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feat(eda): capítulo text_distr (TEXTO/NLP) — primer capítulo de datos no tabulares

Browse Source 
Añade el capítulo `text_distr` al motor AutomaticEDA: perfila columnas de texto
libre largo (reseñas, descripciones, comentarios) que la distribución categórica
no resume bien. Sigue el patrón de cat_distr/num_distr (build_text_distr(profile,
ctx) -> Chapter | None) y se registra en CHAPTER_ORDER tras cat_distr.

Activación en dos fases: gate barato desde el perfil (columna no numérica con
len_mean >= 50 chars) + confirmación con muestra cruda (mediana de palabras >= 20).
Un dataset sin texto largo (p.ej. titanic) devuelve None sin tocar el informe.

Bloques por columna (Group con page_break): resumen (longitudes, vocabulario con
TTR y % hapax, idioma dominante, % duplicados, legibilidad), histograma de
longitudes, top términos (tabla + barras), bigramas/trigramas, idiomas detectados
y nube de palabras opcional. Términos ttr/hapax enganchados al glosario clicable.

Lógica delegada a 7 funciones nuevas del registry (datascience, tag eda),
estilo dict-no-throw:
- extract_text_sample (impura, push-down SQL DuckDB/Postgres)
- compute_text_length_stats, compute_vocabulary_stats, compute_top_ngrams (puras, stdlib)
- detect_corpus_language (langdetect opcional), compute_text_readability (textstat
  opcional), compute_text_duplicates (hash + datasketch opcional)

Versión barata sin modelos pesados: las piezas que dependen de una librería
opcional (langdetect, textstat, wordcloud, datasketch) degradan a omitidas sin
lanzar. Añade langdetect y textstat (ligeras) al pyproject + uv.lock.

Verificado: golden sobre dataset de reviews multi-idioma (capítulo presente en
PDF+PPTX+MD con métricas reales), titanic sin capítulo (None), degradación sin
libs, suite automatic_eda + pipeline verde (128 passed), fn index OK.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
This commit is contained in:
Egutierrez
2026-06-30 20:38:17 +02:00
parent a1e2e3567c
commit 105e56cf05
26 changed files with 2880 additions and 0 deletions
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