Metadata-Version: 2.4
Name: datachart
Version: 0.8.1
Summary: The customizable data chart creation package
Author: Erik Novak
Maintainer: Erik Novak
License: BSD 3-Clause License
        
        Copyright (c) 2023, Erik Novak
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        1. Redistributions of source code must retain the above copyright notice, this
           list of conditions and the following disclaimer.
        
        2. 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.
        
        3. Neither the name of the copyright holder 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
        IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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        DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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Project-URL: Source, https://github.com/eriknovak/datachart
Project-URL: Docs, https://github.com/eriknovak/datachart
Keywords: python,dataviz,visualization
Classifier: Intended Audience :: Science/Research
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: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Multimedia :: Graphics
Classifier: Framework :: Matplotlib
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: matplotlib
Requires-Dist: pypalettes
Requires-Dist: scipy
Provides-Extra: dev
Requires-Dist: black; extra == "dev"
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Requires-Dist: python-githooks; extra == "dev"
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Requires-Dist: mkdocs-llmstxt==0.5.0; extra == "dev"
Requires-Dist: mkdocstrings[python]; extra == "dev"
Provides-Extra: test
Requires-Dist: coverage; extra == "test"
Requires-Dist: nbmake; extra == "test"
Provides-Extra: all
Requires-Dist: datachart[dev,test]; extra == "all"
Dynamic: license-file

<p align="center">
  <img src="https://raw.githubusercontent.com/eriknovak/datachart/main/docs/assets/imgs/logo.png" alt="logo" height="200" style="height:200px">
</p>

<p align="center">
  <i>Data visualization package, simple to use, highly customizable</i>
</p>

<p align="center">
  <a href="https://github.com/eriknovak/datachart/actions/workflows/unittests.yaml" target="_blank"><img
    src="https://github.com/eriknovak/datachart/actions/workflows/unittests.yaml/badge.svg" alt="Test"
  /></a>
  <a href="https://pypi.org/project/datachart" target="_blank"><img
    src="https://img.shields.io/pypi/v/datachart?color=%2334D058" alt="Package Package Index"
  /></a>
  <a href="https://pypi.org/project/datachart" target="_blank"><img
    src="https://img.shields.io/pypi/pyversions/datachart.svg?color=%2334D058" alt="Supported Python Versions"
  /></a>
</p>


---

**Documentation:** [https://eriknovak.github.io/datachart](https://eriknovak.github.io/datachart)

**Source code:** [https://github.com/eriknovak/datachart](https://github.com/eriknovak/datachart)

---

The datachart package is a python package for creating data visualizations, built on top of [matplotlib](https://matplotlib.org/). It is designed to be simple to use and highly customizable, i.e. it is easy to change the look and feel of the charts.

**Features:**

- **Charts.** Bar charts, line charts, scatter charts, histograms, heatmaps, box plots, pyramid charts, radial charts, and parallel coordinates — each created with a single function call from plain lists of dicts.
- **Composition.** Combine rendered charts with `Panel` (overlay charts on a single plot, with optional dual y-axes) and `Grid` (arrange charts in a grid; grids nest).
- **Themes & configuration.** Six predefined themes, each named for its visual trait, plus a global `config` for tweaking any style attribute — per-chart `style` overrides included.

## Requirements
Before starting the project make sure these requirements are available:

- [python]. The python programming language (v3.10 or higher).

## Install

```bash
pip install datachart
```

## Upgrade

```bash
pip install datachart --upgrade
```

## Example

Set a theme once and every chart follows it. The example below uses the `INK` theme:

```python
from datachart.charts import LineChart
from datachart.config import config
from datachart.constants import THEME

config.set_theme(THEME.INK)

figure = LineChart(
    [
        [{"x": x, "y": y} for x, y in enumerate([40, 45, 43, 50, 56, 54, 61])],
        [{"x": x, "y": y} for x, y in enumerate([38, 40, 44, 43, 48, 52, 55])],
    ],
    title="Line",
    subtitle=["Run 1", "Run 2"],
    show_legend=True,
)
```

The same theme, across chart types and composed with `Grid`:

<p align="center">
  <img src="https://raw.githubusercontent.com/eriknovak/datachart/main/docs/assets/imgs/example-ink.png" alt="INK theme example charts" width="720" />
</p>

More examples on how to use the `datachart` package are available
on the official [How-to Guides](https://eriknovak.github.io/datachart/how-to-guides/).

## Using with LLMs

The documentation is available in LLM-friendly formats:

- [llms.txt](https://eriknovak.github.io/datachart/llms.txt) — index of the documentation with descriptions
- [llms-full.txt](https://eriknovak.github.io/datachart/llms-full.txt) — full documentation in a single file
- Every documentation page is also available as plain markdown by appending `index.md` to its URL, e.g. [how-to-guides/charts/linechart/index.md](https://eriknovak.github.io/datachart/how-to-guides/charts/linechart/index.md)

You can also connect your AI assistant directly:

- [Context7](https://context7.com/eriknovak/datachart) — up-to-date, version-aware docs for AI coding assistants
- [GitMCP](https://gitmcp.io/eriknovak/datachart) — an MCP server serving this repository's documentation

[python]: https://www.python.org/
