“python数据分析与机器学习实战-02.numpy基础结构”

import numpy

vector = numpy.array([3,6,7,89,90])
vector == 6

matrix = numpy.array([[12,3,67,9],[34,2,7,9],[3,8,9,6]])
matrix == 3

vector = numpy.array([3,6,7,89,90])
equal_to_six = (vector == 6)
print(equal_to_six)
print(vector[equal_to_six])

matrix = numpy.array([[12,3,67,9],[34,2,7,9],[3,8,9,6]])
second_column_three = (matrix[:,1] == 3)
print(second_column_three)
print(matrix[second_column_three,:])

#逻辑运算
vector = numpy.array([3,6,7,89,90])
equal_to_three_and_six = (vector == 3)&(vector == 6)
print(equal_to_three_and_six)

vector = numpy.array([3,6,7,89,90])
equal_to_three_or_six = (vector == 3)|(vector == 6)
print(equal_to_three_or_six)

#类型转换
vector = numpy.array(['3','6','7','89','90'])
print(vector.dtype)
vector = vector.astype(float)
print(vector.dtype)
print(vector)

#最小值
vector = numpy.array([3,6,7,89,90])
print(vector.min())

#最大值
vector = numpy.array([3,6,7,89,90])
print(vector.max())

#列求和
matrix = numpy.array([[12,3,67,9],[34,2,7,9],[3,8,9,6]])
print(matrix.sum(axis=0))

#行求和
matrix = numpy.array([[12,3,67,9],[34,2,7,9],[3,8,9,6]])
print(matrix.sum(axis=1))