Automatically Profile Pandas DataFrame with AutoProfiler

...without writing any redundant code.

If you are a JupyterLab user, here’s a pretty interesting extension for you that I discovered some time back.

AutoProfiler is an open-source DataFrame analysis tool in Jupyter.

It reads your notebook and automatically profiles every DataFrame in memory as you change/create them.

A demo is shown below:

In other words, if you modify an existing DataFrame, AutoProfiler will automatically update its corresponding profiling.

Moreover, if you create a new DataFrame (from an existing DataFrame, for instance), AutoProfiler will automatically profile that as well, as shown below:

Profiling info includes column distribution, summary stats, null stats, and many more.

Lastly, you can also generate the corresponding code, with its export feature.

Isn’t that cool?

Find more info here: GitHub Repo.

Along the lines of profiling, I shared two more tools in a recent newsletter issue. These were Skimpy and SummaryTools.

You can read that newsletter issue here: Skimpy and SummaryTools issue.

👉 Over to you: What are some other cool Jupyter tools that you are aware of?

Thanks for reading!

Whenever you are ready, here’s one more way I can help you:

Every week, I publish 1-2 in-depth deep dives (typically 20+ mins long). Here are some of the latest ones that you will surely like:

To receive all full articles and support the Daily Dose of Data Science, consider subscribing:

👉 If you love reading this newsletter, feel free to share it with friends!

👉 Tell the world what makes this newsletter special for you by leaving a review here :)

Reply

or to participate.