06 矩阵(Matrices)
《Python数据分析技术栈》第05章 06 矩阵(Matrices)
A matrix is a two-dimensional data structure, while an array can consist of any number of dimensions.
矩阵是一种二维数据结构,而数组可以包含任意维数。
With the np.matrix class, we can create a matrix object, using the following syntax:
通过 np.matrix 类,我们可以使用以下语法创建一个矩阵对象:
python
x=np.matrix([[2,3],[33,3],[4,1]])
#OR
x=np.matrix('2,3;33,3;4,1') #Using semicolons to separate the rows x
Most of the functions that can be applied to arrays can be used on matrices as well. Matrices use some arithmetic operators that make matrix operations more intuitive. For instance, we can use the * operator to get the dot product of two matrices that replicates the functionality of the np.dot function.
大多数可用于数组的函数也可用于矩阵。矩阵使用一些算术运算符,使矩阵运算更加直观。例如,我们可以使用 * 运算符获取两个矩阵的点积,这与 np.dot 函数的功能相同。
Since matrices are just one specific case of arrays and might be deprecated in future releases of NumPy, it is generally preferable to use NumPy arrays.
由于矩阵只是数组的一种特殊情况,而且在未来的 NumPy 版本中可能会被弃用,因此通常最好使用 NumPy 数组。