This is the Linux app named Python Data Science Handbook whose latest release can be downloaded as PythonDataScienceHandbooksourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Python Data Science Handbook
DESCRIPTION:
The Python Data Science Handbook is a comprehensive collection of Jupyter notebooks written by Jake VanderPlas covering fundamental Python libraries for data science, including IPython, NumPy, Pandas, Matplotlib, Scikit-Learn and more. The project is designed for data scientists, researchers, and anyone transitioning into Python-based data work; it assumes you already know basic Python and focuses more on how to use the ecosystem effectively. Each chapter is a standalone Jupyter notebook, with runnable code, explanatory prose, visuals, and examples showing how to handle data-wrangling, exploratory data analysis, machine learning workflows, and visualization. The repository is freely available and the code is released under the MIT license; the textual content is released under a Creative Commons license. Users can also launch the notebooks in Google Colab or Binder directly, making it extremely accessible.
Features
- Collection of Jupyter notebooks covering IPython, NumPy, Pandas, Matplotlib, Scikit-Learn and other data science tools
- Free and open access under MIT (code) and CC-BY-NC-ND (text) licenses
- Executable examples and visualizations so readers can run code, modify it, and learn by practice
- Compatibility with Google Colab and Binder for browser-based interactive learning
- Structured like a full textbook (table of contents, chapters, index) but organized as code + narrative
- Widely referenced in the data science community as a go-to resource for Python-based workflows
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/python-data-science.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.