---
license: other
license_name: sdss-data-use-policy
license_link: https://www.sdss4.org/dr17/data_access/
pretty_name: "APOGEE DR17 Stellar Parameters & Abundances"
language:
  - en
description: >-
  APOGEE DR17 AllStar catalog: high-resolution infrared spectroscopic stellar
  parameters and 20+ individual chemical element abundances for ~657K stars.
  The final SDSS-IV APOGEE release and the premier stellar chemical abundance catalog.
task_categories:
  - tabular-classification
  - tabular-regression
tags:
  - space
  - stars
  - stellar
  - spectroscopy
  - chemical-abundances
  - apogee
  - sdss
  - astronomy
  - open-data
  - tabular-data
  - parquet
size_categories:
  - 100K<n<1M
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/apogee_dr17.parquet
    default: true
---

# APOGEE DR17 Stellar Parameters & Abundances

*Part of the [Astronomy Datasets](https://huggingface.co/collections/juliensimon/astronomy-datasets-69c24caf2f17e36128946743) collection on Hugging Face.*

The APOGEE DR17 AllStar catalog provides high-resolution infrared (H-band)
spectroscopic stellar parameters and **20+ individual chemical element
abundances** for **733,901** stars across the Milky Way. This is the final
data release from SDSS-IV APOGEE and represents the premier stellar chemical
abundance catalog available today.

## Dataset description

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) is a
large-scale, high-resolution (R ~ 22,500), near-infrared (H-band, 1.51-1.70 um)
spectroscopic survey of Milky Way stellar populations. DR17 is the final release
of SDSS-IV, containing the complete APOGEE-2 dataset with observations from both
the Northern (APO 2.5m) and Southern (du Pont 2.5m at LCO) hemispheres.

The ASPCAP pipeline (APOGEE Stellar Parameter and Chemical Abundances Pipeline)
derives effective temperature, surface gravity, metallicity, and individual
elemental abundances by comparing observed spectra against synthetic spectral
libraries. The catalog covers a wide range of stellar types including red giants,
red clump stars, and main-sequence stars across the Galactic disk, bulge, and halo.

## Schema

| Column | Type | Description |
|--------|------|-------------|
| `file` | object | -- |
| `apogee_id` | string | APOGEE unique star identifier |
| `target_id` | object | -- |
| `ap_star` | object | -- |
| `ascap` | object | -- |
| `tel` | object | -- |
| `loc` | int64 | -- |
| `field` | object | -- |
| `alt_id` | object | -- |
| `ra_deg` | float64 | Right ascension ICRS (degrees) |
| `dec_deg` | float64 | Declination ICRS (degrees) |
| `glon_deg` | float64 | Galactic longitude (degrees) |
| `glat_deg` | float64 | Galactic latitude (degrees) |
| `j_mag` | float64 | 2MASS J magnitude |
| `j_mag_error` | float64 | -- |
| `h_mag` | float64 | 2MASS H magnitude |
| `h_mag_error` | float64 | -- |
| `k_mag` | float64 | 2MASS K magnitude |
| `e_ksmag` | float64 | -- |
| `r_hmag` | object | -- |
| `mmag` | float64 | -- |
| `e_mmag` | float64 | -- |
| `t2mag` | float64 | -- |
| `e_t2mag` | float64 | -- |
| `ddo51` | float64 | -- |
| `e_ddo51` | float64 | -- |
| `3_6mag` | float64 | -- |
| `e_3_6mag` | float64 | -- |
| `4_5mag` | float64 | -- |
| `e_4_5mag` | float64 | -- |
| `5_8mag` | float64 | -- |
| `e_5_8mag` | float64 | -- |
| `8_0mag` | float64 | -- |
| `e_8_0mag` | float64 | -- |
| `4_5mag_w` | float64 | -- |
| `e_4_5mag_w` | float64 | -- |
| `4_5mag_t` | float64 | -- |
| `e_4_5mag_t` | float64 | -- |
| `giant` | int64 | -- |
| `star` | int64 | -- |
| `pm_rat` | float64 | -- |
| `pm_det` | float64 | -- |
| `r_pm_t` | object | -- |
| `ak_t` | float64 | -- |
| `n_ak_t` | object | -- |
| `ak` | float64 | -- |
| `e(b_v)` | float64 | -- |
| `ap1_t1` | int64 | -- |
| `ap1_t2` | int64 | -- |
| `ap2_t1` | int64 | -- |
| `ap2_t2` | int64 | -- |
| `ap2_t3` | int64 | -- |
| `survey` | object | -- |
| `prog` | object | -- |
| `n_visits` | Int64 | Number of visits |
| `snr` | float64 | Combined signal-to-noise ratio |
| `snrev` | float64 | -- |
| `s_flag` | int64 | -- |
| `sa_flag` | int64 | -- |
| `radial_velocity_kms` | float64 | Heliocentric radial velocity (km/s) |
| `rv_scatter_kms` | float64 | RV scatter across visits (km/s) |
| `radial_velocity_error_kms` | float64 | RV uncertainty (km/s) |
| `teff_rv` | float64 | -- |
| `logg_rv` | float64 | -- |
| `fe_h_rv` | float64 | -- |
| `chi2_rv` | float64 | -- |
| `fwhmcc` | float64 | -- |
| `fwhm` | float64 | -- |
| `fl_rv` | int64 | -- |
| `ncomp` | int64 | -- |
| `nfib` | float64 | -- |
| `e_nfib` | float64 | -- |
| `hmin` | float64 | -- |
| `hmax` | float64 | -- |
| `j_kmin` | float64 | -- |
| `j_kmax` | float64 | -- |
| `gaia_source_id` | string | Gaia DR3 source ID |
| `parallax_mas` | float64 | Parallax (mas) |
| `parallax_error_mas` | float64 | Parallax uncertainty (mas) |
| `pmra_mas_yr` | float64 | Proper motion in RA (mas/yr) |
| `e_pm_ra` | float64 | -- |
| `pmdec_mas_yr` | float64 | Proper motion in Dec (mas/yr) |
| `e_pm_de` | float64 | -- |
| `gaia_g_mag` | float64 | -- |
| `gaia_bp_mag` | float64 | -- |
| `gaia_rp_mag` | float64 | -- |
| `gaia_radial_velocity_kms` | float64 | -- |
| `gaia_radial_velocity_error_kms` | float64 | -- |
| `distance_geo_pc` | float64 | -- |
| `b_rgeo` | float64 | -- |
| `distance_photogeo_pc` | float64 | -- |
| `b_rpgeo` | float64 | -- |
| `grid` | object | -- |
| `chi2` | float64 | -- |
| `a_flag` | int64 | -- |
| `bad_px` | float64 | -- |
| `low_snr` | float64 | -- |
| `sig_sky` | float64 | -- |
| `e_flag` | int64 | -- |
| `p_mm` | object | -- |
| `teff_k` | float64 | Effective temperature (K) |
| `teff_error_k` | float64 | Teff uncertainty (K) |
| `logg` | float64 | Surface gravity log g (dex) |
| `logg_error` | float64 | log g uncertainty (dex) |
| `m_h` | float64 | [M/H] abundance (dex) |
| `m_h_error` | float64 | -- |
| `alpha_m` | float64 | Alpha enhancement [alpha/M] (dex) |
| `e_[a/m]` | float64 | -- |
| `vmicro_kms` | float64 | -- |
| `vmacro_kms` | float64 | -- |
| `vsini_kms` | float64 | -- |
| `teff_sp` | float64 | -- |
| `logg_sp` | float64 | -- |
| `c_fe` | float64 | [C/Fe] abundance (dex) |
| `c_fe_sp` | float64 | -- |
| `c_fe_err` | float64 | -- |
| `c_fe_flag` | int64 | -- |
| `ci_fe` | float64 | [CI/Fe] abundance (dex) |
| `ci_fe_sp` | float64 | -- |
| `ci_fe_err` | float64 | -- |
| `ci_fe_flag` | int64 | -- |
| `n_fe` | float64 | [N/Fe] abundance (dex) |
| `n_fe_sp` | float64 | -- |
| `n_fe_err` | float64 | -- |
| `n_fe_flag` | int64 | -- |
| `o_fe` | float64 | [O/Fe] abundance (dex) |
| `o_fe_sp` | float64 | -- |
| `o_fe_err` | float64 | -- |
| `o_fe_flag` | int64 | -- |
| `na_fe` | float64 | [NA/Fe] abundance (dex) |
| `na_fe_sp` | float64 | -- |
| `na_fe_err` | float64 | -- |
| `na_fe_flag` | int64 | -- |
| `mg_fe` | float64 | [MG/Fe] abundance (dex) |
| `mg_fe_sp` | float64 | -- |
| `mg_fe_err` | float64 | -- |
| `mg_fe_flag` | int64 | -- |
| `al_fe` | float64 | [AL/Fe] abundance (dex) |
| `al_fe_sp` | float64 | -- |
| `al_fe_err` | float64 | -- |
| `al_fe_flag` | int64 | -- |
| `si_fe` | float64 | [SI/Fe] abundance (dex) |
| `si_fe_sp` | float64 | -- |
| `si_fe_err` | float64 | -- |
| `si_fe_flag` | int64 | -- |
| `s_fe` | float64 | [S/Fe] abundance (dex) |
| `s_fe_sp` | float64 | -- |
| `s_fe_err` | float64 | -- |
| `s_fe_flag` | int64 | -- |
| `k_fe` | float64 | [K/Fe] abundance (dex) |
| `k_fe_sp` | float64 | -- |
| `k_fe_err` | float64 | -- |
| `k_fe_flag` | int64 | -- |
| `ca_fe` | float64 | [CA/Fe] abundance (dex) |
| `ca_fe_sp` | float64 | -- |
| `ca_fe_err` | float64 | -- |
| `ca_fe_flag` | int64 | -- |
| `ti_fe` | float64 | [TI/Fe] abundance (dex) |
| `ti_fe_sp` | float64 | -- |
| `ti_fe_err` | float64 | -- |
| `ti_fe_flag` | int64 | -- |
| `tiii_fe` | float64 | [TIII/Fe] abundance (dex) |
| `tiii_fe_sp` | float64 | -- |
| `tiii_fe_err` | float64 | -- |
| `tiii_fe_flag` | int64 | -- |
| `v_fe` | float64 | [V/Fe] abundance (dex) |
| `v_fe_sp` | float64 | -- |
| `v_fe_err` | float64 | -- |
| `v_fe_flag` | int64 | -- |
| `cr_fe` | float64 | [CR/Fe] abundance (dex) |
| `cr_fe_sp` | float64 | -- |
| `cr_fe_err` | float64 | -- |
| `cr_fe_flag` | int64 | -- |
| `mn_fe` | float64 | [MN/Fe] abundance (dex) |
| `mn_fe_sp` | float64 | -- |
| `mn_fe_err` | float64 | -- |
| `mn_fe_flag` | int64 | -- |
| `fe_h` | float64 | Metallicity [Fe/H] (dex) |
| `fe_h_sp` | float64 | -- |
| `fe_h_err` | float64 | -- |
| `fe_h_flag` | int64 | -- |
| `co_fe` | float64 | [CO/Fe] abundance (dex) |
| `co_fe_sp` | float64 | -- |
| `co_fe_err` | float64 | -- |
| `co_fe_flag` | int64 | -- |
| `ni_fe` | float64 | [NI/Fe] abundance (dex) |
| `ni_fe_sp` | float64 | -- |
| `ni_fe_err` | float64 | -- |
| `ni_fe_flag` | int64 | -- |
| `ce_fe` | float64 | [CE/Fe] abundance (dex) |
| `ce_fe_sp` | float64 | -- |
| `ce_fe_err` | float64 | -- |
| `ce_fe_flag` | int64 | -- |
| `dr16` | int64 | -- |

## Quick stats

- **733,901** stars total
- **689,024** with effective temperature
- **647,042** with [Fe/H] metallicity
- **20** individual abundance elements
- Teff range: **3088** -- **19870** K
- [Fe/H] range: **-2.47** to **0.96** dex

## Usage

```python
from datasets import load_dataset

ds = load_dataset("juliensimon/apogee-dr17", split="train")
df = ds.to_pandas()

# Kiel diagram (Teff vs log g)
import matplotlib.pyplot as plt
valid = df.dropna(subset=["teff_k", "logg"])
plt.scatter(valid["teff_k"], valid["logg"], c=valid["fe_h"],
            s=0.1, alpha=0.3, cmap="coolwarm", vmin=-2, vmax=0.5)
plt.gca().invert_xaxis()
plt.gca().invert_yaxis()
plt.xlabel("Teff (K)")
plt.ylabel("log g (dex)")
plt.colorbar(label="[Fe/H]")
plt.title("APOGEE DR17 Kiel Diagram")

# [Mg/Fe] vs [Fe/H] — chemical evolution
if "mg_fe" in df.columns:
    valid = df.dropna(subset=["fe_h", "mg_fe"])
    plt.figure()
    plt.scatter(valid["fe_h"], valid["mg_fe"], s=0.1, alpha=0.2)
    plt.xlabel("[Fe/H] (dex)")
    plt.ylabel("[Mg/Fe] (dex)")
    plt.title("Chemical Evolution: [Mg/Fe] vs [Fe/H]")
```

## Data source

Abdurro'uf et al. (2022), "The Seventeenth Data Release of the Sloan Digital
Sky Surveys: Complete Release of MaNGA, MaStar, and APOGEE-2 Data", ApJS, 259, 35.
Accessed via [VizieR III/286](https://vizier.cds.unistra.fr/viz-bin/VizieR?-source=III/286),
CDS Strasbourg.

## Related datasets

- [rave-dr6](https://huggingface.co/datasets/juliensimon/rave-dr6) -- RAVE DR6 stellar parameters and chemical abundances
- [wolf-rayet-stars](https://huggingface.co/datasets/juliensimon/wolf-rayet-stars) -- Galactic Wolf-Rayet star catalog
- [brown-dwarf-catalog](https://huggingface.co/datasets/juliensimon/brown-dwarf-catalog) -- Brown dwarf catalog

## Pipeline

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

## Support

If you find this dataset useful, please give it a heart on the [dataset page](https://huggingface.co/datasets/juliensimon/apogee-dr17) and share feedback in the Community tab! Also consider giving a star to the [space-datasets](https://github.com/juliensimon/space-datasets) repo.

## Citation

```bibtex
@dataset{apogee_dr17,
  author = {Simon, Julien},
  title = {APOGEE DR17 Stellar Parameters & Abundances},
  year = {2026},
  publisher = {Hugging Face},
  url = {https://huggingface.co/datasets/juliensimon/apogee-dr17},
  note = {Based on Abdurro'uf et al. (2022, ApJS 259 35) via VizieR CDS Strasbourg}
}
```

## License



[SDSS Data Use Policy](https://www.sdss4.org/dr17/data_access/)