# root-project/root

The official repository for ROOT: analyzing, storing and visualizing big data, scientifically

Repository: https://github.com/root-project/root
Canonical: https://ross.abutalabs.com/products/root
Homepage: https://root.cern
Language: C++
License: NOASSERTION
License Family: other
Topics: data-analysis, root-cern, root, c-plus-plus, python, physics, statistics, mathematics, machine-learning, interpreter, cling, graphics, visualization, geometry, parallel, hacktoberfest
Last push: 2026-08-26T19:16:03+00:00

## Health v2 (maintenance only)
Score: 96/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 89, longevity 100
- inputs: {"age_days": 4815, "days_push": 7, "days_rel": 76, "gap_med": 11.5, "n_releases_24m": 37}
- 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 3288, forks 1549 (observed 2026-08-28T04:07:53.831265+00:00)

## What it is
ROOT is a C++ data analysis framework developed at CERN for storing, processing, and visualizing large scientific datasets, with a columnar file format that scales to exabytes. It includes a C++ interpreter (Cling), Python interoperability, statistical tools, histogramming, fitting, and the RDataFrame parallel processing framework.

## Use cases
- analyze petabyte-scale physics experiment data
- store and read columnar scientific data files
- fit curves and do statistical modeling of datasets
- create publication-quality plots and histograms
- prototype C++ analysis code interactively
- process large datasets in parallel with RDataFrame
- use C++ and Python together for data analysis
- train machine learning models on scientific data

## When to choose
- you work in high-energy or particle physics and need the community-standard tool
- you need to read or write ROOT files or interoperate with experiments that use them
- you need exabyte-scale columnar data storage with fast tree-based access
- you want interactive C++ prototyping with an interpreter and Python bindings

## When to avoid
- you just need general-purpose data analysis without ROOT file compatibility - pandas or NumPy are simpler
- you want lightweight plotting only - matplotlib or similar is easier to adopt
- your team has no C++ background and the steep learning curve is a barrier
- you need a small dependency - ROOT is a very large framework

## Facets
- artifact type: framework
- maturity: stable
- function: data-science, data-visualization, interpreter, machine-learning, graphics, math, file-system, concurrency
- domain: data-science, big-data, data-visualization, machine-learning
- platform: windows, cpp, python, cross-platform
- tags: high-energy-physics, scientific-computing, cling, rdataframe, root-files, columnar-data, histograms, cern, jupyter, statistics, physics, algorithms, linux, macos

## Member repositories
- root-project/root (main) score 96

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:53.831265+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 2026-08-30T07:22:50.856590+00:00, confidence not recorded.
  - readme: https://github.com/root-project/root (fetched 2026-08-28T04:07:53.831265+00:00, sha 815cddd75893)
  - homepage: https://root.cern (fetched 2026-08-29T09:35:57.662097+00:00, sha b1d685d8410b)
  - site_page: https://root.cern/about (fetched 2026-08-29T09:35:57.670914+00:00, sha d6a1d61d03a9)
  - site_page: https://root.cern/install/all_releases (fetched 2026-08-29T09:35:57.672749+00:00, sha f48d2126ce47)
  - site_page: https://root.cern/install (fetched 2026-08-29T09:35:57.674920+00:00, sha af395d1679ea)
  - site_page: https://root.cern/about/license (fetched 2026-08-29T09:35:57.676930+00:00, sha 5ab94bfa5501)
  - site_page: https://root.cern/install/build_from_source (fetched 2026-08-29T09:35:57.679861+00:00, sha b94d678a8019)
  - site_page: https://root.cern/releases/release-64004 (fetched 2026-08-29T09:35:57.684512+00:00, sha 4da993983268)
  - site_page: https://root.cern/releases/release-64002 (fetched 2026-08-29T09:35:57.686544+00:00, sha 71c6e2269c2e)
  - site_page: https://root.cern/releases/release-64000 (fetched 2026-08-29T09:35:57.688277+00:00, sha 3ef3ed7b614d)
- Data as of 2026-08-30T08:39:29.467469+00:00.