Metadata-Version: 2.1 Name: altair Version: 5.2.0 Summary: Vega-Altair: A declarative statistical visualization library for Python. Project-URL: Documentation, https://altair-viz.github.io Project-URL: Source, https://github.com/altair-viz/altair Author: Vega-Altair Contributors License-File: LICENSE Keywords: declarative,interactive,json,statistics,vega-lite,visualization Classifier: Development Status :: 5 - Production/Stable Classifier: Environment :: Console Classifier: Intended Audience :: Science/Research Classifier: License :: OSI Approved :: BSD License Classifier: Natural Language :: English Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3.10 Classifier: Programming Language :: Python :: 3.11 Classifier: Programming Language :: Python :: 3.12 Classifier: Typing :: Typed Requires-Python: >=3.8 Requires-Dist: jinja2 Requires-Dist: jsonschema>=3.0 Requires-Dist: numpy Requires-Dist: packaging Requires-Dist: pandas>=0.25 Requires-Dist: toolz Requires-Dist: typing-extensions>=4.0.1; python_version < '3.11' Provides-Extra: dev Requires-Dist: anywidget; extra == 'dev' Requires-Dist: geopandas; extra == 'dev' Requires-Dist: hatch; extra == 'dev' Requires-Dist: ipython; extra == 'dev' Requires-Dist: m2r; extra == 'dev' Requires-Dist: mypy; extra == 'dev' Requires-Dist: pandas-stubs; extra == 'dev' Requires-Dist: pyarrow>=11; extra == 'dev' Requires-Dist: pytest; extra == 'dev' Requires-Dist: pytest-cov; extra == 'dev' Requires-Dist: ruff>=0.1.3; extra == 'dev' Requires-Dist: types-jsonschema; extra == 'dev' Requires-Dist: types-setuptools; extra == 'dev' Requires-Dist: vega-datasets; extra == 'dev' Requires-Dist: vegafusion[embed]>=1.4.0; extra == 'dev' Requires-Dist: vl-convert-python>=1.1.0; extra == 'dev' Provides-Extra: doc Requires-Dist: docutils; extra == 'doc' Requires-Dist: jinja2; extra == 'doc' Requires-Dist: myst-parser; extra == 'doc' Requires-Dist: numpydoc; extra == 'doc' Requires-Dist: pillow<10,>=9; extra == 'doc' Requires-Dist: pydata-sphinx-theme>=0.14.1; extra == 'doc' Requires-Dist: scipy; extra == 'doc' Requires-Dist: sphinx; extra == 'doc' Requires-Dist: sphinx-copybutton; extra == 'doc' Requires-Dist: sphinx-design; extra == 'doc' Requires-Dist: sphinxext-altair; extra == 'doc' Description-Content-Type: text/markdown # Vega-Altair [![github actions](https://github.com/altair-viz/altair/workflows/build/badge.svg)](https://github.com/altair-viz/altair/actions?query=workflow%3Abuild) [![code style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.01057/status.svg)](https://joss.theoj.org/papers/10.21105/joss.01057) [![PyPI - Downloads](https://img.shields.io/pypi/dm/altair)](https://pypi.org/project/altair) **Vega-Altair** is a declarative statistical visualization library for Python. With Vega-Altair, you can spend more time understanding your data and its meaning. Vega-Altair's API is simple, friendly and consistent and built on top of the powerful [Vega-Lite](https://github.com/vega/vega-lite) JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code. *Vega-Altair was originally developed by [Jake Vanderplas](https://github.com/jakevdp) and [Brian Granger](https://github.com/ellisonbg) in close collaboration with the [UW Interactive Data Lab](https://idl.cs.washington.edu/).* *The Vega-Altair open source project is not affiliated with Altair Engineering, Inc.* ## Documentation See [Vega-Altair's Documentation Site](https://altair-viz.github.io) as well as the [Tutorial Notebooks](https://github.com/altair-viz/altair_notebooks). You can run the notebooks directly in your browser by clicking on one of the following badges: [![Binder](https://beta.mybinder.org/badge.svg)](https://beta.mybinder.org/v2/gh/altair-viz/altair_notebooks/master) [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/altair-viz/altair_notebooks/blob/master/notebooks/Index.ipynb) ## Example Here is an example using Vega-Altair to quickly visualize and display a dataset with the native Vega-Lite renderer in the JupyterLab: ```python import altair as alt # load a simple dataset as a pandas DataFrame from vega_datasets import data cars = data.cars() alt.Chart(cars).mark_point().encode( x='Horsepower', y='Miles_per_Gallon', color='Origin', ) ``` ![Vega-Altair Visualization](https://raw.githubusercontent.com/altair-viz/altair/main/images/cars.png) One of the unique features of Vega-Altair, inherited from Vega-Lite, is a declarative grammar of not just visualization, but _interaction_. With a few modifications to the example above we can create a linked histogram that is filtered based on a selection of the scatter plot. ```python import altair as alt from vega_datasets import data source = data.cars() brush = alt.selection_interval() points = alt.Chart(source).mark_point().encode( x='Horsepower', y='Miles_per_Gallon', color=alt.condition(brush, 'Origin', alt.value('lightgray')) ).add_params( brush ) bars = alt.Chart(source).mark_bar().encode( y='Origin', color='Origin', x='count(Origin)' ).transform_filter( brush ) points & bars ``` ![Vega-Altair Visualization Gif](https://raw.githubusercontent.com/altair-viz/altair/main/images/cars_scatter_bar.gif) ## Features * Carefully-designed, declarative Python API. * Auto-generated internal Python API that guarantees visualizations are type-checked and in full conformance with the [Vega-Lite](https://github.com/vega/vega-lite) specification. * Display visualizations in JupyterLab, Jupyter Notebook, Visual Studio Code, on GitHub and [nbviewer](https://nbviewer.jupyter.org/), and many more. * Export visualizations to various formats such as PNG/SVG images, stand-alone HTML pages and the [Online Vega-Lite Editor](https://vega.github.io/editor/#/). * Serialize visualizations as JSON files. ## Installation Vega-Altair can be installed with: ```bash pip install altair ``` If you are using the conda package manager, the equivalent is: ```bash conda install altair -c conda-forge ``` For full installation instructions, please see [the documentation](https://altair-viz.github.io/getting_started/installation.html). ## Getting Help If you have a question that is not addressed in the documentation, you can post it on [StackOverflow](https://stackoverflow.com/questions/tagged/altair) using the `altair` tag. For bugs and feature requests, please open a [Github Issue](https://github.com/altair-viz/altair/issues). ## Development You can find the instructions on how to install the package for development in [the documentation](https://altair-viz.github.io/getting_started/installation.html). To run the tests and linters, use ``` hatch run test ``` For information on how to contribute your developments back to the Vega-Altair repository, see [`CONTRIBUTING.md`](https://github.com/altair-viz/altair/blob/main/CONTRIBUTING.md) ## Citing Vega-Altair [![JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.01057/status.svg)](https://joss.theoj.org/papers/10.21105/joss.01057) If you use Vega-Altair in academic work, please consider citing https://joss.theoj.org/papers/10.21105/joss.01057 as ```bib @article{VanderPlas2018, doi = {10.21105/joss.01057}, url = {https://doi.org/10.21105/joss.01057}, year = {2018}, publisher = {The Open Journal}, volume = {3}, number = {32}, pages = {1057}, author = {Jacob VanderPlas and Brian Granger and Jeffrey Heer and Dominik Moritz and Kanit Wongsuphasawat and Arvind Satyanarayan and Eitan Lees and Ilia Timofeev and Ben Welsh and Scott Sievert}, title = {Altair: Interactive Statistical Visualizations for Python}, journal = {Journal of Open Source Software} } ``` Please additionally consider citing the [Vega-Lite](https://vega.github.io/vega-lite/) project, which Vega-Altair is based on: https://dl.acm.org/doi/10.1109/TVCG.2016.2599030 ```bib @article{Satyanarayan2017, author={Satyanarayan, Arvind and Moritz, Dominik and Wongsuphasawat, Kanit and Heer, Jeffrey}, title={Vega-Lite: A Grammar of Interactive Graphics}, journal={IEEE transactions on visualization and computer graphics}, year={2017}, volume={23}, number={1}, pages={341-350}, publisher={IEEE} } ```