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Metadata-Version: 2.1 |
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Name: altair |
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Version: 5.1.1 |
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Summary: Vega-Altair: A declarative statistical visualization library for Python. |
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Project-URL: Documentation, https://altair-viz.github.io |
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Project-URL: Source, https://github.com/altair-viz/altair |
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Author: Vega-Altair Contributors |
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License-File: LICENSE |
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Keywords: declarative,interactive,json,statistics,vega-lite,visualization |
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Classifier: Development Status :: 5 - Production/Stable |
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Classifier: Environment :: Console |
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Classifier: Intended Audience :: Science/Research |
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Classifier: License :: OSI Approved :: BSD License |
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Classifier: Natural Language :: English |
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Classifier: Programming Language :: Python :: 3.8 |
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Classifier: Programming Language :: Python :: 3.9 |
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Classifier: Programming Language :: Python :: 3.10 |
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Classifier: Programming Language :: Python :: 3.11 |
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Description-Content-Type: text/markdown |
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# Vega-Altair <a href="https://altair-viz.github.io/"><img align="right" src="https://altair-viz.github.io/_static/altair-logo-light.png" height="50"></img></a> |
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[![github actions](https://github.com/altair-viz/altair/workflows/build/badge.svg)](https://github.com/altair-viz/altair/actions?query=workflow%3Abuild) |
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[![code style black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) |
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[![JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.01057/status.svg)](https://joss.theoj.org/papers/10.21105/joss.01057) |
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[![PyPI - Downloads](https://img.shields.io/pypi/dm/altair)](https://pypi.org/project/altair) |
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**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 |
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API is simple, friendly and consistent and built on top of the powerful |
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[Vega-Lite](https://github.com/vega/vega-lite) JSON specification. This elegant |
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simplicity produces beautiful and effective visualizations with a minimal amount of code. |
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*Vega-Altair was originally developed by [Jake Vanderplas](https://github.com/jakevdp) and [Brian |
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Granger](https://github.com/ellisonbg) in close collaboration with the [UW |
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Interactive Data Lab](https://idl.cs.washington.edu/).* |
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*The Vega-Altair open source project is not affiliated with Altair Engineering, Inc.* |
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## Documentation |
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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 |
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run the notebooks directly in your browser by clicking on one of the following badges: |
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[![Binder](https://beta.mybinder.org/badge.svg)](https://beta.mybinder.org/v2/gh/altair-viz/altair_notebooks/master) |
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[![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) |
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## Example |
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Here is an example using Vega-Altair to quickly visualize and display a dataset with the native Vega-Lite renderer in the JupyterLab: |
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```python |
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import altair as alt |
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# load a simple dataset as a pandas DataFrame |
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from vega_datasets import data |
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cars = data.cars() |
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alt.Chart(cars).mark_point().encode( |
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x='Horsepower', |
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y='Miles_per_Gallon', |
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color='Origin', |
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) |
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``` |
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![Vega-Altair Visualization](https://raw.githubusercontent.com/altair-viz/altair/main/images/cars.png) |
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One of the unique features of Vega-Altair, inherited from Vega-Lite, is a declarative grammar of not just visualization, but _interaction_. |
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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. |
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```python |
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import altair as alt |
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from vega_datasets import data |
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source = data.cars() |
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brush = alt.selection_interval() |
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points = alt.Chart(source).mark_point().encode( |
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x='Horsepower', |
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y='Miles_per_Gallon', |
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color=alt.condition(brush, 'Origin', alt.value('lightgray')) |
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).add_params( |
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brush |
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) |
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bars = alt.Chart(source).mark_bar().encode( |
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y='Origin', |
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color='Origin', |
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x='count(Origin)' |
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).transform_filter( |
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brush |
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) |
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points & bars |
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``` |
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![Vega-Altair Visualization Gif](https://raw.githubusercontent.com/altair-viz/altair/main/images/cars_scatter_bar.gif) |
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## Features |
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* Carefully-designed, declarative Python API. |
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* Auto-generated internal Python API that guarantees visualizations are type-checked and |
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in full conformance with the [Vega-Lite](https://github.com/vega/vega-lite) |
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specification. |
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* Display visualizations in JupyterLab, Jupyter Notebook, Visual Studio Code, on GitHub and |
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[nbviewer](https://nbviewer.jupyter.org/), and many more. |
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* Export visualizations to various formats such as PNG/SVG images, stand-alone HTML pages and the |
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[Online Vega-Lite Editor](https://vega.github.io/editor/#/). |
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* Serialize visualizations as JSON files. |
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## Installation |
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Vega-Altair can be installed with: |
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```bash |
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pip install altair |
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``` |
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If you are using the conda package manager, the equivalent is: |
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```bash |
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conda install altair -c conda-forge |
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``` |
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For full installation instructions, please see [the documentation](https://altair-viz.github.io/getting_started/installation.html). |
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## Getting Help |
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If you have a question that is not addressed in the documentation, |
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you can post it on [StackOverflow](https://stackoverflow.com/questions/tagged/altair) using the `altair` tag. |
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For bugs and feature requests, please open a [Github Issue](https://github.com/altair-viz/altair/issues). |
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## Development |
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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). |
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To run the tests and linters, use |
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``` |
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hatch run test |
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``` |
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For information on how to contribute your developments back to the Vega-Altair repository, see |
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[`CONTRIBUTING.md`](https://github.com/altair-viz/altair/blob/main/CONTRIBUTING.md) |
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## Citing Vega-Altair |
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[![JOSS Paper](https://joss.theoj.org/papers/10.21105/joss.01057/status.svg)](https://joss.theoj.org/papers/10.21105/joss.01057) |
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If you use Vega-Altair in academic work, please consider citing https://joss.theoj.org/papers/10.21105/joss.01057 as |
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```bib |
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@article{VanderPlas2018, |
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doi = {10.21105/joss.01057}, |
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url = {https://doi.org/10.21105/joss.01057}, |
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year = {2018}, |
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publisher = {The Open Journal}, |
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volume = {3}, |
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number = {32}, |
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pages = {1057}, |
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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}, |
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title = {Altair: Interactive Statistical Visualizations for Python}, |
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journal = {Journal of Open Source Software} |
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} |
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``` |
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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 |
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```bib |
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@article{Satyanarayan2017, |
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author={Satyanarayan, Arvind and Moritz, Dominik and Wongsuphasawat, Kanit and Heer, Jeffrey}, |
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title={Vega-Lite: A Grammar of Interactive Graphics}, |
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journal={IEEE transactions on visualization and computer graphics}, |
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year={2017}, |
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volume={23}, |
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number={1}, |
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pages={341-350}, |
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publisher={IEEE} |
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} |
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``` |
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