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")
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
- 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-0.2.2.tar.gz
(279.5 kB
view details)
Built Distribution
pyobsplot-0.2.2-py3-none-any.whl
(281.7 kB
view details)
File details
Details for the file pyobsplot-0.2.2.tar.gz
.
File metadata
- Download URL: pyobsplot-0.2.2.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 | 2112561cb0f535bab34311713db3b91231134622e02fa9f016314b3bf62b5158 |
|
MD5 | d7e55eae44b62600bb601521fcde5c75 |
|
BLAKE2b-256 | 29c251f0eb06b9a47ba75917e12702b3056c00641490d9210557b4efa1ef2a20 |
File details
Details for the file pyobsplot-0.2.2-py3-none-any.whl
.
File metadata
- Download URL: pyobsplot-0.2.2-py3-none-any.whl
- Upload date:
- Size: 281.7 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 | a33e3c0ffa8584a7a455068cfe4a99f37bf63376b5701414bb2a0c2c48ef6333 |
|
MD5 | e561282b63c035c5aa2ce10dbcb3856f |
|
BLAKE2b-256 | acdfc8c296ca6e56a61ccb09228e3249f71126aab1f6990be96f5756c606887c |