# 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. stacked : ndarray The array formed by stacking the given arrays.

`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([, , ])
>>> b = np.array([, , ])
>>> np.vstack((a,b))
array([,
,
,
,
,
])
```

numpy.hstack

numpy.block