Python教程：矩阵特有的数据结构操作

矩阵是二维数组的特殊情况，它的每个数据元素具有严格相同的大小。 所以每个矩阵也是一个二维数组，但反之亦然。 矩阵是许多数学和科学计算中非常重要的数据结构。 正如在前一章中已经讨论过的二维数组结构，我们将在本章中专注于矩阵特有的数据结构操作。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

也使用numpy包进行矩阵数据操作。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

矩阵示例

考虑在早上，中午，晚上和深夜测量记录1周温度的情况。 它可以使用数组在numpy中可用的重塑方法以7 x 5矩阵的形式呈现。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

from numpy import * 
a = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

m = reshape(a,(7,5))
print(m)

执行上面示例代码，得到以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

[['Mon' '18' '20' '22' '17']
 ['Tue' '11' '18' '21' '18']
 ['Wed' '15' '21' '20' '19']
 ['Thu' '11' '20' '22' '21']
 ['Fri' '18' '17' '23' '22']
 ['Sat' '12' '22' '20' '18']
 ['Sun' '13' '15' '19' '16']]

访问矩阵中的值

矩阵中的数据元素可以通过使用索引来访问。 访问方法与在二维数组中访问数据的方式相同。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

from numpy import * 
m = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

# Print data for Wednesday
print(m[2])

# Print data for friday evening
print(m[4][3])

执行上面示例代码，得到以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

['Wed' '15' '21' '20' '19']
23

添加一行

from numpy import * 
m = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

m_r = append(m,[['Avg',12,15,13,11]],0)

print(m_r)

当上面的代码执行时，它会产生以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

[['Mon' '18' '20' '22' '17']
 ['Tue' '11' '18' '21' '18']
 ['Wed' '15' '21' '20' '19']
 ['Thu' '11' '20' '22' '21']
 ['Fri' '18' '17' '23' '22']
 ['Sat' '12' '22' '20' '18']
 ['Sun' '13' '15' '19' '16']
 ['Avg' '12' '15' '13' '11']]

添加一列

可以使用insert()方法将一列数据添加到矩阵。 这里指定想要添加列的索引以及包含添加的列的新值的数组。 在下面的例子中，在开头的第五个位置添加一个新的列。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

from numpy import * 
m = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

m_c = insert(m,[5],[[1],[2],[3],[4],[5],[6],[7]],1)

print(m_c)

执行上面示例代码，得到以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

[['Mon' '18' '20' '22' '17' '1']
 ['Tue' '11' '18' '21' '18' '2']
 ['Wed' '15' '21' '20' '19' '3']
 ['Thu' '11' '20' '22' '21' '4']
 ['Fri' '18' '17' '23' '22' '5']
 ['Sat' '12' '22' '20' '18' '6']
 ['Sun' '13' '15' '19' '16' '7']]

从矩阵中删除一行

可以使用delete()方法从矩阵中删除一行。 必须指定行的索引以及行的值为0，列的值为1的轴值。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

from numpy import * 
m = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

m = delete(m,[2],0)

print(m)

执行上面示例代码，得到以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

[['Mon' '18' '20' '22' '17']
 ['Tue' '11' '18' '21' '18']
 ['Thu' '11' '20' '22' '21']
 ['Fri' '18' '17' '23' '22']
 ['Sat' '12' '22' '20' '18']
 ['Sun' '13' '15' '19' '16']]

从Matrix中删除一列

可以使用delete()方法从矩阵中删除一列。 必须指定列的索引以及一行为0，一列为1的轴值。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

from numpy import * 
m = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

m = delete(m,s_[2],1)

print(m)

执行上面示例代码，得到以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

[['Mon' '18' '22' '17']
 ['Tue' '11' '21' '18']
 ['Wed' '15' '20' '19']
 ['Thu' '11' '22' '21']
 ['Fri' '18' '23' '22']
 ['Sat' '12' '20' '18']
 ['Sun' '13' '19' '16']]

更新矩阵中的一行

要更新矩阵行中的值，只需在行的索引处重新分配值。 在下面的例子中，星期几数据的所有值都标记为0。 该行的索引是3。文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

from numpy import * 
m = array([['Mon',18,20,22,17],['Tue',11,18,21,18],
           ['Wed',15,21,20,19],['Thu',11,20,22,21],
           ['Fri',18,17,23,22],['Sat',12,22,20,18],
           ['Sun',13,15,19,16]])

m[3] = ['Thu',0,0,0,0]

print(m)

当上面的代码执行时，它会产生以下结果 -文章源自菜鸟学院-https://www.cainiaoxueyuan.com/suanfa/6665.html

[['Mon' '18' '20' '22' '17']
 ['Tue' '11' '18' '21' '18']
 ['Wed' '15' '21' '20' '19']
 ['Thu' '0' '0' '0' '0']
 ['Fri' '18' '17' '23' '22']
 ['Sat' '12' '22' '20' '18']
 ['Sun' '13' '15' '19' '16']]