Quickstart: Plotting Gallery

Use this when you need to choose a manuscript figure style before adapting it to a real cohort.

Install

bash

uv add "fyron[ml,survival]"

Browse The Gallery

Start with the Visual Figure Gallery. Each figure is generated from deterministic synthetic data so you can copy the call shape safely.

Good first choices:

Question	Start with
Survival by group	Kaplan-Meier or KM reference bands
Biomarker distribution	histogram, density, raincloud, grouped boxplot
Clinical reference intervals	reference band grid
Classifier performance	ROC, PR, calibration, decision curve
Feature selection or explainability	feature importance, stability selection, signed feature weights

Use A Figure Function

python

import pandas as pd
from fyron import plotting as fp

df = pd.DataFrame(
    {
        "age": [54, 58, 61, 69, 73, 77],
        "group": ["A", "A", "B", "B", "B", "A"],
        "marker": [1.2, 1.4, 2.1, 2.5, 2.8, 1.9],
    }
)

fig, ax = fp.plot_grouped_boxplot(
    df,
    x="group",
    y="marker",
    ylabel="Marker value",
    title="Synthetic biomarker distribution",
)

Next Steps

Read Clinical Plotting for parameters shared across plot helpers.
Read Colors And Styles for palettes and publication styling.