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Module « numpy.matlib »

Fonction append - module numpy.matlib

Signature de la fonction append

def append(arr, values, axis=None) 

Description

help(numpy.matlib.append)

Append values to the end of an array.

Parameters
----------
arr : array_like
    Values are appended to a copy of this array.
values : array_like
    These values are appended to a copy of `arr`.  It must be of the
    correct shape (the same shape as `arr`, excluding `axis`).  If
    `axis` is not specified, `values` can be any shape and will be
    flattened before use.
axis : int, optional
    The axis along which `values` are appended.  If `axis` is not
    given, both `arr` and `values` are flattened before use.

Returns
-------
append : ndarray
    A copy of `arr` with `values` appended to `axis`.  Note that
    `append` does not occur in-place: a new array is allocated and
    filled.  If `axis` is None, `out` is a flattened array.

See Also
--------
insert : Insert elements into an array.
delete : Delete elements from an array.

Examples
--------
>>> import numpy as np
>>> np.append([1, 2, 3], [[4, 5, 6], [7, 8, 9]])
array([1, 2, 3, ..., 7, 8, 9])

When `axis` is specified, `values` must have the correct shape.

>>> np.append([[1, 2, 3], [4, 5, 6]], [[7, 8, 9]], axis=0)
array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])

>>> np.append([[1, 2, 3], [4, 5, 6]], [7, 8, 9], axis=0)
Traceback (most recent call last):
    ...
ValueError: all the input arrays must have same number of dimensions, but
the array at index 0 has 2 dimension(s) and the array at index 1 has 1
dimension(s)

>>> a = np.array([1, 2], dtype=int)
>>> c = np.append(a, [])
>>> c
array([1., 2.])
>>> c.dtype
float64

Default dtype for empty ndarrays is `float64` thus making the output of dtype
`float64` when appended with dtype `int64`

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