[云炬python3玩转机器学习笔记] 3-6Numpy数组和矩阵的合并和分割

import numpy as np

x=np.arange(10)x

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

X= np.arange(15).reshape(3,5)X

array([[ 0, 1, 2, 3, 4],[ 5, 6, 7, 8, 9],[10, 11, 12, 13, 14]])

基本属性

x.ndim # 查看数组维数

1

X.ndim

2

x.shape

(10,)

X.shape

(3, 5)

x.size

10

X.size

15

numpy.array的数据访问

x

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

x[0]

0

x[-1]

9

X

array([[ 0, 1, 2, 3, 4],[ 5, 6, 7, 8, 9],[10, 11, 12, 13, 14]])

X[0][0]

0

X[(0,0)]

0

X[2,2]

12

x

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

x[0:5]

array([0, 1, 2, 3, 4])

x[:5]

array([0, 1, 2, 3, 4])

x[5:]

array([5, 6, 7, 8, 9])

x[::2] #间隔

array([0, 2, 4, 6, 8])

x[::-1] #倒序

array([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])

X

array([[ 0, 1, 2, 3, 4],[ 5, 6, 7, 8, 9],[10, 11, 12, 13, 14]])

X[:2,:3]

array([[0, 1, 2],[5, 6, 7]])

X[:2][:3] #前两行的前三列

array([[0, 1, 2, 3, 4],[5, 6, 7, 8, 9]])

X[:2][:3] #X[:2]的前3行

array([[0, 1, 2, 3, 4],[5, 6, 7, 8, 9]])

X[:2,::2]

array([[0, 2, 4],[5, 7, 9]])

X[::-1,::-1]

array([[14, 13, 12, 11, 10],[ 9, 8, 7, 6, 5],[ 4, 3, 2, 1, 0]])

X[0]

array([0, 1, 2, 3, 4])

X[0,:]

array([0, 1, 2, 3, 4])

X[0,:].ndim

1

X[:,0]

array([ 0, 5, 10])

X[:,0].ndim

1

subX=X[:2,:3]subX

array([[0, 1, 2],[5, 6, 7]])

subX[0,0]=100subX

array([[100, 1, 2],[ 5, 6, 7]])

X #子矩阵对原矩阵右影响，子矩阵引用的原矩阵的元素

array([[100, 1, 2, 3, 4],[ 5, 6, 7, 8, 9],[ 10, 11, 12, 13, 14]])

X[0,0]=0X

array([[ 0, 1, 2, 3, 4],[ 5, 6, 7, 8, 9],[10, 11, 12, 13, 14]])

subX

array([[0, 1, 2],[5, 6, 7]])

subX =X[:2,:3].copy() #副本subX

array([[0, 1, 2],[5, 6, 7]])

subX[0,0]=100subX

array([[100, 1, 2],[ 5, 6, 7]])

X

array([[ 0, 1, 2, 3, 4],[ 5, 6, 7, 8, 9],[10, 11, 12, 13, 14]])

Reshape

x.shape

(10,)

x.ndim

1

x.reshape(2,5)

array([[0, 1, 2, 3, 4],[5, 6, 7, 8, 9]])

x

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

A= x.reshape(2,5)A

array([[0, 1, 2, 3, 4],[5, 6, 7, 8, 9]])

x

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

B= x.reshape(1,10)

B #一维转二维

array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])

B.shape

(1, 10)

x.reshape(10,-1) #指定行数，智能计算列数

array([[0],[1],[2],[3],[4],[5],[6],[7],[8],[9]])

x.reshape(-1,10)

array([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])

x.reshape(2,-1)

array([[0, 1, 2, 3, 4],[5, 6, 7, 8, 9]])

x.reshape(3,-1)

---------------------------------------------------------------------------ValueError Traceback (most recent call last)<ipython-input-54-27fb2acd3ab6> in <module>----> 1 x.reshape(3,-1)ValueError: cannot reshape array of size 10 into shape (3,newaxis)

合并操作

x=np.array([1,2,3])

y=np.array([3,2,1])

x

array([1, 2, 3])

y

array([3, 2, 1])

np.concatenate([x,y])

array([1, 2, 3, 3, 2, 1])

z=np.array([666,666,666])

np.concatenate([x,y,z])

array([ 1, 2, 3, 3, 2, 1, 666, 666, 666])

A=np.array([[1,2,3],[4,5,6]])

np.concatenate([A,A]) #沿行的方向拼接

array([[1, 2, 3],[4, 5, 6],[1, 2, 3],[4, 5, 6]])

np.concatenate([A,A], axis=1) #沿列的方向拼接

array([[1, 2, 3, 1, 2, 3],[4, 5, 6, 4, 5, 6]])

np.concatenate([A,z.reshape(1,-1)]) #拼接的矩阵维度必须相同

array([[ 1, 2, 3],[ 4, 5, 6],[666, 666, 666]])

A2 =np.concatenate([A,z.reshape(1,-1)]) #拼接的矩阵维度必须相同

A2

array([[ 1, 2, 3],[ 4, 5, 6],[666, 666, 666]])

np.vstack([A,z]) #在垂直的防线叠加，维度可以不同

array([[ 1, 2, 3],[ 4, 5, 6],[666, 666, 666]])

B=np.full((2,2), 100)B

array([[100, 100],[100, 100]])

np.hstack([A,B])#在水平的防线叠加，维度可以不同

array([[ 1, 2, 3, 100, 100],[ 4, 5, 6, 100, 100]])

np.hstack([A,z])

---------------------------------------------------------------------------ValueError Traceback (most recent call last)<ipython-input-78-54818211901c> in <module>----> 1 np.hstack([A,z])<__array_function__ internals> in hstack(*args, **kwargs)~\anaconda3\lib\site-packages\numpy\core\shape_base.py in hstack(tup)344 return _nx.concatenate(arrs, 0)345else:--> 346 return _nx.concatenate(arrs, 1)347 348 <__array_function__ internals> in concatenate(*args, **kwargs)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)

分割操作

x=np.arange(10)x

array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])

x1,x2,x3=np.split(x,[3,7]) #分割

x1

array([0, 1, 2])

x2

array([3, 4, 5, 6])

x3

array([7, 8, 9])

x1,x2=np.split(x,[5])

x1

array([0, 1, 2, 3, 4])

x2

array([5, 6, 7, 8, 9])

A=np.arange(16).reshape((4,4))A

array([[ 0, 1, 2, 3],[ 4, 5, 6, 7],[ 8, 9, 10, 11],[12, 13, 14, 15]])

A1,A2=np.split(A,[2])

A1

array([[0, 1, 2, 3],[4, 5, 6, 7]])

A2

array([[ 8, 9, 10, 11],[12, 13, 14, 15]])

A1,A2=np.split(A,[2],axis=1)

A1

array([[ 0, 1],[ 4, 5],[ 8, 9],[12, 13]])

A2

array([[ 2, 3],[ 6, 7],[10, 11],[14, 15]])

upper,lower=np.vsplit(A,[2])

upper

array([[0, 1, 2, 3],[4, 5, 6, 7]])

lower

array([[ 8, 9, 10, 11],[12, 13, 14, 15]])

left,right=np.hsplit(A,[2])

left

array([[ 0, 1],[ 4, 5],[ 8, 9],[12, 13]])

right

array([[ 2, 3],[ 6, 7],[10, 11],[14, 15]])

data=np.arange(16).reshape([4,4])data

array([[ 0, 1, 2, 3],[ 4, 5, 6, 7],[ 8, 9, 10, 11],[12, 13, 14, 15]])

x,y=np.hsplit(data,[-1])#取下最后一列

x

array([[ 0, 1, 2],[ 4, 5, 6],[ 8, 9, 10],[12, 13, 14]])

y

array([[ 3],[ 7],[11],[15]])

y[:,0] #抽出所有行的第一列

array([ 3, 7, 11, 15])