如下所示：

def append(arr, values, axis=None): """ 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.

numpy.append(arr, values, axis=None):

簡(jiǎn)答來(lái)說(shuō)，就是arr和values會(huì)重新組合成一個(gè)新的數(shù)組，做為返回值。而axis是一個(gè)可選的值

當(dāng)axis無(wú)定義時(shí)，是橫向加成，返回總是為一維數(shù)組！

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

當(dāng)axis有定義的時(shí)候，分別為0和1的時(shí)候。（注意加載的時(shí)候，數(shù)組要設(shè)置好，行數(shù)或者列數(shù)要相同。不然會(huì)有error：all the input array dimensions except for the concatenation axis must match exactly）

當(dāng)axis為0時(shí)，數(shù)組是加在下面（列數(shù)要相同）：

import numpy as npaa= np.zeros((1,8))bb=np.ones((3,8))c = np.append(aa,bb,axis = 0)print(c)

[[ 0. 0. 0. 0. 0. 0. 0. 0.] [ 1. 1. 1. 1. 1. 1. 1. 1.] [ 1. 1. 1. 1. 1. 1. 1. 1.] [ 1. 1. 1. 1. 1. 1. 1. 1.]]

當(dāng)axis為1時(shí)，數(shù)組是加在右邊（行數(shù)要相同）：

import numpy as npaa= np.zeros((3,8))bb=np.ones((3,1))c = np.append(aa,bb,axis = 1)print(c)

[[ 0. 0. 0. 0. 0. 0. 0. 0. 1.] [ 0. 0. 0. 0. 0. 0. 0. 0. 1.] [ 0. 0. 0. 0. 0. 0. 0. 0. 1.]]

以上這篇對(duì)numpy.append()里的axis的用法詳解就是小編分享給大家的全部?jī)?nèi)容了，希望能給大家一個(gè)參考，也希望大家多多支持武林站長(zhǎng)站。