seaborn_objects_recipes 0.2.4.post1

A collection of recipes that can be used together with the seaborn library to create custom plots.

Seaborn Objects Recipes

📘 About

seaborn_objects_recipes is a Python package that extends the functionality of the Seaborn library, providing custom recipes for enhanced data visualization. This package includes below features to augment your Seaborn plots with additional capabilities.

• Rolling
• LineLabel
• Lowess
• PolyFitWithCI

[!TIP] For the full gallery and API, see the docs: API-Gallery Docs

📊 Combined Example: Rolling + LOWESS + Direct Line Labels

This example shows how multiple recipes can be layered to clarify noisy time-series data. We generate two synthetic series (sin and cos), apply a short-window rolling mean to smooth local fluctuations, overlay a LOWESS curve to reveal the long-term structure, and add LineLabel to place direct text labels at the right edge of each line.

This pattern is useful when you want:

• Local smoothing (Rolling) to reduce short-term noise
• Nonparametric smoothing (Lowess) to reveal global trends
• Direct labeling (LineLabel) to avoid legends and improve readability in multi-series plots

Together, these transforms produce a clean, interpretable visualization that emphasizes both local variation and overall structure — ideal for exploratory time-series analysis, sensor measurements, economic indicators, or any repeated noisy signal.

    import seaborn.objects as so
    import seaborn_objects_recipes as sor
    import seaborn as sns
    import numpy as np
    import pandas as pd

    # ---- Example data ----
    np.random.seed(42)
    x = np.linspace(0, 10, 200)
    y1 = np.sin(x) + np.random.normal(scale=0.25, size=len(x))
    y2 = np.cos(x) + np.random.normal(scale=0.25, size=len(x))

    df = pd.DataFrame(
        {
            "x": np.tile(x, 2),
            "y": np.concatenate([y1, y2]),
            "series": np.repeat(["sin", "cos"], len(x)),
        }
    )

    (
        so.Plot(df, x="x", y="y", color="series", text="series")
        # Rolling-smoothed line
        .add(so.Line(), rolling := sor.Rolling(window=8, agg="mean"),legend=False,)
        # LOWESS-smoothed line (overlaid)
        .add(so.Line(), sor.Lowess(frac=0.25),legend=False,)
        # Direct labels at the right edge of each series
        .add(sor.LineLabel(offset=8), rolling)
        .layout(size=(10, 4))
        .label(
            title="Smoothed Sin/Cos Time Series with Direct Labels",
            x="x",
            y="Smoothed value",
        )
        .show()
    )

⚙️ Installation

To install seaborn_objects_recipes, run the following command:

pip install seaborn_objects_recipes

✉️ Contact

For questions or feedback regarding seaborn_objects_recipes, please contact Ofosu Osei.

🌟 Credits

• Special thanks to @nickeubank for the support and mentorship on this project
• Special thanks to @JesseFarebro for Rolling, LineLabel
• Special thanks to @tbpassin and @kcarnold for LOWESS Smoother

🤝 Contributing

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

[!IMPORTANT] Quick Checklist:

• ✅ Distinct x-value count valid for LOWESS (frac ≥ 2/n)
• ✅ CI columns present (ymin, ymax) when bootstrapping is on
• ✅ alpha respected and bootstraps defaulted if unset