Observable Plot in Jupyter notebooks
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")
op = Obsplot()
op({
"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
- Two renderers available:
widget
, which generates plots as Jupyter widgets, andjsdom
, which generate SVG or HTML outputs - 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 - Works with Jupyter notebooks and Quarto HTML documents. Plots without legends are also supported in PDF and docx outputs with the
jsdom
renderer.
Limitations:
- Plots with legends don't work in Quarto in formats other than HTML.
- Some faceting operations produce warnings when used as top-level faceting (but the plots should be fine). This doesn't happen when 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.
- Some code from the
jsdom
renderer has been adapted from altair_saver. - The documentation website is generated by Quarto and the bookup custom format.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pyobsplot-0.3.0.tar.gz
(279.5 kB
view details)
Built Distribution
pyobsplot-0.3.0-py3-none-any.whl
(281.8 kB
view details)
File details
Details for the file pyobsplot-0.3.0.tar.gz
.
File metadata
- Download URL: pyobsplot-0.3.0.tar.gz
- Upload date:
- Size: 279.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.4.1 CPython/3.10.6 Linux/5.19.0-35-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | eaa1ff6e058fb99bc09182e275f59f29b149a3af697d23b79928fe29e6a84cad |
|
MD5 | 4713f319f348adcd239632377d6c349f |
|
BLAKE2b-256 | bfbfdc54a884900f456b9d252b36e940500f8f921b38bac8ac4c54a803218793 |
File details
Details for the file pyobsplot-0.3.0-py3-none-any.whl
.
File metadata
- Download URL: pyobsplot-0.3.0-py3-none-any.whl
- Upload date:
- Size: 281.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.4.1 CPython/3.10.6 Linux/5.19.0-35-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a6fdb551f7c19a1825dcdc63f7c66a2b5216195fd81c4da303d62272d45989fd |
|
MD5 | 787ebb20f26ecee73fbfa995f1333258 |
|
BLAKE2b-256 | 3c4897178dad326043cb88cdc6ba0d626dfd65e581b06ce50fe9db3490545ecf |