Data-Centric-AI-Community / awesome-python-for-data-science

A curated list of awesome resources such as books, tutorials, courses, open-source libraries, exercises, and other materials that support Pythonistas in the making, and Pythonistas migrating into Data Science! πŸ“Š
http://discord.com/invite/mw7xjJ7b7s
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Awesome Python for Data Science

The Data-Centric AI Community is the home of all things data 🐍

This repository was created by our community members to build a curated list of awesome resources such books, tutorials, courses, open-source libraries, exercises and other materials that support Pythonistas in the making, and Pythonistas migrating into Data Science!

πŸ”¨ Contributing to the Repo?

Check our CONTRIBUTING guide!

πŸ’« You can also find us at our Discord Server to meet other learners, find co-developers or mentors, and engage in small hands-on coding sessions!

🐍 Python Mastery

❓ Where to Start!

If you're serious about starting your journey as a Pythonista, then you need to start with the basics. As a first approach to the language, we suggest that you start with the book "How to Think Like a Computer Scientist: Learning with Python 3" and follow up with the exercises presented in "Python By Example: Learning to Program in 150 Challenges". All exercises in the latter book have solutions, so it could be a nice way for you to start practicing.

If you feel up to it, and to keep yourself in check, you can contribute with exercises and solutions that you come up with to this repository. Just make sure to follow the structure under python-mastery and add your exercise and solution.py, or add a new version of a solution in case the exercise already exists and you think your solution is different from the one(s) presented (e.g. solution-03.py).

πŸ‘©πŸ½β€πŸ« Awesome Tutorials & Courses

πŸ“š Awesome Books

😸 List of Repos

πŸ‹πŸ½β€β™€οΈ Exercises

Please refer to this folder.

πŸ›  Projects


πŸ“Š Python for Data Science

❓ Where to Start!

To learn data science, the CRISP-DM is a good approach:

CRISP-DM methodology

  1. Business/Problem Understanding
  2. πŸ†• Data Understanding: Check our EDA Projects in the Exercises section below! πŸŽ‰
  3. πŸ†• Data Preparation: Follow the Tutorials below!
  4. Modelling
  5. Evaluation
  6. Deployment

πŸ“š Awesome Books

🚧 WIP

😸 List of Repos

πŸ‘©πŸ½β€πŸ« Tutorials

Data Understanding:

Data Preparation

Dealing with Missing Data

Data Transformation

πŸ’Ώ Datasets (for exploration)

πŸ•΅πŸ» Exploratory Data Analysis

  1. Olympic 124 Years Dataset: Exploring a dataset of the Olympic Games
πŸ«‚ How to contribute?

πŸ”— Resources

πŸ‘Ύ An Open Invitation

We are open to collaboration! If you want to start contributing you only need to create a pull request with relevant resources πŸš€ If you found these resources useful, please feel free to join our Discord server. We hope to say "Hi" on the other side! πŸ‘‹

A special shoutout to all contributors who keep pushing the boundaries of Data Science πŸ‘

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