GithubHelp home page GithubHelp logo

jodie606 / 01_python_introduction Goto Github PK

View Code? Open in Web Editor NEW

This project forked from milaan9/01_python_introduction

0.0 0.0 0.0 16.59 MB

Learn the basics of Python. These tutorials are for Python beginners. so even if you have no prior knowledge of Python, you won’t face any difficulty understanding these tutorials.

License: MIT License

Jupyter Notebook 100.00%

01_python_introduction's Introduction

Last Commit Last Commit Stars Badge Forks Badge Size Pull Requests Badge Issues Badge Language MIT License

binder colab

01_Python_Introduction

Introduction 👋

Python is a modern, robust, high level programming language. It is very easy to pick up even if you are completely new to programming.


Online

  1. JupyterLab → binder
  1. Open any Github repository → binder

Installation

Mac OS X and Linux comes pre installed with python. Windows users can download Python

To install IPython run,

 pip install ipython[all]

This will install all the necessary dependencies for the notebook, qtconsole, tests etc.

Installation from unofficial distributions

Installing all the necessary libraries might prove troublesome. Anaconda and Canopy comes pre packaged with all the necessary python libraries and also IPython.

Anaconda

Download Anaconda

Anaconda is completely free and includes more than 300 python packages. Both python 2.7 and 3.9 options are available.

Launching Jupyter Notebook

From the terminal

ipython notebook

In Anaconda, Open the respective terminals and execute the above.


Table of contents 📋

No. Name
000 What_is_Programming
00 Intro_to_Python
01 Python_Programming
02 How_to_install_Python
03 Jupyter_Keyboard_Shortcuts_Practice
markdown
04 Hello_World
05 Python_Keywords_and_Identifiers
Python_Keywords_List
06 Python_Statement_Indentation_Comments
07 Python_Variables_& Constants
08 Python_Literals
09 Python_Data_Types
10 Python_Type_Conversion
11 Python_Input_Output_Import
12 Python_Operators
13 Python_Namespace_and_Scope
14 Jupyter Notebook Cheat Sheet.pdf
15 Python For Data Science Cheat Sheet For Beginners.pdf
16 constant
17 main

These are read-only versions. However you can Run ▶ all the codes online by clicking here → binder


Frequently asked questions (FAQ) ❔

1. How can I thank you for writing and sharing this tutorial? 🌷

You can Star Badge and Fork Badge Starring and Forking is free for you, but it tells me and other people that it was helpful and you like this tutorial.

Go here if you aren't here already and click ➞ ✰ Star and ⵖ Fork button in the top right corner. You'll be asked to create a GitHub account if you don't already have one.


2. How can I read this tutorial without an Internet connection? GIF

  1. Go here and click the big green ➞ Code button in the top right of the page, then click ➞ Download ZIP.

    Download ZIP

  2. Extract the ZIP and open it. Unfortunately I don't have any more specific instructions because how exactly this is done depends on which operating system you run.

  3. Launch ipython notebook from the folder which contains the notebooks. Open each one of them

    Kernel ➞ Restart & Clear Output

This will clear all the outputs and now you can understand each statement and learn interactively.

If you have git and you know how to use it, you can also clone the repository instead of downloading a zip and extracting it. An advantage with doing it this way is that you don't need to download the whole tutorial again to get the latest version of it, all you need to do is to pull with git and run ipython notebook again.


Authors ✍️

I'm Dr. Milaan Parmar and I have written this tutorial. If you think you can add/correct/edit and enhance this tutorial you are most welcome🙏

See github's contributors page for details.

If you have trouble with this tutorial please tell me about it by Create an issue on GitHub PNG and I'll make this tutorial better. This is probably the best choice if you had trouble following the tutorial, and something in it should be explained better. You will be asked to create a GitHub account if you don't already have one.

If you like this tutorial, please give it a ⭐ star.


Licence 📜

You may use this tutorial freely at your own risk. See LICENSE.

01_python_introduction's People

Contributors

milaan9 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.