numpy基础

import numpy  as np

my_arr = np.arange(1000000)

my_list = list(range(1000000))

%time for _ in range(10):my_arr2 = my_arr * 2 #numpy   

CPU times: user 27.2 ms, sys: 24.1 ms, total: 51.3 ms
Wall time: 67.1 ms

%time for _ in range(10):my_list2 = [x * 2 for x in my_list] #pure python
    

CPU times: user 892 ms, sys: 230 ms, total: 1.12 s
Wall time: 1.19 s

#产生随机数据
data = np.random.randn(2,3)

data

array([[ 1.31865052,  0.16184505, -0.19516902],
       [-0.11928384, -1.53401869,  0.42106552]])

#乘法
data * 10

array([[ 13.18650519,   1.61845053,  -1.95169017],
       [ -1.1928384 , -15.34018694,   4.21065522]])

#加法
data + data

array([[ 2.63730104,  0.32369011, -0.39033803],
       [-0.23856768, -3.06803739,  0.84213104]])

#shape,维度
data.shape

(2, 3)

#dtype,数据类型
data.dtype

dtype('float64')

#list to array
data1 = [6,7.5,8,0,1]
arr1 = np.array(data1)
arr1

array([6. , 7.5, 8. , 0. , 1. ])

#list to multidimensional array
data2 = [[1,2,3,4],[5,6,7,8]]  #内嵌列表长度相等
arr2 = np.array(data2)
arr2

array([[1, 2, 3, 4],
       [5, 6, 7, 8]])

#ndim 维度
arr2.ndim

2

arr2.shape #详细

(2, 4)

# 零
np.zeros(10)
np.zeros_like(10)

array(0)

# 多维零
np.zeros((3,6)) #括号数量

array([[0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0.],
       [0., 0., 0., 0., 0., 0.]])

# 空
np.empty((2,3,2)) #产生的数字无意义

array([[[1., 0.],
        [0., 0.],
        [0., 1.]],

       [[0., 0.],
        [0., 0.],
        [1., 0.]]])

# 生成1
np.ones(10)

array([1., 1., 1., 1., 1., 1., 1., 1., 1., 1.])

#多维1
np.ones((3,6))

array([[1., 1., 1., 1., 1., 1.],
       [1., 1., 1., 1., 1., 1.],
       [1., 1., 1., 1., 1., 1.]])

np.eye(3) #矩阵

array([[1., 0., 0.],
       [0., 1., 0.],
       [0., 0., 1.]])

np.eye(3,4) #行列不等

array([[1., 0., 0., 0.],
       [0., 1., 0., 0.],
       [0., 0., 1., 0.]])

np.identity(3) #矩阵

array([[1., 0., 0.],
       [0., 1., 0.],
       [0., 0., 1.]])

# 生成序列,
np.arange(15)

array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14])

# asarray 并不复制
np.asarray(arr1)

array([6. , 7.5, 8. , 0. , 1. ])