Files
egutierrez cfdf515228 chore: auto-commit (799 archivos)
- .claude/CLAUDE.md
- .claude/commands/subagentes.md
- .claude/rules/INDEX.md
- .mcp.json
- bash/functions/cybersecurity/analyze_dns.md
- bash/functions/cybersecurity/audit_http_headers.md
- bash/functions/cybersecurity/audit_ssh_config.md
- bash/functions/cybersecurity/check_firewall.md
- bash/functions/cybersecurity/detect_suspicious_users.md
- bash/functions/cybersecurity/encrypt_file.md
- ...

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-14 00:28:20 +02:00

1.0 KiB

name, kind, lang, domain, version, purity, signature, description, tags, uses_functions, uses_types, returns, returns_optional, error_type, imports, params, output, tested, tests, test_file_path, file_path
name kind lang domain version purity signature description tags uses_functions uses_types returns returns_optional error_type imports params output tested tests test_file_path file_path
pearson function py datascience 1.0.0 pure def pearson(xs: list, ys: list) -> float Calcula el coeficiente de correlacion de Pearson entre dos listas de floats.
statistics
correlation
python
pendiente-usar
false
math
name desc
xs lista de valores numericos de la primera variable (ej: [1, 2, 3])
name desc
ys lista de valores numericos de la segunda variable, misma longitud que xs
coeficiente de correlacion de Pearson en rango [-1, 1]. 1.0=correlacion perfecta positiva, -1.0=negativa, 0.0=sin correlacion false
python/functions/datascience/datascience.py

Ejemplo

r = pearson([1, 2, 3], [2, 4, 6])
# r = 1.0

Notas

Usa solo math stdlib. No requiere numpy. Retorna 0.0 si las listas tienen longitud diferente, estan vacias, o la desviacion es cero.