bixplot 0.1.0

The bixplot: A variation on the boxplot suited for bimodal data

bixplot

bixplot is a visualization designed to detect and display bimodal and multimodal structure in univariate data. It combines density visualization (like violin plots), summary statistics (like boxplot), and individual observations (like rug plot).

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Background

The method is based on the research paper:

“The bixplot: A variation on the boxplot suited for bimodal data”

The classical boxplot assumes unimodality and may fail to reveal meaningful subgroups in the data.
The bixplot addresses this by:

• testing for unimodality
• if unimodality is rejected, it applies a univariate clustering method that ensures contiguous clusters, meaning that no cluster has members inside another cluster, and such that each cluster contains at least a given number of unique members.
• visualizing clusters as separate components

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Installation

pip install bixplot

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Quick example

from bixplot import bixplot import seaborn as sns

df_penguins = sns.load_dataset("penguins") print(df_penguins.shape) display(df_penguins.head(2))

fig, axs = plt.subplots(1,2, figsize=(8, 4)) sns.violinplot(data=df_penguins, x='island', y='bill_length_mm', color=R_orange, linecolor="k", ax=axs[0]) axs[0].set_title("violin plot", fontweight='bold', fontsize=10)

bixplot(data=df_penguins, x='island', y='bill_length_mm', ax=axs[1]) axs[1].set_title("bixplot", fontweight='bold', fontsize=10) plt.tight_layout()

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Examples

More examples are available in the examples/ folder.

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Data

The data/ folder contains datasets used for demonstrations.

See data/README.md for full attribution and sources.

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License

MIT http://opensource.org/licenses/MIT

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Author

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