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broom

Convert statistical analysis objects from R into tidy format

https://github.com/tidymodels/broom

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

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    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    21 of 151 committers (13.9%) from academic institutions
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    Low similarity (20.7%) to scientific vocabulary

Keywords

modeling r tidy-data

Keywords from Contributors

tidyverse package-creation rmarkdown pandoc coverage travis-ci literate-programming codecov coverage-report factor
Last synced: 6 months ago · JSON representation

Repository

Convert statistical analysis objects from R into tidy format

Basic Info
Statistics
  • Stars: 1,494
  • Watchers: 52
  • Forks: 306
  • Open Issues: 16
  • Releases: 36
Topics
modeling r tidy-data
Created over 11 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Codeowners

README.Rmd 

---
output: github_document
---



```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  message = FALSE,
  warning = FALSE,
  out.width = "100%"
)
```

# broom  


[![CRAN status](https://www.r-pkg.org/badges/version/broom)](https://CRAN.R-project.org/package=broom)
[![Downloads](https://cranlogs.r-pkg.org/badges/broom)](https://CRAN.R-project.org/package=broom)
[![R-CMD-check](https://github.com/tidymodels/broom/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tidymodels/broom/actions/workflows/R-CMD-check.yaml)


## Overview

`broom` summarizes key information about models in tidy `tibble()`s. `broom` provides three verbs to make it convenient to interact with model objects:

- `tidy()` summarizes information about model components
- `glance()` reports information about the entire model
- `augment()` adds informations about observations to a dataset

For a detailed introduction, please see `vignette("broom")`.

`broom` tidies 100+ models from popular modelling packages and almost all of the model objects in the `stats` package that comes with base R. `vignette("available-methods")` lists method availability.

If you aren't familiar with tidy data structures and want to know how they can make your life easier, we highly recommend reading Hadley Wickham's [Tidy Data](https://www.jstatsoft.org/v59/i10).

## Installation

```{r, eval = FALSE}
# we recommend installing the entire tidyverse
# modeling set, which includes broom:
install.packages("tidymodels")

# alternatively, to install just broom:
install.packages("broom")

# to get the development version from GitHub:
install.packages("pak")
pak::pak("tidymodels/broom")
```

If you find a bug, please file a minimal reproducible example in the [issues](https://github.com/tidymodels/broom/issues).

## Usage

`tidy()` produces a `tibble()` where each row contains information about an important component of the model. For regression models, this often corresponds to regression coefficients. This is can be useful if you want to inspect a model or create custom visualizations.

```{r}
library(broom)

fit <- lm(Volume ~ Girth + Height, trees)
tidy(fit)
```

`glance()` returns a tibble with exactly one row of goodness of fitness measures and related statistics. This is useful to check for model misspecification and to compare many models.

```{r}
glance(fit)
```

`augment` adds columns to a dataset, containing information such as fitted values, residuals or cluster assignments. All columns added to a dataset have `.` prefix to prevent existing columns from being overwritten.

```{r}
augment(fit, data = trees)
```

### Contributing

We welcome contributions of all types!

For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on Posit Community](https://forum.posit.co/new-topic?category_id=15https://rstd.io/tidymodels-communitytags=tidymodels,question). If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/broom/issues). Either way, learn how to create and share a [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html) (a minimal, reproducible example), to clearly communicate about your code. Check out further details on [contributing guidelines for tidymodels packages](https://www.tidymodels.org/contribute/) and [how to get help](https://www.tidymodels.org/help/).

If you have never directly contributed to an R package before, `broom` is an excellent place to start. Find an [issue](https://github.com/tidymodels/broom/issues/) with the **Beginner Friendly** tag and comment that you'd like to take it on and we'll help you get started.

Generally, too, we encourage typo corrections, bug reports, bug fixes and feature requests. Feedback on the clarity of the documentation is especially valuable!

If you are interested in adding tidier methods for new model objects, please read [this article](https://www.tidymodels.org/learn/develop/broom/) on the tidymodels website.

We have a [Contributor Code of Conduct](https://github.com/tidymodels/broom/blob/main/.github/CODE_OF_CONDUCT.md). By participating in `broom` you agree to abide by its terms.

Owner

  • Name: tidymodels
  • Login: tidymodels
  • Kind: organization

GitHub Events

Total
  • Create event: 6
  • Release event: 1
  • Issues event: 27
  • Watch event: 48
  • Delete event: 5
  • Issue comment event: 37
  • Push event: 50
  • Pull request event: 16
  • Fork event: 5
Last Year
  • Create event: 6
  • Release event: 1
  • Issues event: 27
  • Watch event: 48
  • Delete event: 5
  • Issue comment event: 37
  • Push event: 50
  • Pull request event: 16
  • Fork event: 5

Committers

Last synced: 8 months ago

All Time
  • Total Commits: 1,557
  • Total Committers: 151
  • Avg Commits per committer: 10.311
  • Development Distribution Score (DDS): 0.66
Past Year
  • Commits: 56
  • Committers: 4
  • Avg Commits per committer: 14.0
  • Development Distribution Score (DDS): 0.054
Top Committers
Name Email Commits
Simon P. Couch s****h@g****m 529
alex hayes a****s@g****m 205
dgrtwo d****o@p****u 127
Dave Robinson d****n@s****m 66
Grant McDermott g****t@g****m 54
Derek Chiu d****u@b****a 50
Matthew Lincoln m****n@g****m 33
David Hugh-Jones d****s@g****m 28
jgabry j****y@g****m 22
Vincent Arel-Bundock v****k@u****a 20
bbolker b****r@g****m 18
Greg Macfarlane g****e@b****u 17
Daniel Sjoberg d****g@g****m 16
karldw k****w 15
David Robinson a****d@g****m 15
Matthieu Stigler M****r@g****m 12
Indrajeet Patil p****e@g****m 11
Lily Medina l****u@g****m 10
Benjamin b****r@g****m 10
Michael Kuehn m****0@g****m 8
Joran Elias j****s@u****u 7
François b****e@g****m 7
Brenton M. Wiernik b****k 7
Joseph Larmarange j****h@l****t 7
Max Kuhn m****n@g****m 7
Nic t****c@g****m 6
helix123 k****t@g****e 6
Matt Lehman 1****4 5
Michal Bojanowski m****2@g****m 5
olivroy 5****y 5
and 121 more...
Committer Domains (Top 20 + Academic)
rstudio.com: 2 uni-koeln.de: 2 uoregon.edu: 1 menne-biomed.de: 1 mpi-bn.mpg.de: 1 uwaterloo.ca: 1 reed.edu: 1 refsmmat.com: 1 dynamic-oit-fishnet-d-25.princeton.edu: 1 gmail.crom: 1 acu.edu.au: 1 normalesup.org: 1 gmx.de: 1 larmarange.net: 1 umontana.edu: 1 byu.edu: 1 umontreal.ca: 1 bccrc.ca: 1 stackoverflow.com: 1 aroma-project.org: 1 psych.ubc.ca: 1 sodas.ku.dk: 1 lshtm.ac.uk: 1 uchicago.edu: 1 u.northwestern.edu: 1 gsb.columbia.edu: 1 uchc.edu: 1 uga.edu: 1 unl.edu: 1 ivt.baug.ethz.ch: 1 princeton.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 115
  • Total pull requests: 82
  • Average time to close issues: 5 months
  • Average time to close pull requests: 2 months
  • Total issue authors: 71
  • Total pull request authors: 28
  • Average comments per issue: 2.59
  • Average comments per pull request: 2.44
  • Merged pull requests: 64
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 27
  • Pull requests: 14
  • Average time to close issues: 18 days
  • Average time to close pull requests: 4 days
  • Issue authors: 12
  • Pull request authors: 4
  • Average comments per issue: 1.15
  • Average comments per pull request: 0.93
  • Merged pull requests: 10
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • simonpcouch (29)
  • larmarange (4)
  • bbolker (4)
  • alexpghayes (3)
  • DanChaltiel (3)
  • MichaelChirico (3)
  • ddsjoberg (3)
  • cretecht (2)
  • ThomasSoeiro (2)
  • jwilliman (2)
  • oliverbothe (1)
  • HywelMJ (1)
  • AaronRendahl (1)
  • oskasf (1)
  • awcm0n (1)
Pull Request Authors
  • simonpcouch (43)
  • olivroy (6)
  • jrob95 (4)
  • bbolker (3)
  • vincentarelbundock (3)
  • ddsjoberg (2)
  • remlapmot (2)
  • MichaelChirico (2)
  • ebrejonl (2)
  • gregmacfarlane (2)
  • grantmcdermott (2)
  • DanChaltiel (2)
  • Dpananos (2)
  • zietzm (2)
  • capnrefsmmat (2)
Top Labels
Issue Labels
stale issue (8) new-tidiers (5) upkeep (3) feature-request (1) consistency/specification (1) tests (1) documentation (1)
Pull Request Labels
stale pull request (2)

Packages

  • Total packages: 2
  • Total downloads:
    • cran 624,433 last-month
  • Total docker downloads: 46,727,819
  • Total dependent packages: 299
    (may contain duplicates)
  • Total dependent repositories: 1,194
    (may contain duplicates)
  • Total versions: 74
  • Total maintainers: 1
cran.r-project.org: broom

Convert Statistical Objects into Tidy Tibbles

  • Versions: 41
  • Dependent Packages: 299
  • Dependent Repositories: 1,194
  • Downloads: 624,433 Last month
  • Docker Downloads: 46,727,819
Rankings
Stargazers count: 0.2%
Forks count: 0.2%
Dependent repos count: 0.4%
Downloads: 0.4%
Dependent packages count: 0.4%
Average: 3.1%
Docker downloads count: 17.3%
Maintainers (1)
simon.couch@posit.co
Last synced: 6 months ago
proxy.golang.org: github.com/tidymodels/broom
  • Versions: 33
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.5%
Average: 5.7%
Dependent repos count: 5.9%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.1 depends
  • backports * imports
  • dplyr >= 1.0.0 imports
  • ellipsis * imports
  • generics >= 0.0.2 imports
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  • tibble >= 3.0.0 imports
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  • muhaz * suggests
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  • network * suggests
  • nnet * suggests
  • orcutt >= 2.2 suggests
  • ordinal * suggests
  • plm * suggests
  • poLCA * suggests
  • psych * suggests
  • quantreg * suggests
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  • rmarkdown * suggests
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  • spdep >= 1.1 suggests
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  • spelling * suggests
  • survey * suggests
  • survival * suggests
  • systemfit * suggests
  • testthat >= 2.1.0 suggests
  • tseries * suggests
  • vars * suggests
  • zoo * suggests
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