NaiveNeuron/github-stars-in-context

GitHub Stars in Context

A dataset of repository popularity across GitHub accounts. It links 3,671,497 GitHub user accounts to 53,990,808 rows of public, non-fork repositories they own, with each repository's star count. A row is one repository under one account.

Provenance, checks and known limits are documented in PROVENANCE.md.

Most GitHub datasets describe repositories one by one. This one keeps the ownership context: every stored repository of an account, including those with zero stars. That makes it possible to see what a star-threshold filter leaves out, to compare concentrated and spread-out portfolios, and to group repositories by owner when building samples or benchmark splits.

Processing code, reuse examples and reproduction instructions: https://github.com/NaiveNeuron/github-stars-in-context

Files

File	Rows	Contents
users.parquet	3,671,497	Account IDs, login, retrieval status, profile-availability flag, follower count
repositories.parquet	53,990,808	Owner key, GitHub repository ID, name, creation time, stars
portfolios.parquet	3,671,497	Per-account repository count, total and maximum stars, h-index, concentration
data-dictionary.md / .json		Field meanings, types and NULL rules
release.json		Version, licences, counts, collection dates and file checksums
crosswalk.sql		View mapping local keys to GitHub IDs, names and URLs
PARQUET-SHA256SUMS		Checksums of the files above

repositories.user_id joins users.id. Both are local keys. users.github_id and repositories.repository_id are GitHub's numeric IDs and join to other resources such as GH Archive.

Quick start

Download the files once (1.57 GiB). This needs the Hugging Face CLI, or use the curl commands in the code repository's README:

hf download NaiveNeuron/github-stars-in-context --repo-type dataset --revision v1.1.0 --local-dir data
(cd data && shasum -a 256 -c PARQUET-SHA256SUMS)

Then query the local files, for example with DuckDB (pip install duckdb):

import duckdb
print(duckdb.sql("""
SELECT count(*) FILTER (WHERE r.stars >= 10) AS kept, count(*) AS total
FROM 'data/repositories.parquet' r
JOIN 'data/users.parquet' u ON r.user_id = u.id
WHERE u.retrieval_status = 'complete'
""").fetchall())
# [(1560798, 53987867)]

DuckDB can also read the files remotely through hf:// paths, but a query over the large table sends several thousand requests and can exceed Hugging Face's limit for anonymous access. Download the files, or log in first.

How it was collected

• Accounts were found on 8–9 December 2025 through GitHub GraphQL user search, split by follower count (1–9 up to 10,000+) and registration date to stay under the 1,000-result search limit. Organizations are excluded. Accounts with no followers were not searched
• Repositories were fetched per account from about December 2025 to early January 2026, by the collector author's estimate. The query selects owned, public, non-fork repositories, including archived ones, and follows pagination. Per-request times were not stored
• Follower counts were fetched from 28 January to 2 February 2026

What to know before using it

• Not a random sample of GitHub. Discovery searched for accounts with at least one follower. Follower counts fetched later can be zero (1,719 accounts). Search cells that still exceeded 1,000 results on a single registration day were skipped, and a failed search request could drop a cell. The number of missed accounts is unknown
• Retrieval status. retrieval_status is complete for 3,615,479 accounts (372,821 of them own no stored repository), failed for 56,012 and unknown for 6. The classes are derived from the collector's logic. They are not an independent check against GitHub
• Missing follower counts. profile_available is false for 1,151,092 accounts whose profile fields are missing or ambiguous. Their followers_count is NULL. The rule masks NULL biographies and profiles with only default values, which can include genuinely empty profiles. In a sample of 300 such accounts of the complete class checked on 10 November 2026, 298 still existed and 296 had followers. This supports treating the stored zeros as missing, but it does not show their values in January 2026. The raw stored value is kept in followers_count_raw and must not be read as zero followers. Follower analyses cover only the accounts with available profiles, measured after the repositories
• Historical observations. Star counts are as of retrieval. Per-request times were not stored, so this is not a star history
• Repository IDs are not unique keys. Twenty repository IDs appear under more than one account
• Stars are not a measure of people. Do not use this dataset to rank or evaluate individuals

Personal data

The dataset contains only fields that were public on GitHub: account logins and numeric IDs, repository names, creation times and star counts. Logins and numeric IDs can identify people. Numeric IDs are needed to join the tables to other datasets, and logins allow lookup by name. Biographies, company, location and external links were collected but are not included.

To have an account removed, write to [email protected] or open an issue in the code repository. Please do not post personal documents in a public issue. We remove the account's rows from all three tables in a new release. Copies that others have already downloaded cannot be recalled.

Licence

The data are released under CC BY-NC 4.0. The licence covers the rights the authors hold in the compilation. It does not grant rights held by GitHub users or other third parties. The code is MIT-licensed.

Versions

• 1.1.0 (2026-11-10): documentation only. The data dictionary is rewritten in plain language, and release.json replaces analysis-manifest.json. The three Parquet files are byte-identical to 1.0.0
• 1.0.0 (2026-11-10): first public release

Each version is a Git tag of this repository (v1.1.0, v1.0.0). The code repository has matching tags.

Citation

A paper describing the dataset is under review. Until it is published, please cite this dataset page:

@misc{pavlov2026githubstars,
  author = {Pavlov, Mykhailo and {\v{S}}uppa, Marek},
  title  = {{GitHub} Stars in Context: A Dataset of Repository Popularity Across Accounts},
  year   = {2026},
  version = {1.1.0},
  howpublished = {\url{https://huggingface.co/datasets/NaiveNeuron/github-stars-in-context}}
}