Metadata-Version: 2.4
Name: fleur
Version: 0.0.4
Summary: Combining statistics with visualization for Python
Author-email: Joseph Barbier <joseph.barbierdarnal@gmail.com>
License-Expression: MIT
Project-URL: Homepage, https://y-sunflower.github.io/fleur/
Project-URL: Issues, https://github.com/y-sunflower/fleur/issues
Project-URL: Documentation, https://y-sunflower.github.io/fleur/
Project-URL: Repository, https://github.com/y-sunflower/fleur
Keywords: statistics,visualization,data,annotations,reproductibility
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: matplotlib>=3.10
Requires-Dist: narwhals>=1.41.0
Requires-Dist: scipy>=1.13.1
Dynamic: license-file

# `fleur`: combining statistics with visualization

<!-- Automatically generated, uses README.qmd to modify README.md -->

<img src="https://github.com/JosephBARBIERDARNAL/static/blob/main/python-libs/fleur/image.png?raw=true" alt="fleur logo" align="right" width="150px"/>

With `fleur` (_pronounced “flur”_), statistics and data visualization
are done at the same time. It’s meant as a modern tool for highly
detailed statistical annotations in plots with high customization
capabilities.

It’s lightweight in the sense that it only requires foundational
libraries: `matplotlib`, `scipy` and `narwhals`. Learn more [about
fleur](./about.md).

> [!WARNING] fleur is still in a very early stage: expect regular
> breaking changes.

[Documentation website](https://y-sunflower.github.io/fleur/)

![Coverage](coverage-badge.svg)

<br>

## Quick start

### Group comparison

```python
from fleur import BetweenStats
from fleur import data

df = data.load_iris()

BetweenStats(df["sepal_length"], df["species"]).plot()
```

![](https://github.com/y-sunflower/fleur/blob/main/docs/img/quickstart-betweenstats.png)

### Correlation

```python
from fleur import ScatterStats
from fleur import data

df = data.load_iris()

ScatterStats(df["sepal_length"], df["sepal_width"]).plot()
```

![](https://github.com/y-sunflower/fleur/blob/main/docs/img/quickstart-scatterstats.png)

<br><br>

## Installation

```bash
pip install fleur
```

<br><br>
