numpy之基本操作02

1.判断矩阵中的元素

import numpy
matrix = numpy.array([
    [5,10,15],
    [20,25,30],
    [35,40,45]
])
# 判断向量中的每个元素
matrix == 10

array([[False, True, False],
[False, False, False],
[False, False, False]])

2.取矩阵的元素

vector = numpy.array([5,10,15,20])
equal_to_ten = (vector == 10)
print(equal_to_ten)
print(vector[equal_to_ten]) #取向量中元素为10的元素

[False True False False]
[10]

3.矩阵的&与运算

vector = numpy.array([5,10,15,20])
equal_to_5_10 = (vector == 10) & (vector == 5) #向量中&运算
print(equal_to_5_10)

[False False False False]

4.矩阵的|或运算

vector = numpy.array([5,10,15,20])
equal_to_5_10 = (vector == 10) | (vector == 5) #向量中|运算
print(equal_to_5_10)

[ True True False False]

vector = numpy.array([5,10,15,20])
equal_to_5_10 = (vector == 10) | (vector == 5) #向量中|运算
vector[equal_to_5_10]=50 #向量中为真的赋值为50
print(vector)

[50 50 15 20]

5.矩阵的赋值运算

matrix = numpy.array([
    [5,10,15],
    [20,25,30],
    [35,40,45]
])
second_column_25 = matrix[:,1] == 25
print(second_column_25)
matrix[second_column_25,1]=10
print(matrix)

[False True False]
[[ 5 10 15]
[20 10 30]
[35 40 45]]

6.矩阵的转换

#矩阵类型转换
vector = numpy.array(['1','2','3'])
print(vector.dtype)
print(vector)
vector = vector.astype(int)
print(vector.dtype)
print(vector)

<U1
[‘1’ ‘2’ ‘3’]
int64
[1 2 3]

7.矩阵的最大、最小、求和

#取矩阵中最小的元素
vector = numpy.array([5,10,15,20])
print(vector.min())
print(vector.max())

5
20

matrix = numpy.array([
    [5,10,15],
    [20,25,30],
    [35,40,45]
])
#按行求和
matrix.sum(axis=1)

array([ 30, 75, 120])

matrix = numpy.array([
    [5,10,15],
    [20,25,30],
    [35,40,45]
])
#按列求和
matrix.sum(axis=0)

array([60, 75, 90])