Implementation:DistrictDataLabs Yellowbrick PosTagVisualizer

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

Overview

Concrete tool for visualizing part-of-speech tag frequencies in text documents, supporting both Penn Treebank and Universal tagsets via NLTK or spaCy parsers.

Description

The PosTagVisualizer parses documents to extract part-of-speech (POS) tags and displays their frequency distribution as bar charts. It supports two tagsets (Penn Treebank and Universal), two NLP parsers (NLTK and spaCy), and both single-bar and stacked-bar display modes. It can show either raw counts or normalized frequencies.

Usage

Import this visualizer when analyzing the grammatical structure of text documents. It requires either NLTK or spaCy to be installed for POS tagging.

Code Reference

Source Location

Repository: DistrictDataLabs_Yellowbrick
File: yellowbrick/text/postag.py
Lines: 1-676

Signature

class PosTagVisualizer(TextVisualizer):
    def __init__(
        self,
        ax=None,
        tagset="penn_treebank",
        colormap=None,
        colors=None,
        frequency=False,
        stack=False,
        parser=None,
        **kwargs,
    ):
        """Part-of-speech tag frequency visualizer."""

def postag(
    X, y=None, ax=None, tagset="penn_treebank", colormap=None, colors=None,
    frequency=False, stack=False, parser=None, show=True, **kwargs,
):
    """Quick method for one-off POS tag visualization."""

Import

from yellowbrick.text import PosTagVisualizer
from yellowbrick.text.postag import postag

I/O Contract

Inputs

Name	Type	Required	Description
X	list of str	Yes	Documents to parse for POS tags
tagset	str	No	"penn_treebank" or "universal" (default: "penn_treebank")
parser	str	No	"nltk" or "spacy" (auto-detected)
frequency	bool	No	Show normalized frequencies (default: False)
stack	bool	No	Use stacked bar chart (default: False)

Outputs

Name	Type	Description
ax	matplotlib.Axes	Axes with POS tag bar chart

Usage Examples

from yellowbrick.text import PosTagVisualizer

documents = [
    "The quick brown fox jumped over the lazy dog.",
    "She sells sea shells by the sea shore.",
]

viz = PosTagVisualizer(tagset="penn_treebank")
viz.fit(documents)
viz.show()

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