Reference Reference tableQC clean AI-training-safe

Exoplanet Catalog (NASA Exoplanet Archive)

Every confirmed exoplanet and its host star in one clean table - the authoritative NASA catalog, ready to use. The NASA Exoplanet Archive's composite-parameters table gives the best published value per planet across all studies; we query it and ship one fat, tidy row per planet: planet & host-star identity, discovery method/year/facility, orbital parameters (period, semi-major axis, eccentricity), physical parameters (radius & mass in Earth units, equilibrium temperature), stellar parameters (spectral type, temperature, radius, mass), distance and sky position. Updates as new planets are confirmed.

6K
rows
20
columns
0.9 MB
download
Source
NASA / Caltech
Licence
Redistributable open data
Quality
QC clean · 0 failures
Format
Apache Parquet + dictionary

Safe to train on

Built only from a named, redistributable official source under a documented open licence - not scraped web data. No copyright grey zone, no personal data. Ships machine-readable Croissant metadata (ML Commons - loads in Hugging Face / Kaggle / Google), an AI training-licence manifest documenting source, licence and provenance for your model's data governance, and a machine-readable data dictionary (drop it into an agent / RAG prompt so the model knows every column) - all inspectable before you buy.

What's included

  • One fat row per confirmed exoplanet (~6,300) - planet + host star + orbit + physics
  • Discovery method, year and facility; orbital period, semi-major axis, eccentricity
  • Radius & mass (Earth units), equilibrium temperature; stellar temp/radius/mass/spectral type
  • Distance (parsecs) + sky position (RA/Dec) - plot or join to star catalogs
  • The maintained cut vs stale one-off Kaggle uploads; audiences: astronomy edu, vis apps, ML demos
  • NASA/Caltech-IPAC - freely available, attribution requested
  • Source: NASA Exoplanet Archive (Caltech/IPAC under contract with NASA)

Schema

ColumnTypeDescriptionFilledDistinct
planet str Planet name (primary key) 100.0% 6,316
host_star str Host star name 100.0% 4,732
n_stars int Number of stars in the system 100.0% 4
n_planets int Number of known planets in the system 100.0% 8
discovery_method str Detection method (Transit, Radial Velocity, …) 100.0% 11
discovery_year int Year of discovery 100.0% 34
discovery_facility str Discovering facility / survey 100.0% 73
orbital_period_days float Orbital period (days) 94.6% 5,960
semi_major_axis_au float Semi-major axis (AU) 93.2% 3,566
eccentricity float Orbital eccentricity 83.3% 613
radius_earth float Planet radius (Earth radii) 99.2% 2,270
mass_earth float Planet mass / best-mass (Earth masses) 99.5% 2,861
equilibrium_temp_k float Equilibrium temperature (K) 91.7% 2,988
star_spectral_type str Host-star spectral type 37.0% 331
star_temp_k float Host-star effective temperature (K) 95.3% 2,417
star_radius_sun float Host-star radius (solar radii) 94.9% 1,932
star_mass_sun float Host-star mass (solar masses) 99.9% 1,229
distance_pc float Distance to the system (parsecs) 99.6% 4,615
ra_deg float Right ascension (degrees) 100.0% 4,729
dec_deg float Declination (degrees) 100.0% 4,729

Sample & preview

Every purchase ships as Apache Parquet with a data dictionary and the full QC report. A free sample (first rows + schema) is downloadable here - confirm fit before you buy. Source: NASA / Caltech (redistributable open data; attribution passes through - see our Licence).

Don't trust screenshots - drop the sample into your notebook right now.

import pandas as pd
df = pd.read_parquet("global-exoplanet-catalog_sample.parquet")
df.info()   # typed columns, gap-aware, ready to join
⬇ Download free Parquet sample or CSV for Excel