CDS services in Jupyter notebooks#

Katarina A. Lutz¹, Manon Marchand¹

  1. Université de Strasbourg, CNRS, Observatoire Astronomique de Strasbourg, UMR 7550, F-67000, Strasbourg, France


Introduction#

Welcome to a Jupyter notebook demonstrating how to access some of the services provided by the Strasbourg astronomical Data Center (CDS) with Python.

In this tutorial, we will:

  1. gather information on a specific object using Simbad,

  2. visualise it through survey images using the Aladin Lite widget,

  3. find and download a catalogue from Vizier,

  4. overlay the sources of this catalog on the sky view in the Aladin Lite widget,

  5. cross-match the sources with a large catalogue using Xmatch.

# Astronomy tools
import astropy.units as u

# Access astronomical databases
from astroquery.simbad import Simbad
from astroquery.vizier import Vizier
from astroquery.xmatch import XMatch

# Sky visualization
from ipyaladin import Aladin

Step #1: Gather information on NGC4038#

Simbad

As a first step, we check what information is directly available from the Simbad python module. We can look at the methods available for the Simbad class with the help() command:

help(Simbad)
Help on SimbadClass in module astroquery.simbad.core object:

class SimbadClass(SimbadBaseQuery)
 |  The class for querying the Simbad web service.
 |  
 |  Note that SIMBAD suggests submitting no more than 6 queries per second; if
 |  you submit more than that, your IP may be temporarily blacklisted
 |  (http://simbad.u-strasbg.fr/simbad/sim-help?Page=sim-url)
 |  
 |  Method resolution order:
 |      SimbadClass
 |      SimbadBaseQuery
 |      astroquery.query.BaseQuery
 |      builtins.object
 |  
 |  Methods defined here:
 |  
 |  __init__(self)
 |      Initialize self.  See help(type(self)) for accurate signature.
 |  
 |  add_votable_fields(self, *args)
 |      Sets fields to be fetched in the VOTable. Must be one of those listed
 |      by `list_votable_fields`.
 |      
 |      Parameters
 |      ----------
 |      list of field_names
 |  
 |  get_field_description(self, field_name)
 |      Displays a description of the VOTable field.
 |      
 |      Parameters
 |      ----------
 |      field_name : str
 |          the name of the field to describe. Must be one of those listed
 |          by `list_votable_fields`.
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.simbad import Simbad
 |      >>> Simbad.get_field_description('main_id')
 |      main identifier of an astronomical object. It is the same as id(1)
 |      >>> Simbad.get_field_description('bibcodelist(y1-y2)')
 |      number of references. The parameter is optional and limit the count to
 |      the references between the years y1 and y2
 |  
 |  get_votable_fields(self)
 |      Display votable fields
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.simbad import Simbad
 |      >>> Simbad.get_votable_fields()
 |      ['main_id', 'coordinates']
 |  
 |  list_votable_fields(self)
 |      Lists all the fields that can be fetched for a VOTable.
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.simbad import Simbad
 |      >>> Simbad.list_votable_fields()
 |      --NOTES--...
 |  
 |  list_wildcards(self)
 |      Displays the available wildcards that may be used in Simbad queries and
 |      their usage.
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.simbad import Simbad
 |      >>> Simbad.list_wildcards()
 |      * : Any string of characters (including an empty one)...
 |      
 |      [^0-9] : Any (one) character not in the list.
 |      
 |      ? : Any character (exactly one character)
 |      
 |      [abc] : Exactly one character taken in the list.
 |              Can also be defined by a range of characters: [A-Z]
 |  
 |  query_bibcode(self, bibcode, wildcard=False, verbose=False, cache=True, get_query_payload=False)
 |      Queries the references corresponding to a given bibcode, and returns
 |      the results in a `~astropy.table.Table`. Wildcards may be used to
 |      specify bibcodes.
 |      
 |      Parameters
 |      ----------
 |      bibcode : str
 |          the bibcode of the article
 |      wildcard : boolean, optional
 |          When it is set to `True` it implies that the object is specified
 |          with wildcards. Defaults to `False`.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_bibcode_async(self, bibcode, wildcard=False, cache=True, get_query_payload=False)
 |      Serves the same function as `query_bibcode`, but
 |      only collects the response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      bibcode : str
 |          the bibcode of the article
 |      wildcard : boolean, optional
 |          When it is set to `True` it implies that the object is specified
 |          with wildcards. Defaults to `False`.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |           Response of the query from the server.
 |  
 |  query_bibobj(self, bibcode, verbose=False, get_query_payload=False)
 |      Query all the objects that are contained in the article specified by
 |      the bibcode, and return results as a `~astropy.table.Table`.
 |      
 |      Parameters
 |      ----------
 |      bibcode : str
 |          the bibcode of the article
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_bibobj_async(self, bibcode, cache=True, get_query_payload=False)
 |      Serves the same function as `query_bibobj`, but only collects the
 |      response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      bibcode : str
 |          the bibcode of the article
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |           Response of the query from the server.
 |  
 |  query_catalog(self, catalog, verbose=False, cache=True, get_query_payload=False)
 |      Queries a whole catalog.
 |      
 |      Results may be very large -number of rows
 |      should be controlled by configuring `SimbadClass.ROW_LIMIT`.
 |      
 |      Parameters
 |      ----------
 |      catalog : str
 |          the name of the catalog.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_catalog_async(self, catalog, cache=True, get_query_payload=False)
 |      Serves the same function as `query_catalog`, but
 |      only collects the response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      catalog : str
 |          the name of the catalog.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |           Response of the query from the server.
 |  
 |  query_criteria(self, *args, **kwargs)
 |      Query SIMBAD based on any criteria.
 |      
 |      Parameters
 |      ----------
 |      args:
 |          String arguments passed directly to SIMBAD's script
 |          (e.g., 'region(box, GAL, 10.5 -10.5, 0.5d 0.5d)')
 |      kwargs:
 |          Keyword / value pairs passed to SIMBAD's script engine
 |          (e.g., {'otype':'SNR'} will be rendered as otype=SNR)
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_criteria_async(self, *args, **kwargs)
 |      Query SIMBAD based on any criteria.
 |      
 |      Parameters
 |      ----------
 |      args:
 |          String arguments passed directly to SIMBAD's script
 |          (e.g., 'region(box, GAL, 10.5 -10.5, 0.5d 0.5d)')
 |      kwargs:
 |          Keyword / value pairs passed to SIMBAD's script engine
 |          (e.g., {'otype':'SNR'} will be rendered as otype=SNR)
 |      cache : bool
 |          Cache the query?
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |          Response of the query from the server
 |  
 |  query_object(self, object_name, wildcard=False, verbose=False, get_query_payload=False)
 |      Queries Simbad for the given object and returns the result as a
 |      `~astropy.table.Table`. Object names may also be specified with
 |      wildcard.  See examples below.
 |      
 |      Parameters
 |      ----------
 |      object_name : str
 |          name of object to be queried
 |      wildcard : boolean, optional
 |          When it is set to `True` it implies that the object is specified
 |          with wildcards. Defaults to `False`.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_object_async(self, object_name, wildcard=False, cache=True, get_query_payload=False)
 |      Serves the same function as `query_object`, but
 |      only collects the response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      object_name : str
 |          name of object to be queried
 |      wildcard : boolean, optional
 |          When it is set to `True` it implies that the object is specified
 |          with wildcards. Defaults to `False`.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |          Response of the query from the server
 |  
 |  query_objectids(self, object_name, verbose=False, cache=True, get_query_payload=False)
 |      Query Simbad with an object name, and return a table of all
 |      names associated with that object in a `~astropy.table.Table`.
 |      
 |      Parameters
 |      ----------
 |      object_name : str
 |          name of object to be queried
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_objectids_async(self, object_name, cache=True, get_query_payload=False)
 |      Serves the same function as `query_objectids`, but
 |      only collects the response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      object_name : str
 |          name of object to be queried
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |           Response of the query from the server.
 |  
 |  query_objects(self, object_names, wildcard=False, verbose=False, get_query_payload=False)
 |      Queries Simbad for the specified list of objects and returns the
 |      results as a `~astropy.table.Table`. Object names may be specified
 |      with wildcards if desired.
 |      
 |      Parameters
 |      ----------
 |      object_names : sequence of strs
 |          names of objects to be queried
 |      wildcard : boolean, optional
 |          When `True`, the names may have wildcards in them. Defaults to
 |          `False`.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : `~astropy.table.Table`
 |          Query results table
 |  
 |  query_objects_async(self, object_names, wildcard=False, cache=True, get_query_payload=False)
 |      Same as `query_objects`, but only collects the response from the
 |      Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      object_names : sequence of strs
 |          names of objects to be queried
 |      wildcard : boolean, optional
 |          When `True`, the names may have wildcards in them. Defaults to
 |          `False`.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |          Response of the query from the server
 |  
 |  query_region(self, *args, **kwargs)
 |      Queries the service and returns a table object.
 |      
 |      Serves the same function as `query_region`, but
 |      only collects the response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      coordinates : str or `astropy.coordinates` object
 |          the identifier or coordinates around which to query.
 |      radius : str or `~astropy.units.Quantity`, optional
 |          the radius of the region. If missing, set to default
 |          value of 2 arcmin.
 |      equinox : float, optional
 |          the equinox of the coordinates. If missing set to
 |          default 2000.0.
 |      epoch : str, optional
 |          the epoch of the input coordinates. Must be specified as
 |          [J|B] <epoch>. If missing, set to default J2000.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      table : A `~astropy.table.Table` object.
 |  
 |  query_region_async(self, coordinates, radius=<Quantity 2. arcmin>, equinox=2000.0, epoch='J2000', cache=True, get_query_payload=False)
 |      Serves the same function as `query_region`, but
 |      only collects the response from the Simbad server and returns.
 |      
 |      Parameters
 |      ----------
 |      coordinates : str or `astropy.coordinates` object
 |          the identifier or coordinates around which to query.
 |      radius : str or `~astropy.units.Quantity`, optional
 |          the radius of the region. If missing, set to default
 |          value of 2 arcmin.
 |      equinox : float, optional
 |          the equinox of the coordinates. If missing set to
 |          default 2000.0.
 |      epoch : str, optional
 |          the epoch of the input coordinates. Must be specified as
 |          [J|B] <epoch>. If missing, set to default J2000.
 |      get_query_payload : bool, optional
 |          When set to `True` the method returns the HTTP request parameters.
 |          Defaults to `False`.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |           Response of the query from the server.
 |  
 |  remove_votable_fields(self, *args, **kwargs)
 |      Removes the specified field names from ``SimbadClass._VOTABLE_FIELDS``
 |      
 |      Parameters
 |      ----------
 |      list of field_names to be removed
 |      strip_params: bool
 |          If true, strip the specified keywords before removing them:
 |          e.g., ra(foo) would remove ra(bar) if this is True
 |  
 |  reset_votable_fields(self)
 |      resets VOTABLE_FIELDS to defaults
 |  
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 |  
 |  ROW_LIMIT = 0
 |  
 |  SIMBAD_URL = 'http://simbad.u-strasbg.fr/simbad/sim-script'
 |  
 |  TIMEOUT = 60
 |  
 |  WILDCARDS = {'*': 'Any string of characters (including an empty one)',...
 |  
 |  __abstractmethods__ = frozenset()
 |  
 |  ----------------------------------------------------------------------
 |  Methods inherited from astroquery.query.BaseQuery:
 |  
 |  __call__(self, *args, **kwargs)
 |      init a fresh copy of self
 |  
 |  ----------------------------------------------------------------------
 |  Data descriptors inherited from astroquery.query.BaseQuery:
 |  
 |  __dict__
 |      dictionary for instance variables (if defined)
 |  
 |  __weakref__
 |      list of weak references to the object (if defined)

Feel free to explore these methods. But in the next cell, let’s print the results of list_votable_fields

print(Simbad.list_votable_fields())
--NOTES--

1. The parameter filtername must correspond to an existing filter. Filters include: B,V,R,I,J,K.  They are checked by SIMBAD but not astroquery.simbad

2. Fields beginning with rvz display the data as it is in the database. Fields beginning with rv force the display as a radial velocity. Fields beginning with z force the display as a redshift

3. For each measurement catalog, the VOTable contains all fields of the first measurement. When applicable, the first measurement is the mean one. 

Available VOTABLE fields:

bibcodelist(y1-y2)
biblio
cel
cl.g
coo(opt)
coo_bibcode
coo_err_angle
coo_err_maja
coo_err_mina
coo_qual
coo_wavelength
coordinates
dec(opt)
dec_prec
diameter
dim
dim_angle
dim_bibcode
dim_incl
dim_majaxis
dim_minaxis
dim_qual
dim_wavelength
dimensions
distance
distance_result
einstein
fe_h
flux(filtername)
flux_bibcode(filtername)
flux_error(filtername)
flux_name(filtername)
flux_qual(filtername)
flux_system(filtername)
flux_unit(filtername)
fluxdata(filtername)
gcrv
gen
gj
hbet
hbet1
hgam
id(opt)
ids
iras
irc
iso
iue
jp11
link_bibcode
main_id
measurements
membership
mesplx
mespm
mk
morphtype
mt
mt_bibcode
mt_qual
otype
otype(opt)
otypes
parallax
plx
plx_bibcode
plx_error
plx_prec
plx_qual
pm
pm_bibcode
pm_err_angle
pm_err_maja
pm_err_mina
pm_qual
pmdec
pmdec_prec
pmra
pmra_prec
pos
posa
propermotions
ra(opt)
ra_prec
rot
rv_value
rvz_bibcode
rvz_error
rvz_qual
rvz_radvel
rvz_type
rvz_wavelength
sao
sp
sp_bibcode
sp_nature
sp_qual
sptype
td1
typed_id
ubv
uvby
uvby1
v*
velocity
xmm
z_value
For more information on a field:
Simbad.get_field_description ('field_name') 
Currently active VOTABLE fields:
 ['main_id', 'coordinates']
None

We get a list of the available fields we could query to obtain in a table. If we are uncertain about the meaning of a field, we can get a description with Simbad.get_field_description('field_name').

Scrolling the output of the cell above we also learn that the currently active fields are the main_id and the coordinates. If we want more information, we need to request it specifically. We can do so by running Simbad.add_votable_fields('field_name') before querying the object:

Simbad.get_field_description("biblio")
all bibcodes of an astronomical object separated with a ipipe
Simbad.reset_votable_fields()
Simbad.add_votable_fields("otype", "otypes", "dim", "dim_bibcode", "biblio")
info_simbad = Simbad.query_object("NGC4038")
info_simbad
Table length=1
MAIN_IDRADECRA_PRECDEC_PRECCOO_ERR_MAJACOO_ERR_MINACOO_ERR_ANGLECOO_QUALCOO_WAVELENGTHCOO_BIBCODEOTYPEOTYPESGALDIM_MAJAXISGALDIM_MINAXISGALDIM_ANGLEGALDIM_BIBCODEBIBLIOSCRIPT_NUMBER_ID
"h:m:s""d:m:s"masmasdegarcminarcmindeg
objectstr13str13int16int16float32float32int16str1str1objectobjectobjectfloat32float32int16objectobjectint32
NGC 403812 01 53.002-18 52 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We now know the main object type of NGC4038: “Emission line Galaxy” EmG. We can also read the object dimensions (major axis GALDIM_MAJAXIS, minor axis GALDIM_MINAXIS, inclination angle GALDIM_ANGLE), and the related bibliographic reference. We can also see the full list of object types attributed to NGC4038 (ex: HI HI (21cm) Source, G Galaxy, GiP Galaxy in Pair, Rad Radio Source…). This comes from the fact that an object can have a lot of descriptions, a galaxy can very well also be a radio source. The descriptions and relations between object types can be explored on Simbad’s webpages.

As we saw that NGC4038 is a galaxy in a pair, let’s search for its linked object: we query sources in a circle of 2 arcmin around NGC4038 of the same object type to find the other galaxy of the pair; then we query sources in the same area with 100% membership probability.

siblings = Simbad.query_criteria("region(circle, NGC4038, 2m)", otype="GiP")
siblings
Table length=2
MAIN_IDRADECRA_PRECDEC_PRECCOO_ERR_MAJACOO_ERR_MINACOO_ERR_ANGLECOO_QUALCOO_WAVELENGTHCOO_BIBCODEOTYPEOTYPESGALDIM_MAJAXISGALDIM_MINAXISGALDIM_ANGLEGALDIM_BIBCODEBIBLIOSCRIPT_NUMBER_ID
"h:m:s""d:m:s"masmasdegarcminarcmindeg
objectstr13str13int16int16float32float32int16str1str1objectobjectobjectfloat32float32int16objectobjectint32
NGC 403812 01 53.002-18 52 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members = Simbad.query_criteria("region(circle, NGC4038, 2m)", membership=100)
members
Table length=4
MAIN_IDRADECRA_PRECDEC_PRECCOO_ERR_MAJACOO_ERR_MINACOO_ERR_ANGLECOO_QUALCOO_WAVELENGTHCOO_BIBCODEOTYPEOTYPESGALDIM_MAJAXISGALDIM_MINAXISGALDIM_ANGLEGALDIM_BIBCODEBIBLIOSCRIPT_NUMBER_ID
"h:m:s""d:m:s"masmasdegarcminarcmindeg
objectstr13str13int16int16float32float32int16str1str1objectobjectobjectfloat32float32int16objectobjectint32
NAME Antennae12 01 53.170-18 52 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[CEB2007] Cluster 312 01 54.56-18 53 04.066----0D2007ApJ...658..319CCluster*NIR|Cl*|Cl*----02010ApJ...710.1746G|2007ApJ...658..319C0
NGC 403812 01 53.002-18 52 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You can learn more on the features of the Simbad python module here: https://astroquery.readthedocs.io/en/latest/simbad/simbad.html

and on the Simbad query criteria: http://simbad.cds.unistra.fr/simbad/sim-fsam

Step #2: Visualise the source on a sky map#

Aladin

We now open the Aladin Lite widget. We set it first to center on the Antennae galaxies, have a field of view of 0.5 \(^\circ\) and show colour images from the Digitized Sky Survey (DSS). Typing aladin in the second line of code tells the notebook to display the widget.

aladin = Aladin(target="Antennae", fov=0.5, survey="P/DSS2/color", height=600)
aladin

As with any Aladin Lite implementation, you can interact with this widget. Try to:

  • scroll with your mouse pointer on the image to zoom in and out,

  • select other image surveys and manage the current view with

  • look at another target using the search field

  • find more information on something with the target tool

  • do a right click to discover more tools

You can also directly change the properties of the variable aladin. For example, to focus on M101 instead of the Antennae galaxies:

aladin.target = "M101"

Feel free to explore other targets and methods available for the Aladin widget.

Step #3: Find and visualize additional data#

Aladin Simbad Vizier

We want to look for data related to HII regions in these interacting galaxies. We make a query in Simbad for HII regions within 14 arcmins around the Antennae galaxies.

table_simbad = Simbad.query_criteria("region(circle, Antennae, 14m)", maintype="HII")
table_simbad
Table length=317
MAIN_IDRADECRA_PRECDEC_PRECCOO_ERR_MAJACOO_ERR_MINACOO_ERR_ANGLECOO_QUALCOO_WAVELENGTHCOO_BIBCODEOTYPEOTYPESGALDIM_MAJAXISGALDIM_MINAXISGALDIM_ANGLEGALDIM_BIBCODEBIBLIOSCRIPT_NUMBER_ID
"h:m:s""d:m:s"masmasdegarcminarcmindeg
objectstr13str13int16int16float32float32int16str1str1objectobjectobjectfloat32float32int16objectobjectint32
RX J120155.4-18520912 01 55.4-18 52 0955----0DHIIRegHII|X----01997ApJ...478..542F|1995MNRAS.277..397R0
RX J120150.8-18522012 01 50.9-18 52 2055----0DHIIRegHII|X----02000AJ....120..670N|1997ApJ...478..542F|1995MNRAS.277..397R0
[MDL92] I12 01 27.29-19 00 54.766----0D2004AJ....127..660SHIIRegHII|*|G----02004AJ....127..660S|2001AJ....122.2969H|1992A&A...256L..19M0
[MDL92] II12 01 27.57-19 01 01.666----0D2004AJ....127..660SHIIRegHII|*|G----02004AJ....127..660S|2001AJ....122.2969H|1992A&A...256L..19M0
[MDL92] III12 01 25.30-19 00 40.366----0D2004AJ....127..660SHIIRegHII|*|G----02004AJ....127..660S|2001AJ....122.2969H|1992A&A...256L..19M0
[ZBF2015] Arp244 112 01 54.60-18 53 03.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.08750.0875902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 212 01 55.70-18 52 42.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0790.079902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 312 01 55.40-18 52 48.566----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05850.0585902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 412 01 54.50-18 51 55.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.08780.0878902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 512 01 53.00-18 52 08.666----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0610.061902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 612 01 55.50-18 52 23.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.07850.0785902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 712 01 50.50-18 52 13.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05850.0585902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 812 01 52.60-18 51 37.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.07070.0707902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZFB2014] HII 912 01 50.50-18 52 21.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04180.0418902014MNRAS.445.1412Z2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1112 01 50.50-18 52 05.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05430.0543902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1212 01 52.20-18 52 20.666----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04250.0425902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1312 01 54.60-18 52 08.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.03350.0335902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1412 01 53.60-18 51 43.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05820.0582902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1512 01 51.90-18 51 38.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.06470.0647902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1612 01 55.20-18 52 29.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.06750.0675902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1712 01 54.10-18 52 03.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05880.0588902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 1912 01 54.20-18 51 42.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.07150.0715902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2012 01 51.00-18 52 31.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04530.0453902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2112 01 55.70-18 52 13.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04470.0447902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2412 01 55.40-18 53 02.066----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05680.0568902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2512 01 50.80-18 52 16.066----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04030.0403902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2612 01 51.00-18 52 24.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04750.0475902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2712 01 52.00-18 52 27.066----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.02850.0285902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2812 01 53.00-18 51 48.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.06180.0618902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 2912 01 51.20-18 51 46.566----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.04780.0478902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 3012 01 54.90-18 52 32.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.03280.0328902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 3212 01 52.30-18 51 55.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0640.064902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 3312 01 52.30-18 52 10.566----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05680.0568902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 3412 01 53.50-18 51 38.066----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05780.0578902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 3612 01 51.10-18 51 58.866----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05650.0565902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 4012 01 52.00-18 51 32.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.050.05902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 4212 01 52.00-18 52 29.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.02630.0263902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 4512 01 55.50-18 52 23.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.05570.0557902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
.........................................................
[ZFB2014] HII 23012 01 55.90-18 52 17.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.02180.0218902014MNRAS.445.1412Z2014MNRAS.445.1412Z0
[ZBF2015] Arp244 23112 01 53.00-18 51 56.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0250.025902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 23512 01 54.30-18 51 48.566----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.02130.0213902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZFB2014] HII 23612 01 52.20-18 52 24.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0140.014902014MNRAS.445.1412Z2014MNRAS.445.1412Z0
[ZBF2015] Arp244 23712 01 54.60-18 52 02.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01880.0188902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 23812 01 55.50-18 52 33.866----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 24312 01 55.70-18 52 07.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01220.0122902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 24412 01 54.10-18 53 06.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01880.0188902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 24512 01 55.20-18 52 18.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 24712 01 54.70-18 52 37.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01070.0107902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 24912 01 53.50-18 53 08.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25112 01 54.20-18 51 49.666----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01880.0188902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25212 01 53.30-18 53 06.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.00930.0093902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25312 01 55.20-18 52 11.066----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25412 01 53.50-18 51 35.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25512 01 54.70-18 52 48.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01570.0157902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25812 01 56.00-18 52 46.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01280.0128902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 25912 01 51.70-18 52 35.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0160.016902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 26012 01 55.40-18 52 49.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01180.0118902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 26212 01 54.60-18 53 07.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01570.0157902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 26412 01 54.10-18 52 02.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01570.0157902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 26712 01 50.70-18 51 58.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01180.0118902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZFB2014] HII 26812 01 54.60-18 52 27.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2014MNRAS.445.1412Z0
[ZBF2015] Arp244 26912 01 54.50-18 52 54.866----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 27112 01 53.60-18 53 11.766----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01570.0157902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 27312 01 53.30-18 52 01.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0140.014902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 27712 01 56.00-18 52 12.466----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01350.0135902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 27812 01 53.40-18 53 03.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 28112 01 52.80-18 52 02.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 28312 01 55.20-18 52 40.366----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 28512 01 55.80-18 52 09.266----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 28712 01 52.60-18 52 15.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.00850.0085902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 28912 01 55.00-18 52 47.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 29212 01 53.40-18 53 05.666----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 29312 01 54.70-18 52 57.166----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.00930.0093902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZFB2014] HII 29412 01 53.60-18 51 49.066----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.01250.0125902014MNRAS.445.1412Z2014MNRAS.445.1412Z0
[ZBF2015] Arp244 29512 01 54.80-18 53 01.966----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.0110.011902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0
[ZBF2015] Arp244 30012 01 54.70-18 52 38.666----0DO2014MNRAS.445.1412ZHIIRegHII|HII0.00930.0093902014MNRAS.445.1412Z2015MNRAS.451.1307Z|2014MNRAS.445.1412Z0

Once we have identified a bibliographic reference of interest, we can search the corresponding catalogs on VizieR. Here, the Biblio column has quite some occurrences of the reference '2015MNRAS.451.1307Z'.

Remember that by default VizieR will only return 50 entries (as in the web interface). To get all sources, set ROW_LIMIT=-1.

A good practice is to check first what data are available by querying only a subsample, then customize your Vizier query with the useful rows and columns before downloading the entire catalog.

cat_viz = Vizier(row_limit=10).get_catalogs("2015MNRAS.451.1307Z")
cat_viz
TableList with 2 tables:
	'0:J/MNRAS/451/1307/HIIreg' with 15 column(s) and 10 row(s) 
	'1:J/MNRAS/451/1307/list' with 13 column(s) and 10 row(s) 

In the example above, we see that 2 tables are associated with the reference 2015MNRAS.451.1307Z: a table called ‘HIIreg’ accessible by the index [0] and a table called ‘list’ accessible by the index [1]. The number of rows has been fixed by the parameter row_limit=10.

Let’s check the ‘HIIreg’ table:

# print the metadata
cat_viz[0].meta
{'ID': 'J_MNRAS_451_1307_HIIreg',
 'name': 'J/MNRAS/451/1307/HIIreg',
 'description': 'Physical properties of the brightest HII regions in interacting galaxies (table A1) and isolated galaxies (table A2)'}
# print the table itself
cat_viz[0]
Table length=10
Seqn_NameNameNfRAJ2000DEJ2000logLHaRlogMHIIrhoHIIsigmaalpVirEWHalogAgeSimbad
log(1e-07W)pclog(solMass)solMass / pc3km / s0.1 nmlog(yr)
int16str3str7int16str10str11float32int16float32float32float32float32float32float32str6
1intNGC2146306 18 39.4+78 21 18.239.0401145.900.127015.040.0159.796.770Simbad
2intNGC2146306 18 38.1+78 21 26.838.8301165.800.097017.060.054.706.810Simbad
3intNGC2146306 18 44.6+78 21 50.638.5901425.800.055011.030.0125.306.780Simbad
4intNGC2146306 18 27.7+78 22 21.038.4701555.810.04108.620.0119.646.780Simbad
5intNGC2146306 18 35.0+78 21 28.038.4401245.650.056015.080.0103.356.790Simbad
6intNGC2146306 18 42.8+78 21 58.138.4101365.700.04704.0--155.866.770Simbad
7intNGC2146306 18 39.8+78 21 22.538.350815.300.096015.0100.0109.476.790Simbad
8intNGC2146306 18 48.0+78 21 43.338.3201445.690.03904.0--81.896.800Simbad
9intNGC2146306 18 42.1+78 21 12.038.310945.400.07304.0--103.956.790Simbad
10intNGC2146306 18 44.2+78 21 00.938.300965.400.07004.0--67.876.800Simbad

As for every function in python, we can call help(Vizier) in a code cell and run it to print the documentation.

help(Vizier)
Help on VizierClass in module astroquery.vizier.core object:

class VizierClass(astroquery.query.BaseQuery)
 |  VizierClass(columns=['*'], column_filters={}, catalog=None, keywords=None, ucd='', timeout=60, vizier_server='vizier.u-strasbg.fr', row_limit=50)
 |  
 |  Method resolution order:
 |      VizierClass
 |      astroquery.query.BaseQuery
 |      builtins.object
 |  
 |  Methods defined here:
 |  
 |  __init__(self, columns=['*'], column_filters={}, catalog=None, keywords=None, ucd='', timeout=60, vizier_server='vizier.u-strasbg.fr', row_limit=50)
 |      Parameters
 |      ----------
 |      columns : list
 |          List of strings
 |      column_filters : dict
 |      catalog : str or None
 |      keywords : str or None
 |      ucd : string
 |          "Unified Content Description" column descriptions.  Specifying
 |          these will select only catalogs that have columns matching the
 |          column descriptions defined on the Vizier web pages.
 |          See http://vizier.u-strasbg.fr/vizier/vizHelp/1.htx#ucd and
 |          http://cds.u-strasbg.fr/w/doc/UCD/
 |      vizier_server : string
 |          Name of the VizieR mirror to use.
 |          (This parameter's default is set from a configuration object.)
 |      timeout : number
 |          timeout for connecting to server
 |          (This parameter's default is set from a configuration object.)
 |      row_limit : int
 |          Maximum number of rows that will be fetched from the result
 |          (set to -1 for unlimited).
 |          (This parameter's default is set from a configuration object.)
 |  
 |  find_catalogs(self, keywords, include_obsolete=False, verbose=False, max_catalogs=None, return_type='votable')
 |      Search Vizier for catalogs based on a set of keywords, e.g. author name
 |      
 |      Parameters
 |      ----------
 |      keywords : list or string
 |          List of keywords, or space-separated set of keywords.
 |          From `Vizier <http://vizier.u-strasbg.fr/doc/asu-summary.htx>`_:
 |          "names or words of title of catalog. The words are and'ed, i.e.
 |          only the catalogues characterized by all the words are selected."
 |      include_obsolete : bool, optional
 |          If set to True, catalogs marked obsolete will also be returned.
 |      max_catalogs : int or None
 |          The maximum number of catalogs to return.  If ``None``, all
 |          catalogs will be returned.
 |      
 |      Returns
 |      -------
 |      resource_dict : dict
 |          Dictionary of the "Resource" name and the VOTable resource object.
 |          "Resources" are generally publications; one publication may contain
 |          many tables.
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.vizier import Vizier
 |      >>> catalog_list = Vizier.find_catalogs('Kang W51')
 |      >>> print(catalog_list)
 |      {u'J/ApJ/706/83': <astropy.io.votable.tree.Resource at 0x108d4d490>,
 |       u'J/ApJS/191/232': <astropy.io.votable.tree.Resource at 0x108d50490>}
 |      >>> print({k:v.description for k,v in catalog_list.items()})
 |      {u'J/ApJ/706/83': u'Embedded YSO candidates in W51 (Kang+, 2009)',
 |       u'J/ApJS/191/232': u'CO survey of W51 molecular cloud (Bieging+, 2010)'}
 |  
 |  get_catalogs(self, *args, **kwargs)
 |      Queries the service and returns a table object.
 |      
 |      Query the Vizier service for a specific catalog
 |      
 |      Parameters
 |      ----------
 |      catalog : str, Resource, or list, optional
 |          The catalog(s) that will be retrieved
 |      
 |      Returns
 |      -------
 |      table : A `~astropy.table.Table` object.
 |  
 |  get_catalogs_async(self, catalog, verbose=False, return_type='votable', get_query_payload=False)
 |      Query the Vizier service for a specific catalog
 |      
 |      Parameters
 |      ----------
 |      catalog : str, Resource, or list, optional
 |          The catalog(s) that will be retrieved
 |      
 |      Returns
 |      -------
 |      response : `~requests.Response`
 |          Returned if asynchronous method used
 |  
 |  query_constraints(self, *args, **kwargs)
 |      Queries the service and returns a table object.
 |      
 |      Send a query to Vizier in which you specify constraints with
 |      keyword/value pairs.
 |      
 |      See `the vizier constraints page
 |      <http://vizier.cfa.harvard.edu/vizier/vizHelp/cst.htx>`_ for details.
 |      
 |      Parameters
 |      ----------
 |      catalog : str or list, optional
 |          The catalog(s) which must be searched for this identifier.
 |          If not specified, all matching catalogs will be searched.
 |      kwargs : dict
 |          Any key/value pairs besides "catalog" will be parsed
 |          as additional column filters.
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.vizier import Vizier
 |      >>> # note that glon/glat constraints here *must* be floats
 |      >>> result = Vizier.query_constraints(catalog='J/ApJ/723/492/table1',
 |      ...                                   GLON='>49.0 & <51.0', GLAT='<0')
 |      >>> result[result.keys()[0]].pprint()
 |          GRSMC      GLON   GLAT   VLSR  ... RD09 _RA.icrs _DE.icrs
 |      ------------- ------ ------ ------ ... ---- -------- --------
 |      G049.49-00.41  49.49  -0.41  56.90 ... RD09   290.95    14.50
 |      G049.39-00.26  49.39  -0.26  50.94 ... RD09   290.77    14.48
 |      G049.44-00.06  49.44  -0.06  62.00 ... RD09   290.61    14.62
 |      G049.04-00.31  49.04  -0.31  66.25 ... RD09   290.64    14.15
 |      G049.74-00.56  49.74  -0.56  67.95 ... RD09   291.21    14.65
 |      G050.39-00.41  50.39  -0.41  41.17 ... RD09   291.39    15.29
 |      G050.24-00.61  50.24  -0.61  41.17 ... RD09   291.50    15.06
 |      G050.94-00.61  50.94  -0.61  40.32 ... RD09   291.85    15.68
 |      G049.99-00.16  49.99  -0.16  46.27 ... RD09   290.97    15.06
 |      G049.44-00.06  49.44  -0.06  46.27 ... RD09   290.61    14.62
 |      G049.54-00.01  49.54  -0.01  56.05 ... RD09   290.61    14.73
 |      G049.74-00.01  49.74  -0.01  48.39 ... RD09   290.71    14.91
 |      G049.54-00.91  49.54  -0.91  43.29 ... RD09   291.43    14.31
 |      G049.04-00.46  49.04  -0.46  58.60 ... RD09   290.78    14.08
 |      G049.09-00.06  49.09  -0.06  46.69 ... RD09   290.44    14.31
 |      G050.84-00.11  50.84  -0.11  50.52 ... RD09   291.34    15.83
 |      G050.89-00.11  50.89  -0.11  59.45 ... RD09   291.37    15.87
 |      G050.44-00.41  50.44  -0.41  64.12 ... RD09   291.42    15.34
 |      G050.84-00.76  50.84  -0.76  61.15 ... RD09   291.94    15.52
 |      G050.29-00.46  50.29  -0.46  14.81 ... RD09   291.39    15.18
 |      
 |      Returns
 |      -------
 |      table : A `~astropy.table.Table` object.
 |  
 |  query_constraints_async(self, catalog=None, return_type='votable', cache=True, get_query_payload=False, **kwargs)
 |      Send a query to Vizier in which you specify constraints with
 |      keyword/value pairs.
 |      
 |      See `the vizier constraints page
 |      <http://vizier.cfa.harvard.edu/vizier/vizHelp/cst.htx>`_ for details.
 |      
 |      Parameters
 |      ----------
 |      catalog : str or list, optional
 |          The catalog(s) which must be searched for this identifier.
 |          If not specified, all matching catalogs will be searched.
 |      kwargs : dict
 |          Any key/value pairs besides "catalog" will be parsed
 |          as additional column filters.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |          The response of the HTTP request.
 |      
 |      Examples
 |      --------
 |      >>> from astroquery.vizier import Vizier
 |      >>> # note that glon/glat constraints here *must* be floats
 |      >>> result = Vizier.query_constraints(catalog='J/ApJ/723/492/table1',
 |      ...                                   GLON='>49.0 & <51.0', GLAT='<0')
 |      >>> result[result.keys()[0]].pprint()
 |          GRSMC      GLON   GLAT   VLSR  ... RD09 _RA.icrs _DE.icrs
 |      ------------- ------ ------ ------ ... ---- -------- --------
 |      G049.49-00.41  49.49  -0.41  56.90 ... RD09   290.95    14.50
 |      G049.39-00.26  49.39  -0.26  50.94 ... RD09   290.77    14.48
 |      G049.44-00.06  49.44  -0.06  62.00 ... RD09   290.61    14.62
 |      G049.04-00.31  49.04  -0.31  66.25 ... RD09   290.64    14.15
 |      G049.74-00.56  49.74  -0.56  67.95 ... RD09   291.21    14.65
 |      G050.39-00.41  50.39  -0.41  41.17 ... RD09   291.39    15.29
 |      G050.24-00.61  50.24  -0.61  41.17 ... RD09   291.50    15.06
 |      G050.94-00.61  50.94  -0.61  40.32 ... RD09   291.85    15.68
 |      G049.99-00.16  49.99  -0.16  46.27 ... RD09   290.97    15.06
 |      G049.44-00.06  49.44  -0.06  46.27 ... RD09   290.61    14.62
 |      G049.54-00.01  49.54  -0.01  56.05 ... RD09   290.61    14.73
 |      G049.74-00.01  49.74  -0.01  48.39 ... RD09   290.71    14.91
 |      G049.54-00.91  49.54  -0.91  43.29 ... RD09   291.43    14.31
 |      G049.04-00.46  49.04  -0.46  58.60 ... RD09   290.78    14.08
 |      G049.09-00.06  49.09  -0.06  46.69 ... RD09   290.44    14.31
 |      G050.84-00.11  50.84  -0.11  50.52 ... RD09   291.34    15.83
 |      G050.89-00.11  50.89  -0.11  59.45 ... RD09   291.37    15.87
 |      G050.44-00.41  50.44  -0.41  64.12 ... RD09   291.42    15.34
 |      G050.84-00.76  50.84  -0.76  61.15 ... RD09   291.94    15.52
 |      G050.29-00.46  50.29  -0.46  14.81 ... RD09   291.39    15.18
 |  
 |  query_object(self, *args, **kwargs)
 |      Queries the service and returns a table object.
 |      
 |      Serves the same purpose as `query_object` but only
 |      returns the HTTP response rather than the parsed result.
 |      
 |      Parameters
 |      ----------
 |      object_name : str
 |          The name of the identifier.
 |      catalog : str or list, optional
 |          The catalog(s) which must be searched for this identifier.
 |          If not specified, all matching catalogs will be searched.
 |      radius : `~astropy.units.Quantity` or None
 |          A degree-equivalent radius (optional).
 |      coordinate_system : str or None
 |          If the object name is given as a coordinate, you *should* use
 |          `~astroquery.vizier.VizierClass.query_region`, but you can
 |          specify a coordinate frame here instead (today, J2000, B1975,
 |          B1950, B1900, B1875, B1855, Galactic, Supergal., Ecl.J2000, )
 |      
 |      
 |      Returns
 |      -------
 |      table : A `~astropy.table.Table` object.
 |  
 |  query_object_async(self, object_name, catalog=None, radius=None, coordinate_frame=None, get_query_payload=False, return_type='votable', cache=True)
 |      Serves the same purpose as `query_object` but only
 |      returns the HTTP response rather than the parsed result.
 |      
 |      Parameters
 |      ----------
 |      object_name : str
 |          The name of the identifier.
 |      catalog : str or list, optional
 |          The catalog(s) which must be searched for this identifier.
 |          If not specified, all matching catalogs will be searched.
 |      radius : `~astropy.units.Quantity` or None
 |          A degree-equivalent radius (optional).
 |      coordinate_system : str or None
 |          If the object name is given as a coordinate, you *should* use
 |          `~astroquery.vizier.VizierClass.query_region`, but you can
 |          specify a coordinate frame here instead (today, J2000, B1975,
 |          B1950, B1900, B1875, B1855, Galactic, Supergal., Ecl.J2000, )
 |      
 |      Returns
 |      -------
 |      response : `~requests.Response`
 |          The response of the HTTP request.
 |  
 |  query_region(self, *args, **kwargs)
 |      Queries the service and returns a table object.
 |      
 |      Serves the same purpose as `query_region` but only
 |      returns the HTTP response rather than the parsed result.
 |      
 |      Parameters
 |      ----------
 |      coordinates : str, `astropy.coordinates` object, or `~astropy.table.Table`
 |          The target around which to search. It may be specified as a
 |          string in which case it is resolved using online services or as
 |          the appropriate `astropy.coordinates` object. ICRS coordinates
 |          may also be entered as a string.  If a table is used, each of
 |          its rows will be queried, as long as it contains two columns
 |          named ``_RAJ2000`` and ``_DEJ2000`` with proper angular units.
 |      radius : convertible to `~astropy.coordinates.Angle`
 |          The radius of the circular region to query.
 |      inner_radius : convertible to `~astropy.coordinates.Angle`
 |          When set in addition to ``radius``, the queried region becomes
 |          annular, with outer radius ``radius`` and inner radius
 |          ``inner_radius``.
 |      width : convertible to `~astropy.coordinates.Angle`
 |          The width of the square region to query.
 |      height : convertible to `~astropy.coordinates.Angle`
 |          When set in addition to ``width``, the queried region becomes
 |          rectangular, with the specified ``width`` and ``height``.
 |      catalog : str or list, optional
 |          The catalog(s) which must be searched for this identifier.
 |          If not specified, all matching catalogs will be searched.
 |      column_filters: dict, optional
 |          Constraints on columns of the result. The dictionary contains
 |          the column name as keys, and the constraints as values.
 |      frame : str, optional
 |          The frame to use for the request. It should be 'fk5', 'icrs',
 |          or 'galactic'. This choice influences the the orientation of
 |          box requests.
 |      
 |      
 |      Returns
 |      -------
 |      table : A `~astropy.table.Table` object.
 |  
 |  query_region_async(self, coordinates, radius=None, inner_radius=None, width=None, height=None, catalog=None, get_query_payload=False, cache=True, return_type='votable', column_filters={}, frame='fk5')
 |      Serves the same purpose as `query_region` but only
 |      returns the HTTP response rather than the parsed result.
 |      
 |      Parameters
 |      ----------
 |      coordinates : str, `astropy.coordinates` object, or `~astropy.table.Table`
 |          The target around which to search. It may be specified as a
 |          string in which case it is resolved using online services or as
 |          the appropriate `astropy.coordinates` object. ICRS coordinates
 |          may also be entered as a string.  If a table is used, each of
 |          its rows will be queried, as long as it contains two columns
 |          named ``_RAJ2000`` and ``_DEJ2000`` with proper angular units.
 |      radius : convertible to `~astropy.coordinates.Angle`
 |          The radius of the circular region to query.
 |      inner_radius : convertible to `~astropy.coordinates.Angle`
 |          When set in addition to ``radius``, the queried region becomes
 |          annular, with outer radius ``radius`` and inner radius
 |          ``inner_radius``.
 |      width : convertible to `~astropy.coordinates.Angle`
 |          The width of the square region to query.
 |      height : convertible to `~astropy.coordinates.Angle`
 |          When set in addition to ``width``, the queried region becomes
 |          rectangular, with the specified ``width`` and ``height``.
 |      catalog : str or list, optional
 |          The catalog(s) which must be searched for this identifier.
 |          If not specified, all matching catalogs will be searched.
 |      column_filters: dict, optional
 |          Constraints on columns of the result. The dictionary contains
 |          the column name as keys, and the constraints as values.
 |      frame : str, optional
 |          The frame to use for the request. It should be 'fk5', 'icrs',
 |          or 'galactic'. This choice influences the the orientation of
 |          box requests.
 |      
 |      Returns
 |      -------
 |      response : `requests.Response`
 |          The response of the HTTP request.
 |  
 |  ----------------------------------------------------------------------
 |  Readonly properties defined here:
 |  
 |  valid_keywords
 |  
 |  ----------------------------------------------------------------------
 |  Data descriptors defined here:
 |  
 |  catalog
 |      The default catalog to search.  If left empty, will search all
 |      catalogs.
 |  
 |  column_filters
 |      Filters to run on the individual columns. See the Vizier website
 |      for details.
 |  
 |  columns
 |      Columns to include.  The special keyword 'all' will return ALL
 |      columns from ALL retrieved tables.
 |  
 |  keywords
 |      The set of keywords to filter the Vizier search
 |  
 |  ucd
 |      UCD criteria: see http://vizier.u-strasbg.fr/vizier/vizHelp/1.htx#ucd
 |      
 |      Examples
 |      --------
 |      >>> Vizier.ucd = '(spect.dopplerVeloc*|phys.veloc*)'
 |  
 |  ----------------------------------------------------------------------
 |  Data and other attributes defined here:
 |  
 |  __abstractmethods__ = frozenset()
 |  
 |  ----------------------------------------------------------------------
 |  Methods inherited from astroquery.query.BaseQuery:
 |  
 |  __call__(self, *args, **kwargs)
 |      init a fresh copy of self
 |  
 |  ----------------------------------------------------------------------
 |  Data descriptors inherited from astroquery.query.BaseQuery:
 |  
 |  __dict__
 |      dictionary for instance variables (if defined)
 |  
 |  __weakref__
 |      list of weak references to the object (if defined)

Here we learn that columns should be a list, column_filters a dictionary, and row_limits is an int for which -1 means infinity. Now we can customize our VizieR query by selecting columns, filtering over the interacting galaxies (n_Name='int'), and keeping only the first region for each galaxy (Seq=1, for visualization purposes).

cat_hii = Vizier(
    columns=["Name", "RAJ2000", "DEJ2000", "logLHa", "R", "sigma"],
    column_filters={"Seq": "==1", "n_Name": "int"},
    row_limit=-1,
).get_catalogs("2015MNRAS.451.1307Z")[0]
cat_hii
Table length=12
NameRAJ2000DEJ2000logLHaRsigma
log(1e-07W)pckm / s
str7str10str11float32int16float32
NGC214606 18 39.4+78 21 18.239.04011415.0
Arp24412 01 54.6-18 53 03.140.20028032.8
NGC52001 24 33.3+03 48 04.639.12025514.1
UGC399507 44 09.2+29 14 51.340.29027043.0
NGC378811 39 41.4+31 54 23.339.70028011.9
NGC378611 39 45.1+31 55 46.339.86030016.5
NGC278209 14 05.3+40 06 50.439.80016628.0
NGC299309 45 48.3-14 22 05.940.07025812.0
NGC299209 45 41.9-14 19 33.439.18010016.0
NGC399111 57 31.7+32 20 29.640.44047020.9
Arp27010 49 55.8+32 59 28.040.22022920.4
NGC376911 37 43.7+47 53 24.438.310664.0

We can also display the table on Aladin. This should work by simply typing aladin.add_table(cat_hii) but if you get errors in the format of some columns, you can just send the name and coordinates to Aladin:

aladin.add_table(cat_hii["Name", "RAJ2000", "DEJ2000"])

Go up to the Aladin Lite widget, zoom out to see all the sources, then rotate and zoom in to see the interacting galaxies. You can click on one source to display the information in the table.

Change the view to the AllWISE Infrared survey, either in the widget:

Base image layer -> The Wide-field Infrared Survey Explorer

or in the command line below.

You can find the list of available sky maps at https://aladin.u-strasbg.fr/hips/list

aladin.survey = "P/allWISE/color"

If you want to overlay the survey instead of replacing it:

aladin.overlay_survey= 'P/allWISE/color'

aladin.overlay_survey_opacity = 0.5

Exercise:

Retrieve the second table from Zaragoza-Cardiel+, 2015 (2015MNRAS.451.1307Z) containing data related to the image fits files and try to answer the questions:

  • What are the typical sizes of the fits images?

  • What is the approximate resolution of the images? [arcsec/pix]

# write your code here

Step #5: Cross-match tables#

Vizier Xmatch

We have HII data for a sample of interacting galaxies. Since we are also interested in the infrared fluxes we search for the Wide-field Infrared Survey Explorer (AllWISE) data release.

We want to match the sources in J/MNRAS/451/1307/HIIreg with the AllWISE source catalog that contains 747 million objects!

We use the X-Match python module for cross-identification of objects. It is particularly efficient and fast with very large catalogs, like AllWISE. All we need are the names of the catalogs, the names of the columns containing the coordinates of the sources, and the desired maximum distance for the match (optionally the area as well, otherwise all-sky is the default).

# What is the AllWISE catalogue reference in VizieR?
cat_allwise = Vizier.get_catalogs("AllWISE")
cat_allwise
TableList with 1 tables:
	'0:II/328/allwise' with 28 column(s) and 50 row(s) 
xmatch_zbf_wise = XMatch.query(
    cat1="vizier:J/MNRAS/451/1307/HIIreg",
    cat2="vizier:II/328/allwise",
    max_distance=10 * u.arcsec,
    colRA1="RAJ2000",
    colDec1="DEJ2000",
    colRA2="RAJ2000",
    colDec2="DEJ2000",
)
xmatch_zbf_wise
Table length=1314
angDist_RAJ2000_DEJ2000recnoSeqn_NameNameNfRAJ2000_1DEJ2000_1logLHaRlogMHIIrhoHIIsigmaalpVirEWHalogAgeSimbadAllWISERAJ2000_2DEJ2000_2eeMajeeMineePAW1magW2magW3magW4magJmagHmagKmage_W1mage_W2mage_W3mage_W4mage_Jmage_Hmage_KmagIDccfexvarqphpmRAe_pmRApmDEe_pmDEd2M
float64float64float64int64int64str3str7int64str10str11float64int64float64float64float64float64float64float64str6str19float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64float64int64str4int64str4str4int64int64int64int64float64
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3.96280340.896251.375806186128isoNGC1073002 43 35.1+01 22 32.937.55514.60.0764.0--403.46.72SimbadJ024335.06+012236.840.89611451.37689840.07770.0726113.514.66514.54710.1167.751------0.0320.0590.070.201------40810150135102865900003nnnnAAAB519113184115--
...................................................................................................................................................
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5.037162262.41575.699917176045isoNGC6412017 29 39.6+75 41 59.738.181405.60.0344.0--28.056.83SimbadJ172940.66+754202.8262.419441375.70078560.04510.0442119.913.35413.2569.2267.002------0.0260.0280.0310.077------2613175701351028326000033111AAAA77043-48544--
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2.988374262.39041775.7145176550isoNGC6412017 29 33.7+75 42 52.238.09905.30.064.0--231.76.76SimbadJ172934.49+754251.7262.393747175.71438230.04070.040196.213.35813.1718.816.27916.86215.92315.3850.0240.0280.0240.0480.1960.1960.2212613175701351028243000031000AAAA0410412.868
5.552158262.42575.700083176651isoNGC6412017 29 42.0+75 42 00.338.021705.70.0214.0--37.146.82SimbadJ172940.66+754202.8262.419441375.70078560.04510.0442119.913.35413.2569.2267.002------0.0260.0280.0310.077------2613175701351028326000033111AAAA77043-48544--
1.626631262.38575.699611176853isoNGC6412017 29 32.4+75 41 58.638.01105.40.044.0--58.136.8SimbadJ172932.06+754159.6262.383599275.69990160.05610.0511146.413.82913.7129.4147.001------0.030.0320.0340.089------2613175701351028261000032100AAAA052054--
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8.06568262.372575.704583177257isoNGC6412017 29 29.4+75 42 16.537.951305.50.0284.0--34.996.82SimbadJ172930.59+754209.7262.377476875.70270970.04910.0482111.813.76813.7289.5577.203------0.0280.0310.0330.086------2613175701351028264000031122AAAA051053--
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2.033969262.3637575.690222178369isoNGC6412017 29 27.3+75 41 24.837.6604.80.064.0--1.187.29SimbadJ172927.37+754122.7262.364050775.68966190.04030.037477.512.0512.09712.9179.36912.5212.17712.1070.0230.021----0.0220.0190.02526131757013510282120000211nnAAUU-483426340.157
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2.461872262.36458375.690333178975isoNGC6412017 29 27.5+75 41 25.237.541005.10.0264.0--1.637.24SimbadJ172927.37+754122.7262.364050775.68966190.04030.037477.512.0512.09712.9179.36912.5212.17712.1070.0230.021----0.0220.0190.02526131757013510282120000211nnAAUU-483426340.157
6.919677262.36458375.690333178975isoNGC6412017 29 27.5+75 41 25.237.541005.10.0264.0--1.637.24SimbadJ172925.67+754123.7262.356990375.68991730.32680.1897101.416.10416.51812.6199.184------0.1260.248----------2613175701351029820000023nnnBBUU-253460362559--
9.385763262.39916775.702444179177isoNGC6412017 29 35.8+75 42 08.837.471005.00.0274.0--10.67.06SimbadJ172937.39+754216.1262.40579375.70447380.03360.03378.611.65611.6368.1195.81514.42413.63913.5060.0220.0220.0190.0370.0820.0940.0862613175701351028211000054200AAAA0300300.861
2.430664262.3637575.690333179278isoNGC6412017 29 27.3+75 41 25.237.3804.80.034.0--1.437.25SimbadJ172927.37+754122.7262.364050775.68966190.04030.037477.512.0512.09712.9179.36912.5212.17712.1070.0230.021----0.0220.0190.02526131757013510282120000211nnAAUU-483426340.157
6.198088262.3637575.690333179278isoNGC6412017 29 27.3+75 41 25.237.3804.80.034.0--1.437.25SimbadJ172925.67+754123.7262.356990375.68991730.32680.1897101.416.10416.51812.6199.184------0.1260.248----------2613175701351029820000023nnnBBUU-253460362559--
2.619531262.36416775.690389179480isoNGC6412017 29 27.4+75 41 25.436.9604.40.034.0--3.337.12SimbadJ172927.37+754122.7262.364050775.68966190.04030.037477.512.0512.09712.9179.36912.5212.17712.1070.0230.021----0.0220.0190.02526131757013510282120000211nnAAUU-483426340.157
6.607669262.36416775.690389179480isoNGC6412017 29 27.4+75 41 25.436.9604.40.034.0--3.337.12SimbadJ172925.67+754123.7262.356990375.68991730.32680.1897101.416.10416.51812.6199.184------0.1260.248----------2613175701351029820000023nnnBBUU-253460362559--
5.639364250.7637536.83472217951isoNGC6207016 43 03.3+36 50 05.039.511546.330.1418.027.068.46.8SimbadJ164303.76+365003.8250.765668636.83441250.02120.0201135.010.79211.247.0284.23212.86612.60312.5230.030.0190.0130.0210.0430.0560.0582499136301351044679hd003n9n3AAAA-92925-1205260.458
7.969164250.7637536.83472217951isoNGC6207016 43 03.3+36 50 05.039.511546.330.1418.027.068.46.8SimbadJ164303.79+364959.7250.765819936.83325380.03790.0338158.610.95310.9367.7585.483------0.0230.0220.0240.066------2499136301351044647d0d053200AAAA1133148432--
7.499991250.76458336.83630617962isoNGC6207016 43 03.5+36 50 10.739.361316.150.14813.921.0138.946.78SimbadJ164303.76+365003.8250.765668636.83441250.02120.0201135.010.79211.247.0284.23212.86612.60312.5230.030.0190.0130.0210.0430.0560.0582499136301351044679hd003n9n3AAAA-92925-1205260.458
3.3028250.77536.84236117973isoNGC6207016 43 06.0+36 50 32.538.881385.940.0796.07.0264.236.75SimbadJ164305.83+365029.8250.774321736.84162140.03740.036967.012.8712.9188.295.588------0.0730.0250.0220.037------2499136301351044678000033000AAAA104035942--
2.552215250.77458336.840944180612isoNGC6207016 43 05.9+36 50 27.438.26725.20.14.0--264.146.75SimbadJ164305.83+365029.8250.774321736.84162140.03740.036967.012.8712.9188.295.588------0.0730.0250.0220.037------2499136301351044678000033000AAAA104035942--
7.317245250.76458336.83625181724isoNGC6207016 43 03.5+36 50 10.537.73724.90.0564.0--200.196.76SimbadJ164303.76+365003.8250.765668636.83441250.02120.0201135.010.79211.247.0284.23212.86612.60312.5230.030.0190.0130.0210.0430.0560.0582499136301351044679hd003n9n3AAAA-92925-1205260.458

This is the end of the tutorial.

Try to apply what you have learned here to your data sets and science cases!