# tidymodels/broom

Convert statistical analysis objects from R into tidy format

Repository: https://github.com/tidymodels/broom
Canonical: https://ross.abutalabs.com/products/broom
Homepage: https://broom.tidymodels.org
Language: R
License: NOASSERTION
License Family: other
Topics: r, tidy-data, modeling
Last push: 2026-05-14T16:34:12+00:00

## Health v2 (maintenance only)
Score: 78/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 82, release rhythm 60, longevity 100
- inputs: {"age_days": 4374, "days_push": 111, "days_rel": 111, "gap_med": 102.0, "n_releases_24m": 7}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1525, forks 301 (observed 2026-08-28T04:04:58.320752+00:00)

## What it is
broom is an R package that converts statistical model objects from 100+ modeling packages into tidy tibbles. It provides three verbs—tidy(), glance(), and augment()—to summarize model components, whole-model fit statistics, and observation-level information.

## Use cases
- extract regression coefficients as a tidy data frame
- compare goodness-of-fit statistics across many models
- turn model output into tibbles for ggplot2 visualization
- tidy statistical model results for further dplyr manipulation
- augment a dataset with fitted values and residuals
- summarize lm, glm, and other stats package model objects

## When to choose
- you work in R with statistical models and want tidy, consistent output
- you need to combine or visualize results from many different model types
- you use the tidymodels or tidyverse ecosystem

## When to avoid
- you need model tidiers for mixed models beyond what broom.mixed provides
- you work outside R or need non-tidy data structures

## Facets
- artifact type: library
- maturity: active
- function: data-science, serialization, data-visualization
- domain: data-science, machine-learning
- platform: -
- tags: tidy-data, r-package, statistical-modeling, tidymodels, tibble, model-summarization, statistics, data-engineering, r

## Member repositories
- tidymodels/broom (main) score 78

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:58.320752+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 2026-08-30T04:31:40.682261+00:00, confidence not recorded.
  - readme: https://github.com/tidymodels/broom (fetched 2026-08-28T04:04:58.320752+00:00, sha d38c02636082)
  - homepage: https://broom.tidymodels.org (fetched 2026-08-29T11:34:21.898253+00:00, sha e8be0813b9f9)
  - site_page: https://broom.tidymodels.org/news/index.html (fetched 2026-08-29T11:34:21.907500+00:00, sha db36edf0baa3)
  - site_page: https://broom.tidymodels.org/authors.html (fetched 2026-08-29T11:34:21.910838+00:00, sha 8e7ad73a207f)
- Data as of 2026-08-30T08:39:29.467469+00:00.