# SciRuby/daru

Data Analysis in RUby

Repository: https://github.com/SciRuby/daru
Canonical: https://ross.abutalabs.com/products/daru
Language: Ruby
License: BSD-2-Clause
License Family: permissive
Last push: 2023-08-15T13:17:11+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4351, "days_push": 1114, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1061, forks 139 (observed 2026-08-28T04:03:25.999924+00:00)

## What it is
Daru (Data Analysis in RUby) is a pure Ruby library providing DataFrame and Vector data structures for storing, analyzing, manipulating, and visualizing data. It supports indexing, grouping, pivot tables, time series, and integrates with IRuby notebooks and SciRuby statistics gems.

## Use cases
- analyze tabular data in ruby
- manipulate spreadsheets-like dataframes in ruby
- group and aggregate data in ruby
- create pivot tables for data summaries
- work with time series data in ruby
- import and export data between formats like  and csv
- plot data in iruby notebooks

## When to choose
- you are a Rubyist doing data analysis and want pandas-like structures
- you need pure Ruby data manipulation without native dependencies
- you work within the SciRuby ecosystem (statsample, iruby)

## When to avoid
- you need cutting-edge performance or large-scale data processing
- you want a rapidly evolving feature set with frequent updates
- your stack is Python or JVM-based where pandas or Spark are better fits

## Facets
- artifact type: library
- maturity: maintenance
- function: data-science, data-visualization, etl, csv, math
- domain: data-science, data-visualization, analytics, developer-tools
- platform: ruby, cross-platform
- tags: dataframe, vector, ruby-gem, pivot-tables, time-series

## Member repositories
- SciRuby/daru (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:25.999924+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 2026-08-30T06:56:48.580012+00:00, confidence not recorded.
  - readme: https://github.com/SciRuby/daru (fetched 2026-08-28T04:03:25.999924+00:00, sha 44cc83d7fb92)
- Data as of 2026-08-30T08:39:29.467469+00:00.