venv/lib/python3.13/site-packages/altair-5.5.0.dist-info/METADATA

Metadata-Version: 2.3
Name: altair
Version: 5.5.0
Summary: Vega-Altair: A declarative statistical visualization library for Python.
Project-URL: Documentation, https://altair-viz.github.io
Project-URL: Source, https://github.com/vega/altair
Author: Vega-Altair Contributors
License: Copyright (c) 2015-2023, Vega-Altair Developers
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        * Redistributions of source code must retain the above copyright notice, this
          list of conditions and the following disclaimer.
        
        * Redistributions in binary form must reproduce the above copyright notice,
          this list of conditions and the following disclaimer in the documentation
          and/or other materials provided with the distribution.
        
        * Neither the name of vega-altair nor the names of its
          contributors may be used to endorse or promote products derived from
          this software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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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 :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Typing :: Typed
Requires-Python: >=3.9
Requires-Dist: jinja2
Requires-Dist: jsonschema>=3.0
Requires-Dist: narwhals>=1.14.2
Requires-Dist: packaging
Requires-Dist: typing-extensions>=4.10.0; python_version < '3.14'
Provides-Extra: all
Requires-Dist: altair-tiles>=0.3.0; extra == 'all'
Requires-Dist: anywidget>=0.9.0; extra == 'all'
Requires-Dist: numpy; extra == 'all'
Requires-Dist: pandas>=1.1.3; extra == 'all'
Requires-Dist: pyarrow>=11; extra == 'all'
Requires-Dist: vega-datasets>=0.9.0; extra == 'all'
Requires-Dist: vegafusion[embed]>=1.6.6; extra == 'all'
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Provides-Extra: dev
Requires-Dist: duckdb>=1.0; extra == 'dev'
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Requires-Dist: pytest-cov; extra == 'dev'
Requires-Dist: pytest-xdist[psutil]~=3.5; extra == 'dev'
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Provides-Extra: save
Requires-Dist: vl-convert-python>=1.7.0; extra == 'save'
Description-Content-Type: text/markdown

# 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>

[![github actions](https://github.com/vega/altair/workflows/build/badge.svg)](https://github.com/vega/altair/actions?query=workflow%3Abuild)
[![typedlib_mypy](https://www.mypy-lang.org/static/mypy_badge.svg)](https://www.mypy-lang.org)
[![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.when(brush).then("Origin").otherwise(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/vega/altair/issues).

## Development

[![Hatch project](https://img.shields.io/badge/%F0%9F%A5%9A-Hatch-4051b5.svg)](https://github.com/pypa/hatch)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![pytest](https://img.shields.io/badge/logo-pytest-blue?logo=pytest&labelColor=5c5c5c&label=%20)](https://github.com/pytest-dev/pytest)

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

```bash
hatch test
```

For information on how to contribute your developments back to the Vega-Altair repository, see
[`CONTRIBUTING.md`](https://github.com/vega/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}
} 
```