PySpark DataFrames in charts

Chart with the full power of your Spark cluster

Here’s what’s new: you can now build charts directly from PySpark DataFrames, which means you’re no longer limited to small samples. Whether your dataset has a few million rows or hundreds of millions, you can explore it visually without extra preprocessing.

Here's what's new:

• No more sampling limits – Build charts from your complete PySpark DataFrames, whether your dataset has a few million rows or hundreds of millions
• Fast interactive preview – While setting up your chart, see instant previews as you try different dimensions, filters, and colors
• Full cluster power on demand – Click Apply and Spark runs the complete aggregation across your entire dataset using your full cluster.

Check out this quick video to see PySpark DataFrames in charts:

You can now create the same rich, interactive charts you’re used to, now backed by the scale of Spark. From quick category breakdowns to stacked sales-over-time views, everything runs natively on your cluster.

This release completes our native Spark support in Deepnote—both data tables and charts now work seamlessly with your complete datasets, giving you an end-to-end Spark experience.