numpy基本操作(二)

在jupyternotebook下面输入&＃xff1a;

import numpy as np
a&＃61;np.arange(2,14).reshape((3,4))print(a)print(np.argmin(a))print(np.argmax(a))print(np.mean(a))print(np.average(a))print(np.median(a))print(np.cumsum(a))
#每两个元素之间的差值
print(np.diff(a))print(np.nonzero(a))b&＃61;np.arange(14,2,-1).reshape((3,4))
print(b)
#对每一行排序
print(np.sort(b))
#转置
print(np.transpose(a))print(b.T)print((b.T).dot(b))
#小于5 的替换为5&＃xff0c;大于9的替换为9
print(np.clip(a,5,9))
#对列进行平均
print(np.mean(a,axis&＃61;0))
#对行进行平均
print(np.mean(a,axis&＃61;1))a&＃61;np.arange(3,15)
print(a)print(a[3])a&＃61;np.arange(3,15).reshape((3,4))
print(a)print(a[2])print(a[2][2])print(a[2,2])print(a[2,:])print(a[1,1:3])
#输出每一行
for row in a:print(row)for column in a.T:print(column)for item in a.flat:print(item)
#进行数组合并&＃xff08;组合&＃xff09;
a&＃61;np.array([1,1,1])
b&＃61;np.array([2,2,2])
print(np.vstack((a,b)))#vertical stackprint(np.hstack((a,b)))print(a[:,np.newaxis])a&＃61;np.array([1,1,1])[:,np.newaxis]
b&＃61;np.array([2,2,2])[:,np.newaxis]
c&＃61;np.concatenate((a,b,b,a),axis&＃61;1)print(c)a&＃61;np.arange(12).reshape((3,4))
print(a)
#分割
print(np.split(a,2,axis&＃61;1))print(np.array_split(a,3,axis&＃61;1))
#垂直分割
print(np.vsplit(a,3))
#水平分割
print(np.hsplit(a,2))a&＃61;np.arange(4)
a
print(a)
#地址拷贝
b&＃61;a
c&＃61;a
d&＃61;b
a[0]&＃61;11
print(a)print(b)
print(c)
print(d)b is a
#deep copy&＃xff0c;只是复制值过去
b&＃61;a.copy()
print(b)b&＃61;np.copy(a)
print(b)a[0]&＃61;34
print(b)