Implementation:DistrictDataLabs Yellowbrick TextVisualizer

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

Overview

Base class providing the common interface for all Yellowbrick text visualization tools, combining the Visualizer and scikit-learn TransformerMixin APIs.

Description

The TextVisualizer is the abstract base class for all text-specific visualizers in Yellowbrick. It inherits from both Visualizer (providing matplotlib integration) and scikit-learn's TransformerMixin (providing fit_transform). It adds a fit_transform_show convenience method for the common workflow of fitting, transforming, and displaying in one call.

Usage

Subclass TextVisualizer when creating new text visualization tools. End users typically do not instantiate this class directly but use its subclasses like TSNEVisualizer, PosTagVisualizer, etc.

Code Reference

Source Location

• Repository: DistrictDataLabs_Yellowbrick
• File: yellowbrick/text/base.py
• Lines: 1-127

Signature

class TextVisualizer(Visualizer, TransformerMixin):
    def __init__(self, ax=None, fig=None, **kwargs):
        """Base class for text visualizers."""

    def fit(self, X, y=None, **fit_params):
        """Fits the text visualizer to data."""

    def transform(self, X):
        """Pass-through transform returning X unchanged."""

    def fit_transform_show(self, X, y=None, **kwargs):
        """Fit, transform, and show in one call."""

Import

from yellowbrick.text.base import TextVisualizer

I/O Contract

Inputs

Name	Type	Required	Description
X	array-like	Yes	Text data or vectorized text
y	array-like	No	Target labels

Outputs

Name	Type	Description
self	TextVisualizer	Fitted visualizer (from fit)
X	array-like	Unchanged input (from transform)

Usage Examples

# TextVisualizer is used as a base class:
from yellowbrick.text.base import TextVisualizer

class MyTextViz(TextVisualizer):
    def fit(self, X, y=None):
        self.draw(X)
        return self

    def draw(self, X):
        self.ax.hist([len(doc) for doc in X])

    def finalize(self):
        self.ax.set_title("Document Length Distribution")

Related Pages

• Environment:DistrictDataLabs_Yellowbrick_Python_Scikit_Learn_Environment