BeginnersGuide/Programmers
Please Note This is a Wiki page. Users with edit rights can edit it. You are therefore free to (in fact, encouraged to) add details of material that other Python users will find useful.
Online Python exercises
I've been thinking about online Python learners. There have been some cool examples of online code exercises, like Nathan's Javascript Lessons. These are great because they require absolutely no setup, and can run right on the web page that describes the concepts involved. But of course, it's easy to run Javascript in a browser. What are the options for doing something similar for Python?
BeginnersGuide
New to programming? Python is free and easy to learn if you know where to start! This guide will help you to get started quickly. Chinese Translation New to Python?
Tutorial - Learn Python in 10 minutes
NOTE: If you would like some Python development done, my company, Stochastic Technologies, is available for consulting. This tutorial is available as a short ebook. The e-book features extra content from follow-up posts on various Python best practices, all in a convenient, self-contained format.
TkInter
Tkinter is Python's de-facto standard GUI (Graphical User Interface) package. It is a thin object-oriented layer on top of Tcl/Tk. Tkinter is not the only GuiProgramming toolkit for Python. It is however the most commonly used one. CameronLaird calls the yearly decision to keep TkInter "one of the minor traditions of the Python world."
Python 2.4 Quick Reference
Style chooser: Modern, Modern B&W, Classic, High contrast or Printing [Hint: Use styles Modern B&W or Printing to print. If you get problems, try printing the PDF versions instead] Contents
s Python Class - Google's Python Class - Google Code
Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is.
Data visualization with Seaborn
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Online CSS3 Code Generator With a Simple Graphical Interface - EnjoyCSS
Its handy and easy-to-use UI allows you to adjust rich graphical styles quickly and without coding. The main features: 2D and 3D transformsmultiple complex transitionsmultiple linear and radial gradientsmultiple box and text shadowscustom fonts (including google fonts)and much moreYou’ll be able to play with all EnjoyCSS parameters just like in photoshop or illustarator (with sliders, colorpickers and etc) combining all possible CSS3 style capabilities for the same element. Moreover you can include pseudo states (:hover, :active, :focus, :after, :before) and style them as well. All required CSS code will be automatically generated by EnjoyCSS. You can easily copy-pase all the code into your environment or get the code for each style aspect separately, e.g., code for each gradient, shadow or transform.
Getting Started with Plotly for Python
Plotly for Python can be configured to render locally inside Jupyter (IPython) notebooks, locally inside your web browser, or remotely in your online Plotly account. Remote hosting on Plotly is free for public use. For private use, view our paid plans. Offline Use
Example gallery — seaborn 0.8.1 documentation
seaborn 0.8.1 Example gallery¶ lmplot barplot kdeplot distplot
Top 15 Python Libraries for Data Science in 2017 – ActiveWizards: machine learning company – Medium
As Python has gained a lot of traction in the recent years in Data Science industry, I wanted to outline some of its most useful libraries for data scientists and engineers, based on recent experience. And, since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity. Core Libraries. 1. NumPy (Commits: 15980, Contributors: 522) When starting to deal with the scientific task in Python, one inevitably comes for help to Python’s SciPy Stack, which is a collection of software specifically designed for scientific computing in Python (do not confuse with SciPy library, which is part of this stack, and the community around this stack).
