Welcome to Data Awesome #5! 🎉
Greetings! I hope your are well and that you are making data driven decisions as best you can in these uncertain times.
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Everything below is designed to help you sharpen your data skills and everything has a lot of awesome!
As a special bonus this month I've included links to my intro pandas book Memorable Pandas that's free while it's in pre-release and to my hot-off-the-press guide to using APIs that includes the largest curated list of Python API wrappers. ⚡️
Let's get right to it! 🚀
Awesome articles 🖥
Julia Evans's When debugging, your attitude matters A valuable read for anyone learning a new programming skill.
GitLab's Taylor Murphy's Lessons learned managing the GitLab Data team. Good advice if you find yourself taking a more managerial data science role.
Awesome package, plugin, or extension 🔌
Jupytext - a Jupyter notebook and JupyterLab extension that allows you to save Jupyter notebooks as Markdown documents or scripts in many languages. It's super useful for keeping notebooks in sync and can be used to make diffs more meaningful for version control.
Awesome book for learning pandas 📖
If you or someone you know is looking to learn pandas, I just released Memorable Pandas. It's free while it's in pre-release, so download the .pdf and .epub versions and check it out! I would love to hear any constructive feedback you have. 🎉
Awesome visualization 🖼
Len Kiefer, Deputy Chief Economist at Freddie Mac, made the US initial jobless claims chart that went viral a few weeks back. Below is an updated version taken from his website. That original graphic made me say WOW!
There was a good discussion of the chart here. Len has a number of good charts worth checking out!
Awesome keyboard shortcut ⌨️
In a Jupyter Notebook, type the esc key and then change a cell to markdown with m or code with y. 😀 Here's my list of useful JupyterLab shortcut keys in this Gist. I highly recommend you make the switch to JupyterLab is you're still using vanilla Jupyter notebooks.
Awesome people to follow
Chris Albon 📘He writes insightful and funny commentary on Twitter and he has a really helpful website for common questions about Data Science and Machine Learning - lots of good stuff on Python, NumPy, pandas, and scikit-learn.
Awesome series of tips 💡
Justin Markham's scikit-learn tips are great! They can help you get up to speed on the latest tricks from the Python machine learning library. You can see them all here.
What I've been working on 🛠
It's been a busy spring! 🌷 In addition to Memorable Pandas , here are a few other resources I made that you might find useful:
Tips for new programmers and data scientists in Ten Tips to Save you Time and Frustration When Programming, which includes a list of common pandas errors and remedies here.
I've got a bunch more stuff in the works, so stay tuned!