GRIDINT RESEARCH · DATA HUB
Exoplanets.
Every confirmed planet beyond this solar system with a measured radius — 4,706 worlds from NASA's Exoplanet Archive, each with its orbital period, radius, discovery method, and year. The archive is the census of a working field; this catalog holds it as published, updated by dated edition. Where a method cannot see, the gap is in the picture — absence drawn, never filled.
Three decades of discovery, one method at a time.
Plot it on any two axes.
The shape of the records.
Records by detection method
SOURCE · NASA Exoplanet Archive, ps table · data cutoff 2026-08-26 · counted from the records
How this hub was made.
What this set is. Every confirmed planet with BOTH a measured radius and a measured orbital period, from NASA's Exoplanet Archive. It is a separate pull from the report's, five rows apart; the two converge to one fetch at the next edition, and until then each states its own vintage. 4,706 records. Pulled 2026-08-26T10:35Z.
The methodology note for this hub — source classes, what the source does and does not establish, quantified uncertainty — is being written.
Every edition, dated.
- Edition 1 published 2026-08-26 · data cutoff 2026-08-26 · first edition
A hub changes only as a new dated edition, on the institute's word — never on a schedule. Collection continues underneath; publication is deliberate.
Verify this hub.
Verification extracts — the working records with their receipts, attribution first, pointing at the origin. We never provide data; the source is the authority, this hub is the lens.
Cite this hub
GRIDINT Research (2026). Exoplanets data hub, edition 1 (data cutoff 2026-08-26). https://gridint.ai/data/exoplanets
@misc{gridint_exoplanets_2026,
title = {Exoplanets data hub, edition 1},
author = {{GRIDINT Research}},
year = {2026},
note = {Data cutoff 2026-08-26; source: NASA Exoplanet Archive, ps table},
url = {https://gridint.ai/data/exoplanets}
}
In pandas
import pandas as pd
D = pd.read_json("https://gridint.ai/demo/exoplanets/data.json")
records = pd.DataFrame(D["scatter"].tolist(), columns=["period_days", "radius_earth", "method", "name", "year"])