topic-wizard 0.2.3

Pretty and opinionated topic model visualization in Python.

topicwizard

Pretty and opinionated topic model visualization in Python.

https://user-images.githubusercontent.com/13087737/219967955-1263c35b-4c5b-4ccc-adb9-23e073e099f0.mp4

Features

• Investigate complex relations between topics, words and documents
• Highly interactive
• Name topics
• Pretty :art:
• Intuitive :cow:
• Clean API :candy:
• Sklearn compatible :nut_and_bolt:
• Easy deployment :earth_africa:

Installation

Install from PyPI:

pip install topic-wizard

Usage (documentation)

Step 1:

Train a scikit-learn compatible topic model.

from sklearn.decomposition import NMF
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.pipeline import Pipeline

topic_pipeline = Pipeline(
    [
        ("bow", CountVectorizer()),
        ("nmf", NMF(n_components=10)),
    ]
)
topic_pipeline.fit(texts)

Step 2:

Visualize with topicwizard.

import topicwizard

topicwizard.visualize(pipeline=topic_pipeline, corpus=texts)

Step 3:

Investigate :eyes: .

a) Topics

b) Words

c) Documents