juliensimon/gaia-dr3-rrlyrae

---
license: cc-by-4.0
pretty_name: "Gaia DR3 RR Lyrae Variables"
language:
- en
description: "Gaia DR3 catalog of 271,779 RR Lyrae variable stars with periods, amplitudes, metallicities, and distances."
task_categories:
- tabular-classification
- tabular-regression
tags:
- space
- gaia
- rr-lyrae
- variable-star
- distance-ladder
- astronomy
- open-data
size_categories:
- 100K<n<1M
---

# Gaia DR3 RR Lyrae Variables

The Gaia Data Release 3 catalog of **271,779** RR Lyrae variable stars -- the largest
homogeneous catalog of pulsating horizontal-branch stars ever compiled. RR Lyrae stars are
essential standard candles for the cosmic distance ladder.

## Dataset description

RR Lyrae stars are old, low-metallicity pulsating variables found in the Milky Way halo,
bulge, globular clusters, and nearby galaxies. Their well-defined period-luminosity-metallicity
relation makes them fundamental distance indicators. Gaia DR3 provides the most comprehensive
all-sky census of RR Lyrae variables, with precise astrometry, multi-band photometry, light
curve parameters, metallicity estimates from the light curve shape, and photometric distances.

This dataset is a cornerstone for Galactic archaeology, enabling studies of the Milky Way's
stellar halo substructure, tidal streams, and satellite galaxies.

## Schema

| Column | Type | Description |
|--------|------|-------------|
| `source_id` | string | Gaia DR3 source identifier |
| `ra_deg` | float64 | Right ascension J2016.0 (degrees) |
| `dec_deg` | float64 | Declination J2016.0 (degrees) |
| `period_days` | float64 | Pulsation period (days) |
| `epoch_g_bjd` | float64 | Epoch of maximum in G band (Barycentric JD) |
| `amplitude_g_mag` | float64 | Peak-to-peak amplitude in G band (mag) |
| `mean_g_mag` | float64 | Mean G-band magnitude |
| `mean_bp_mag` | float64 | Mean BP-band magnitude |
| `mean_rp_mag` | float64 | Mean RP-band magnitude |
| `metallicity_feh` | float64 | Photometric metallicity [Fe/H] (dex) |
| `distance_pc` | float64 | Photometric distance (parsec) |
| `subclassification` | string | RR Lyrae subtype (RRab, RRc, RRd) |
| `best_classification` | string | Best classification label |
| `n_transits` | float64 | Number of Gaia transits used |

## Quick stats

- **271,779** RR Lyrae variables
- **0** classification subtypes: N/A
- **0** with pulsation period (median 0.0000 days)
- **0** with metallicity estimate
- **0** with photometric distance

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/gaia-dr3-rrlyrae", split="train")
df = ds.to_pandas()

# Period distribution (Bailey diagram)
import matplotlib.pyplot as plt
valid = df.dropna(subset=["period_days", "amplitude_g_mag"])
plt.scatter(valid["period_days"], valid["amplitude_g_mag"], s=0.5, alpha=0.2)
plt.xlabel("Period (days)")
plt.ylabel("Amplitude G (mag)")
plt.title("Gaia DR3 RR Lyrae Bailey Diagram")
plt.show()

# Metallicity distribution
df["metallicity_feh"].dropna().hist(bins=100)
plt.xlabel("[Fe/H] (dex)")
plt.ylabel("Count")
plt.title("RR Lyrae Metallicity Distribution")
plt.show()

# Sky distribution (Galactic coordinates would be ideal)
plt.scatter(df["ra_deg"], df["dec_deg"], s=0.01, alpha=0.1,
c=df["distance_pc"].clip(upper=50000), cmap="viridis")
plt.colorbar(label="Distance (pc)")
plt.xlabel("RA (deg)")
plt.ylabel("Dec (deg)")
plt.title("Gaia DR3 RR Lyrae Sky Distribution")
plt.show()
```

## Data source

Clementini, G. et al. (2023), *Gaia Data Release 3: Specific processing and validation
of all-sky RR Lyrae and Cepheid stars.* Astronomy & Astrophysics, 674, A18.
Via [VizieR](https://vizier.cds.unistra.fr/) CDS Strasbourg (I/358).

## Pipeline

Source code: [juliensimon/space-datasets](https://github.com/juliensimon/space-datasets)

## Citation

```bibtex
@dataset{gaia_dr3_rrlyrae,
author = {Simon, Julien},
title = {Gaia DR3 RR Lyrae Variables},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/juliensimon/gaia-dr3-rrlyrae},
note = {Based on Clementini et al. (2023), Gaia DR3, via VizieR CDS Strasbourg}
}
```

## License

[CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/)