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Very cool. The whole pandas API is huge. What was your focus for your implementation? Isn't there another well known js library that allows SQL operations including aggregates? How fast is it compared to that?

What happens if I load a 100MB csv file into a pandas.js dataframe in the browser and compute an aggregate? How fast is this?

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The initial focus was on using it for plotting in React. We wanted to make shouldComponentUpdate decisions quickly and the Immutable base of pandas-js allows for quick, cheap comparisons after querying data directly from our API. See the post on it here: “Pandas & Immutable.js” @StratoDem https://insights.stratodem.com/pandas-immutable-js-2d9bf0106...

The next step will involve performance optimizations as the aggregates will be slow at 100MB. At that scale, we do the operations server side (we've exclusively been using this client side). Thanks for raising that concern!

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