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Tuesday Tip #41: Profile your pandas DataFrame 🔎

Published about 1 month ago • 1 min read

Hi Reader,

I just published a new blog post, Get started with conda environments. If you’re new to virtual environments in Python, give it a read!

Once you start using virtual environments, you’ll wonder how you ever got along without them!


🔗 Link of the week

Yann LeCun on the future of AI (Lex Fridman interview)

Yann LeCun is one of the “godfathers of Deep Learning”, the Chief AI Scientist at Meta, and (in my opinion) one of the clearest and most convincing thinkers on the future of AI.

It’s a long interview (2 hr 45 min), and some of the sections are highly technical, so use the timestamps to jump to the parts that interest you most.

Lex is a world-class interviewer and an AI researcher, and he was the perfect person to conduct this conversation. Highly recommended!


👉 Tip #41: Profile your pandas DataFrame in one line of code

Let’s say that you’ve got a new dataset you want to quickly explore without too much work. Here’s what to do:

Step 1: Install ydata-profiling

Step 2: Import ydata_profiling in Jupyter

Step 3: Run the ProfileReport() function and pass it any DataFrame

Voilà! It returns an interactive report in HTML format.

The report’s first section is an overview of the dataset and a list of possible issues with the data:

The second section gives a summary of each column:

The third section lets you explore feature interactions:

The fourth section visualizes missing values:

And the final section shows a sample of the dataset:

Want more tricks like this? Check out My top 25 pandas tricks on YouTube (250K+ views), or enroll in my new course, pandas in 30 days!


👋 See you next Tuesday!

Did you like this week’s tip? Please forward it to a friend or share this link with your favorite online community. It really helps me out! 🙌

- Kevin

P.S. How This Guy Makes the World’s Best Puzzle Boxes (WIRED video)

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Kevin Markham

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