C2VistaHist

Enriched Univariate Histogram — Cepheus AI Labs

Dr Subbiah | https://cepheusonline.com/

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What It Does

A plain histogram shows shape. C2VistaHist reveals the full story.

enriched_histogram() produces a single, self-contained, publication-ready interactive histogram that simultaneously displays:

• Histogram bars
• Mean, Median, and Mode as distinct vertical reference lines (color + line type differentiated)
• User-defined percentile lines (up to 5)
• Fitted normal distribution curve overlay (optional)
• Integrated statistics footnote panel: n, Min, Max, Mean, Median, Mode, SD, Skewness, Kurtosis

All components are designed for both human eyeball judgement and future AI-assisted interpretation pipelines.

Built on Plotly — fully interactive, hoverable, exportable.

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Installation

Install directly from GitHub:

pip install git+https://github.com/CepheusAILabs/C2VistaHist.git

Or clone and install locally:

git clone https://github.com/CepheusAILabs/C2VistaHist.git
cd C2VistaHist
pip install -r requirements.txt

Then in your script:

from c2vistahist import enriched_histogram

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Quick Start

Minimal call — all defaults applied:

from c2vistahist import enriched_histogram

enriched_histogram(
    filepath = "your_data.csv",
    column   = "your_column"
)

Full custom call:

enriched_histogram(
    filepath      = "your_data.csv",
    column        = "bweight",
    variable_name = "Birth Weight (grams)",
    bin_rule      = "fd",
    y_axis_mode   = "frequency",
    show_normal   = True,
    percentiles   = [5, 25, 75, 95]
)

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Parameters

Parameter	Default	Description
filepath	—	Path to CSV file. Required.
column	—	Column name to analyse. Required.
variable_name	"Study Variable"	X-axis label and plot title
bin_rule	"fd"	"sturges" / "scott" / "fd" / integer
y_axis_mode	"frequency"	"frequency" or "density"
show_normal	True	Overlay fitted normal curve
percentiles	[25, 75]	Up to 5 percentile lines. Do not include 50.

See PARAMETERS.md for full details on every parameter.

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Saving Output

The figure opens in the browser automatically. To save:

fig = enriched_histogram(filepath="data.csv", column="bweight")

# Save as interactive HTML
fig.write_html("histogram.html")

# Save as static image (requires kaleido)
# pip install kaleido
fig.write_image("histogram.png", width=1200, height=750, scale=2)

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Dependencies

numpy
scipy
plotly
pandas

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Roadmap

Module	Status
enriched_histogram	✅ v0.1.0
enriched_kde	Coming — C2VistaKDE
enriched_scatter	Coming — C2VistaScatter

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License

MIT License — see LICENSE

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Cepheus AI Labs | https://cepheusonline.com/