Pretty and opinionated topic model visualization in Python.
Project description
topicwizard
Pretty and opinionated topic model visualization in Python.
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
Project details
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