Alternatives and similar repositories for data-science-is-software

Users that are interested in data-science-is-software are comparing it to the libraries listed below

• TomAugspurger / PyDataSeattle
  For the pandas tutorial at PyData Seattle: https://www.youtube.com/watch?v=otCriSKVV_8
  ☆116Updated 3 years ago
• jbwhit / jupyter-tips-and-tricks
  Using Project Jupyter for data science.
  ☆259Updated 4 years ago
• AllenDowney / CompStats
  Code for a workshop on statistical interference using computational methods in Python.
  ☆225Updated 4 years ago
• ianozsvald / data_science_delivered
  Observations from Ian on successfully delivering data science products
  ☆544Updated 4 years ago
• jakevdp / JupyterWorkflow
  Reproducible Data Analysis Workflow in Jupyter
  ☆118Updated 6 years ago
• jreback / PyDataNYC2015
  PyData NYC 2015 conference
  ☆94Updated 9 years ago
• jonathanrocher / pandas_tutorial
  Pandas tutorial for SciPy2015 and SciPy2016 conference
  ☆142Updated 8 years ago
• hgrif / example-project
  Example Python DS project
  ☆71Updated 6 years ago
• engarde-dev / engarde
  A library for defensive data analysis.
  ☆501Updated 5 years ago
• croach / oreilly-matplotlib-course
  Jupyter notebooks from my O'Reilly Media course "Matplolib for Developers: Data Visualization and Analysis with Python"
  ☆139Updated 8 years ago
• DataTau / datascience-anthology-pydata
  PyData, The Complete Works of
  ☆298Updated 8 years ago
• fonnesbeck / intro_stat_modeling_2017
  Introduction to Statistical Modeling with Python (PyCon 2017)
  ☆168Updated 4 years ago
• TomAugspurger / pandas-head-to-tail
  ☆86Updated 7 years ago
• ericmjl / data-testing-tutorial
  A short tutorial for data scientists on how to write tests for code + data.
  ☆120Updated 4 years ago
• manifoldai / docker-cookiecutter-data-science
  A fork of the cookiecutter-data-science leveraging Docker for local development.
  ☆131Updated 5 years ago
• joelgrus / stupid-itertools-tricks-pydata
  code for my "stupid itertools tricks" talk from pydata seattle 2015
  ☆153Updated 9 years ago
• amitkaps / weed
  Analysing Weed Pricing across US - Data Analysis Workshop
  ☆129Updated 8 years ago
• stitchfix / d3-jupyter-tutorial
  ☆196Updated last month
• jseabold / depy
  DePy 2015 Talk
  ☆117Updated 7 years ago
• jakevdp / sklearn_pydata2015
  Scikit-Learn Tutorial for PyData Seattle 2015
  ☆136Updated 10 years ago
• gjreda / pydata2014nyc
  Materials for my pandas tutorial at PyData 2014, NYC
  ☆111Updated 9 years ago
• TomAugspurger / pydata-nyc-ph2t
  PyData NYC 2017: Pandas Head to Tail
  ☆57Updated 7 years ago
• podopie / DAT18NYC
  General Assembly repo for Data Science 18
  ☆36Updated 10 years ago
• jbwhit / OSCON-2015
  Code for my OSCON 2015 talk
  ☆83Updated 9 years ago
• culturedbun / pandas-exercises
  Walkthrough exercises from PandasTutorial by Wes McKinney.
  ☆150Updated 4 years ago
• TomAugspurger / pydata-chi-h2t
  Materials for the pandas tutorial at PyData Chicago 2016
  ☆55Updated 4 years ago
• s-heisler / pycon2017-optimizing-pandas
  Materials for PyCon 2017 presentation on optimizing Pandas code
  ☆213Updated 5 years ago
• ben519 / DataWrangling
  The ultimate reference guide to data wrangling with Python and R
  ☆240Updated 3 years ago
• amueller / scipy-2017-sklearn
  Scipy 2017 scikit-learn tutorial by Alex Gramfort and Andreas Mueller
  ☆286Updated 7 years ago
• mdagost / pug_classifier
  Deep Learning for Pugs
  ☆74Updated 7 years ago