Observable Plot as Jupyter widget
Project description
pyobsplot
pyobsplot
allows to use Observable Plot to create charts in Jupyter notebooks. Plots are produced as widgets from Python code with a syntax as close as possible to the JavaScript one.
It allows to do things like :
import polars as pl
from pyobsplot import Obsplot, Plot
penguins = pl.read_csv("data/penguins.csv")
Obsplot({
"grid": True,
"color": {"legend": True},
"marks": [
Plot.dot(
penguins,
{"x": "flipper_length_mm", "y": "body_mass_g", "fill": "species"}
),
Plot.density(
penguins,
{"x": "flipper_length_mm", "y": "body_mass_g", "stroke": "species"}
)
]
})
Installation and usage
Warning: this project is at a very early stage. There will be bugs, and please take a look at the limitations listed below.
pyobsplot
can be installed with pip
:
pip install pyobsplot
For usage instructions, see the documentation website:
- See getting started for a quick usage overview.
- See usage for more detailed usage instructions.
Features and limitations
Features:
- Syntax as close as possible to the JavaScript one
- Pandas and polars DataFrame and Series objects are serialized using Arrow IPC format for improved speed and data type conversions
- Works offline, no iframe or dependency to Observable runtime
- Caching mechanism of data objects if they are used several times in the same plot
- Custom JavaScript code can be passed as strings with the
js
method - Python
date
anddatetime
objects are automatically converted to JavaScriptDate
objects - Plots can be defined with a dictionary, a call to a
Plot
mark function, or withkwargs
. See alternative syntaxes. - Works with Jupyter notebooks and Quarto HTML documents
Limitations:
- When using notebooks inside VSCode, the cells output states are not saved between sessions. So when a notebook is closed and reopened, plots have to be recomputed to be displayed. This is currently a VSCode limitation.
- Doesn't work in Quarto in formats other than HTML.
- When exporting to HTML, the resulting documents can be quite big as each plot is embedded as a widget, with the data and the code needed to generate it (there is currently no way to embed SVG or HTML directly).
- Some faceting operations produce warnings when used as top-level faceting (but the plots should be fine). This doesn't happen when you using mark-level faceting (with the
fx
andfy
channels).
Credits
- Observable Plot, developed by Mike Bostock and Philippe Rivière among others.
- The widget is developed thanks to the anywidget framework.
- This documentation website is generated by Quarto and the bookup custom format.
Project details
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