Implementation:DistrictDataLabs Yellowbrick MissingDataVisualizer

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

Overview

Base class providing the common interface for missing data visualization tools in the Yellowbrick contrib module.

Description

The MissingDataVisualizer extends DataVisualizer with missing-data-specific functionality. Its fit method handles conversion of DataFrames to numpy arrays and delegates to draw. The get_feature_names method extracts column names from DataFrames or generates numeric indices for arrays.

Usage

Subclass MissingDataVisualizer when building new missing data visualizers. End users typically use its subclasses MissingValuesBar and MissingValuesDispersion directly.

Code Reference

Source Location

• Repository: DistrictDataLabs_Yellowbrick
• File: yellowbrick/contrib/missing/base.py
• Lines: 1-81

Signature

class MissingDataVisualizer(DataVisualizer):
    def fit(self, X, y=None, **kwargs):
        """Fits the missing data visualizer."""

    def get_feature_names(self):
        """Returns feature names or numeric indices."""

Import

from yellowbrick.contrib.missing.base import MissingDataVisualizer

I/O Contract

Inputs

Name	Type	Required	Description
X	array-like or DataFrame	Yes	Feature data
y	array-like	No	Target labels

Outputs

Name	Type	Description
self	MissingDataVisualizer	Fitted visualizer

Usage Examples

# MissingDataVisualizer is a base class used by:
from yellowbrick.contrib.missing import MissingValuesBar, MissingValuesDispersion

Related Pages

• Environment:DistrictDataLabs_Yellowbrick_Python_Scikit_Learn_Environment