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{octicon}`briefcase;1em;caption-text`**A Whirlwind Tour of Python**
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{octicon}`smiley;1em;caption-text`**A Whirlwind Tour of Python**
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A Whirlwind Tour of Python is a fast-paced introduction to essential features of the Python language, aimed at researchers and developers who are already familiar with programming in another language.
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[Read more or use this reference »](https://jakevdp.github.io/WhirlwindTourOfPython/)
An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley.
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[Read more or use this reference »](https://github.com/dabeaz-course/python-mastery)
{octicon}`megaphone;1em;caption-text`**Python & OpenGL for Scientific Visualization**
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{octicon}`pencil;1em;caption-text`**Python & OpenGL for Scientific Visualization**
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he goal of this book is to reconciliate Python programmers with OpenGL, providing both an introduction to modern OpenGL and a set of basic and advanced techniques in order to achieve both fast, scalable & beautiful scientific visualizations.
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{octicon}`pencil;1em;caption-text`**Python Programming for Economics and Finance**
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{octicon}`briefcase;1em;caption-text`**Python Programming for Economics and Finance**
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Python for scientific computing, with a focus on economics and finance.
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:link:https://wesmckinney.com/book/
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{octicon}`pencil;1em;caption-text`**Python for Data Analysis, 3E**
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{octicon}`note;1em;caption-text`**Python for Data Analysis, 3E**
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This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python.
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:link:https://goodresearch.dev/
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{octicon}`tools;1em;caption-text`**The Good Research Code Handbook**
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{octicon}`telescope;1em;caption-text`**The Good Research Code Handbook**
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Handbook is for all who do a lot of programming as part of their research. It will teach you, in a practical manner, how to organize your code so that it is easy to understand and works reliably.
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:link:https://www.anaconda.com/
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{octicon}`report;1em;caption-text`**Anaconda**
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{octicon}`bookmark;1em;caption-text`**Anaconda**
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Anaconda sits at the center of the AI revolution. We provide data science tools, MLOps, and data & model management to empower our customers and community with AI capabilities to propel their projects forward.
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The Documentation Team will be contributors to documentation who participate regularly to CPython documentation and monthly meetings (synchronously or asynchronously). A goal of this team will be to build a global community around CPython documentation.
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The scientific Python ecosystem is a loose federation of community-developed and -owned Python projects widely used in scientific research, technical computing, and data science.
Learn data visualization, statistics, probability, and dimensionality reduction using a computational-first approach, without giving up mathematical rigor. A great textbook for an Introduction to Data Science or Engineering Statistics class. Sources on https://github.com/jmshea/Foundations-of-Data-Science-with-Python
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[Read more or use this reference »](https://jmshea.github.io/Foundations-of-Data-Science-with-Python/intro.html)
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:link:https://learningds.org/intro.html
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{octicon}`stack;1em;caption-text`**Learning Data Science**
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Principles and Techniques of Data Science: This open book is tailored for ML! (Python numpy, classification etc)
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[Read more or use this reference »](https://learningds.org/intro.html)
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% This file is GENERATED using a simple tool. Check the tools on https://nocomplexity.com/ or my github.com/nocomplexity to use it too! Its FOSS.
NumFOCUS is to promote open practices in research, data, and scientific computing
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{octicon}`book;1em;caption-text`**WheelNext**
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{octicon}`hubot;1em;caption-text`**WheelNext**
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WheelNext is an open-source initiative (https://github.com/wheelnext & https://wheelnext.dev/) aiming to improve the user experience in the Python packaging ecosystem, specifically around the scientific computing and machine/deep learning space. We also anticipate benefits in other domains that heavily rely on performance of compiled Python extension modules - the benefit of utilizing one's hardware more optimally is not exclusive to any single domain.
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:link:https://github.com/lona-web-org/lona
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{octicon}`checklist;1em;caption-text`**Lona**
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{octicon}`thumbsup;1em;caption-text`**Lona**
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Write responsive web apps in full python
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:link:https://github.com/web2py/py4web
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{octicon}`tools;1em;caption-text`**PY4WEB**
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{octicon}`tag;1em;caption-text`**PY4WEB**
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PY4WEB is a web framework for the rapid development of efficient database driven web applications. It is an evolution of the popular web2py framework but much faster and slicker.
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:link:https://github.com/urllib3/urllib3
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{octicon}`pencil;1em;caption-text`**urllib3**
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{octicon}`thumbsup;1em;caption-text`**urllib3**
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urllib3 is a powerful, user-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3 and you should too. urllib3 brings many critical features that are missing from the Python standard libraries:
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