Finding HATS catalogs via VO#
Introduction#
Virtual Observatory (VO) is the name for the set of common standards, protocols, and infrastructure for Astronomy Data. These are proposed and agreed upon by the International Virtual Observatory Alliance (IVOA).
Many archives and data publishers participate in the VO registry, where data resources are gathered for Astronomers around the world to discover. You can easily query this registry with the pyVO library.
You can also discover additional HATS-related services registered across the community, using the Virtual Observatory Registry search
In this tutorial, we will:
execute some example registry searches to find HATS catalogs (usable by LSDB)
use registry results to retrieve catalogs in LSDB
find the best mirror for data, for your machine
1. Install and import required packages#
[1]:
# Uncomment to install pyvo
# %pip install --upgrade --quiet pyvo
[2]:
import lsdb
from pyvo import registry
lsdb.show_versions()
-------- SYSTEM INFO --------
python : 3.13.12
python-bits : 64
OS : Linux
OS-release : 5.14.0-687.33.1.el9_8.x86_64
Version : #1 SMP PREEMPT_DYNAMIC Fri Jul 31 22:46:57 UTC 2026
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL :
LANG : C.UTF-8
-------- INSTALLED VERSIONS --------
lsdb : 0.10.4
hats : 0.10.4
nested-pandas : 0.6.10
pandas : 2.3.3
numpy : 2.4.2
dask : 2026.3.0
pyarrow : 23.0.1
fsspec : 2026.7.0
2. Issue a broad query#
First, we will just look for any HATS service resources. This is going to have a lot of results, but we can explore the result types as tables, or convert to pandas tables.
[3]:
results = registry.search(servicetype="hats")
results
[3]:
<DALResultsTable length=43>
ivoid ... cap_descriptions
...
object ... object
---------------------------------------------------- ... ----------------
ivo://archive.stsci.edu/hats/ps1dr2 ...
ivo://data.lsdb/epyc/2mass ...
ivo://data.lsdb/irsa/euclid_q1_ipac ...
ivo://data.lsdb/irsa/ztf_dr23_lightcu ...
ivo://data.lsdb/irsa/ztf_dr23_objects ...
ivo://data.lsdb/s3/gaia_dr3_stsci ...
ivo://data.lsdb/s3/pan_starrs1_dete ...
ivo://data.lsdb/s3/pan_starrs1_obje ...
ivo://data.lsdb/uw/2mass_psc ...
... ... ...
ivo://data.lsdb/uw/ztf_dr14_sources ...
ivo://data.lsdb/uw/ztf_dr22 ...
ivo://data.lsdb/uw/zubercal_dr16 ...
ivo://data.lsdb/uw/zubercal_dr20 ...
ivo://irsa.ipac/euclid/hats/euclid_q1_merged_objects ...
ivo://irsa.ipac/ztf/hats/dr23_lightcurves ...
ivo://irsa.ipac/ztf/hats/dr23_objects ...
ivo://irsa.ipac/ztf/lc/hats/ztf_dr23_lightcurves ...
ivo://irsa.ipac/ztf/lc/hats/ztf_dr23_objects ...
[4]:
results.get_summary()
[4]:
Table length=43
| index | short_name | title | description | interfaces |
|---|---|---|---|---|
| int64 | str22 | str92 | str1007 | str13 |
| 0 | MAST PS1DR2 HATS | MAST PanSTARRS1 DR2 Mean Object HATS Survey | This is MAST's Hierarchical Adaptive Tiling Scheme (HATS) survey service for PanSTARRS 1 DR2. | hats#hats-1.0 |
| 1 | two_mass | LINCC Frameworks - UW/epyc - 2MASS PSC | The Two Micron All-Sky Survey (2MASS) is an infrared survey of the whole sky by The University of Massachusetts \n and the Infrared Processing and Analysis Center (JPL / Caltech). \n This Point Source Release (PSC) contains accurate astrometry and \n photometric for over 470 million objects as observed from the northern \n 2MASS facility at Mt. Hopkins, Arizona, and the southern 2MASS facility at Cerro Tololo, Chile. | hats#hats-1.0 |
| 2 | euclid_q1_ipac | LINCC Frameworks - NASA/IRSA - Euclid Quick Data Release 1 | Euclid is a space-based survey observatory launched by the European Space Agency (ESA) in July 2023, which aims to map the large-scale structure of the Universe to better understand dark energy and dark matter. The first Quick Data Release (Q1) covers 63 square degrees of the sky and including observations of 26 million galaxies. | hats#hats-1.0 |
| 3 | ztf_dr23_lightcu | LINCC Frameworks - IPAC/IRSA - Zwicky Transient Facility Data Release 23 (lightcurves) | Detailed light curve catalog for ZTF DR23 (objects). | hats#hats-1.0 |
| 4 | ztf_dr23_objects | LINCC Frameworks - IPAC/IRSA - Zwicky Transient Facility Data Release 23 (objects) | Comprehensive catalog released by the Zwicky Transient Facility with objects detected in the northern sky. | hats#hats-1.0 |
| 5 | gaia_dr3_stsci | LINCC Frameworks - STScI/Open Space - Gaia Data Release 3 (STScI) | Gaia Data Release 3 (GAIA_SOURCE table) is a comprehensive catalog released by the European Space Agency (ESA) as part of the Gaia mission, which aims to create a detailed three-dimensional map of our galaxy, the Milky Way. Released in June 2022, Gaia DR3 provides highly precise astrometric data (positions, distances, and motions) for nearly 1.8 billion stars, along with detailed photometric and spectroscopic information. | hats#hats-1.0 |
| 6 | pan_starrs1_dete | LINCC Frameworks - STScI/Open Space - Pan-STARRS1 (detection) | Catalog of single epoch photometry of individual detections from a single exposure for the objects in the Pan-STARRS1 survey. | hats#hats-1.0 |
| 7 | pan_starrs1_obje | LINCC Frameworks - STScI/Open Space - Pan-STARRS1 (objects) | Pan-STARRS is a system for wide-field astronomical imaging developed and operated by the Institute for Astronomy at the University of Hawaii. Pan-STARRS1 (PS1) is the first part of Pan-STARRS to be completed. The survey used a 1.8 meter telescope and its 1.4 Gigapixel camera to image the sky in five broadband filters (g, r, i, z, y). This catalog is a view over that survey and it includes over 10 billion objects. | hats#hats-1.0 |
| 8 | 2mass_psc | LINCC Frameworks - UW/Epyc - 2MASS Point Source Catalog | The Two Micron All-Sky Survey (2MASS) is an infrared survey of the whole sky by The University of Massachusetts and the Infrared Processing and Analysis Center (JPL / Caltech). This Point Source Release (PSC) contains accurate astrometry and photometric for over 470 million objects as observed from the northern 2MASS facility at Mt. Hopkins, Arizona, and the southern 2MASS facility at Cerro Tololo, Chile. | hats#hats-1.0 |
| ... | ... | ... | ... | ... |
| 33 | ztf_dr14_objects | LINCC Frameworks - UW/Epyc - Zwicky Transient Facility Data Release 14 (objects) | Comprehensive catalog released by the Zwicky Transient Facility with objects detected in the northern sky, crossmatched to Pan-STARRS objects. It does not include time-domain data. | hats#hats-1.0 |
| 34 | ztf_dr14_sources | LINCC Frameworks - UW/Epyc - Zwicky Transient Facility Data Release 14 (sources) | Detailed light curve catalog for ZTF DR14 (objects). | hats#hats-1.0 |
| 35 | ztf_dr22 | LINCC Frameworks - UW/Epyc - Zwicky Transient Facility Data Release 22 (light curves) | Metadata and light curves for ZTF DR22. Light curves are packed into list-arrays following the original schema. | hats#hats-1.0 |
| 36 | zubercal_dr16 | LINCC Frameworks - UW/Epyc - ZTF Ubercalibration Data Release 16 | Zubercal is a completely new set of photometry based on a detailed recalibration of ZTF science image-based PSF photometry. | hats#hats-1.0 |
| 37 | zubercal_dr20 | LINCC Frameworks - UW/Epyc - ZTF Ubercalibration Data Release 20 | Zubercal is a completely new set of photometry based on a detailed recalibration of ZTF science image-based PSF photometry. | hats#hats-1.0 |
| 38 | Euclid_Q1_MOHATS | IRSA Euclid Q1 Merged Objects HATS Catalog | The IRSA HATS Catalog contains multiple collections in the Hierarchical Adaptive Tiling Scheme.\n This includes: Euclid Q1 Merged Objects - HATS Collection\n\n # Euclid Q1 Merged Objects - HATS Collection\n creator_did = ivo://irsa.ipac/Euclid/HATS\n hats_status = public main cloneable\n obs_collection = Euclid_Q1_Merged_Objects\n hats_primary_table_url = euclid_q1_merged_objects-hats\n all_margins = euclid_q1_merged_objects-hats_margin_10arcsec\n default_margin = euclid_q1_merged_objects-hats_margin_10arcsec\n all_indexes = object_id euclid_q1_merged_objects-hats_index_object_id\n default_index = object_id\n hats_uri = s3://nasa-irsa-euclid-q1/contributed/q1/merged_objects/hats/\n hats_url = https://nasa-irsa-euclid-q1.s3.us-east-1.amazonaws.com/contributed/q1/merged_objects/hats | hats#hats-1.0 |
| 39 | IRSA ZTF DR23 LC HATS | IRSA ZTF DR23 Light Curves HATS Catalog | The IRSA HATS Catalog contains multiple collections in the Hierarchical Adaptive Tiling Scheme.\nThis includes: Zwicky Transient Facility (ZTF) DR 23 Light Curves - HATS Collection\n\n# ZTF DR23 Light Curves - HATS Collection\ncreator_did = ivo://irsa.ipac/ZTF/lc/HATS\nhats_status = public main cloneable\nobs_collection = ZTF_DR23_Lightcurves\nhats_primary_table_url = ztf_dr23_lc-hats\nall_margins = ztf_dr23_lc-hats_margin_10arcsec\ndefault_margin = ztf_dr23_lc-hats_margin_10arcsec\nall_indexes = objectid ztf_dr23_lc-hats_index_objectid\ndefault_index = objectid\nhats_uri = s3://ipac-irsa-ztf/contributed/dr23/lc/hats\nhats_url = https://ipac-irsa-ztf.s3.us-east-1.amazonaws.com/contributed/dr23/lc/hats | hats#hats-1.0 |
| 40 | IRSA ZTF DR23 Obj HATS | IRSA ZTF DR23 Objects HATS Catalog | The IRSA HATS Catalog contains multiple collections in the Hierarchical Adaptive Tiling Scheme.\nThis includes: Zwicky Transient Facility (ZTF) DR 23 Objects Table - HATS Collection\n\n# ZTF DR23 Objects Table - HATS Collection\ncreator_did = ivo://irsa.ipac/ZTF/objects/HATS\nhats_status = public main cloneable\nobs_collection = ZTF_DR23_Objects\nhats_primary_table_url = ztf_dr23_objects-hats\nall_margins = ztf_dr23_objects-hats_margin_10arcsec\ndefault_margin = ztf_dr23_objects-hats_margin_10arcsec\nall_indexes = oid ztf_dr23_objects-hats_index_oid\ndefault_index = oid\nhats_uri = s3://ipac-irsa-ztf/contributed/dr23/objects/hats\nhats_url = https://ipac-irsa-ztf.s3.us-east-1.amazonaws.com/contributed/dr23/objects/hats | hats#hats-1.0 |
| 41 | ZTF DR23 LC HATS | ZTF DR23 Light Curves HATS Catalog | The IRSA HATS Catalog contains multiple collections in the Hierarchical Adaptive Tiling Scheme.\n This includes: ZTF DR23 Light Curves - HATS Collection\n\n # ZTF DR23 Light Curves - HATS Collection\n creator_did = ivo://irsa.ipac/ZTF/lc/HATS/ZTF_DR23_Lightcurves\n hats_status = public main cloneable\n obs_collection = ZTF_DR23_Lightcurves\n hats_primary_table_url = ztf_dr23_lc-hats\n all_margins = ztf_dr23_lc-hats_margin_10arcsec\n default_margin = ztf_dr23_lc-hats_margin_10arcsec\n all_indexes = objectid ztf_dr23_lc-hats_index_objectid\n default_index = objectid\n hats_uri = s3://ipac-irsa-ztf/contributed/dr23/lc/hats\n hats_url = https://ipac-irsa-ztf.s3.us-east-1.amazonaws.com/contributed/dr23/lc/hats\n obs_regime = Optical | hats#hats-1.0 |
| 42 | ZTF DR23 OB HATS | ZTF DR23 Objects Table HATS Catalog | The IRSA HATS Catalog contains multiple collections in the Hierarchical Adaptive Tiling Scheme.\n This includes: ZTF DR23 Objects Table - HATS Collection\n\n # ZTF DR23 Objects Table - HATS Collection\n creator_did = ivo://irsa.ipac/ZTF/objects/HATS/ZTF_DR23_Objects\n hats_status = public main cloneable\n obs_collection = ZTF_DR23_Objects\n hats_primary_table_url = ztf_dr23_objects-hats\n all_margins = ztf_dr23_objects-hats_margin_10arcsec\n default_margin = ztf_dr23_objects-hats_margin_10arcsec\n all_indexes = oid ztf_dr23_objects-hats_index_oid\n default_index = oid\n hats_uri = s3://ipac-irsa-ztf/contributed/dr23/objects/hats\n hats_url = https://ipac-irsa-ztf.s3.us-east-1.amazonaws.com/contributed/dr23/objects/hats\n obs_regime = Optical | hats#hats-1.0 |
[5]:
results_frame = results.to_table().to_pandas()
results_frame
[5]:
| ivoid | res_type | short_name | res_title | content_level | res_description | reference_url | creator_seq | created | updated | ... | content_type | source_format | source_value | region_of_regard | waveband | access_urls | standard_ids | intf_types | intf_roles | cap_descriptions | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | ivo://archive.stsci.edu/hats/ps1dr2 | vs:catalogservice | MAST PS1DR2 HATS | MAST PanSTARRS1 DR2 Mean Object HATS Survey | research | This is MAST's Hierarchical Adaptive Tiling Sc... | http://archive.stsci.edu/vo/mast_services.html | Space Telescope Science Institute Catalogs and... | 2025-10-14T19:29:18 | 2025-10-14T19:54:04 | ... | catalog | NaN | optical | https://stpubdata.s3.us-east-1.amazonaws.com/p... | ivo://ivoa.net/std/hats#hats-1.0 | vs:paramhttp | std | |||
| 1 | ivo://data.lsdb/epyc/2mass | vs:catalogservice | two_mass | LINCC Frameworks - UW/epyc - 2MASS PSC | research | The Two Micron All-Sky Survey (2MASS) is an in... | https://irsa.ipac.caltech.edu/data/2MASS/docs/... | LINCC Frameworks | 2024-10-02T17:35:00 | 2024-10-21T22:06:08 | ... | archive | NaN | https://data.lsdb.io/hats/two_mass/ | ivo://ivoa.net/std/hats#hats-1.0 | vs:paramhttp | std | ||||
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 41 | ivo://irsa.ipac/ztf/lc/hats/ztf_dr23_lightcurves | vs:catalogservice | ZTF DR23 LC HATS | ZTF DR23 Light Curves HATS Catalog | research | The IRSA HATS Catalog contains multiple collec... | https://www.ivoa.net/documents/Notes/HATS/ | IRSA | 2025-10-14T18:16:06 | 2026-05-29T00:00:00 | ... | catalog | NaN | optical | https://ipac-irsa-ztf.s3.us-east-1.amazonaws.c... | ivo://ivoa.net/std/hats#hats-1.0 | vs:paramhttp | std | |||
| 42 | ivo://irsa.ipac/ztf/lc/hats/ztf_dr23_objects | vs:catalogservice | ZTF DR23 OB HATS | ZTF DR23 Objects Table HATS Catalog | research | The IRSA HATS Catalog contains multiple collec... | https://www.ivoa.net/documents/Notes/HATS/ | IRSA | 2025-10-14T18:16:06 | 2026-05-29T00:00:00 | ... | catalog | NaN | optical | https://ipac-irsa-ztf.s3.us-east-1.amazonaws.c... | ivo://ivoa.net/std/hats#hats-1.0 | vs:paramhttp | std |
43 rows × 21 columns
3. Narrow the search#
PyVO supports many special search terms, but we’ll just go for a general keyword search on “gaia”.
[6]:
results = registry.search(servicetype="hats", keywords="gaia")
results
[6]:
<DALResultsTable length=4>
ivoid res_type ... cap_descriptions
...
object object ... object
---------------------------------- ----------------- ... ----------------
ivo://data.lsdb/s3/gaia_dr3_stsci vs:catalogservice ...
ivo://data.lsdb/uw/bailer_jones_20 vs:catalogservice ...
ivo://data.lsdb/uw/gaia_dr3_uw vs:catalogservice ...
ivo://data.lsdb/uw/tic_v8_2 vs:catalogservice ...
4. Pass to LSDB#
There are two GAIA DR3 instances returned from the search. I happen to know that they’re copies of each other, but to find out which might be faster for you to access, you can perform a quick-load of the catalog’s metadata. This will help you find the best mirror for you. Note that this might change based on your location, internet speed, resource availability, server load, etc.
If this is something you find yourself doing often, let us know, and we can work on making the process smoother!
[7]:
%%time
lsdb.open_catalog(results.getrecord(0).access_url)
CPU times: user 296 ms, sys: 53.5 ms, total: 349 ms
Wall time: 3.48 s
[7]:
lsdb Catalog gaia:
| solution_id | designation | source_id | random_index | ref_epoch | ra | ra_error | dec | dec_error | parallax | parallax_error | parallax_over_error | pm | pmra | pmra_error | pmdec | pmdec_error | ra_dec_corr | ra_parallax_corr | ra_pmra_corr | ra_pmdec_corr | dec_parallax_corr | dec_pmra_corr | dec_pmdec_corr | parallax_pmra_corr | parallax_pmdec_corr | pmra_pmdec_corr | astrometric_n_obs_al | astrometric_n_obs_ac | astrometric_n_good_obs_al | astrometric_n_bad_obs_al | astrometric_gof_al | astrometric_chi2_al | astrometric_excess_noise | astrometric_excess_noise_sig | astrometric_params_solved | astrometric_primary_flag | nu_eff_used_in_astrometry | pseudocolour | pseudocolour_error | ra_pseudocolour_corr | dec_pseudocolour_corr | parallax_pseudocolour_corr | pmra_pseudocolour_corr | pmdec_pseudocolour_corr | astrometric_matched_transits | visibility_periods_used | astrometric_sigma5d_max | matched_transits | new_matched_transits | matched_transits_removed | ipd_gof_harmonic_amplitude | ipd_gof_harmonic_phase | ipd_frac_multi_peak | ipd_frac_odd_win | ruwe | scan_direction_strength_k1 | scan_direction_strength_k2 | scan_direction_strength_k3 | scan_direction_strength_k4 | scan_direction_mean_k1 | scan_direction_mean_k2 | scan_direction_mean_k3 | scan_direction_mean_k4 | duplicated_source | phot_g_n_obs | phot_g_mean_flux | phot_g_mean_flux_error | phot_g_mean_flux_over_error | phot_g_mean_mag | phot_bp_n_obs | phot_bp_mean_flux | phot_bp_mean_flux_error | phot_bp_mean_flux_over_error | phot_bp_mean_mag | phot_rp_n_obs | phot_rp_mean_flux | phot_rp_mean_flux_error | phot_rp_mean_flux_over_error | phot_rp_mean_mag | phot_bp_rp_excess_factor | phot_bp_n_contaminated_transits | phot_bp_n_blended_transits | phot_rp_n_contaminated_transits | phot_rp_n_blended_transits | phot_proc_mode | bp_rp | bp_g | g_rp | radial_velocity | radial_velocity_error | rv_method_used | rv_nb_transits | rv_nb_deblended_transits | rv_visibility_periods_used | rv_expected_sig_to_noise | rv_renormalised_gof | rv_chisq_pvalue | rv_time_duration | rv_amplitude_robust | rv_template_teff | rv_template_logg | rv_template_fe_h | rv_atm_param_origin | vbroad | vbroad_error | vbroad_nb_transits | grvs_mag | grvs_mag_error | grvs_mag_nb_transits | rvs_spec_sig_to_noise | phot_variable_flag | l | b | ecl_lon | ecl_lat | in_qso_candidates | in_galaxy_candidates | non_single_star | has_xp_continuous | has_xp_sampled | has_rvs | has_epoch_photometry | has_epoch_rv | has_mcmc_gspphot | has_mcmc_msc | in_andromeda_survey | classprob_dsc_combmod_quasar | classprob_dsc_combmod_galaxy | classprob_dsc_combmod_star | teff_gspphot | teff_gspphot_lower | teff_gspphot_upper | logg_gspphot | logg_gspphot_lower | logg_gspphot_upper | mh_gspphot | mh_gspphot_lower | mh_gspphot_upper | distance_gspphot | distance_gspphot_lower | distance_gspphot_upper | azero_gspphot | azero_gspphot_lower | azero_gspphot_upper | ag_gspphot | ag_gspphot_lower | ag_gspphot_upper | ebpminrp_gspphot | ebpminrp_gspphot_lower | ebpminrp_gspphot_upper | libname_gspphot | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| npartitions=2016 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Order: 2, Pixel: 0 | int64[pyarrow] | string[pyarrow] | int64[pyarrow] | int64[pyarrow] | double[pyarrow] | double[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int8[pyarrow] | bool[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | int8[pyarrow] | int8[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | bool[pyarrow] | int16[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | int8[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int8[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | float[pyarrow] | string[pyarrow] | double[pyarrow] | double[pyarrow] | double[pyarrow] | double[pyarrow] | bool[pyarrow] | bool[pyarrow] | int16[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | string[pyarrow] |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Order: 3, Pixel: 766 | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Order: 3, Pixel: 767 | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
152 out of 152 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
This catalog has an estimated size of 765.3 GB
[8]:
%%time
lsdb.open_catalog(results.getrecord(2).access_url)
CPU times: user 147 ms, sys: 10.7 ms, total: 158 ms
Wall time: 227 ms
[8]:
lsdb Catalog gaia:
| solution_id | designation | source_id | random_index | ref_epoch | ra | ra_error | dec | dec_error | parallax | parallax_error | parallax_over_error | pm | pmra | pmra_error | pmdec | pmdec_error | ra_dec_corr | ra_parallax_corr | ra_pmra_corr | ra_pmdec_corr | dec_parallax_corr | dec_pmra_corr | dec_pmdec_corr | parallax_pmra_corr | parallax_pmdec_corr | pmra_pmdec_corr | astrometric_n_obs_al | astrometric_n_obs_ac | astrometric_n_good_obs_al | astrometric_n_bad_obs_al | astrometric_gof_al | astrometric_chi2_al | astrometric_excess_noise | astrometric_excess_noise_sig | astrometric_params_solved | astrometric_primary_flag | nu_eff_used_in_astrometry | pseudocolour | pseudocolour_error | ra_pseudocolour_corr | dec_pseudocolour_corr | parallax_pseudocolour_corr | pmra_pseudocolour_corr | pmdec_pseudocolour_corr | astrometric_matched_transits | visibility_periods_used | astrometric_sigma5d_max | matched_transits | new_matched_transits | matched_transits_removed | ipd_gof_harmonic_amplitude | ipd_gof_harmonic_phase | ipd_frac_multi_peak | ipd_frac_odd_win | ruwe | scan_direction_strength_k1 | scan_direction_strength_k2 | scan_direction_strength_k3 | scan_direction_strength_k4 | scan_direction_mean_k1 | scan_direction_mean_k2 | scan_direction_mean_k3 | scan_direction_mean_k4 | duplicated_source | phot_g_n_obs | phot_g_mean_flux | phot_g_mean_flux_error | phot_g_mean_flux_over_error | phot_g_mean_mag | phot_bp_n_obs | phot_bp_mean_flux | phot_bp_mean_flux_error | phot_bp_mean_flux_over_error | phot_bp_mean_mag | phot_rp_n_obs | phot_rp_mean_flux | phot_rp_mean_flux_error | phot_rp_mean_flux_over_error | phot_rp_mean_mag | phot_bp_rp_excess_factor | phot_bp_n_contaminated_transits | phot_bp_n_blended_transits | phot_rp_n_contaminated_transits | phot_rp_n_blended_transits | phot_proc_mode | bp_rp | bp_g | g_rp | radial_velocity | radial_velocity_error | rv_method_used | rv_nb_transits | rv_nb_deblended_transits | rv_visibility_periods_used | rv_expected_sig_to_noise | rv_renormalised_gof | rv_chisq_pvalue | rv_time_duration | rv_amplitude_robust | rv_template_teff | rv_template_logg | rv_template_fe_h | rv_atm_param_origin | vbroad | vbroad_error | vbroad_nb_transits | grvs_mag | grvs_mag_error | grvs_mag_nb_transits | rvs_spec_sig_to_noise | phot_variable_flag | l | b | ecl_lon | ecl_lat | in_qso_candidates | in_galaxy_candidates | non_single_star | has_xp_continuous | has_xp_sampled | has_rvs | has_epoch_photometry | has_epoch_rv | has_mcmc_gspphot | has_mcmc_msc | in_andromeda_survey | classprob_dsc_combmod_quasar | classprob_dsc_combmod_galaxy | classprob_dsc_combmod_star | teff_gspphot | teff_gspphot_lower | teff_gspphot_upper | logg_gspphot | logg_gspphot_lower | logg_gspphot_upper | mh_gspphot | mh_gspphot_lower | mh_gspphot_upper | distance_gspphot | distance_gspphot_lower | distance_gspphot_upper | azero_gspphot | azero_gspphot_lower | azero_gspphot_upper | ag_gspphot | ag_gspphot_lower | ag_gspphot_upper | ebpminrp_gspphot | ebpminrp_gspphot_lower | ebpminrp_gspphot_upper | libname_gspphot | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| npartitions=2016 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Order: 2, Pixel: 0 | int64[pyarrow] | string[pyarrow] | int64[pyarrow] | int64[pyarrow] | double[pyarrow] | double[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int8[pyarrow] | bool[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | int8[pyarrow] | int8[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | bool[pyarrow] | int16[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | double[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | int8[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int8[pyarrow] | int16[pyarrow] | int16[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | float[pyarrow] | float[pyarrow] | int16[pyarrow] | float[pyarrow] | string[pyarrow] | double[pyarrow] | double[pyarrow] | double[pyarrow] | double[pyarrow] | bool[pyarrow] | bool[pyarrow] | int16[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | bool[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | float[pyarrow] | string[pyarrow] |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Order: 3, Pixel: 766 | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| Order: 3, Pixel: 767 | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
152 out of 152 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
This catalog has an estimated size of 765.3 GB
For this example (run on a personal laptop in Pittsburgh, PA), the version of GAIA hosted on S3 by Space Telescope takes only 2.7s to open a catalog, and the west coast HTTP takes 9.4s.
About#
Authors: Melissa DeLucchi
Last updated/verified on: August 14, 2026
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