Ross ROSS = Recommend OSS · open-source software intelligence for agents

ropensci/skimr

A frictionless, pipeable approach to dealing with summary statistics observed · 2026-08-28

github.com/ropensci/skimr · homepage · HTML observed · 2026-08-28

Health v2 · maintenance only

50/100

  • Activity 61
  • Release rhythm 8
  • Longevity 100

Flags: no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 3387
  • days_rel: 402
  • days_push: 237
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

1141 stars · 81 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

skimr is an R package providing compact, pipeable summary statistics for data frames, with readable console output including spark-bars and per-type statistics. It returns a skim_df object that integrates with tidyverse pipelines.

Use cases

  • quickly summarize a data frame in R
  • get summary statistics beyond base summary()
  • explore missing values and distributions per column
  • include data summaries in a dplyr pipeline
  • profile datasets during exploratory data analysis

When to choose

  • you work in R and want fast, readable data summaries
  • you need statistics grouped by column type with missing-value counts
  • you want summaries that fit into tidyverse pipes

When to avoid

  • you need full statistical modeling or visualization, not just summaries
  • you work outside R

Facets

library · maturity active

data-science analytics developer-tools data-science analytics developer-tools python cli r rstats summary-statistics exploratory-data-analysis ropensci tidyverse cran

6 sources

Member repositories

RepositoryRoleHealth v2
ropensci/skimrmain50

For agents

markdown · JSON · MCP: product_card(name="ropensci/skimr")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem