|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Whirlwindtourofpython||2,991||a year ago||22||cc0-1.0||Jupyter Notebook|
|The Jupyter Notebooks behind my OReilly report, "A Whirlwind Tour of Python"|
|A Whirlwind Tour Of Python||75||5 years ago||HTML|
|A Whirlwind Tour of Python (Chinese Translation)|
|Business Analytics||52||4 days ago||mit||Jupyter Notebook|
|Course material for Business Analytics in Practice - IS833|
|Material Walkthrough||28||4 years ago||1||November 07, 2017||19||apache-2.0|
|A material tour (eg Inbox from Google).|
|Tour Of Heroes With Material Design||3||6 years ago||TypeScript|
|Angular 4 TOUR OF HEROES in Material 2.0|
|Courseadvancedr||3||2 years ago||gpl-3.0||TeX|
|Material for various teachings around R|
|Ggplot2_basics_to_extensions||2||5 years ago||HTML|
|Material from my talk "ggplot2: whistlestop tour from basics to extensions" at the Oxford R User group meetup.|
|Python38_blog||2||3 years ago||Jupyter Notebook|
|A repo with the source material for a blog|
|Humanities Python Tour||2||4 years ago||Jupyter Notebook|
|Two hour tour of Python materials for Humanists and other text oriented practices|
Course material for Business Analytics in Practice - IS833
This repository is comprised of notebooks, datasets, and other related materials for Business Analytics in Practice (IS833), an introductory course to data science in Python.
This repository can be accessed via this short link:
Most of the content come from Python Data Science Handbook by Jake VanderPlas (under the MIT license. Read more at the Open Source Initiative). Modifications and updates have been made.
Some of the notebooks come from A Whirlwind Tour of Python (free 100-page pdf) by Jake VanderPlas (under CC0 license). Some modifications and updates have been made in some places to keep its content up to date. A Whirlwind Tour of Python is a fast-paced introduction to essential components of the Python language for data science and/or scientific programming. This material was written and tested using Python 3.7, and should work for any Python 3.X version.