numpy.concatenate¶
- numpy.concatenate((a1, a2, ...), axis=0)¶
Join a sequence of arrays along an existing axis.
Parameters: a1, a2, ... : sequence of array_like
The arrays must have the same shape, except in the dimension corresponding to axis (the first, by default).
axis : int, optional
The axis along which the arrays will be joined. Default is 0.
Returns: res : ndarray
The concatenated array.
See also
- ma.concatenate
- Concatenate function that preserves input masks.
- array_split
- Split an array into multiple sub-arrays of equal or near-equal size.
- split
- Split array into a list of multiple sub-arrays of equal size.
- hsplit
- Split array into multiple sub-arrays horizontally (column wise)
- vsplit
- Split array into multiple sub-arrays vertically (row wise)
- dsplit
- Split array into multiple sub-arrays along the 3rd axis (depth).
- stack
- Stack a sequence of arrays along a new axis.
- hstack
- Stack arrays in sequence horizontally (column wise)
- vstack
- Stack arrays in sequence vertically (row wise)
- dstack
- Stack arrays in sequence depth wise (along third dimension)
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.
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]])
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)