Metadata-Version: 2.4
Name: tuesd4y-styles
Version: 0.1.2
Summary: Tuesd4y styling utilities for Python. Adapted from CarbonPlan.
Project-URL: Homepage, https://github.com/tuesd4y/tuesd4y-styles
Project-URL: Repository, https://github.com/tuesd4y/tuesd4y-styles
Author-email: Christopher Stelzmueller <tuesd4y@protonmail.ch>
License-Expression: MIT
License-File: LICENSE
Requires-Python: >=3.8
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: seaborn
Description-Content-Type: text/markdown

# Colors

A Python package providing custom color palettes and themes for data visualization with matplotlib and seaborn.

Styles are adapted from [CarbonPlan Style](https://github.com/carbonplan/styles).

## Installation

```bash
pip install tuesd4y-styles
```

## Usage

### Basic Usage

```python
# Import the required modules
from tuesd4y_styles import colors, mpl

# Set the theme (available themes: carbonplan_light)
mpl.set_theme(style='carbonplan_light')

# Load colors into your local namespace
lcs = locals()
lcs.update(**colors.light)

# Now you can use the colors in your plots
import matplotlib.pyplot as plt
import seaborn as sns

# Example with scatter plot using predefined colors
plt.scatter(*zip(*cluster_1), color=red, label='Cluster 1')

# Example with heatmap using custom colormaps
sns.heatmap(city_corr_matrix, annot=True, cmap='redteal_light_r', center=0, ax=ax)
```

### Available Themes
- `carbonplan_light`
- `carbonplan_dark`

### Available Color Palettes
The package provides color palettes through the `colors.light` module. Colors can be accessed directly after updating the local namespace as shown in the usage example.

### Available Colormaps
- `redteal_light_r`: A reversed red-teal colormap suitable for correlation matrices and heatmaps

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## Building

```bash
python -m build
python -m twine upload dist/*
```

## License

[MIT License](LICENSE)
