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:

A new DataFrame gets profiled automatically

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

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

Export code feature

Isn’t that cool?

Find more info here: GitHub Repo.

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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!

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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:

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• PyTorch Models Are Not Deployment-Friendly! Supercharge Them With TorchScript.

• Federated Learning: A Critical Step Towards Privacy-Preserving Machine Learning.

• You Cannot Build Large Data Projects Until You Learn Data Version Control!

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