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Bringing interactivity to plotnine

Project description

ninejs

Bringing ✨interactivity✨ to plotnine.

ninejs lets you add tooltips and hover grouping to plotnine plots directly from aes() via the tooltip and data_id aesthetic mappings, then export the result as a standalone HTML plot.

It works out of the box with Quarto, marimo, streamlit, and Shiny, and it includes a built-in preview in Positron.


Quick start

from plotnine import aes, geom_point, ggplot, theme_minimal
from plotnine.data import anscombe_quartet

from ninejs import css, interactive, save

gg = (
  ggplot(
      anscombe_quartet,
      aes(x="x", y="y", color="dataset", tooltip="dataset", data_id="dataset")
  )
  + geom_point(size=7, alpha=0.5)
  + theme_minimal()
)

(
  interactive(gg)
  + css(from_dict={".tooltip": {"font-size": "2em"}})
  + save("plot.html")
)

Interactive scatterplot of Anscombe's quartet grouped by dataset with a visible tooltip


Installation

pip install ninejs

Integration

ninejs integrates with other tools out of the box.

  • Quarto

Quarto document rendering ninejs code above an Anscombe quartet scatterplot

  • Marimo

Marimo notebook rendering ninejs code above an Anscombe quartet scatterplot

  • Shiny

Shiny for Python app rendering a ninejs scatterplot with controls for dataset, point size, and opacity

  • Streamlit

  • Positron

Positron viewer showing a ninejs Anscombe quartet scatterplot next to the Python source code

  • Anywhere: ninejs outputs HTML files that only need a browser, so websites and web-based tools can embed them easily.

The next targets are:

  • Jupyter
  • Streamlit

Documentation

See the full documentation and examples here.

See the contributing guide for local setup, tests, and formatting.

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