

numpy.vstack

numpy.hstack

numpy.hstack(tup)[source]

Stack arrays in sequence horizontally (column wise).

Take a sequence of arrays and stack them horizontally to make a single array. Rebuild arrays divided by hsplit.

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

All arrays must have the same shape along all but the second axis.

Returns:

stacked : ndarray

The array formed by stacking the given arrays.

See also

stack
Join a sequence of arrays along a new axis.
vstack
Stack arrays in sequence vertically (row wise).
dstack
Stack arrays in sequence depth wise (along third axis).
concatenate
Join a sequence of arrays along an existing axis.
hsplit
Split array along second axis.
block
Assemble arrays from blocks.

Notes

Equivalent to np.concatenate(tup, axis=1) if tup contains arrays that are at least 2-dimensional.

Examples

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