numpy.hstack

numpy.hstack(tup)

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]])