urbn-viz-chloejbuhl 0.1.1

A tiny, themed data-visualization library with a warm boutique aesthetic, built on matplotlib.

urbn_viz

A tiny, themed data-visualization library built on matplotlib. A handful of guessable functions that draw charts in a warm boutique palette — an original interpretation of the Pantone 2025 Color-of-the-Year mood (Mocha Mousse, olive, lilac, burnt orange, cranberry on a greige canvas). Every chart follows the Evergreen & Emery checklist, using one vivid action color with the supporting hues softened rather than grayed out.

Install

pip install urbn-viz-chloejbuhl

Quick start

import pandas as pd
import urbn_viz as uv

df = pd.read_csv("fashion_boutique_dataset.csv")

ax = uv.bar(df, x="category", y="current_price", agg="sum",
            colorful=True, highlight="Outerwear", value_fmt="${:,.0f}",
            title="Outerwear drives the most revenue, ~$49K",
            subtitle="Total current_price by category")
ax.figure.savefig("revenue.png", bbox_inches="tight")

Every function takes a DataFrame plus column names and never mutates it. Single-axes functions return the matplotlib Axes; faceted functions return the Figure.

Functions

Function	Draws
bar	Ordered bars; colorful=True gives each bar its own hue with the highlight bar vivid and the rest muted
line	Single ordered line, final point labeled
hist	Distribution of one column with the mean marked
scatter	x vs y, optionally split/emphasized by a category
facet_hist	Small-multiple histograms, one panel per category
dumbbell	Two dots per category (e.g. original vs selling price)

Helpers: apply_theme(), mute(hex), category_colors(labels), PALETTE, PALETTE_CYCLE.

The palette

Role / hue	Hex
Canvas	#EAE6DD
Ink	#2C2824
Mocha	#A47864
Apple	#A79555
Lilac	#DCCEDF
Burnt orange	#D57239
Cranberry (default action)	#712E37
Plum / Camel (bridge tones)	#8E5E6E / #C9A66B

mute() keeps a hue but drops its saturation and lifts its lightness, so the non-action elements stay softly colored instead of turning gray.

License

MIT.