Notebooks/Using_astroquery.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K Using astroquery"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Astroquery: part of astropy : https://astroquery.readthedocs.io/en/latest/index.html\n",
    "\n",
    "astroquery: An Astronomical Web-querying Package in Python \n",
    "Ginsburg, A., Sipocz, B. M., Brasseur, C. E., Cowperthwaite, P. S., Craig, M. W., Deil, C., Guillochon, J., Guzman, G., Liedtke, S., Lian Lim, P., Lockhart, K. E., Mommert, M., Morris, B. M., Norman, H., Parikh, M., Persson, M. V., Robitaille, T. P., Segovia, J.-C., Singer, L. P., Tollerud, E. J., de Val-Borro, M., Valtchanov, I., Woillez, J., Astroquery Collaboration, & a subset of astropy Collaboration\n",
    "2019, Astronomical Journal, 157, 98\n",
    "\n",
    "ABSTRACT: astroquery is a collection of tools for requesting data from databases hosted on remote servers with interfaces exposed on the internet, including those with web pages but without formal application program interfaces. These tools are built on the Python requests package, which is used to make HTTP requests, and astropy, which provides most of the data parsing functionality. astroquery modules generally attempt to replicate the web page interface provided by a given service as closely as possible, making the transition from browser-based to command-line interaction easy. astroquery has received significant contributions from throughout the astronomical community, including several from telescope archives. astroquery enables the creation of fully reproducible workflows from data acquisition through publication. This paper describes the philosophy, basic structure, and development model of the astroquery package. The complete documentation for astroquery can be found at <A href=\"http://astroquery.readthedocs.io/\">http://astroquery.readthedocs.io/</A>.\n",
    "ADS URL : https://ui.adsabs.harvard.edu/abs/2019AJ....157...98G\n",
    "\n",
    "* Some examples of Astroquery uses:\n",
    " * part of astroquery: TAP/TAP+: https://astroquery.readthedocs.io/en/latest/utils/tap.html\n",
    " * Gaia TAP+: https://astroquery.readthedocs.io/en/latest/gaia/gaia.html\n",
    " * Atomic line list: https://astroquery.readthedocs.io/en/latest/atomic/atomic.html\n",
    " * Simbad: https://astroquery.readthedocs.io/en/latest/simbad/simbad.html\n",
    " * Vizier: https://astroquery.readthedocs.io/en/latest/vizier/vizier.html\n",
    " * This lecture explains step by step how to extract information from the Gaia database: https://allendowney.github.io/AstronomicalData/\n",
    " \n",
    "* Talk on astroquery from ADASS XXX conference : https://www.youtube.com/watch?v=FcLvhgSHLl0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Querying Vizier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "try:\n",
    "    from astroquery.vizier import Vizier\n",
    "except:\n",
    "    !pip install astroquery\n",
    "    from astroquery.vizier import Vizier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: UnitsWarning: Unit 'Sun' not supported by the VOUnit standard. Did you mean uN? [astropy.units.format.vounit]\n",
      "WARNING: UnitsWarning: The unit 'ct' has been deprecated in the VOUnit standard. [astropy.units.format.utils]\n"
     ]
    }
   ],
   "source": [
    "catalog_list = Vizier.find_catalogs('Kang W51')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('J/ApJ/684/1143', </>),\n",
       "             ('J/ApJ/736/87', </>),\n",
       "             ('J/ApJ/738/79', </>),\n",
       "             ('J/ApJ/760/12', </>),\n",
       "             ('J/ApJ/785/119', </>),\n",
       "             ('J/ApJ/813/39', </>),\n",
       "             ('J/ApJ/839/12', </>),\n",
       "             ('J/ApJ/859/4', </>),\n",
       "             ('J/ApJ/879/10', </>),\n",
       "             ('J/ApJ/886/75', </>),\n",
       "             ('J/ApJ/886/93', </>),\n",
       "             ('J/ApJ/887/134', </>),\n",
       "             ('J/ApJ/889/L34', </>),\n",
       "             ('J/ApJ/892/93', </>),\n",
       "             ('J/ApJ/902/104', </>),\n",
       "             ('J/ApJS/165/360', </>),\n",
       "             ('J/ApJS/191/232', </>),\n",
       "             ('J/ApJS/236/51', </>),\n",
       "             ('J/ApJS/238/29', </>),\n",
       "             ('J/ApJS/249/33', </>),\n",
       "             ('J/ApJS/258/40', </>),\n",
       "             ('J/A+A/454/717', </>),\n",
       "             ('J/A+A/548/A29', </>),\n",
       "             ('J/A+A/563/A120', </>),\n",
       "             ('J/A+A/578/A51', </>),\n",
       "             ('J/A+A/622/A81', </>),\n",
       "             ('J/A+A/642/A85', </>),\n",
       "             ('J/A+A/647/A78', </>),\n",
       "             ('J/A+A/651/A74', </>),\n",
       "             ('J/AJ/127/539', </>),\n",
       "             ('J/AJ/128/846', </>),\n",
       "             ('J/AJ/144/35', </>),\n",
       "             ('J/AJ/144/150', </>),\n",
       "             ('J/AJ/145/167', </>),\n",
       "             ('J/AJ/149/59', </>),\n",
       "             ('J/AJ/150/1', </>),\n",
       "             ('J/MNRAS/310/982', </>),\n",
       "             ('J/MNRAS/359/865', </>),\n",
       "             ('J/MNRAS/385/2225', </>),\n",
       "             ('J/MNRAS/401/160', </>),\n",
       "             ('J/MNRAS/439/611', </>),\n",
       "             ('J/MNRAS/485/2895', </>)])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "catalog_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TableList with 1 tables:\n",
      "\t'0:J/ApJ/706/83/ysos' with 22 column(s) and 737 row(s) \n"
     ]
    }
   ],
   "source": [
    "catalogs = Vizier.get_catalogs('J/ApJ/706/83/ysos')\n",
    "print(catalogs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "TableList with 1 tables:\n",
      "\t'0:J/ApJ/706/83/ysos' with 22 column(s) and 737 row(s) \n"
     ]
    }
   ],
   "source": [
    "Vizier.ROW_LIMIT = -1\n",
    "catalogs = Vizier.get_catalogs('J/ApJ/706/83/ysos')\n",
    "print(catalogs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "Table = catalogs['J/ApJ/706/83/ysos']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "astropy.table.table.Table"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(Table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Seq f_Seq      SSTGLMC       AV   Mstar  ...  A  _2M Simbad  _Glon    _Glat  \n",
      "                            mag  solMass ...                  deg      deg   \n",
      "--- ----- ----------------- ---- ------- ... --- --- ------ -------- --------\n",
      "  1       G048.7567-00.6341  4.0     3.0 ...   F  2M Simbad  48.7567  -0.6341\n",
      "  2       G048.7579-00.2797  1.6     2.7 ...   F  2M Simbad  48.7579  -0.2797\n",
      "  3       G048.7605-00.0388 33.3     4.1 ...   W  2M Simbad  48.7605  -0.0388\n",
      "  4       G048.7618+00.0627 51.8     4.0 ...   W  2M Simbad  48.7618   0.0627\n",
      "  5       G048.7637+00.2022 25.7     3.5 ...   W  2M Simbad  48.7637   0.2022\n",
      "  6       G048.7655+00.1017  3.0     3.2 ...   F  2M Simbad  48.7655   0.1017\n",
      "...   ...               ...  ...     ... ... ... ...    ...      ...      ...\n",
      "731       G049.9937+00.0231  6.4     3.2 ...   F  2M Simbad  49.9937   0.0231\n",
      "732       G049.9952-00.0063 12.5     4.9 ...   W  2M Simbad  49.9952  -0.0063\n",
      "733       G049.9972+00.2599 33.6     5.6 ...   W  2M Simbad  49.9972   0.2599\n",
      "734       G049.9973+00.2605 17.3    10.1 ...   W  2M Simbad  49.9973   0.2605\n",
      "735       G049.9973+00.2630  8.4     5.2 ...   F  2M Simbad  49.9973   0.2630\n",
      "736       G049.9977-00.1261 11.3     8.3 ...   W  2M Simbad  49.9977  -0.1261\n",
      "737       G049.9982-00.1303 25.9     8.1 ...   W  2M Simbad  49.9982  -0.1303\n",
      "Length = 737 rows\n"
     ]
    }
   ],
   "source": [
    "print(Table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Seq', 'f_Seq', 'SSTGLMC', 'AV', 'Mstar', 'Ltot', 'Stg', 'Cl1', 'Cl2', 'Jmag', 'Hmag', 'Ksmag', '__3.6_', '__4.5_', '__5.8_', '__8.0_', '__24_', 'A', '_2M', 'Simbad', '_Glon', '_Glat']\n"
     ]
    }
   ],
   "source": [
    "print(Table.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, ax = plt.subplots()\n",
    "ax.scatter(Table['Jmag'] - Table['Hmag'], Table['Jmag'], c=Table['Mstar']);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Querying MAST\n",
    "\n",
    "https://archive.stsci.edu/access-mast-data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astroquery.mast import Catalogs, Observations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "obs_table = Observations.query_object(\"IC 418\",radius=\".02 deg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "obs_table.show_in_browser(jsviewer=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask_spectrum = obs_table['dataproduct_type'] == 'spectrum'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "203 82\n"
     ]
    }
   ],
   "source": [
    "print(len(obs_table), mask_spectrum.sum())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_products_by_obs = Observations.get_product_list(obs_table[mask_spectrum][0:2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_products_by_obs.show_in_browser(jsviewer=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:IUE/url/pub/iue/data/lwr/02000/lwr02252.mxlo.gz to ./mastDownload/IUE/lwr02252/lwr02252.mxlo.gz ... [Done]\n",
      "Downloading URL https://mast.stsci.edu/api/v0.1/Download/file?uri=mast:IUE/url/pub/vospectra/iue2/lwr02252mxlo_vo.fits to ./mastDownload/IUE/lwr02252/lwr02252mxlo_vo.fits ... [Done]\n"
     ]
    }
   ],
   "source": [
    "obs1 = Observations.download_products('295913', productType=\"SCIENCE\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table length=2</i>\n",
       "<table id=\"table140236292786928\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>Local Path</th><th>Status</th><th>Message</th><th>URL</th></tr></thead>\n",
       "<thead><tr><th>str48</th><th>str8</th><th>object</th><th>object</th></tr></thead>\n",
       "<tr><td>./mastDownload/IUE/lwr02252/lwr02252.mxlo.gz</td><td>COMPLETE</td><td>None</td><td>None</td></tr>\n",
       "<tr><td>./mastDownload/IUE/lwr02252/lwr02252mxlo_vo.fits</td><td>COMPLETE</td><td>None</td><td>None</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=2>\n",
       "                   Local Path                     Status  Message  URL  \n",
       "                     str48                         str8    object object\n",
       "------------------------------------------------ -------- ------- ------\n",
       "    ./mastDownload/IUE/lwr02252/lwr02252.mxlo.gz COMPLETE    None   None\n",
       "./mastDownload/IUE/lwr02252/lwr02252mxlo_vo.fits COMPLETE    None   None"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obs1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Catalogs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "catalog_data = Catalogs.query_object(\"IC 418\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div><i>Table masked=True length=2602</i>\n",
       "<table id=\"table140236292776192\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>MatchID</th><th>Distance</th><th>MatchRA</th><th>MatchDec</th><th>DSigma</th><th>AbsCorr</th><th>NumFilters</th><th>NumVisits</th><th>NumImages</th><th>StartTime</th><th>StopTime</th><th>StartMJD</th><th>StopMJD</th><th>TargetName</th><th>CI</th><th>CI_Sigma</th><th>KronRadius</th><th>KronRadius_Sigma</th><th>Extinction</th><th>SpectrumFlag</th><th>W2_F502N</th><th>W2_F502N_MAD</th><th>W2_F502N_N</th><th>W2_F555W</th><th>W2_F555W_MAD</th><th>W2_F555W_N</th><th>W2_F606W</th><th>W2_F606W_MAD</th><th>W2_F606W_N</th><th>W2_F656N</th><th>W2_F656N_MAD</th><th>W2_F656N_N</th><th>W2_F658N</th><th>W2_F658N_MAD</th><th>W2_F658N_N</th></tr></thead>\n",
       "<thead><tr><th>str9</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str1</th><th>int64</th><th>int64</th><th>int64</th><th>str21</th><th>str21</th><th>float64</th><th>float64</th><th>str10</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>str1</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>int64</th><th>float64</th><th>float64</th><th>int64</th></tr></thead>\n",
       "<tr><td>90374054</td><td>0.00565599521966206</td><td>81.86755647816761</td><td>-12.697274723428315</td><td>140.12916369880315</td><td>Y</td><td>3</td><td>2</td><td>5</td><td>/Date(937279573430)/</td><td>/Date(1189379756870)/</td><td>51435.14321097685</td><td>54352.969408194534</td><td>IC418</td><td>2.7597674796916367</td><td>0.7014744682366316</td><td>0.45499999999999996</td><td>0.0</td><td>0.2232816070318222</td><td>N</td><td>11.487844467163086</td><td>0.7058448791503906</td><td>2</td><td>13.508299827575684</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>11.417695045471191</td><td>0.3621950149536133</td><td>2</td></tr>\n",
       "<tr><td>59074158</td><td>0.011870704932628309</td><td>81.8675081</td><td>-12.6970878</td><td>0.0</td><td>N</td><td>1</td><td>1</td><td>1</td><td>/Date(919163413257)/</td><td>/Date(919165173380)/</td><td>51225.46543117147</td><td>51225.48580298154</td><td>PK215-24D1</td><td>1.3282477315459005</td><td>0.0</td><td>0.45499999999999996</td><td>0.0</td><td>0.2232816070318222</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>11.700789451599121</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>85650262</td><td>0.012636542260362472</td><td>81.867462</td><td>-12.697490600000002</td><td>0.0</td><td>N</td><td>1</td><td>1</td><td>1</td><td>/Date(919163413257)/</td><td>/Date(919165173380)/</td><td>51225.46543117147</td><td>51225.48580298154</td><td>PK215-24D1</td><td>3.672507594359245</td><td>0.0</td><td>0.45499999999999996</td><td>0.0</td><td>0.2232816070318222</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>13.073589324951172</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>49514032</td><td>0.013779232245273892</td><td>81.8673507</td><td>-12.6970766</td><td>0.0</td><td>N</td><td>1</td><td>1</td><td>1</td><td>/Date(1002132615097)/</td><td>/Date(1002133515093)/</td><td>52185.75711911125</td><td>52185.76753574284</td><td>IC418</td><td>2.0561933157307144</td><td>0.0</td><td>0.45499999999999996</td><td>0.0</td><td>0.2232816070318222</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>12.264599800109863</td><td>0.0</td><td>1</td></tr>\n",
       "<tr><td>3849061</td><td>0.022872907687266495</td><td>81.86745490070544</td><td>-12.697661182669316</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(1189374496997)/</td><td>/Date(1189375876997)/</td><td>54352.908530027606</td><td>54352.9245022363</td><td>IC418</td><td>3.8767163433245755</td><td>0.0</td><td>0.45499999999999996</td><td>0.0</td><td>0.2232816070318222</td><td>N</td><td>13.405989646911621</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>79528152</td><td>0.027203546688822525</td><td>81.8675458104757</td><td>-12.697725597380884</td><td>0.0</td><td>Y</td><td>3</td><td>1</td><td>3</td><td>/Date(937279573430)/</td><td>/Date(937287233430)/</td><td>51435.14321097685</td><td>51435.23186839372</td><td>IC418</td><td>3.234443902714927</td><td>0.20027712778925374</td><td>0.4549999999999999</td><td>6.798699777552591e-17</td><td>0.2232816070318222</td><td>N</td><td>12.978099822998047</td><td>0.0</td><td>1</td><td>16.269100189208984</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>16.81999969482422</td><td>0.0</td><td>1</td></tr>\n",
       "<tr><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td><td>...</td></tr>\n",
       "<tr><td>98018064</td><td>6.207720095622486</td><td>81.78285300240735</td><td>-12.634908449161575</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>1.9106977207716123</td><td>0.0</td><td>0.3710000216960907</td><td>0.0</td><td>0.2315555065870285</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>25.186500549316406</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>24343268</td><td>6.239877103651029</td><td>81.80339943978788</td><td>-12.614160758091833</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>1.9168604251950287</td><td>0.0</td><td>0.3499999940395355</td><td>0.0</td><td>0.2315555065870285</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>18.99449920654297</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>33286019</td><td>6.276081288115821</td><td>81.78279148395757</td><td>-12.633113753019495</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>1.9672093003295188</td><td>0.0</td><td>0.3499999940395355</td><td>0.0</td><td>0.2315555065870285</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>24.434900283813477</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>13146491</td><td>6.362803320020495</td><td>81.79527629046265</td><td>-12.617998168506656</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>0.8990697389425234</td><td>0.0</td><td>0.3499999940395355</td><td>0.0</td><td>0.2315555065870285</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>24.90530014038086</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>103027787</td><td>6.37561190345577</td><td>81.77510689904253</td><td>-12.64095593589095</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>1.8162791119065396</td><td>0.0</td><td>0.3499999940395355</td><td>0.0</td><td>0.2097422033548355</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>23.958999633789062</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>69478781</td><td>6.426627664683932</td><td>81.79812954297455</td><td>-12.614233789213866</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>0.7718604664469875</td><td>0.0</td><td>0.3499999940395355</td><td>0.0</td><td>0.2315555065870285</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>24.647499084472656</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "<tr><td>74166488</td><td>6.434089934742176</td><td>81.80108818382145</td><td>-12.611807703304587</td><td>0.0</td><td>Y</td><td>1</td><td>1</td><td>1</td><td>/Date(921328453407)/</td><td>/Date(921330593407)/</td><td>51250.52376624057</td><td>51250.5485347826</td><td>ANY</td><td>1.2626743593881298</td><td>0.0</td><td>0.3499999940395355</td><td>0.0</td><td>0.2315555065870285</td><td>N</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td><td>24.84950065612793</td><td>0.0</td><td>1</td><td>nan</td><td>nan</td><td>0</td><td>nan</td><td>nan</td><td>0</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table masked=True length=2602>\n",
       " MatchID        Distance       ...    W2_F658N_MAD    W2_F658N_N\n",
       "   str9         float64        ...      float64         int64   \n",
       "--------- -------------------- ... ------------------ ----------\n",
       " 90374054  0.00565599521966206 ... 0.3621950149536133          2\n",
       " 59074158 0.011870704932628309 ...                nan          0\n",
       " 85650262 0.012636542260362472 ...                nan          0\n",
       " 49514032 0.013779232245273892 ...                0.0          1\n",
       "  3849061 0.022872907687266495 ...                nan          0\n",
       " 79528152 0.027203546688822525 ...                0.0          1\n",
       "      ...                  ... ...                ...        ...\n",
       " 98018064    6.207720095622486 ...                nan          0\n",
       " 24343268    6.239877103651029 ...                nan          0\n",
       " 33286019    6.276081288115821 ...                nan          0\n",
       " 13146491    6.362803320020495 ...                nan          0\n",
       "103027787     6.37561190345577 ...                nan          0\n",
       " 69478781    6.426627664683932 ...                nan          0\n",
       " 74166488    6.434089934742176 ...                nan          0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "catalog_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "catalog_data.show_in_browser(jsviewer=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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