How to use numpy in Python

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Basic operation of 1.numpy

#! / usr/bin/env python

# coding:utf-8

Import numpy as np

Array = np.array ([[1, 2, 3], [4, 5, 5, 6])

Print (array)

Print ('Dimension:', array.ndim) # has several lines

Print (array.shape) # (2,3) has several rows and columns

Print ('size:',array.size) # Total size

A = np.array ([2jing3jin4], dtype=np.int64) # define type int64

Print (a.dtype)

A = np.zeros ((3p4)) # defines a matrix with three rows and four columns, all of which are 0

A = np.ones ((3p4)) # generates a matrix with three rows and four columns with a value of 1

A = np.empty ((3p4)) # generates a matrix with three rows and four columns with a value of 0

A = np.arange (1 and 10) # generate a matrix with steps from 1 to 9 to 2

A = np.arange (10) # generates a matrix from 0 to 9

A = np.arange (12). Reshape (3p4) # generates a sequence of three rows and four columns

A = np.linspace (1pm 10jue 6). Reshape (2pm 3) # generates a 6 segment with 2 rows and 3 columns between 1 and 10

A = np.array ([10, 20, 30, 40])

B = np.arange (4) # generate a matrix of four digits between 0 and 3, that is, a matrix of four arrays between 0 and 3

Print (aformab) # print a matrix

Addition of print (a b) # matrices

Print (aMub) # Matrix correlation

Print (aqb) # matrix multiplication

Print (aplomb) # Matrix multiplier

2. Numpy matrix operation

C = np.sin (a) * 10 # take sin for each value in a, then multiply by 10, con, tan are all like this

Print (c)

Print (b)