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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 np aa= 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 np aa= 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億速云。
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