# jbesomi/texthero

Text preprocessing, representation and visualization from zero to hero.

Repository: https://github.com/jbesomi/texthero
Canonical: https://ross.abutalabs.com/products/texthero
Homepage: https://texthero.org
Language: Python
License: MIT
License Family: permissive
Topics: text-preprocessing, text-representation, text-visualization, nlp, word-embeddings, machine-learning, text-mining, nlp-pipeline, text-clustering, texthero
Last push: 2023-08-29T08:45:13+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 2340, "days_push": 1100, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2907, forks 236 (observed 2026-08-28T04:07:29.130952+00:00)

## What it is
Texthero is a Python toolkit for text preprocessing, representation, and visualization, designed to work on top of Pandas Series and DataFrames. It provides pipelines for cleaning text, mapping it into vector spaces (TF-IDF, term frequency), clustering, dimensionality reduction, and visualizing text datasets in a few lines of code.

## Use cases
- clean and preprocess text data in pandas
- compute tf-idf vectors for a text corpus
- cluster documents with k-means
- visualize text vector spaces with pca and tsne
- extract named entities from text
- find top words and keywords in a dataset
- remove stopwords, punctuation, and html tags from text

## When to choose
- you work with text datasets in Pandas and want quick cleaning and vectorization
- you need fast exploratory insights into text-only data
- you want a simple scikit-learn-like API for text preprocessing and clustering

## When to avoid
- you need state-of-the-art NLP models or transformer-based pipelines
- you need actively developed features or timely bug fixes
- you need production-grade, highly customizable NLP pipelines

## Facets
- artifact type: library
- maturity: maintenance
- function: nlp, data-science, data-visualization, machine-learning, parser
- domain: data-science, machine-learning
- platform: python
- tags: text-preprocessing, pandas, tf-idf, word-embeddings, text-clustering, topic-modeling, named-entity-recognition, scikit-learn, natural-language-processing, text-mining

## Member repositories
- jbesomi/texthero (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:29.130952+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:34:23.846675+00:00, confidence not recorded.
  - readme: https://github.com/jbesomi/texthero (fetched 2026-08-28T04:07:29.130952+00:00, sha e8bbf98304d9)
  - homepage: https://texthero.org (fetched 2026-08-29T09:49:41.784577+00:00, sha 558e07bfe983)
  - site_page: https://texthero.org/docs/getting-started (fetched 2026-08-29T09:49:41.794195+00:00, sha 4344e832fdf7)
  - site_page: https://texthero.org/docs/api-preprocessing (fetched 2026-08-29T09:49:41.796506+00:00, sha 80b724589586)
  - site_page: https://texthero.org/docs/api-representation (fetched 2026-08-29T09:49:41.798282+00:00, sha 4b71b429f618)
  - registry_pypi: https://pypi.org/pypi/texthero/json (fetched 2026-08-29T09:49:41.799833+00:00, sha c92c0e50d869)
- Data as of 2026-08-30T08:39:29.467469+00:00.