numpy.hstack¶

numpy.
hstack
(tup)[source]¶ Stack arrays in sequence horizontally (column wise).
This is equivalent to concatenation along the second axis, except for 1D arrays where it concatenates along the first axis. Rebuilds arrays divided by
hsplit
.This function makes most sense for arrays with up to 3 dimensions. For instance, for pixeldata with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions
concatenate
,stack
andblock
provide more general stacking and concatenation operations. Parameters
 tupsequence of ndarrays
The arrays must have the same shape along all but the second axis, except 1D arrays which can be any length.
 Returns
 stackedndarray
The array formed by stacking the given arrays.
See also
concatenate
Join a sequence of arrays along an existing axis.
stack
Join a sequence of arrays along a new axis.
block
Assemble an ndarray from nested lists of blocks.
vstack
Stack arrays in sequence vertically (row wise).
dstack
Stack arrays in sequence depth wise (along third axis).
column_stack
Stack 1D arrays as columns into a 2D array.
hsplit
Split an array into multiple subarrays horizontally (columnwise).
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]])