Metadata-Version: 2.1
Name: profiplots
Version: 2.1.4
Summary: Package for helping data scientists create beautiful profinit-styled plots.
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
Requires-Dist: matplotlib
Requires-Dist: seaborn>=0.13.0
Provides-Extra: ci
Requires-Dist: pip-tools; extra == "ci"
Requires-Dist: black; extra == "ci"
Requires-Dist: pytest; extra == "ci"
Requires-Dist: ruff; extra == "ci"
Requires-Dist: pre-commit; extra == "ci"
Requires-Dist: jupyter; extra == "ci"
Requires-Dist: tabulate; extra == "ci"
Requires-Dist: quartodoc; extra == "ci"
Requires-Dist: twine; extra == "ci"
Provides-Extra: docs
Requires-Dist: jupyter; extra == "docs"
Requires-Dist: tabulate; extra == "docs"
Requires-Dist: quartodoc; extra == "docs"

# profiplots

Make Matplotlib and Seaborn plots with Profinit theme!

- Documentation: https://datascience.profinitservices.cz/sablony/profiplots/.

## Installation

```sh
python -m pip install profiplots
```

## Usage

```python
import profiplots as pf
import seaborn as sns
import seaborn.objects as so

# set theme
pf.set_theme()

# create a basic plot
dataset = sns.load_dataset("titanic")
(
    so.Plot(data=dataset, x="survived", y="sex")
    .add(so.Bar(alpha=1), so.Agg(), legend=False)
    .label(title="Female passengers survived much more frequently", x="Survival Rate", y="Sex")
    .save("my_first_plot.png")
)
```
