concatenate((a1, a2, ...), axis=0, out=None, dtype=None, casting="same_kind")

Notes

When one or more of the arrays to be concatenated is a MaskedArray, this function will return a MaskedArray object instead of an ndarray, but the input masks are not preserved. In cases where a MaskedArray is expected as input, use the ma.concatenate function from the masked array module instead.

Parameters

a1, a2, ... : sequence of array_like

The arrays must have the same shape, except in the dimension corresponding to :None:None:`axis` (the first, by default).

axis : int, optional

The axis along which the arrays will be joined. If axis is None, arrays are flattened before use. Default is 0.

out : ndarray, optional

If provided, the destination to place the result. The shape must be correct, matching that of what concatenate would have returned if no out argument were specified.

dtype : str or dtype

If provided, the destination array will have this dtype. Cannot be provided together with :None:None:`out`.

versionadded

casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional

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

versionadded

Returns

res : ndarray

The concatenated array.

Join a sequence of arrays along an existing axis.

See Also

array_split

Split an array into multiple sub-arrays of equal or near-equal size.

block

Assemble arrays from blocks.

column_stack

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

dsplit

Split array into multiple sub-arrays along the 3rd axis (depth).

dstack

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

hsplit

Split array into multiple sub-arrays horizontally (column wise).

hstack

Stack arrays in sequence horizontally (column wise).

ma.concatenate

Concatenate function that preserves input masks.

split

Split array into a list of multiple sub-arrays of equal size.

stack

Stack a sequence of arrays along a new axis.

vsplit

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

vstack

Stack arrays in sequence vertically (row wise).

Examples

>>> a = np.array([[1, 2], [3, 4]])
... b = np.array([[5, 6]])
... np.concatenate((a, b), axis=0)
array([[1, 2],
       [3, 4],
       [5, 6]])

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

>>> np.concatenate((a, b), axis=None)
array([1, 2, 3, 4, 5, 6])

This function will not preserve masking of MaskedArray inputs.

>>> a = np.ma.arange(3)
... a[1] = np.ma.masked
... b = np.arange(2, 5)
... a
masked_array(data=[0, --, 2],
             mask=[False,  True, False],
       fill_value=999999)

>>> b
array([2, 3, 4])

>>> np.concatenate([a, b])
masked_array(data=[0, 1, 2, 2, 3, 4],
             mask=False,
       fill_value=999999)

>>> np.ma.concatenate([a, b])
masked_array(data=[0, --, 2, 2, 3, 4],
             mask=[False,  True, False, False, False, False],
       fill_value=999999)

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.hstack numpy.stack numpy.column_stack numpy.ma.extras.dstack numpy.ma.extras.hstack numpy.ma.extras.stack numpy.lib.index_tricks.RClass numpy.block numpy.ma.core.concatenate numpy.vstack numpy.dstack numpy.split numpy.insert numpy.ma.extras.vstack numpy.ma.extras.column_stack

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