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A next-generation curated knowledge sharing platform for data scientists and other technical professions.
data data-science knowledge data-analysis
  1. Python 38.9%
  2. JavaScript 28.4%
  3. Jupyter Notebook 18.7%
  4. HTML 10.4%
  5. CSS 3.1%
  6. Shell 0.3%
  7. Other 0.2%
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@tcbegley @matthewwardrop
tcbegley and matthewwardrop Add Faculty to INTHEWILD (#496) 
ASI Data Science has relaunched as Faculty.
Latest commit c4c6838 Feb 9, 2019
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.github [Github] Auto-tag people in issues + PRs Nov 3, 2016
docs Added explanation how init creates git repo #482 (#484) Jan 4, 2019
knowledge_repo Fix typo "nane"->"name" (#488) Jan 4, 2019
scripts Add guidance to `kp preview` regarding accessing preview when run on … Dec 17, 2018
tests Configure Travis tests for Python versions (#456) Oct 3, 2018
.gitattributes CSS Cleanup (#196) Jan 16, 2017
.gitignore Deploy with HTTPS for uwsgi and gunicorn (#420) Sep 17, 2018
.travis.yml Temporarily disable Python 3.4 testing until upstream anaconda issues… Oct 4, 2018
INTHEWILD.md Add Faculty to INTHEWILD (#496) Feb 10, 2019
LICENSE Initial commit Aug 17, 2016
MANIFEST.in Improve git initialisation and initially included files. (#386) Mar 25, 2018
README.md Add Sphinx documentation, simplify README and update screenshots. (#230) Mar 17, 2018
appveyor.yml Configure Travis tests for Python versions (#456) Oct 3, 2018
run_tests.bat Improve tooling and backend for creating and working with knowledge p… Oct 4, 2018
run_tests.sh Improve tooling and backend for creating and working with knowledge p… Oct 4, 2018
setup.py Improve tooling and backend for creating and working with knowledge p… Oct 4, 2018
update_screenshots.py Add Sphinx documentation, simplify README and update screenshots. (#230) Mar 17, 2018

README.md

Knowledge Repo

PyPI license PyPI version Python Build Status Windows Build Status

The Knowledge Repo project is focused on facilitating the sharing of knowledge between data scientists and other technical roles using data formats and tools that make sense in these professions. It provides various data stores (and utilities to manage them) for "knowledge posts", with a particular focus on notebooks (R Markdown and Jupyter / IPython Notebook) to better promote reproducible research.

For more information about the motivation and inspiration behind this project, we encourage you to read our Medium Post.

Screenshots

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