How to convert matrix to list in Python
This time I will show you how to convert a matrix into a list in Python. What are the precautions for converting a matrix into a list in Python? The following is a practical case, let's take a look.
This article mainly introduces some functions in Python's numpy library and makes a backup for easy search.(1) Function to convert matrix to list: numpy.matrix.tolist()
Return list listExamples
>>> x = np.matrix(np.arange(12).reshape((3,4))); x matrix([[ 0, 1, 2, 3], [ 4, 5, 6, 7], [ 8, 9, 10, 11]]) >>> x.tolist() [[0, 1, 2, 3], [4, 5, 6, 7], [8, 9, 10, 11]]
(2) Function to convert array to list: numpy.ndarray.tolist()
Notes: (The array may be recreated, a=np.array(a.tolist()).Examples
>>>
>>> a = np.array([1, 2]) >>> a.tolist() [1, 2] >>> a = np.array([[1, 2], [3, 4]]) >>> list(a) [array([1, 2]), array([3, 4])] >>> a.tolist() [[1, 2], [3, 4]]
Examples
>>>
>>> a = np.array([[1, 2], [3, 4]]) #对所有元素求均值 >>> np.mean(a) 2.5 >>> np.mean(a, axis=0) #对每一列求均值 array([ 2., 3.]) >>> np.mean(a, axis=1) #对每一行求均值 array([ 1.5, 3.5])
Examples
>>>
>>> a = np.array([[1, 2], [3, 4]]) #对所有元素求标准差 >>> np.std(a) 1.1180339887498949 >>> np.std(a, axis=0) #对每一列求标准差 array([ 1., 1.]) >>> np.std(a, axis=1) #对每一行求标准差 array([ 0.5, 0.5])
Examples:
>>> a=np.array([[1,2,3],[4,5,6],[7,8,9]]) #先输入3行2列的数组a >>> b=a[:,:2] >>> b.shape #当数组的行与列都大于1时，不需增加维度 (3, 2) >>> c=a[:,2] >>> c.shape #可以看到，当数组只有一列时，缺少列的维度 (3,) >>> c array([3, 6, 9])
>>> d=a[:,2,np.newaxis] #np.newaxis实现增加列的维度 >>> d array([[3], [6], [9]]) >>> d.shape #d的维度成了3行1列（3,1） (3, 1) >>> e=a[:,2,None] #None与np.newaxis实现相同的功能 >>> e array([[3], [6], [9]]) >>> e.shape (3, 1)
shuffle(index): Disorganize the order of dataset (array): Examples:
>>> index = [i for i in range(10)] >>> index [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] >>> np.random.shuffle(index) >>> index [7, 9, 3, 0, 4, 1, 5, 2, 8, 6]
two-dimensional array in a row or column: >>> import numpy as np
>>> a = np.arange(15).reshape(5,3) #构造一个5行3列的二维数组
>>> a
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11],
[12, 13, 14]])
>>> b = a[:,0].min() ##取第0列的最小值，其他列同理
>>> b
0
>>> c = a[0,:].max() ##取第0行的最大值，其他行同理
>>> c
2
n = np.array(np.random.randn(4,2))
n
Out[153]:
array([[ 0.17234 , -0.01480043],
[-0.33356669, -1.33565616],
[-1.11680009, 0.64230761],
[-0.51233174, -0.10359941]])
l = np.array([1,2,3,4])
l
Out[155]: array([1, 2, 3, 4])
l.shape
Out[156]: (4,)
n = np.hstack((n,l)) ValueError: all the input arrays must have same number of dimensions
n = np.hstack((n,l[:,np.newaxis])) ##注意：在使用np.hstack()时必须用()把变量括起来，因为它只接受一个变量
n
Out[161]:
array([[ 0.17234 , -0.01480043, 1. ],
[-0.33356669, -1.33565616, 2. ],
[-1.11680009, 0.64230761, 3. ],
[-0.51233174, -0.10359941, 4. ]])
n = np.array([[1,2,3,4,5,6],[11,22,33,44,55,66],[111,222,333,444,555,666]]) ##产生一个三行六列容易区分的数组 n Out[166]: array([[ 1, 2, 3, 4, 5, 6], [ 11, 22, 33, 44, 55, 66], [111, 222, 333, 444, 555, 666]]) sample = [[]for i in range(3)] ##产生三行一列的空列表 Out[172]: [[], [], []] for i in range(0,6,2): ##每间隔一列便添加到sample中 sample = np.hstack((sample,n[:,i,np.newaxis])) sample Out[170]: array([[ 1., 3., 5.], [ 11., 33., 55.], [ 111., 333., 555.]])
How to convert lists, arrays, and matrices to each other in python
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