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usemodels

Boilerplate Code for tidymodels

https://github.com/tidymodels/usemodels

Science Score: 26.0%

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

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (19.1%) to scientific vocabulary

Keywords from Contributors

tidyverse tidy-data setup
Last synced: 10 months ago · JSON representation

Repository

Boilerplate Code for tidymodels

Basic Info
Statistics
  • Stars: 85
  • Watchers: 6
  • Forks: 6
  • Open Issues: 7
  • Releases: 3
Created about 6 years ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog License Code of conduct Codeowners

README.Rmd 

---
output: github_document
---



```{r}
#| include: false
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "",
  prompt = TRUE,
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# usemodels


[![R-CMD-check](https://github.com/tidymodels/usemodels/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tidymodels/usemodels/actions/workflows/R-CMD-check.yaml)
[![Coverage status](https://codecov.io/gh/tidymodels/usemodels/branch/main/graph/badge.svg)](https://app.codecov.io/github/tidymodels/usemodels?branch=main)
[![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html)


The usemodels package is a helpful way of quickly creating code snippets to fit models using the tidymodels framework. 

Given a simple formula and a data set, the `use_*` functions can create code that appropriate for the data (given the model). 

For example, using the palmerpenguins data with a `glmnet` model: 

```{r}
#| label: glmnet
#| message: false
library(usemodels)
library(palmerpenguins)
data(penguins)
use_glmnet(body_mass_g ~ ., data = penguins)
```

The recipe steps that are used (if any) depend on the type of data as well as the model. In this case, the first two steps handle the fact that `Species` is a factor-encoded predictor (and `glmnet` requires all numeric predictors). The last two steps are added because, for this model, the predictors should be on the same scale to be properly regularized. 

The package includes these templates:


```{r}
#| label: use-list
ls("package:usemodels", pattern = "use_")
```

You can also copy code to the clipboard using the option `clipboard = TRUE`. 

## Installation

You can install usemodels with:

``` r
devtools::install_github("tidymodels/usemodels")
```


## Contributing

This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.

- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on Posit Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).

- If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/usemodels/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/).

Owner

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

GitHub Events

Total
  • Issues event: 3
  • Watch event: 1
  • Delete event: 3
  • Issue comment event: 4
  • Push event: 6
  • Pull request event: 6
  • Fork event: 1
  • Create event: 3
Last Year
  • Issues event: 3
  • Watch event: 1
  • Delete event: 3
  • Issue comment event: 4
  • Push event: 6
  • Pull request event: 6
  • Fork event: 1
  • Create event: 3

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 82
  • Total Committers: 8
  • Avg Commits per committer: 10.25
  • Development Distribution Score (DDS): 0.537
Past Year
  • Commits: 13
  • Committers: 4
  • Avg Commits per committer: 3.25
  • Development Distribution Score (DDS): 0.385
Top Committers
Name Email Commits
Max Kuhn m****n@g****m 38
Emil Hvitfeldt e****t@g****m 22
Julia Silge j****e@g****m 14
Hannah Frick h****h@p****o 3
Qiushi Yan q****n@g****m 2
vinchinzu l****e@g****m 1
Gábor Csárdi c****r@g****m 1
Bryce Roney b****y 1
Committer Domains (Top 20 + Academic)
posit.co: 1

Issues and Pull Requests

Last synced: 12 months ago

All Time
  • Total issues: 23
  • Total pull requests: 31
  • Average time to close issues: 4 months
  • Average time to close pull requests: 10 days
  • Total issue authors: 15
  • Total pull request authors: 9
  • Average comments per issue: 1.74
  • Average comments per pull request: 0.9
  • Merged pull requests: 28
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 2
  • Pull requests: 7
  • Average time to close issues: 2 days
  • Average time to close pull requests: about 11 hours
  • Issue authors: 2
  • Pull request authors: 5
  • Average comments per issue: 0.0
  • Average comments per pull request: 0.0
  • Merged pull requests: 6
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • larry77 (5)
  • topepo (4)
  • EmilHvitfeldt (2)
  • dpprdan (1)
  • jennybc (1)
  • czeildi (1)
  • amazongodman (1)
  • bryceroney (1)
  • aloes2512 (1)
  • DrZhaoJie (1)
  • amcmahon17 (1)
  • brshallo (1)
  • Athospd (1)
  • hfrick (1)
  • juliasilge (1)
Pull Request Authors
  • topepo (11)
  • juliasilge (7)
  • EmilHvitfeldt (5)
  • hfrick (4)
  • qiushiyan (3)
  • jrosell (2)
  • gaborcsardi (2)
  • vinchinzu (1)
  • bryceroney (1)
Top Labels
Issue Labels
feature (7) upkeep (2) bug (1) tidy-dev-day :nerd_face: (1)
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 379 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 3
  • Total maintainers: 1
cran.r-project.org: usemodels

Boilerplate Code for 'Tidymodels' Analyses

  • Versions: 3
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 379 Last month
Rankings
Stargazers count: 4.3%
Forks count: 14.2%
Average: 20.6%
Dependent repos count: 24.0%
Dependent packages count: 28.8%
Downloads: 31.5%
Maintainers (1)
max@rstudio.com
Last synced: 11 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/lock.yaml actions
  • dessant/lock-threads v2 composite
.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.4.1 composite
  • actions/checkout v3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pr-commands.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/pr-fetch v2 composite
  • r-lib/actions/pr-push v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v3 composite
  • actions/upload-artifact v3 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 3.4 depends
  • cli * imports
  • clipr * imports
  • dplyr * imports
  • purrr * imports
  • recipes >= 0.1.15 imports
  • rlang * imports
  • tidyr * imports
  • tune >= 0.1.2 imports
  • covr * suggests
  • modeldata * suggests
  • spelling * suggests
  • testthat * suggests