numpy.vstack — NumPy v1.15 Manual (original) (raw)
Stack arrays in sequence vertically (row wise).
This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided byvsplit.
This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data 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: | tup : sequence of ndarrays The arrays must have the same shape along all but the first axis. 1-D arrays must have the same length. |
|---|---|
| Returns: | stacked : ndarray The array formed by stacking the given arrays, will be at least 2-D. |
See also
Join a sequence of arrays along a new axis.
Stack arrays in sequence horizontally (column wise).
Stack arrays in sequence depth wise (along third dimension).
Join a sequence of arrays along an existing axis.
Split array into a list of multiple sub-arrays vertically.
Assemble arrays from blocks.
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]])