Implementation:DistrictDataLabs Yellowbrick Drawing Utilities

Knowledge Sources	DistrictDataLabs_Yellowbrick
Domains	Visualization, Utilities
Last Updated	2026-02-08 05:00 GMT

Overview

Utility functions for common matplotlib drawing procedures including manual legends and stacked bar charts, provided by the Yellowbrick library.

Description

The draw module provides manual_legend for adding custom legends with colored circle patches to scatter plots, and bar_stack for rendering stacked bar charts with customizable orientation, colors, and legends. These are used internally by multiple Yellowbrick visualizers.

Usage

Import these utilities when building custom visualizations that need manual legend construction or stacked bar chart rendering.

Code Reference

Source Location

• Repository: DistrictDataLabs_Yellowbrick
• File: yellowbrick/draw.py
• Lines: 1-194

Signature

def manual_legend(g, labels, colors, **legend_kwargs):
    """Adds a manual legend with colored circle patches."""

def bar_stack(data, ax=None, labels=None, ticks=None, colors=None,
              colormap=None, orientation="vertical", legend=True,
              legend_kws=None, **kwargs):
    """Creates a stacked bar chart."""

Import

from yellowbrick.draw import manual_legend, bar_stack

I/O Contract

Inputs (manual_legend)

Name	Type	Required	Description
g	Visualizer or Axes	Yes	Target for legend
labels	list of str	Yes	Legend labels
colors	list	Yes	Colors for each label

Inputs (bar_stack)

Name	Type	Required	Description
data	2D array-like	Yes	Data for stacked bars
ax	matplotlib.Axes	No	Target axes
labels	list of str	No	Stack segment labels
orientation	str	No	"vertical" or "horizontal" (default: "vertical")

Outputs

Name	Type	Description
ax	matplotlib.Axes	Axes with rendered elements

Usage Examples

import matplotlib.pyplot as plt
from yellowbrick.draw import manual_legend, bar_stack
import numpy as np

# Stacked bar chart
data = np.random.randint(1, 10, size=(3, 5))
fig, ax = plt.subplots()
bar_stack(data, ax=ax, labels=["A", "B", "C"], ticks=["G1", "G2", "G3", "G4", "G5"])
plt.show()

Related Pages

• Environment:DistrictDataLabs_Yellowbrick_Python_Scikit_Learn_Environment