📊 Awesome Data Resources for September 🚀
Here are awesome data resources just for you! 🎉
This is the Sept. 2020 version of the monthly email with great data science resources from Jeff Hale.
If this message was forwarded to you, you can subscribe at dataawesome.com! 😀
Everything below is designed to help you sharpen your data skills and everything has a lot of awesome! Let's get to it! 🚀
Awesome articles 💻
Rand Au recently wrote a thoughtful piece on the value of data cleaning as EDA recently. 🧹Definitely worth a read to make you feel better about all the time you spend cleaning. 😉
I came across Trey Hunner's Keyword (Named) Arguments in Python: How to Use Them. The guide is very helpful when learning to create functions with required and optional keyword arguments and positional arguments (with or without defaults). That can be a bit of a tangled web. 🕸
Awesome people to follow 🎉
Kareem Carr writes thoughtful data science content over at Twitter. As his Twitter description says in quotes: "Very funny for a statistician!"
Awesome books for learning data skills 📖
If you or someone you know is looking to learn data analysis and data science skills, I've got a deal for you. My Data Skills Book Bundle of 4 ebooks is available for a savings of over 60%! For $29 USD you get Memorable Python, Memorable Pandas, Memorable SQL, and Memorable Docker. You'll learn the foundations of Python programming, data manipulation with the pandas library, SQL with PostgreSQL, and how to use Docker containers. 🎉
Awesome keyboard shortcuts ⌨️
If you haven't yet switched to JupyterLab, I suggest you do. It's a big update over vanilla Jupyter notebooks. While you're at it, check out my updated Missing List of JupyterLab Keyboard Shortcuts.👍
What I've been working on 🛠
Here are a few resources I made that you might find useful:
Speed up your Python data science code and save memory: 17 Strategies for Dealing with Data, Big Data, and Even Bigger Data
A practical guide to conda and friends: 13 Conda Commands for Data Scientists.