# tidyverse/dplyr

dplyr: A grammar of data manipulation

Repository: https://github.com/tidyverse/dplyr
Canonical: https://ross.abutalabs.com/products/dplyr
Homepage: https://dplyr.tidyverse.org/
Language: R
License: NOASSERTION
License Family: other
Topics: r, data-manipulation, grammar
Last push: 2026-06-02T15:25:25+00:00

## Health v2 (maintenance only)
Score: 81/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 85, release rhythm 65, longevity 100
- inputs: {"age_days": 5057, "days_push": 92, "days_rel": 152, "gap_med": 58, "n_releases_24m": 2}
- 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 5062, forks 2115 (observed 2026-08-28T04:09:09.232502+00:00)

## What it is
dplyr is an R package providing a consistent grammar of data manipulation with verbs like mutate(), select(), filter(), summarise(), and arrange() for transforming data frames and tibbles. It supports pluggable backends (Arrow, databases via dbplyr, data.table, DuckDB, Spark) so the same code scales from in-memory data to large datasets.

## Use cases
- filter and summarize rows in an R data frame
- add new computed columns to a dataset
- group data and compute per-group summaries
- join and combine two tables in R
- run the same data transformation code against a SQL database or Spark
- clean and reshape a dataset for analysis

## When to choose
- you work in R and want readable, pipe-friendly data manipulation
- you need consistent verbs across data frames, databases, Arrow, and Spark
- you are following tidyverse conventions or R for Data Science workflows

## When to avoid
- you work outside R
- you need raw maximum performance and prefer writing data.table or SQL directly
- you need non-tabular data structures like graphs or unstructured text

## Facets
- artifact type: library
- maturity: stable
- function: data-science, etl, developer-tools
- domain: data-science, analytics
- platform: -
- tags: data-manipulation, tidyverse, data-frames, grammar-of-data, r-package, data-engineering, r

## Member repositories
- tidyverse/dplyr (main) score 81

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:09.232502+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 2026-08-29T18:17:18.672888+00:00, confidence not recorded.
  - readme: https://github.com/tidyverse/dplyr (fetched 2026-08-28T04:09:09.232502+00:00, sha e0237b9dd892)
  - homepage: https://dplyr.tidyverse.org/ (fetched 2026-08-29T08:57:42.472533+00:00, sha 06d35e186ddf)
  - site_page: https://dplyr.tidyverse.org/news/index.html (fetched 2026-08-29T08:57:42.481935+00:00, sha ad89007bca95)
- Data as of 2026-08-30T08:39:29.467469+00:00.