# dask.array.vstack

dask.array.vstack(tup, allow_unknown_chunksizes=False)

  Stack arrays in sequence vertically (row wise).

  This docstring was copied from numpy.vstack.

  Some inconsistencies with the Dask version may exist.

  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 by vsplit.

  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 and block 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. In the case of a single array_like input, it will be treated as a sequence of arrays; i.e., each element along the zeroth axis is treated as a separate array.

    dtype str or dtype (Not supported in Dask)

      If provided, the destination array will have this dtype. Cannot be provided together with out.

      Added in version 1.24.

    casting{‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional (Not supported in Dask)

      Controls what kind of data casting may occur. Defaults to ‘same_kind’.

      Added in version 1.24.

  Returns:
    stacked ndarray

      The array formed by stacking the given arrays, will be at least 2-D.

  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 nd-array from nested lists of blocks.

  `hstack`

    Stack arrays in sequence horizontally (column wise).

  `dstack`

    Stack arrays in sequence depth wise (along third axis).

  `column_stack`

    Stack 1-D arrays as columns into a 2-D array.

  `vsplit`

    Split an array into multiple sub-arrays vertically (row-wise).

  `unstack`

    Split an array into a tuple of sub-arrays along an axis.

  Examples

      >>> import numpy as np
      >>> a = np.array([1, 2, 3])
      >>> b = np.array([4, 5, 6])
      >>> np.vstack((a,b))
      array([[1, 2, 3],
             [4, 5, 6]])

      >>> a = np.array([[1], [2], [3]])
      >>> b = np.array([[4], [5], [6]])
      >>> np.vstack((a,b))
      array([[1],
             [2],
             [3],
             [4],
             [5],
             [6]])