Numerical and mathematical calculations in Python

Description

NumPy package

As the name implies, this package is related to Python numerical calculations. Num is derived from Numerical and Py from python.

The NumPy package is a set of Python-ready functions for scientific calculations with Python. This package includes the following:

– Powerful N-dimensional array builder

– Complex, complete, wide and various functions

– Tools for communicating with C / C ++ and Fortran

– Generation of high efficiency code

– Very useful capabilities in linear algebra and Fourier transform and generating random numbers

In addition to its scientific uses, NumPy can also be used as a repository for multidimensional data. This package can also be used to communicate with various datasets.

 

 

Of course, there are other packages for numerical calculations in Python, but one of them is known as NumPy.

This package was prepared at MIT.

Content title:

Introduction

Advantages

Install numpy

Pip command

Upgrade a package in Python

Build a one-dimensional array

Calculate the length of the array

Array dimension calculation

Build a 2D array

Calculate the number of rows and columns

Dual integration in output

Build a column array

Array ready functions

Arrange function

Change step

Construction of a reduction vector

Linspace command

Build ones matrix

Build a zeros matrix

Presentation display settings in variable explorer

Making an eye matrix

Generate a random number

Generate a random matrix

Generate a random number according to the standard normal distribution

Generate a random number in the range [a, b]

Generate integer random number

Indexing arrays and matrices

Select part of the matrix

Extract rows and columns of the matrix

Convert row and column vectors

Shared memory feature in Python

Command .copy ()

Python commands shortened

Boolen indexing

Numerical indexing

Data type in Python

The difference between Python and other programming languages

Specify the type of variable

Complex type complex

Mathematical operations on arrays

Multiply by equal

Matrix multiplication

Peer-to-peer subtraction

Apply conditional operators

Test the equality of two arrays

Logical scientists OR, AND, NOT and XOR

trigonometric functions

Maximum, minimum, mean, standard deviation and average

Total column and row matrix

The concept of any and all

The concept of broadcasting in Python

An example of broadcasting in calculating the distance between cities

Commenting in Python

Ravel command

Transpose

Reshaping

Sort the data

Row and column sorting

Extract the sorting index

Advanced data type in Python

Does the assignment change the data type?

Data type in image processing

Change data type in Python

Trending numbers in Python

The difference between astype and around

int8, int16, int32, and int64

unint8, unint16, unint32, and unint64

What kind of data should be used in the program?

Info command

Float16, float32, float64 and float128

complex64, complex128, complex192 and complex256

Polynomials in Python

The root of polynomials

Quantify polynomials

Calculate the degree of a polynomial

Draw a diagram

Fitting a curved fitting in Python

Chebyshev

Read data from an output file

Read textual datasets

Read the picture in Python

Image display

Extract the number of rows and columns of the image