Implementation:DistrictDataLabs Yellowbrick DispersionPlot

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

Overview

Concrete tool for visualizing the lexical dispersion of search terms across documents in a corpus, provided by the Yellowbrick text module.

Description

The DispersionPlot visualizes where specified search terms appear across the documents of a corpus. Each term is plotted on a separate row with markers at the word positions where it occurs, optionally annotated with document boundaries and colored by target class.

Usage

Import this visualizer when analyzing the distribution of specific terms across a text corpus to understand how evenly or unevenly words are distributed.

Code Reference

Source Location

• Repository: DistrictDataLabs_Yellowbrick
• File: yellowbrick/text/dispersion.py
• Lines: 1-421

Signature

class DispersionPlot(TextVisualizer):
    def __init__(
        self,
        search_terms,
        ax=None,
        colors=None,
        colormap=None,
        ignore_case=False,
        annotate_docs=False,
        labels=None,
        **kwargs,
    ):
        """Lexical dispersion plot for search terms across a corpus."""

def dispersion(
    search_terms, corpus, y=None, ax=None, colors=None, colormap=None,
    annotate_docs=False, ignore_case=False, labels=None, show=True, **kwargs,
):
    """Quick method for one-off dispersion visualization."""

Import

from yellowbrick.text import DispersionPlot
from yellowbrick.text.dispersion import dispersion

I/O Contract

Inputs

Name	Type	Required	Description
search_terms	list of str	Yes	Words to track across corpus
X	list of str	Yes	Corpus of documents (fit)
y	array-like	No	Target labels for coloring
ignore_case	bool	No	Case-insensitive matching (default: False)
annotate_docs	bool	No	Show document boundaries (default: False)

Outputs

Name	Type	Description
ax	matplotlib.Axes	Axes with dispersion plot

Usage Examples

from yellowbrick.text import DispersionPlot
from yellowbrick.datasets import load_hobbies

corpus = load_hobbies()

viz = DispersionPlot(["film", "game", "sport", "book"])
viz.fit(corpus.data)
viz.show()

Related Pages

• Environment:DistrictDataLabs_Yellowbrick_Python_Scikit_Learn_Environment