{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "<img src=\"ALminer_logo_header.jpg\" align=\"center\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "# ALminer Tutorial Notebook <a href=\"https://mybinder.org/v2/gh/emerge-erc/ALminer/main?filepath=notebooks/tutorial/ALminer_tutorial.ipynb\"><img style=\"float: right\" src=\"https://img.shields.io/badge/launch-Jupyter%20Notebook-579ACA.svg?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFkAAABZCAMAAABi1XidAAAB8lBMVEX///9XmsrmZYH1olJXmsr1olJXmsrmZYH1olJXmsr1olJXmsrmZYH1olL1olJXmsr1olJXmsrmZYH1olL1olJXmsrmZYH1olJXmsr1olL1olJXmsrmZYH1olL1olJXmsrmZYH1olL1olL0nFf1olJXmsrmZYH1olJXmsq8dZb1olJXmsrmZYH1olJXmspXmspXmsr1olL1olJXmsrmZYH1olJXmsr1olL1olJXmsrmZYH1olL1olLeaIVXmsrmZYH1olL1olL1olJXmsrmZYH1olLna31Xmsr1olJXmsr1olJXmsrmZYH1olLqoVr1olJXmsr1olJXmsrmZYH1olL1olKkfaPobXvviGabgadXmsqThKuofKHmZ4Dobnr1olJXmsr1olJXmspXmsr1olJXmsrfZ4TuhWn1olL1olJXmsqBi7X1olJXmspZmslbmMhbmsdemsVfl8ZgmsNim8Jpk8F0m7R4m7F5nLB6jbh7jbiDirOEibOGnKaMhq+PnaCVg6qWg6qegKaff6WhnpKofKGtnomxeZy3noG6dZi+n3vCcpPDcpPGn3bLb4/Mb47UbIrVa4rYoGjdaIbeaIXhoWHmZYHobXvpcHjqdHXreHLroVrsfG/uhGnuh2bwj2Hxk17yl1vzmljzm1j0nlX1olL3AJXWAAAAbXRSTlMAEBAQHx8gICAuLjAwMDw9PUBAQEpQUFBXV1hgYGBkcHBwcXl8gICAgoiIkJCQlJicnJ2goKCmqK+wsLC4usDAwMjP0NDQ1NbW3Nzg4ODi5+3v8PDw8/T09PX29vb39/f5+fr7+/z8/Pz9/v7+zczCxgAABC5JREFUeAHN1ul3k0UUBvCb1CTVpmpaitAGSLSpSuKCLWpbTKNJFGlcSMAFF63iUmRccNG6gLbuxkXU66JAUef/9LSpmXnyLr3T5AO/rzl5zj137p136BISy44fKJXuGN/d19PUfYeO67Znqtf2KH33Id1psXoFdW30sPZ1sMvs2D060AHqws4FHeJojLZqnw53cmfvg+XR8mC0OEjuxrXEkX5ydeVJLVIlV0e10PXk5k7dYeHu7Cj1j+49uKg7uLU61tGLw1lq27ugQYlclHC4bgv7VQ+TAyj5Zc/UjsPvs1sd5cWryWObtvWT2EPa4rtnWW3JkpjggEpbOsPr7F7EyNewtpBIslA7p43HCsnwooXTEc3UmPmCNn5lrqTJxy6nRmcavGZVt/3Da2pD5NHvsOHJCrdc1G2r3DITpU7yic7w/7Rxnjc0kt5GC4djiv2Sz3Fb2iEZg41/ddsFDoyuYrIkmFehz0HR2thPgQqMyQYb2OtB0WxsZ3BeG3+wpRb1vzl2UYBog8FfGhttFKjtAclnZYrRo9ryG9uG/FZQU4AEg8ZE9LjGMzTmqKXPLnlWVnIlQQTvxJf8ip7VgjZjyVPrjw1te5otM7RmP7xm+sK2Gv9I8Gi++BRbEkR9EBw8zRUcKxwp73xkaLiqQb+kGduJTNHG72zcW9LoJgqQxpP3/Tj//c3yB0tqzaml05/+orHLksVO+95kX7/7qgJvnjlrfr2Ggsyx0eoy9uPzN5SPd86aXggOsEKW2Prz7du3VID3/tzs/sSRs2w7ovVHKtjrX2pd7ZMlTxAYfBAL9jiDwfLkq55Tm7ifhMlTGPyCAs7RFRhn47JnlcB9RM5T97ASuZXIcVNuUDIndpDbdsfrqsOppeXl5Y+XVKdjFCTh+zGaVuj0d9zy05PPK3QzBamxdwtTCrzyg/2Rvf2EstUjordGwa/kx9mSJLr8mLLtCW8HHGJc2R5hS219IiF6PnTusOqcMl57gm0Z8kanKMAQg0qSyuZfn7zItsbGyO9QlnxY0eCuD1XL2ys/MsrQhltE7Ug0uFOzufJFE2PxBo/YAx8XPPdDwWN0MrDRYIZF0mSMKCNHgaIVFoBbNoLJ7tEQDKxGF0kcLQimojCZopv0OkNOyWCCg9XMVAi7ARJzQdM2QUh0gmBozjc3Skg6dSBRqDGYSUOu66Zg+I2fNZs/M3/f/Grl/XnyF1Gw3VKCez0PN5IUfFLqvgUN4C0qNqYs5YhPL+aVZYDE4IpUk57oSFnJm4FyCqqOE0jhY2SMyLFoo56zyo6becOS5UVDdj7Vih0zp+tcMhwRpBeLyqtIjlJKAIZSbI8SGSF3k0pA3mR5tHuwPFoa7N7reoq2bqCsAk1HqCu5uvI1n6JuRXI+S1Mco54YmYTwcn6Aeic+kssXi8XpXC4V3t7/ADuTNKaQJdScAAAAAElFTkSuQmCC\"></a>\n",
    "\n",
    "* This tutorial notebook showcases [`alminer`](https://github.com/emerge-erc/ALminer)'s various functions with examples. \n",
    "* The documentation for all functions is compiled as a [glossery](#glossery) at the end of the tutorial. \n",
    "* To work with the tutorial notebook interactively, click on _launch Jupyter Notebook_ badge in the top right.\n",
    "* In interactive mode, each cell can be executed by pressing <kbd>Shift</kbd>+<kbd>Enter</kbd>.\n",
    "* All fields in this tutorial are write-protected. To work on your own examples, go to the [workstation](#workstation) below, or click on _File > New Notebook > Python 3_ to create a new empty notebook.<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## Table of contents:\n",
    "0. [Load libraries](#libraries)<br>\n",
    "1. [Query tools](#query)<br>\n",
    " 1.1 [Query by target name](#target)<br>\n",
    " 1.2 [Query by position](#position)<br>\n",
    " 1.3 [Query by ALMA keywords](#keysearch)<br>\n",
    "2. [Filter & explore results](#analysis)<br>\n",
    " 2.1 [Explore results](#explore) <br>\n",
    " 2.2 [Summarize results](#summary) <br>\n",
    " 2.3 [Filter results](#filter) <br>\n",
    " 2.4 [Line coverage](#line_coverage) <br>\n",
    " 2.5 [Coverage of CO, 13CO, and C18O lines](#CO_lines) <br>\n",
    "3. [Plot results](#results)<br>\n",
    " 3.1 [Plot an overview of the observations](#plot_overview)<br>\n",
    " 3.2 [Plot an overview of a given line in the observations](#plot_line_overview)<br>\n",
    " 3.3 [Plot observed frequencies in each band](#plot_bands)<br>\n",
    " 3.4 [Plot observations in each band](#plot_observations)<br>\n",
    " 3.5 [Plot sky distribution](#plot_sky)<br>\n",
    "4. [Create reports](#reports)<br>\n",
    " 4.1 [Export results as a table](#save_table)<br>\n",
    " 4.2 [Save overview plots](#save_source_reports)<br>\n",
    "5. [Download data](#download)<br>\n",
    "6. [Advanced query features](#advanced)<br>\n",
    " 6.1 [Create and run your own TAP query](#create_query)<br>\n",
    " 6.2 [Convert results to ALminer format](#filter_results)<br>\n",
    "7. [Glossary of all functions](#glossery)<br>\n",
    "8. [Workstation](#workstation)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "# 0. Load libraries <a name=\"libraries\"></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "import alminer\n",
    "import pandas\n",
    "from astropy.io import ascii"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "# 1. Query tools <a name=\"query\"></a>\n",
    "\n",
    "This Section introduces three methods to query the ALMA archive:<br>\n",
    "* [1.1 - Query by target name (*alminer.target*)](#target)<br>\n",
    "* [1.2 - Query a catalog (*alminer.catalog*)](#catalog)<br>\n",
    "* [1.3 - Query by ALMA keywords (*alminer.keysearch*)](#keysearch)<br>\n",
    "\n",
    "#### General notes about the querying functions:\n",
    "* All querying functions search the ALMA archive for public data by default. To include both public and proprietary data in the search, set *public=None*. Similarly, to search for only propietary data, set *public=False*. \n",
    "* All querying functions search the ALMA archive for both published and unpublished data. To include only unpublished data, set *published=False*.\n",
    "* The querying functions will by default print a summary of the observations, including a list of target names. For large queries, it is useful to turn this feature off in order to not have a long list of targets printed to screen. To turn off this feature, simply set *print_targets=False*.\n",
    "* The queries return all possible observations in [PANDAS DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/frame.html) format that can be used to further narrow down your search as demonstrated in [Section 2](#explore).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 1.1 Query by target name <a name=\"target\"></a>\n",
    "\n",
    "The `alminer.target` function allows one to query objects by name. This function uses the Astropy [SESAME resolver](http://cds.u-strasbg.fr/cgi-bin/Sesame) which searches multiple databases (Simbad, NED, VizieR) to obtain the coordinates of the object of interest, and then queries the ALMA archive for those coordinates and a search radius around them. The search radius is by default 1.0 arcminute, but can be modified using the *search_radius* keyword (in arcmin units). \n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>target</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query targets by name. <br>\n",
    " * This is done by using the astropy SESAME resolver to get the target's coordinates and then the ALMA archive is queried for those coordinates and a search_radius around them. The SESAME resolver searches multiple databases (Simbad, NED, VizieR) to parse names commonly found throughout literature and returns their coordinates. If the target is not resolved in any of these databases, consider using the `keysearch` function and query the archive using the 'target_name' keyword (e.g. `keysearch({'target_name': sources})`).<br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**target**(_sources, search_radius=1., point=True, public=True, published=None, print_query=False, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **sources (list of str)** : list of sources by name. (IMPORTANT: sources names must be identified by at least one of Simbad, NED, or Vizier) <br> \n",
    " * **search_radius (float, optional, default: 1 arcmin)** : Search radius (in arcmin) around the source coordinates. <br>\n",
    " * **point (bool, optional, default: True)** : Search whether the phase center of the observations is contained within the search_radius (*point=True*) or whether any part of the observed region overlaps with the cone extending the search_radius (*point=False*). Note that *point=True* is much faster than *point=False* but the latter should be used if one is interested in searching for mosaics.<br>\n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.1.1: query two sources by name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.target results \n",
      "================================\n",
      "Target = Orion KL\n",
      "--------------------------------\n",
      "Number of projects = 27\n",
      "Number of observations = 63\n",
      "Number of unique subbands = 226\n",
      "Total number of subbands = 272\n",
      "23 target(s) with ALMA data = ['Orion H2O maser outburst', 'OrionKL', 'Orion_Source_I', 'Orion KL', 'Orion-KL', 'Orion_KL', 'BN-KL', 'OrionKL-SV', 'f15', 'f14', 'OMC1_NW', 'Orion1', 'OMC1_SE', 'BN', 'f23', 'Orion', 'Orion_BNKL_source_I', 'OMC-1_Region2', 'orion_kl', 'orion-IRc2', 'Orion_KL_Field_1_Orion_Hot_Core', 'Orion_KL_Field_3_North-west_Clump', 'Orion_KL_Field_2_SMA1']\n",
      "--------------------------------\n",
      "Target = AB Aur\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 17\n",
      "Total number of subbands = 17\n",
      "3 target(s) with ALMA data = ['ab_aurigae', 'AB_Aur', 'AB_Auriga']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.target(['Orion KL', \"AB Aur\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "Now let's increase the search radius:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.target results \n",
      "================================\n",
      "Target = Orion KL\n",
      "--------------------------------\n",
      "Number of projects = 35\n",
      "Number of observations = 100\n",
      "Number of unique subbands = 283\n",
      "Total number of subbands = 451\n",
      "46 target(s) with ALMA data = ['HC602_HC606_HC608', 'Orion H2O maser outburst', 'OrionField1-2', 'OrionKL', 'Orion_Source_I', 'HC672', 'OrionField1-1', 'OrionField2', 'Orion KL', 'OMC-1S', 'Orion-KL', '104', 'Orion_KL', '71', 'BN-KL', 'OrionKL-SV', 'f11', 'f12', 'f15', 'f13', 'f14', 'OMC1_SE', 'OMC1_NW', 'f10', 'Orion1', 'f8', 'f4', 'f5', 'f1', 'f7', 'f3', 'BN', 'f23', 'Orion', 'Orion_BNKL_source_I', 'f16', 'OMC-1_Region4', 'OMC-1_Region2', 'orion_kl', 'ONC_Mosaic', 'orion-IRc2', 'Orion_KL_Field_1_Orion_Hot_Core', 'ONC', 'Orion_KL_Field_3_North-west_Clump', 'Orion_KL_Field_2_SMA1', 'ORS-8']\n",
      "--------------------------------\n",
      "Target = AB Aur\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 17\n",
      "Total number of subbands = 17\n",
      "3 target(s) with ALMA data = ['ab_aurigae', 'AB_Aur', 'AB_Auriga']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.target(['Orion KL', \"AB Aur\"], search_radius=2.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.1.2: query a list of objects by name\n",
    "\n",
    "First create a catalog or a list of object names. In this example, the catalog `Sample_cat.dat` has the following content:\n",
    "```\n",
    " Name     RA      DEC   \n",
    "------ -------- --------\n",
    "AB_Aur  73.9412  30.5511\n",
    "AK_Sco 253.6867 -36.8886\n",
    "AS_310 278.3383  -4.9683\n",
    "AS_470 324.0592  57.3586\n",
    "AS_477 328.1421  47.2289\n",
    "```\n",
    "\n",
    "Note that the column that is used is the *Name* column and the coordinates are ignored in this example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.target results \n",
      "================================\n",
      "Target = AB_Aur\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 17\n",
      "Total number of subbands = 17\n",
      "3 target(s) with ALMA data = ['ab_aurigae', 'AB_Aur', 'AB_Auriga']\n",
      "--------------------------------\n",
      "Target = AK_Sco\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 12\n",
      "Total number of subbands = 12\n",
      "2 target(s) with ALMA data = ['AK_Sco', 'HIP_82747']\n",
      "--------------------------------\n",
      "Target = AS_310\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "Target = AS_470\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "Target = AS_477\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "mylist = ascii.read(\"Sample_cat.dat\", header_start=0, data_start=1)\n",
    "myquery = alminer.target(mylist['Name'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.1.3: include proprietary data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.target results \n",
      "================================\n",
      "Target = AB_Aur\n",
      "--------------------------------\n",
      "Number of projects = 4\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 25\n",
      "Total number of subbands = 25\n",
      "3 target(s) with ALMA data = ['ab_aurigae', 'AB_Aur', 'AB_Auriga']\n",
      "--------------------------------\n",
      "Target = AK_Sco\n",
      "--------------------------------\n",
      "Number of projects = 4\n",
      "Number of observations = 4\n",
      "Number of unique subbands = 16\n",
      "Total number of subbands = 16\n",
      "2 target(s) with ALMA data = ['AK_Sco', 'HIP_82747']\n",
      "--------------------------------\n",
      "Target = AS_310\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "Target = AS_470\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "Target = AS_477\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.target(mylist['Name'], public=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.1.4: account for mosaics\n",
    "\n",
    "The `alminer.target` function will by default search whether the phase center of any ALMA observations lie within the search radius around the target of interest's position. To search whether any part of the observed region overlaps with the cone extending the search radius, one can set *point=False*. Note that this option is slower, hence it's not the dafault mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.target results \n",
      "================================\n",
      "Target = Orion KL\n",
      "--------------------------------\n",
      "Number of projects = 35\n",
      "Number of observations = 90\n",
      "Number of unique subbands = 283\n",
      "Total number of subbands = 399\n",
      "40 target(s) with ALMA data = ['HC602_HC606_HC608', 'Orion H2O maser outburst', 'OrionField1-2', 'OrionKL', 'Orion_Source_I', 'OrionField1-1', 'Orion KL', 'Orion-KL', '104', 'Orion_KL', 'BN-KL', 'OrionKL-SV', 'f11', 'f12', 'f15', 'f13', 'f14', 'OMC1_SE', 'OMC1_NW', 'f10', 'Orion1', 'f1', 'f3', 'BN', 'f23', 'Orion', 'OMC-1_Region5', 'Orion_BNKL_source_I', 'f16', 'OMC-1_Region4', 'OMC-1_Region2', 'orion_kl', 'OMC-1', 'ONC_Mosaic', 'orion-IRc2', 'Orion_KL_Field_1_Orion_Hot_Core', 'ONC', 'Orion_KL_Field_3_North-west_Clump', 'Orion_KL_Field_2_SMA1', 'ORS-8']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.target(['Orion KL'], point=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 1.2 Query by position <a name=\"position\"></a>\n",
    "\n",
    "The `alminer.conesearch` and `alminer.catalog` functions can be used to directly query the ALMA archive by positions in the sky and a search radius around them. The right ascension and declinations must be given in units of degrees (ICRS). You can use the [Astropy coordinates package](https://docs.astropy.org/en/stable/coordinates/index.html) to convert your desired coordinates to degrees.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>conesearch</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query the ALMA archive for a given position and radius around it.<br>\n",
    "    <br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**conesearch**(_ra, dec, search_radius=1., point=True, public=True, published=None, print_targets=True, print_query=False_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **ra (float)** : Right ascension in degrees (ICRS). <br>\n",
    " * **dec (float)** : Declination in degrees (ICRS). <br>\n",
    " * **search_radius (float, optional, default: 1 arcmin)** : Search radius (in arcmin) around the source coordinates. <br>\n",
    " * **point (bool, optional, default: True)** : Search whether the phase center of the observations is contained within the search_radius (*point=True*) or whether any part of the observed region overlaps with the cone extending the search_radius (*point=False*). Note that *point=True* is much faster than *point=False* but the latter should be used if one is interested in searching for mosaics.<br>\n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>  \n",
    "\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>catalog</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query the ALMA archive for a list of coordinates or a catalog of sources based on their coordinates. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**catalog**(_target_df, search_radius=1., point=True, public=True, published=None, print_query=False, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **target_df (pandas.DataFrame)** : DataFrame with source names and coordinates; it must have at least the following three columns: \"*Name*\", \"*RAJ2000*\", \"*DEJ2000*\". \"*Name*\" describes the target name (can be numbers or dummy names), \"*RAJ2000*\" is the right ascension in degrees (ICRS), \"*DEJ2000*\" is the declination in degrees (ICRS) <br>\n",
    " * **search_radius (float, optional, default: 1 arcmin)** : Search radius (in arcmin) around the source coordinates. <br>\n",
    " * **point (bool, optional, default: True)** : Search whether the phase center of the observations is contained within the search_radius (*point=True*) or whether any part of the observed region overlaps with the cone extending the search_radius (*point=False*). Note that *point=True* is much faster than *point=False* but the latter should be used if one is interested in searching for mosaics.<br>\n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
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    "deletable": false,
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   },
   "source": [
    "### Example 1.2.1:  query an object by its coordinates (RA, Dec)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 23\n",
      "Number of observations = 74\n",
      "Number of unique subbands = 190\n",
      "Total number of subbands = 301\n",
      "9 target(s) with ALMA data = ['CenA', 'J1325-430', 'Centaurus_a', 'J1325-4301', 'Centaurus A', 'Centaurus_A', '3FGL_J1325.4-4301', 'NGC_5128', 'Cen_A']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.conesearch(ra=201.365063, dec=-43.019112, search_radius=10.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
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   },
   "source": [
    "### Example 1.2.2:  query a catalog of objects by their coordinates (RA, Dec)\n",
    "\n",
    "Let's first import a catalog, for example the catalog of Spitzer YSOs in Orion from Megeath et al. (2009), and create a PANDAS DataFrame using rows 866 to 869 of this catalog. Then use the `alminer.catalog` function to query the ALMA archive for each target in the DataFrame."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.catalog results\n",
      "================================\n",
      "Target = 866\n",
      "--------------------------------\n",
      "Number of projects = 1\n",
      "Number of observations = 1\n",
      "Number of unique subbands = 4\n",
      "Total number of subbands = 4\n",
      "1 target(s) with ALMA data = ['M12_866']\n",
      "--------------------------------\n",
      "Target = 867\n",
      "--------------------------------\n",
      "Number of projects = 1\n",
      "Number of observations = 1\n",
      "Number of unique subbands = 4\n",
      "Total number of subbands = 4\n",
      "1 target(s) with ALMA data = ['M12_867']\n",
      "--------------------------------\n",
      "Target = 868\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 2\n",
      "Number of unique subbands = 8\n",
      "Total number of subbands = 8\n",
      "1 target(s) with ALMA data = ['HOPS-172']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "Spitzer = ascii.read(\"Spitzer_sample.dat\", header_start=0, data_start=866, data_end=869)\n",
    "\n",
    "mycat =  {\"Name\": Spitzer['Seq'], \n",
    "          \"RAJ2000\" : Spitzer[\"RA2000\"], \n",
    "          \"DEJ2000\" : Spitzer[\"DEC2000\"]}\n",
    "\n",
    "mycat = pandas.DataFrame(mycat)\n",
    "\n",
    "myquery = alminer.catalog(mycat, search_radius=1.)"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "## 1.3 Query by ALMA keywords <a name=\"keysearch\"></a>\n",
    "\n",
    "Query the ALMA archive for any (string-type) keywords defined in ALMA TAP system (see [table below](#TAP_table)). \n",
    "\n",
    "The power of this function is in combining keywords. When multiple keywords are provided, they are queried using 'AND' logic, while when multiple values are provided for a given keyword, they are queried using 'OR' logic. For example,\n",
    "\n",
    " * `alminer.keysearch({\"proposal_abstract\": [\"high-mass star formation outflow disk\"]})`\n",
    "will query the archive for projects with the words \"high-mass\" AND \"star\" AND \"formation\" AND \"outflow\" AND \"disk\" in their proposal abstracts.\n",
    "<br>\n",
    "\n",
    " * `alminer.keysearch({\"proposal_abstract\": [\"high-mass\", \"star\", \"formation\", \"outflow\", \"disk\"]})`\n",
    "will query the archive for projects with the words \"high-mass\" OR \"star\" OR \"formation\" OR \"outflow\" OR \"disk\" in their proposal abstracts.\n",
    "<br>\n",
    "\n",
    " * `alminer.keysearch({\"proposal_abstract\": [\"star formation\"], \"scientific_category\":['Galaxy evolution']})`\n",
    "will query the archive for projects with the words \"star\" AND \"formation\" in their proposal abstracts AND projects that are within the scientific_category of 'Galaxy evolution'.\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>keysearch</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query the ALMA archive for any (string-type) keywords defined in ALMA TAP system. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**keysearch**(_search_dict, public=True, published=None, print_query=False, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **search_dict (dict[str, list of str])** : Dictionary of keywords in the ALMA archive and their values. Values must be formatted as a list of strings. For a list of valid keywords see [table](#TAP_table) below. <br> \n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>"
   ]
  },
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   "source": [
    "<details>\n",
    "<summary style=\"display:list-item\">Table of possible query keywords  <a name=\"TAP_table\" ></a></summary>\n",
    "\n",
    "<table  align=\"left\">   \n",
    "<tr  style=\"border-bottom:1px solid black\"><th style=\"text-align:left\" >ALMA query keyword</th><th style=\"text-align:left\" >Type</th><th style=\"text-align:left\" >Description</th></tr>\n",
    "    <tr><td style=\"text-align:left\" >access_format</td><td  style=\"text-align:left\">char(9)</td><td  style=\"text-align:left\">Content format of the data</td>\n",
    "    <tr><td style=\"text-align:left\" >access_url</td><td  style=\"text-align:left\">char(72*)</td><td  style=\"text-align:left\">URL to download the data</td>\n",
    "    <tr><td style=\"text-align:left\" >antenna_arrays</td><td  style=\"text-align:left\">char(660*)</td><td  style=\"text-align:left\">Blank-separated list of Pad:Antenna pairs, i.e., A109:DV09 J504:DV02 J505:DV05 <br> for antennas DV09, DV02 and DV05 sitting on pads A109, J504, and J505, respectively.</td>\n",
    "    <tr><td style=\"text-align:left\" >asdm_uid</td><td  style=\"text-align:left\">char(32*)</td><td  style=\"text-align:left\">UID of the ASDM containing this Field.</td>\n",
    "    <tr><td style=\"text-align:left\" >authors</td><td  style=\"text-align:left\">char(4000*)</td><td  style=\"text-align:left\">Full list of first author and all co-authors</td>\n",
    "    <tr><td style=\"text-align:left\" >band_list</td><td  style=\"text-align:left\">char(30*)</td><td  style=\"text-align:left\">Space delimited list of bands</td>\n",
    "    <tr><td style=\"text-align:left\" >bib_reference</td><td  style=\"text-align:left\">char(30*)</td><td  style=\"text-align:left\">Bibliography code</td>\n",
    "    <tr><td style=\"text-align:left\" >data_rights</td><td  style=\"text-align:left\">char(11)</td><td  style=\"text-align:left\">Access to data.</td>\n",
    "    <tr><td style=\"text-align:left\" >dataproduct_type</td><td  style=\"text-align:left\">char(5*)</td><td  style=\"text-align:left\">type of product</td>\n",
    "    <tr><td style=\"text-align:left\" >facility_name</td><td  style=\"text-align:left\">char(3)</td><td  style=\"text-align:left\">telescope name</td>\n",
    "    <tr><td style=\"text-align:left\" >first_author</td><td  style=\"text-align:left\">char(256*)</td><td  style=\"text-align:left\">The first author as provided by <a href=\"http://telbib.eso.org\">telbib.eso.org</a>.</td>\n",
    "    <tr><td style=\"text-align:left\" >frequency_support</td><td  style=\"text-align:left\">char(4000*)</td><td  style=\"text-align:left\">All frequency ranges used by the field</td>\n",
    "    <tr><td style=\"text-align:left\" >group_ous_uid</td><td  style=\"text-align:left\">char(64*)</td><td  style=\"text-align:left\">Group OUS ID</td>\n",
    "    <tr><td style=\"text-align:left\" >instrument_name</td><td  style=\"text-align:left\">char(4)</td><td  style=\"text-align:left\">instrument name</td>\n",
    "    <tr><td style=\"text-align:left\" >is_mosaic</td><td  style=\"text-align:left\">char(1)</td><td  style=\"text-align:left\">Flag to indicate if this ASDM represents a mosaic or not.</td>\n",
    "    <tr><td style=\"text-align:left\" >lastModified</td><td  style=\"text-align:left\">char(*)</td><td  style=\"text-align:left\">Time stamp of last modification of the metadata</td>\n",
    "    <tr><td style=\"text-align:left\" >member_ous_uid</td><td  style=\"text-align:left\">char(64*)</td><td  style=\"text-align:left\">Member OUS ID</td>\n",
    "    <tr><td style=\"text-align:left\" >o_ucd</td><td  style=\"text-align:left\">char(35)</td><td  style=\"text-align:left\">UCD describing the observable axis (pixel values)</td>\n",
    "    <tr><td style=\"text-align:left\" >obs_collection</td><td  style=\"text-align:left\">char(4)</td><td  style=\"text-align:left\">short name for the data collection</td>\n",
    "    <tr><td style=\"text-align:left\" >obs_creator_name</td><td  style=\"text-align:left\">char(256*)</td><td  style=\"text-align:left\">case-insensitive partial match over the full PI name. Wildcards can be used</td>\n",
    "    <tr><td style=\"text-align:left\" >obs_id</td><td  style=\"text-align:left\">char(64*)</td><td  style=\"text-align:left\">internal dataset identifier</td>\n",
    "    <tr><td style=\"text-align:left\" >obs_publisher_did</td><td  style=\"text-align:left\">char(33*)</td><td  style=\"text-align:left\">publisher dataset identifier</td>\n",
    "    <tr><td style=\"text-align:left\" >obs_release_date</td><td  style=\"text-align:left\">char(*)</td><td  style=\"text-align:left\">timestamp of date the data becomes publicly available</td>\n",
    "    <tr><td style=\"text-align:left\" >obs_title</td><td  style=\"text-align:left\">char(256*)</td><td  style=\"text-align:left\">Case-insensitive search over the project title</td>\n",
    "    <tr><td style=\"text-align:left\" >pol_states</td><td  style=\"text-align:left\">char(64*)</td><td  style=\"text-align:left\">polarization states present in the data</td>\n",
    "    <tr><td style=\"text-align:left\" >proposal_abstract</td><td  style=\"text-align:left\">char(4000*)</td><td  style=\"text-align:left\">Text search on the proposal abstract. Only abstracts will be returned <br> which contain the given text. The search is case-insensitive.</td>\n",
    "    <tr><td style=\"text-align:left\" >proposal_authors</td><td  style=\"text-align:left\">char(2000*)</td><td  style=\"text-align:left\">Full name of CoIs.</td>\n",
    "    <tr><td style=\"text-align:left\" >proposal_id</td><td  style=\"text-align:left\">char(64*)</td><td  style=\"text-align:left\">Identifier of proposal to which NO observation belongs.</td>\n",
    "    <tr><td style=\"text-align:left\" >pub_abstract</td><td  style=\"text-align:left\">char(4000*)</td><td  style=\"text-align:left\">Case insensitive text search through the abstract of the publication.</td>\n",
    "    <tr><td style=\"text-align:left\" >pub_title</td><td  style=\"text-align:left\">char(256*)</td><td  style=\"text-align:left\">Case insensitive search through the title of the publication.</td>\n",
    "    <tr><td style=\"text-align:left\" >qa2_passed</td><td  style=\"text-align:left\">char(1)</td><td  style=\"text-align:left\">Quality Assessment 2 status: does the Member / Group OUS  <br> fulfil the PI's requirements?</td>\n",
    "    <tr><td style=\"text-align:left\" >s_region</td><td  style=\"text-align:left\">char(*)</td><td  style=\"text-align:left\">region bounded by observation</td>\n",
    "    <tr><td style=\"text-align:left\" >scan_intent</td><td  style=\"text-align:left\">char(256*)</td><td  style=\"text-align:left\">Scan intent list for the observed field.</td>\n",
    "    <tr><td style=\"text-align:left\" >schedblock_name</td><td  style=\"text-align:left\">char(128*)</td><td  style=\"text-align:left\">Name of the Scheduling Block used as a template for executing the ASDM containing this Field.</td>\n",
    "    <tr><td style=\"text-align:left\" >science_keyword</td><td  style=\"text-align:left\">char(200*)</td><td  style=\"text-align:left\">Chosen by the PI in the observing tool at the time of proposal submission. For an overview, <br> see <a href=\"https://almascience.nrao.edu/proposing/proposers-guide#section-63\">Appendix D of the ALMA Proposer's Guide</a>. For a precise list, see <a href=\"#sci_keywords\">Table of science keywords</a> below.</td>\n",
    "    <tr><td style=\"text-align:left\" >science_observation</td><td  style=\"text-align:left\">char(1)</td><td  style=\"text-align:left\">Flag to indicate whether this is a science observation.</td>\n",
    "    <tr><td style=\"text-align:left\" >scientific_category</td><td  style=\"text-align:left\">char(200*)</td><td  style=\"text-align:left\">Chosen by the PI in the observing tool at the time of proposal submission. For an overview, <br>  see <a href=\"https://almascience.nrao.edu/proposing/proposers-guide#section-63\">Appendix D of the ALMA Proposer's Guide</a>. For a precise list, see <a href=\"#sci_category\">Table of science categories</a> below.</td>\n",
    "    <tr><td style=\"text-align:left\" >target_name</td><td  style=\"text-align:left\">char(256*)</td><td  style=\"text-align:left\">name of intended target</td>\n",
    "    <tr><td style=\"text-align:left\" >type</td><td  style=\"text-align:left\">char(16*)</td><td  style=\"text-align:left\">Type flags.</td>\n",
    "</table>\n",
    "</details>"
   ]
  },
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   "source": [
    "<details>\n",
    "<summary style=\"display:list-item\">Table of possible ALMA science categories <a name=\"sci_category\" ></a></summary>\n",
    "\n",
    "<table  align=\"left\">   \n",
    "<tr  style=\"border-bottom:1px solid black\"><th style=\"text-align:left\" >ALMA science category</th></tr>\n",
    "<tr><td style=\"text-align:left\" >Active galaxies</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Cosmology</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Disks and planet formation</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Galaxy evolution</td></tr>\n",
    "<tr><td style=\"text-align:left\" >ISM and star formation</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Local Universe</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Solar system</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Stars and stellar evolution</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Sun</td></tr>\n",
    "</table><br>\n",
    "</details>"
   ]
  },
  {
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   "source": [
    "<details>\n",
    "<summary style=\"display:list-item\">Table of possible ALMA science keywords <a name=\"sci_keywords\" ></a></summary>\n",
    "\n",
    "<table  align=\"left\">   \n",
    "<tr  style=\"border-bottom:1px solid black\"><th style=\"text-align:left\" >ALMA science keyword</th></tr>\n",
    "<tr><td style=\"text-align:left\" >Active Galactic Nuclei (AGN)/Quasars (QSO)</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Astrochemistry</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Asymptotic Giant Branch (AGB) stars</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Black holes</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Brown dwarfs</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Cataclysmic stars</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Cosmic Microwave Background (CMB)/Sunyaev-Zel'dovich Effect (SZE)\"</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Damped Lyman Alpha (DLA) systems</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Debris disks</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Disks around high-mass stars</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Disks around low-mass stars</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Dwarf/metal-poor galaxies</td></tr>\n",
    "<tr><td style=\"text-align:left\" >Early-type galaxies</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Evolved stars - Chemistry</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Evolved stars - Shaping/physical structure</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Evolved stars: Shaping/physical structure</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Exo-planets</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Galactic centres/nuclei</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Galaxy Clusters</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Galaxy chemistry</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Galaxy groups and clusters</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Galaxy structure & evolution</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Gamma Ray Bursts (GRB)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Giant Molecular Clouds (GMC) properties</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Gravitational lenses</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >HII regions</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >High-mass star formation</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >High-z Active Galactic Nuclei (AGN)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Hypergiants</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Infra-Red Dark Clouds (IRDC)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Inter-Stellar Medium (ISM)/Molecular clouds</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Intermediate-mass star formation</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Low-mass star formation</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Luminous Blue Variables (LBV)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Luminous and Ultra-Luminous Infra-Red Galaxies (LIRG & ULIRG)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Lyman Alpha Emitters/Blobs (LAE/LAB)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Lyman Break Galaxies (LBG)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Magellanic Clouds</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Main sequence stars</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Merging and interacting galaxies</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Outflows, jets, feedback</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Outflows, jets and ionized winds</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Photon-Dominated Regions (PDR)/X-Ray Dominated Regions (XDR)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Post-AGB stars</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Pre-stellar cores</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Pulsars and neutron stars</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Solar system - Asteroids</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Solar system - Comets</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Solar system - Planetary atmospheres</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Solar system - Planetary surfaces</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Solar system - Trans-Neptunian Objects (TNOs)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Spiral galaxies</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Starburst galaxies</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Starbursts, star formation</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Sub-mm Galaxies (SMG)</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Supernovae (SN) ejecta</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Surveys of galaxies</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >The Sun</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >Transients</td></tr>\n",
    "<tr><td  style=\"text-align:left\" >White dwarfs</td></tr>\n",
    "</table>\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.3.1: query a list of ALMA target names that may not be in SIMBAD/NED/VizieR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "--------------------------------\n",
      "Number of projects = 16\n",
      "Number of observations = 28\n",
      "Number of unique subbands = 121\n",
      "Total number of subbands = 179\n",
      "10 target(s) with ALMA data = ['GRB021004', 'G345.5', 'SPT0319-47', 'G345.5043+00.3480', 'G345.49+1.47', 'G345.50+0.35', 'G345.6487+0.0089', 'G345.01', 'G345.11', 'G345.0029-0.2241']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.keysearch({'target_name': ['GRB021004','SPT0319-47', 'G345']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.3.2: query a list of ALMA projects by their proposal IDs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 16\n",
      "Number of unique subbands = 16\n",
      "Total number of subbands = 64\n",
      "16 target(s) with ALMA data = ['KMOS3DGS4-27882', 'KMOS3DCOS4-24763', 'KMOS3DU4-34138', 'KMOS3DCOS4-19680', 'KMOS3DCOS4-13701', 'KMOS3DCOS4-10347', 'KMOS3DCOS4-13174', 'KMOS3DCOS4-15820', 'KMOS3DCOS4-15813', 'KMOS3DU4-22227', 'KMOS3DU4-20547', 'KMOS3DU4-32147', 'KMOS3DGS4-24110', 'KMOS3DGS4-11016', 'KMOS3DGS4-25151', 'AK_Sco']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.keysearch({'proposal_id': ['2015.1.00664.S', '2016.1.00204.S']})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.3.3: query by words in the proposal abstract\n",
    "\n",
    "Query the ALMA archive for proposals that have the words 'high-mass' AND 'star' AND 'formation' AND 'outflow', and do not print the long list of target names in the summary."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "--------------------------------\n",
      "Number of projects = 34\n",
      "Number of observations = 419\n",
      "Number of unique subbands = 416\n",
      "Total number of subbands = 2799\n",
      "Total number of targets with ALMA data = 239\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.keysearch({'proposal_abstract': ['high-mass star formation outflow']}, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.3.4: query by combination of keywords\n",
    "\n",
    "Query the ALMA archive for proposals that have the words ('high-mass' AND 'star' AND 'formation' AND 'outflow') OR ('massive' AND 'star' AND 'formation') corresponding to the scientific category of 'Galaxy evolution'."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "--------------------------------\n",
      "Number of projects = 119\n",
      "Number of observations = 2056\n",
      "Number of unique subbands = 2481\n",
      "Total number of subbands = 8247\n",
      "Total number of targets with ALMA data = 1376\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.keysearch({'proposal_abstract': ['high-mass star formation', 'massive star formation'], \n",
    "                             'scientific_category':['Galaxy evolution']}, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 1.3.5: query for full polarization data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "--------------------------------\n",
      "Number of projects = 27\n",
      "Number of observations = 48\n",
      "Number of unique subbands = 94\n",
      "Total number of subbands = 192\n",
      "Total number of targets with ALMA data = 34\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery = alminer.keysearch({'science_keyword':['disks around low-mass stars'], \n",
    "                             'pol_states':['XY', 'YX']}, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "# 2. Filter & explore results <a name=\"analysis\"></a>\n",
    "\n",
    "The querying functions presented in the previous section return a [PANDAS DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/frame.html) that can be used to further narrow down your search. This section presents some examples of how you can further filter and explore the results of your queries:\n",
    "\n",
    "* [2.1 - Explore results (*alminer.explore*)](#explore) <br>\n",
    "* [2.2 - Summarize results (*alminer.summary*)](#summary) <br>\n",
    "* [2.3 - Filter results (*alminer.get_info*)](#filter) <br>\n",
    "* [2.4 - Line coverage (*alminer.line_coverage*)](#line_coverage) <br>\n",
    "* [2.5 - CO, 13CO, C18O lines (*alminer.CO_lines*)](#CO_lines) <br>\n",
    "\n",
    "To explore these options, we will first query the archive using one of the methods presented in the previous section and use the results in the remainder of this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "--------------------------------\n",
      "Number of projects = 47\n",
      "Number of observations = 339\n",
      "Number of unique subbands = 1162\n",
      "Total number of subbands = 1361\n",
      "Total number of targets with ALMA data = 63\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "observations = alminer.keysearch({'science_keyword':['Galaxy chemistry']}, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 2.1  Explore results <a name=\"explore\"></a>\n",
    "\n",
    "You can simply display the DataFrame table returned by the query functions using the name you gave it (in this case *observations*), but often there are limits to how many rows and columns are presented. With the <code>alminer.explore</code> function, you can control whether or not you want to display all rows (*allrows=True/False*) and/or all columns (*allcols=True/False*). By default, only the 18 most useful columns are shown and the number of rows is truncated.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>explore</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Control how much of the pandas.DataFrame with the query results is presented in the displayed table. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**explore**(_observations, allcols=False, allrows=False_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **allcols (bool, optional, default: False)** : Show all 81 columns (*allcols=True*), or the first 18 columns (*allcols=False*). <br>\n",
    " * **allrows (bool, optional, default: False)** : Show all rows in the DataFrame (*allrows=True*), or just a summary (*allrows=False*). <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results displayed to the user interface as specified by the user.\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.1.1: View the queried observations as a table (shortened)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
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       "      <td>1500.60</td>\n",
       "      <td>61.02</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>256.63</td>\n",
       "      <td>258.53</td>\n",
       "      <td>257.58</td>\n",
       "      <td>1.894</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.132</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2189.73</td>\n",
       "      <td>147.77</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>244.13</td>\n",
       "      <td>246.02</td>\n",
       "      <td>245.08</td>\n",
       "      <td>1.893</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.190</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2229.45</td>\n",
       "      <td>146.80</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.455</td>\n",
       "      <td>295.51</td>\n",
       "      <td>297.38</td>\n",
       "      <td>296.45</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.984</td>\n",
       "      <td>3.448</td>\n",
       "      <td>20.113</td>\n",
       "      <td>60.429</td>\n",
       "      <td>1735.78</td>\n",
       "      <td>126.28</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.455</td>\n",
       "      <td>293.63</td>\n",
       "      <td>295.51</td>\n",
       "      <td>294.57</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.991</td>\n",
       "      <td>3.448</td>\n",
       "      <td>20.113</td>\n",
       "      <td>60.429</td>\n",
       "      <td>1655.25</td>\n",
       "      <td>120.04</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>242.31</td>\n",
       "      <td>244.20</td>\n",
       "      <td>243.25</td>\n",
       "      <td>1.894</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.199</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2229.83</td>\n",
       "      <td>146.24</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>304.55</td>\n",
       "      <td>306.43</td>\n",
       "      <td>305.49</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.955</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1868.50</td>\n",
       "      <td>137.78</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>1.331</td>\n",
       "      <td>93.07</td>\n",
       "      <td>94.95</td>\n",
       "      <td>94.01</td>\n",
       "      <td>1.878</td>\n",
       "      <td>976.56</td>\n",
       "      <td>3.083</td>\n",
       "      <td>12.937</td>\n",
       "      <td>58.774</td>\n",
       "      <td>29.824</td>\n",
       "      <td>1440.54</td>\n",
       "      <td>59.16</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>290.68</td>\n",
       "      <td>292.56</td>\n",
       "      <td>291.62</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.001</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1903.65</td>\n",
       "      <td>137.16</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>302.68</td>\n",
       "      <td>304.56</td>\n",
       "      <td>303.62</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.961</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1848.24</td>\n",
       "      <td>135.87</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.665</td>\n",
       "      <td>261.72</td>\n",
       "      <td>263.60</td>\n",
       "      <td>262.66</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.111</td>\n",
       "      <td>8.262</td>\n",
       "      <td>22.748</td>\n",
       "      <td>191.363</td>\n",
       "      <td>5507.00</td>\n",
       "      <td>377.20</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.355</td>\n",
       "      <td>97.88</td>\n",
       "      <td>99.75</td>\n",
       "      <td>98.82</td>\n",
       "      <td>1.875</td>\n",
       "      <td>976.56</td>\n",
       "      <td>2.935</td>\n",
       "      <td>9.305</td>\n",
       "      <td>63.355</td>\n",
       "      <td>60.616</td>\n",
       "      <td>2862.27</td>\n",
       "      <td>120.59</td>\n",
       "      <td>uid://A002/X327408/X100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>251.60</td>\n",
       "      <td>253.47</td>\n",
       "      <td>252.54</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.155</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5492.90</td>\n",
       "      <td>368.94</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>266.60</td>\n",
       "      <td>268.47</td>\n",
       "      <td>267.53</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.090</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5382.61</td>\n",
       "      <td>372.08</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>249.97</td>\n",
       "      <td>251.85</td>\n",
       "      <td>250.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.162</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5505.70</td>\n",
       "      <td>368.62</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>264.97</td>\n",
       "      <td>266.85</td>\n",
       "      <td>265.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.097</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5393.90</td>\n",
       "      <td>371.73</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.665</td>\n",
       "      <td>246.72</td>\n",
       "      <td>248.60</td>\n",
       "      <td>247.66</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.178</td>\n",
       "      <td>8.262</td>\n",
       "      <td>22.748</td>\n",
       "      <td>191.363</td>\n",
       "      <td>5623.83</td>\n",
       "      <td>374.09</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.665</td>\n",
       "      <td>248.35</td>\n",
       "      <td>250.22</td>\n",
       "      <td>249.29</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.170</td>\n",
       "      <td>8.262</td>\n",
       "      <td>22.748</td>\n",
       "      <td>191.363</td>\n",
       "      <td>5610.45</td>\n",
       "      <td>374.41</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>1336</td>\n",
       "      <td>2018.1.01395.S</td>\n",
       "      <td>NGC_253</td>\n",
       "      <td>11.888058</td>\n",
       "      <td>-25.288800</td>\n",
       "      <td>0.019</td>\n",
       "      <td>217.98</td>\n",
       "      <td>219.85</td>\n",
       "      <td>218.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>1128.91</td>\n",
       "      <td>1.539</td>\n",
       "      <td>0.500</td>\n",
       "      <td>25.549</td>\n",
       "      <td>12.404</td>\n",
       "      <td>398.35</td>\n",
       "      <td>24.92</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1336</th>\n",
       "      <td>1337</td>\n",
       "      <td>2018.1.01395.S</td>\n",
       "      <td>NGC_253</td>\n",
       "      <td>11.888058</td>\n",
       "      <td>-25.288800</td>\n",
       "      <td>0.019</td>\n",
       "      <td>235.98</td>\n",
       "      <td>237.85</td>\n",
       "      <td>236.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>1128.91</td>\n",
       "      <td>1.434</td>\n",
       "      <td>0.500</td>\n",
       "      <td>25.549</td>\n",
       "      <td>12.404</td>\n",
       "      <td>382.31</td>\n",
       "      <td>24.78</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>1338</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>108.29</td>\n",
       "      <td>110.16</td>\n",
       "      <td>109.23</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.366</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>468.79</td>\n",
       "      <td>20.59</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1338</th>\n",
       "      <td>1339</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>91.70</td>\n",
       "      <td>93.57</td>\n",
       "      <td>92.63</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.210</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>508.68</td>\n",
       "      <td>20.77</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1339</th>\n",
       "      <td>1340</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>97.97</td>\n",
       "      <td>99.84</td>\n",
       "      <td>98.90</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.820</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>507.47</td>\n",
       "      <td>21.40</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1340</th>\n",
       "      <td>1341</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>96.28</td>\n",
       "      <td>98.15</td>\n",
       "      <td>97.21</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.920</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>511.67</td>\n",
       "      <td>21.39</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1341</th>\n",
       "      <td>1342</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>108.87</td>\n",
       "      <td>110.74</td>\n",
       "      <td>109.80</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.338</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>799.25</td>\n",
       "      <td>35.19</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1342</th>\n",
       "      <td>1343</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>110.76</td>\n",
       "      <td>112.63</td>\n",
       "      <td>111.69</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.247</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>792.83</td>\n",
       "      <td>35.21</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1343</th>\n",
       "      <td>1344</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>98.49</td>\n",
       "      <td>100.36</td>\n",
       "      <td>99.42</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.791</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>976.30</td>\n",
       "      <td>41.27</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1344</th>\n",
       "      <td>1345</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>96.80</td>\n",
       "      <td>98.67</td>\n",
       "      <td>97.73</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.890</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>984.33</td>\n",
       "      <td>41.26</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1345</th>\n",
       "      <td>1346</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>103.38</td>\n",
       "      <td>105.26</td>\n",
       "      <td>104.32</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.621</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>461.89</td>\n",
       "      <td>19.82</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1346</th>\n",
       "      <td>1347</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>101.58</td>\n",
       "      <td>103.45</td>\n",
       "      <td>102.51</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.721</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>459.66</td>\n",
       "      <td>19.55</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1347</th>\n",
       "      <td>1348</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>91.51</td>\n",
       "      <td>93.39</td>\n",
       "      <td>92.45</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.223</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>480.47</td>\n",
       "      <td>19.59</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1348</th>\n",
       "      <td>1349</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>89.72</td>\n",
       "      <td>91.59</td>\n",
       "      <td>90.65</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.345</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>494.60</td>\n",
       "      <td>19.97</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1349</th>\n",
       "      <td>1350</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>89.43</td>\n",
       "      <td>91.30</td>\n",
       "      <td>90.36</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.364</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>466.81</td>\n",
       "      <td>18.82</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1350</th>\n",
       "      <td>1351</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>101.78</td>\n",
       "      <td>103.65</td>\n",
       "      <td>102.72</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.710</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>475.79</td>\n",
       "      <td>20.26</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>1352</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>108.65</td>\n",
       "      <td>110.52</td>\n",
       "      <td>109.59</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.349</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>960.67</td>\n",
       "      <td>42.25</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1352</th>\n",
       "      <td>1353</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>110.54</td>\n",
       "      <td>112.42</td>\n",
       "      <td>111.48</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.257</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>1131.63</td>\n",
       "      <td>50.21</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1353</th>\n",
       "      <td>1354</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>98.29</td>\n",
       "      <td>100.16</td>\n",
       "      <td>99.23</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.802</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>1007.18</td>\n",
       "      <td>42.54</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1354</th>\n",
       "      <td>1355</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>103.05</td>\n",
       "      <td>104.92</td>\n",
       "      <td>103.99</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.639</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>436.95</td>\n",
       "      <td>18.72</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1355</th>\n",
       "      <td>1356</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>91.20</td>\n",
       "      <td>93.07</td>\n",
       "      <td>92.13</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.243</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>459.55</td>\n",
       "      <td>18.71</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>1357</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>101.24</td>\n",
       "      <td>103.11</td>\n",
       "      <td>102.18</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.740</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>437.00</td>\n",
       "      <td>18.56</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1357</th>\n",
       "      <td>1358</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>96.60</td>\n",
       "      <td>98.47</td>\n",
       "      <td>97.53</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.902</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>1015.52</td>\n",
       "      <td>42.52</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1358</th>\n",
       "      <td>1359</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>103.59</td>\n",
       "      <td>105.46</td>\n",
       "      <td>104.52</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.610</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>478.30</td>\n",
       "      <td>20.54</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>1360</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>89.90</td>\n",
       "      <td>91.77</td>\n",
       "      <td>90.84</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.332</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>513.50</td>\n",
       "      <td>20.76</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>1361</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>110.17</td>\n",
       "      <td>112.05</td>\n",
       "      <td>111.11</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.274</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>465.01</td>\n",
       "      <td>20.60</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1361 rows × 18 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Obs    project_code ALMA_source_name     RAJ2000    DEJ2000  ang_res_arcsec  ...  LAS_arcsec  FoV_arcsec  cont_sens_bandwidth  line_sens_10kms  line_sens_native                  MOUS_id\n",
       "0        1  2011.0.00268.S  LESS J0332-2756   53.122042 -27.938694           1.167  ...       8.943      23.564               79.299          1708.54            111.94   uid://A002/X303d22/X7b\n",
       "1        2  2011.0.00268.S  LESS J0332-2756   53.122042 -27.938694           1.167  ...       8.943      23.564               79.299          1675.07            112.74   uid://A002/X303d22/X7b\n",
       "2        3  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           1.331  ...      12.937      58.774               29.824          1370.09             59.71   uid://A002/X36d874/X80\n",
       "3        4  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.455  ...       3.448      20.113               60.429          1673.64            119.28   uid://A002/X36d874/X7a\n",
       "4        5  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.455  ...       3.448      20.113               60.429          1677.23            119.14   uid://A002/X36d874/X7a\n",
       "5        6  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           1.331  ...      12.937      58.774               29.824          1381.77             59.69   uid://A002/X36d874/X80\n",
       "6        7  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.563  ...       5.088      23.118               74.597          2278.21            154.60   uid://A002/X36d874/X7c\n",
       "7        8  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.442  ...       4.104      19.504               68.197          1867.41            134.98   uid://A002/X36d874/X7e\n",
       "8        9  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           1.331  ...      12.937      58.774               29.824          1500.60             61.02   uid://A002/X36d874/X80\n",
       "9       10  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.563  ...       5.088      23.118               74.597          2189.73            147.77   uid://A002/X36d874/X7c\n",
       "10      11  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.563  ...       5.088      23.118               74.597          2229.45            146.80   uid://A002/X36d874/X7c\n",
       "11      12  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.455  ...       3.448      20.113               60.429          1735.78            126.28   uid://A002/X36d874/X7a\n",
       "12      13  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.455  ...       3.448      20.113               60.429          1655.25            120.04   uid://A002/X36d874/X7a\n",
       "13      14  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.563  ...       5.088      23.118               74.597          2229.83            146.24   uid://A002/X36d874/X7c\n",
       "14      15  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.442  ...       4.104      19.504               68.197          1868.50            137.78   uid://A002/X36d874/X7e\n",
       "15      16  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           1.331  ...      12.937      58.774               29.824          1440.54             59.16   uid://A002/X36d874/X80\n",
       "16      17  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.442  ...       4.104      19.504               68.197          1903.65            137.16   uid://A002/X36d874/X7e\n",
       "17      18  2011.0.00405.S      PKS1830-211  278.416330 -21.061080           0.442  ...       4.104      19.504               68.197          1848.24            135.87   uid://A002/X36d874/X7e\n",
       "18      19  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.665  ...       8.262      22.748              191.363          5507.00            377.20  uid://A002/X314ea1/X1fa\n",
       "19      20  2011.0.00820.S          ngc4418  186.727617  -0.877642           1.355  ...       9.305      63.355               60.616          2862.27            120.59  uid://A002/X327408/X100\n",
       "20      21  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.657  ...       8.158      22.463              184.788          5492.90            368.94  uid://A002/X314ea1/X1ee\n",
       "21      22  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.657  ...       8.158      22.463              184.788          5382.61            372.08  uid://A002/X314ea1/X1ee\n",
       "22      23  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.657  ...       8.158      22.463              184.788          5505.70            368.62  uid://A002/X314ea1/X1ee\n",
       "23      24  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.657  ...       8.158      22.463              184.788          5393.90            371.73  uid://A002/X314ea1/X1ee\n",
       "24      25  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.665  ...       8.262      22.748              191.363          5623.83            374.09  uid://A002/X314ea1/X1fa\n",
       "25      26  2011.0.00820.S          ngc4418  186.727617  -0.877642           0.665  ...       8.262      22.748              191.363          5610.45            374.41  uid://A002/X314ea1/X1fa\n",
       "...    ...             ...              ...         ...        ...             ...  ...         ...         ...                  ...              ...               ...                      ...\n",
       "1335  1336  2018.1.01395.S          NGC_253   11.888058 -25.288800           0.019  ...       0.500      25.549               12.404           398.35             24.92   uid://A001/X133d/X3025\n",
       "1336  1337  2018.1.01395.S          NGC_253   11.888058 -25.288800           0.019  ...       0.500      25.549               12.404           382.31             24.78   uid://A001/X133d/X3025\n",
       "1337  1338  2019.1.00130.S          NGC4418  186.727617  -0.877642           1.357  ...      24.940      55.903               10.485           468.79             20.59   uid://A001/X1465/X389c\n",
       "1338  1339  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.523  ...      27.132      59.612               10.282           508.68             20.77   uid://A001/X1465/X3888\n",
       "1339  1340  2019.1.00130.S          NGC4418  186.727617  -0.877642           1.357  ...      24.940      55.903               10.485           507.47             21.40   uid://A001/X1465/X389c\n",
       "1340  1341  2019.1.00130.S          NGC4418  186.727617  -0.877642           1.357  ...      24.940      55.903               10.485           511.67             21.39   uid://A001/X1465/X389c\n",
       "1341  1342  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.309  ...      22.321      55.608               18.936           799.25             35.19   uid://A001/X1465/X388c\n",
       "1342  1343  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.309  ...      22.321      55.608               18.936           792.83             35.21   uid://A001/X1465/X388c\n",
       "1343  1344  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.309  ...      22.321      55.608               18.936           976.30             41.27   uid://A001/X1465/X388c\n",
       "1344  1345  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.309  ...      22.321      55.608               18.936           984.33             41.26   uid://A001/X1465/X388c\n",
       "1345  1346  2019.1.00130.S          NGC1068   40.669879  -0.013289           1.609  ...      20.838      59.730                9.858           461.89             19.82   uid://A001/X1465/X3890\n",
       "1346  1347  2019.1.00130.S          NGC1068   40.669879  -0.013289           1.609  ...      20.838      59.730                9.858           459.66             19.55   uid://A001/X1465/X3890\n",
       "1347  1348  2019.1.00130.S          NGC1068   40.669879  -0.013289           1.609  ...      20.838      59.730                9.858           480.47             19.59   uid://A001/X1465/X3890\n",
       "1348  1349  2019.1.00130.S          NGC1068   40.669879  -0.013289           1.609  ...      20.838      59.730                9.858           494.60             19.97   uid://A001/X1465/X3890\n",
       "1349  1350  2019.1.00130.S          NGC4418  186.727617  -0.877642           2.537  ...      27.048      59.922                9.343           466.81             18.82   uid://A001/X1465/X3898\n",
       "1350  1351  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.523  ...      27.132      59.612               10.282           475.79             20.26   uid://A001/X1465/X3888\n",
       "1351  1352  2019.1.00130.S          NGC1068   40.669879  -0.013289           2.247  ...      21.118      55.719               21.996           960.67             42.25   uid://A001/X1465/X3894\n",
       "1352  1353  2019.1.00130.S          NGC1068   40.669879  -0.013289           2.247  ...      21.118      55.719               21.996          1131.63             50.21   uid://A001/X1465/X3894\n",
       "1353  1354  2019.1.00130.S          NGC1068   40.669879  -0.013289           2.247  ...      21.118      55.719               21.996          1007.18             42.54   uid://A001/X1465/X3894\n",
       "1354  1355  2019.1.00130.S          NGC4418  186.727617  -0.877642           2.537  ...      27.048      59.922                9.343           436.95             18.72   uid://A001/X1465/X3898\n",
       "1355  1356  2019.1.00130.S          NGC4418  186.727617  -0.877642           2.537  ...      27.048      59.922                9.343           459.55             18.71   uid://A001/X1465/X3898\n",
       "1356  1357  2019.1.00130.S          NGC4418  186.727617  -0.877642           2.537  ...      27.048      59.922                9.343           437.00             18.56   uid://A001/X1465/X3898\n",
       "1357  1358  2019.1.00130.S          NGC1068   40.669879  -0.013289           2.247  ...      21.118      55.719               21.996          1015.52             42.52   uid://A001/X1465/X3894\n",
       "1358  1359  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.523  ...      27.132      59.612               10.282           478.30             20.54   uid://A001/X1465/X3888\n",
       "1359  1360  2019.1.00130.S          NGC4945  196.363663 -49.467900           2.523  ...      27.132      59.612               10.282           513.50             20.76   uid://A001/X1465/X3888\n",
       "1360  1361  2019.1.00130.S          NGC4418  186.727617  -0.877642           1.357  ...      24.940      55.903               10.485           465.01             20.60   uid://A001/X1465/X389c\n",
       "\n",
       "[1361 rows x 18 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alminer.explore(observations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.1.2: View the queried observations as a table and show all columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Obs</th>\n",
       "      <th>project_code</th>\n",
       "      <th>ALMA_source_name</th>\n",
       "      <th>RAJ2000</th>\n",
       "      <th>DEJ2000</th>\n",
       "      <th>ang_res_arcsec</th>\n",
       "      <th>min_freq_GHz</th>\n",
       "      <th>max_freq_GHz</th>\n",
       "      <th>central_freq_GHz</th>\n",
       "      <th>bandwidth_GHz</th>\n",
       "      <th>freq_res_kHz</th>\n",
       "      <th>vel_res_kms</th>\n",
       "      <th>LAS_arcsec</th>\n",
       "      <th>FoV_arcsec</th>\n",
       "      <th>cont_sens_bandwidth</th>\n",
       "      <th>line_sens_10kms</th>\n",
       "      <th>line_sens_native</th>\n",
       "      <th>MOUS_id</th>\n",
       "      <th>access_url</th>\n",
       "      <th>access_format</th>\n",
       "      <th>proposal_id</th>\n",
       "      <th>data_rights</th>\n",
       "      <th>gal_longitude</th>\n",
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       "      <th>target_name</th>\n",
       "      <th>s_ra</th>\n",
       "      <th>s_dec</th>\n",
       "      <th>s_fov</th>\n",
       "      <th>s_region</th>\n",
       "      <th>s_resolution</th>\n",
       "      <th>t_min</th>\n",
       "      <th>t_max</th>\n",
       "      <th>t_exptime</th>\n",
       "      <th>t_resolution</th>\n",
       "      <th>em_min</th>\n",
       "      <th>em_max</th>\n",
       "      <th>em_res_power</th>\n",
       "      <th>pol_states</th>\n",
       "      <th>o_ucd</th>\n",
       "      <th>band_list</th>\n",
       "      <th>em_resolution</th>\n",
       "      <th>authors</th>\n",
       "      <th>pub_abstract</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>proposal_abstract</th>\n",
       "      <th>schedblock_name</th>\n",
       "      <th>proposal_authors</th>\n",
       "      <th>sensitivity_10kms</th>\n",
       "      <th>cont_sensitivity_bandwidth</th>\n",
       "      <th>pwv</th>\n",
       "      <th>group_ous_uid</th>\n",
       "      <th>member_ous_uid</th>\n",
       "      <th>asdm_uid</th>\n",
       "      <th>obs_title</th>\n",
       "      <th>type</th>\n",
       "      <th>scan_intent</th>\n",
       "      <th>science_observation</th>\n",
       "      <th>spatial_scale_max</th>\n",
       "      <th>bandwidth</th>\n",
       "      <th>antenna_arrays</th>\n",
       "      <th>is_mosaic</th>\n",
       "      <th>obs_release_date</th>\n",
       "      <th>spatial_resolution</th>\n",
       "      <th>frequency_support</th>\n",
       "      <th>frequency</th>\n",
       "      <th>velocity_resolution</th>\n",
       "      <th>obs_creator_name</th>\n",
       "      <th>pub_title</th>\n",
       "      <th>first_author</th>\n",
       "      <th>qa2_passed</th>\n",
       "      <th>bib_reference</th>\n",
       "      <th>science_keyword</th>\n",
       "      <th>scientific_category</th>\n",
       "      <th>lastModified</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011.0.00268.S</td>\n",
       "      <td>LESS J0332-2756</td>\n",
       "      <td>53.122042</td>\n",
       "      <td>-27.938694</td>\n",
       "      <td>1.167</td>\n",
       "      <td>239.50</td>\n",
       "      <td>241.37</td>\n",
       "      <td>240.43</td>\n",
       "      <td>1.875</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.213</td>\n",
       "      <td>8.943</td>\n",
       "      <td>23.564</td>\n",
       "      <td>79.299</td>\n",
       "      <td>1708.54</td>\n",
       "      <td>111.94</td>\n",
       "      <td>uid://A002/X303d22/X7b</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00268.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>223.796062</td>\n",
       "      <td>-54.451922</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00268.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X303d22/X7b</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>LESS J0332-2756</td>\n",
       "      <td>53.122042</td>\n",
       "      <td>-27.938694</td>\n",
       "      <td>0.006546</td>\n",
       "      <td>Circle ICRS 53.122042 -27.938694 0.003273</td>\n",
       "      <td>1.167248</td>\n",
       "      <td>55936.913188</td>\n",
       "      <td>55939.193372</td>\n",
       "      <td>4536.000</td>\n",
       "      <td>4536.000</td>\n",
       "      <td>0.001242</td>\n",
       "      <td>0.001252</td>\n",
       "      <td>247134.408560</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.928016e+14</td>\n",
       "      <td>Leon, S.; Cortes, P.C.; Guerard, M.; Villard, ...</td>\n",
       "      <td>Aims: We aim at analyzing the (sub-)millimeter...</td>\n",
       "      <td>2012</td>\n",
       "      <td>Metallicity of galaxies and its redshift evolu...</td>\n",
       "      <td>LESS J0332-2756</td>\n",
       "      <td>De Breuck, Carlos; Hatsukade, Bunyo; Maiolino,...</td>\n",
       "      <td>1.708538</td>\n",
       "      <td>0.079299</td>\n",
       "      <td>1.422843</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X303d22/X7b</td>\n",
       "      <td>uid://A002/X36a70f/X318</td>\n",
       "      <td>Metallicity of a Submillimeter Galaxy at z=5</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET WVR</td>\n",
       "      <td>T</td>\n",
       "      <td>8.943092</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A002:PM02 A004:DV04 A009:DA43 A011:DV12 A013:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-02-09T01:45:00.000</td>\n",
       "      <td>1.167248</td>\n",
       "      <td>[239.50..241.37GHz,976.56kHz,1.7mJy/beam@10km/...</td>\n",
       "      <td>247.112856</td>\n",
       "      <td>1149.468553</td>\n",
       "      <td>Nagao, Tohru</td>\n",
       "      <td>ALMA reveals a chemically evolved submillimete...</td>\n",
       "      <td>Leon, S. Nagao, T. Ono, Yoshiaki</td>\n",
       "      <td>T</td>\n",
       "      <td>2012A&amp;A...542L..34N 2014ApJ...795....5O 2016A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
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       "      <td>LESS J0332-2756</td>\n",
       "      <td>53.122042</td>\n",
       "      <td>-27.938694</td>\n",
       "      <td>1.167</td>\n",
       "      <td>252.85</td>\n",
       "      <td>254.73</td>\n",
       "      <td>253.79</td>\n",
       "      <td>1.875</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.149</td>\n",
       "      <td>8.943</td>\n",
       "      <td>23.564</td>\n",
       "      <td>79.299</td>\n",
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       "      <td>112.74</td>\n",
       "      <td>uid://A002/X303d22/X7b</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00268.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>223.796062</td>\n",
       "      <td>-54.451922</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00268.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X303d22/X7b</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>LESS J0332-2756</td>\n",
       "      <td>53.122042</td>\n",
       "      <td>-27.938694</td>\n",
       "      <td>0.006546</td>\n",
       "      <td>Circle ICRS 53.122042 -27.938694 0.003273</td>\n",
       "      <td>1.167248</td>\n",
       "      <td>55936.913188</td>\n",
       "      <td>55939.193372</td>\n",
       "      <td>4536.000</td>\n",
       "      <td>4536.000</td>\n",
       "      <td>0.001177</td>\n",
       "      <td>0.001186</td>\n",
       "      <td>260809.621360</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.928016e+14</td>\n",
       "      <td>Leon, S.; Cortes, P.C.; Guerard, M.; Villard, ...</td>\n",
       "      <td>Aims: We aim at analyzing the (sub-)millimeter...</td>\n",
       "      <td>2012</td>\n",
       "      <td>Metallicity of galaxies and its redshift evolu...</td>\n",
       "      <td>LESS J0332-2756</td>\n",
       "      <td>De Breuck, Carlos; Hatsukade, Bunyo; Maiolino,...</td>\n",
       "      <td>1.675071</td>\n",
       "      <td>0.079299</td>\n",
       "      <td>1.422843</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X303d22/X7b</td>\n",
       "      <td>uid://A002/X36a70f/X318</td>\n",
       "      <td>Metallicity of a Submillimeter Galaxy at z=5</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET WVR</td>\n",
       "      <td>T</td>\n",
       "      <td>8.943092</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A002:PM02 A004:DV04 A009:DA43 A011:DV12 A013:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-02-09T01:45:00.000</td>\n",
       "      <td>1.167248</td>\n",
       "      <td>[239.50..241.37GHz,976.56kHz,1.7mJy/beam@10km/...</td>\n",
       "      <td>247.112856</td>\n",
       "      <td>1149.468553</td>\n",
       "      <td>Nagao, Tohru</td>\n",
       "      <td>ALMA reveals a chemically evolved submillimete...</td>\n",
       "      <td>Leon, S. Nagao, T. Ono, Yoshiaki</td>\n",
       "      <td>T</td>\n",
       "      <td>2012A&amp;A...542L..34N 2014ApJ...795....5O 2016A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>1.331</td>\n",
       "      <td>105.07</td>\n",
       "      <td>106.95</td>\n",
       "      <td>106.01</td>\n",
       "      <td>1.878</td>\n",
       "      <td>976.56</td>\n",
       "      <td>2.737</td>\n",
       "      <td>12.937</td>\n",
       "      <td>58.774</td>\n",
       "      <td>29.824</td>\n",
       "      <td>1370.09</td>\n",
       "      <td>59.71</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.016326</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.008163</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>56069.374548</td>\n",
       "      <td>56093.397660</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>0.002803</td>\n",
       "      <td>0.002853</td>\n",
       "      <td>109524.742000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_HCOplus_b3_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.370093</td>\n",
       "      <td>0.029824</td>\n",
       "      <td>0.923567</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>uid://A002/X411025/X441</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>12.936728</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-10T14:47:51.000</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>[91.20..93.08GHz,976.56kHz,1.5mJy/beam@10km/s,...</td>\n",
       "      <td>99.075504</td>\n",
       "      <td>2737.212182</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.455</td>\n",
       "      <td>283.51</td>\n",
       "      <td>285.39</td>\n",
       "      <td>284.45</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.026</td>\n",
       "      <td>3.448</td>\n",
       "      <td>20.113</td>\n",
       "      <td>60.429</td>\n",
       "      <td>1673.64</td>\n",
       "      <td>119.28</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005587</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002793</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>56028.238332</td>\n",
       "      <td>56028.363572</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>0.001050</td>\n",
       "      <td>0.001057</td>\n",
       "      <td>292274.950000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927253e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CH_and_H2O_b7_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.673643</td>\n",
       "      <td>0.060429</td>\n",
       "      <td>0.703871</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>uid://A002/X3cb0a0/X9e8</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>3.448268</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A011:DV12 A025:DV14 A037:PM01 A045:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-05-22T07:31:59.000</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>[281.64..283.51GHz,976.56kHz,1.7mJy/beam@10km/...</td>\n",
       "      <td>289.509775</td>\n",
       "      <td>984.336598</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.455</td>\n",
       "      <td>281.64</td>\n",
       "      <td>283.51</td>\n",
       "      <td>282.57</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.033</td>\n",
       "      <td>3.448</td>\n",
       "      <td>20.113</td>\n",
       "      <td>60.429</td>\n",
       "      <td>1677.23</td>\n",
       "      <td>119.14</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005587</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002793</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>56028.238332</td>\n",
       "      <td>56028.363572</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>0.001057</td>\n",
       "      <td>0.001064</td>\n",
       "      <td>290354.950000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927253e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CH_and_H2O_b7_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.677226</td>\n",
       "      <td>0.060429</td>\n",
       "      <td>0.703871</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>uid://A002/X3cb0a0/X9e8</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>3.448268</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A011:DV12 A025:DV14 A037:PM01 A045:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-05-22T07:31:59.000</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>[281.64..283.51GHz,976.56kHz,1.7mJy/beam@10km/...</td>\n",
       "      <td>289.509775</td>\n",
       "      <td>984.336598</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>1.331</td>\n",
       "      <td>103.20</td>\n",
       "      <td>105.08</td>\n",
       "      <td>104.14</td>\n",
       "      <td>1.878</td>\n",
       "      <td>976.56</td>\n",
       "      <td>2.786</td>\n",
       "      <td>12.937</td>\n",
       "      <td>58.774</td>\n",
       "      <td>29.824</td>\n",
       "      <td>1381.77</td>\n",
       "      <td>59.69</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.016326</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.008163</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>56069.374548</td>\n",
       "      <td>56093.397660</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>0.002853</td>\n",
       "      <td>0.002905</td>\n",
       "      <td>107605.766000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_HCOplus_b3_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.381767</td>\n",
       "      <td>0.029824</td>\n",
       "      <td>0.923567</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>uid://A002/X411025/X441</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>12.936728</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-10T14:47:51.000</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>[91.20..93.08GHz,976.56kHz,1.5mJy/beam@10km/s,...</td>\n",
       "      <td>99.075504</td>\n",
       "      <td>2737.212182</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>259.58</td>\n",
       "      <td>261.47</td>\n",
       "      <td>260.52</td>\n",
       "      <td>1.894</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.120</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2278.21</td>\n",
       "      <td>154.60</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.006422</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.003211</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>56026.250749</td>\n",
       "      <td>56093.330969</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>0.001147</td>\n",
       "      <td>0.001155</td>\n",
       "      <td>267762.499440</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927251e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830-211_CO4-3_b6_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>2.278214</td>\n",
       "      <td>0.074597</td>\n",
       "      <td>2.122151</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>uid://A002/X3ca066/Xa6f</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>5.088294</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-19T12:40:13.000</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>[242.31..244.20GHz,976.56kHz,2.2mJy/beam@10km/...</td>\n",
       "      <td>251.884124</td>\n",
       "      <td>1119.620778</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>292.55</td>\n",
       "      <td>294.43</td>\n",
       "      <td>293.49</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.994</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1867.41</td>\n",
       "      <td>134.98</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005418</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002709</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>56070.225109</td>\n",
       "      <td>56082.381661</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>0.001018</td>\n",
       "      <td>0.001025</td>\n",
       "      <td>301521.659760</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CO5-4_b7_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.867413</td>\n",
       "      <td>0.068197</td>\n",
       "      <td>1.027013</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>uid://A002/X4122f3/X133</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>4.104185</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A011:DV12 A021:DV08 A025:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-07-05T11:49:39.000</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>[290.68..292.56GHz,976.56kHz,1.9mJy/beam@10km/...</td>\n",
       "      <td>298.550728</td>\n",
       "      <td>955.332153</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>1.331</td>\n",
       "      <td>91.20</td>\n",
       "      <td>93.08</td>\n",
       "      <td>92.14</td>\n",
       "      <td>1.878</td>\n",
       "      <td>976.56</td>\n",
       "      <td>3.145</td>\n",
       "      <td>12.937</td>\n",
       "      <td>58.774</td>\n",
       "      <td>29.824</td>\n",
       "      <td>1500.60</td>\n",
       "      <td>61.02</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.016326</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.008163</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>56069.374548</td>\n",
       "      <td>56093.397660</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>0.003221</td>\n",
       "      <td>0.003287</td>\n",
       "      <td>95317.766000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_HCOplus_b3_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.500603</td>\n",
       "      <td>0.029824</td>\n",
       "      <td>0.923567</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>uid://A002/X411025/X441</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>12.936728</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-10T14:47:51.000</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>[91.20..93.08GHz,976.56kHz,1.5mJy/beam@10km/s,...</td>\n",
       "      <td>99.075504</td>\n",
       "      <td>2737.212182</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>256.63</td>\n",
       "      <td>258.53</td>\n",
       "      <td>257.58</td>\n",
       "      <td>1.894</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.132</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2189.73</td>\n",
       "      <td>147.77</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.006422</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.003211</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>56026.250749</td>\n",
       "      <td>56093.330969</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>0.001160</td>\n",
       "      <td>0.001168</td>\n",
       "      <td>264749.082480</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927251e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830-211_CO4-3_b6_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>2.189729</td>\n",
       "      <td>0.074597</td>\n",
       "      <td>2.122151</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>uid://A002/X3ca066/Xa6f</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>5.088294</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-19T12:40:13.000</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>[242.31..244.20GHz,976.56kHz,2.2mJy/beam@10km/...</td>\n",
       "      <td>251.884124</td>\n",
       "      <td>1119.620778</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>244.13</td>\n",
       "      <td>246.02</td>\n",
       "      <td>245.08</td>\n",
       "      <td>1.893</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.190</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2229.45</td>\n",
       "      <td>146.80</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.006422</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.003211</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>56026.250749</td>\n",
       "      <td>56093.330969</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>0.001219</td>\n",
       "      <td>0.001228</td>\n",
       "      <td>251943.624560</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927251e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830-211_CO4-3_b6_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>2.229454</td>\n",
       "      <td>0.074597</td>\n",
       "      <td>2.122151</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>uid://A002/X3ca066/Xa6f</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>5.088294</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-19T12:40:13.000</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>[242.31..244.20GHz,976.56kHz,2.2mJy/beam@10km/...</td>\n",
       "      <td>251.884124</td>\n",
       "      <td>1119.620778</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.455</td>\n",
       "      <td>295.51</td>\n",
       "      <td>297.38</td>\n",
       "      <td>296.45</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.984</td>\n",
       "      <td>3.448</td>\n",
       "      <td>20.113</td>\n",
       "      <td>60.429</td>\n",
       "      <td>1735.78</td>\n",
       "      <td>126.28</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005587</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002793</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>56028.238332</td>\n",
       "      <td>56028.363572</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>0.001008</td>\n",
       "      <td>0.001014</td>\n",
       "      <td>304562.950000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927253e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CH_and_H2O_b7_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.735785</td>\n",
       "      <td>0.060429</td>\n",
       "      <td>0.703871</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>uid://A002/X3cb0a0/X9e8</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>3.448268</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A011:DV12 A025:DV14 A037:PM01 A045:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-05-22T07:31:59.000</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>[281.64..283.51GHz,976.56kHz,1.7mJy/beam@10km/...</td>\n",
       "      <td>289.509775</td>\n",
       "      <td>984.336598</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.455</td>\n",
       "      <td>293.63</td>\n",
       "      <td>295.51</td>\n",
       "      <td>294.57</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.991</td>\n",
       "      <td>3.448</td>\n",
       "      <td>20.113</td>\n",
       "      <td>60.429</td>\n",
       "      <td>1655.25</td>\n",
       "      <td>120.04</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005587</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002793</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>56028.238332</td>\n",
       "      <td>56028.363572</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>3144.960</td>\n",
       "      <td>0.001014</td>\n",
       "      <td>0.001021</td>\n",
       "      <td>302642.950000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927253e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CH_and_H2O_b7_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.655253</td>\n",
       "      <td>0.060429</td>\n",
       "      <td>0.703871</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7a</td>\n",
       "      <td>uid://A002/X3cb0a0/X9e8</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>3.448268</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A011:DV12 A025:DV14 A037:PM01 A045:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-05-22T07:31:59.000</td>\n",
       "      <td>0.454758</td>\n",
       "      <td>[281.64..283.51GHz,976.56kHz,1.7mJy/beam@10km/...</td>\n",
       "      <td>289.509775</td>\n",
       "      <td>984.336598</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.563</td>\n",
       "      <td>242.31</td>\n",
       "      <td>244.20</td>\n",
       "      <td>243.25</td>\n",
       "      <td>1.894</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.199</td>\n",
       "      <td>5.088</td>\n",
       "      <td>23.118</td>\n",
       "      <td>74.597</td>\n",
       "      <td>2229.83</td>\n",
       "      <td>146.24</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.006422</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.003211</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>56026.250749</td>\n",
       "      <td>56093.330969</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>4838.400</td>\n",
       "      <td>0.001228</td>\n",
       "      <td>0.001237</td>\n",
       "      <td>250078.682480</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927251e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830-211_CO4-3_b6_run_x2</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>2.229828</td>\n",
       "      <td>0.074597</td>\n",
       "      <td>2.122151</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7c</td>\n",
       "      <td>uid://A002/X3ca066/Xa6f</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>5.088294</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-19T12:40:13.000</td>\n",
       "      <td>0.562899</td>\n",
       "      <td>[242.31..244.20GHz,976.56kHz,2.2mJy/beam@10km/...</td>\n",
       "      <td>251.884124</td>\n",
       "      <td>1119.620778</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>304.55</td>\n",
       "      <td>306.43</td>\n",
       "      <td>305.49</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.955</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1868.50</td>\n",
       "      <td>137.78</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005418</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002709</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>56070.225109</td>\n",
       "      <td>56082.381661</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>0.000978</td>\n",
       "      <td>0.000984</td>\n",
       "      <td>313809.659760</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CO5-4_b7_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.868498</td>\n",
       "      <td>0.068197</td>\n",
       "      <td>1.027013</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>uid://A002/X4122f3/X133</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>4.104185</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A011:DV12 A021:DV08 A025:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-07-05T11:49:39.000</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>[290.68..292.56GHz,976.56kHz,1.9mJy/beam@10km/...</td>\n",
       "      <td>298.550728</td>\n",
       "      <td>955.332153</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>1.331</td>\n",
       "      <td>93.07</td>\n",
       "      <td>94.95</td>\n",
       "      <td>94.01</td>\n",
       "      <td>1.878</td>\n",
       "      <td>976.56</td>\n",
       "      <td>3.083</td>\n",
       "      <td>12.937</td>\n",
       "      <td>58.774</td>\n",
       "      <td>29.824</td>\n",
       "      <td>1440.54</td>\n",
       "      <td>59.16</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.016326</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.008163</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>56069.374548</td>\n",
       "      <td>56093.397660</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>3719.520</td>\n",
       "      <td>0.003157</td>\n",
       "      <td>0.003221</td>\n",
       "      <td>97236.742000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_HCOplus_b3_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.440543</td>\n",
       "      <td>0.029824</td>\n",
       "      <td>0.923567</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X80</td>\n",
       "      <td>uid://A002/X411025/X441</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>12.936728</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A008:DV19 A011:DV12 A021:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-10-10T14:47:51.000</td>\n",
       "      <td>1.331051</td>\n",
       "      <td>[91.20..93.08GHz,976.56kHz,1.5mJy/beam@10km/s,...</td>\n",
       "      <td>99.075504</td>\n",
       "      <td>2737.212182</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>290.68</td>\n",
       "      <td>292.56</td>\n",
       "      <td>291.62</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.001</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1903.65</td>\n",
       "      <td>137.16</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005418</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002709</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>56070.225109</td>\n",
       "      <td>56082.381661</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>0.001025</td>\n",
       "      <td>0.001031</td>\n",
       "      <td>299601.659760</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CO5-4_b7_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.903645</td>\n",
       "      <td>0.068197</td>\n",
       "      <td>1.027013</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>uid://A002/X4122f3/X133</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>4.104185</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A011:DV12 A021:DV08 A025:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-07-05T11:49:39.000</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>[290.68..292.56GHz,976.56kHz,1.9mJy/beam@10km/...</td>\n",
       "      <td>298.550728</td>\n",
       "      <td>955.332153</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.442</td>\n",
       "      <td>302.68</td>\n",
       "      <td>304.56</td>\n",
       "      <td>303.62</td>\n",
       "      <td>1.880</td>\n",
       "      <td>976.56</td>\n",
       "      <td>0.961</td>\n",
       "      <td>4.104</td>\n",
       "      <td>19.504</td>\n",
       "      <td>68.197</td>\n",
       "      <td>1848.24</td>\n",
       "      <td>135.87</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00405.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>12.165817</td>\n",
       "      <td>-5.711677</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00405.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>PKS1830-211</td>\n",
       "      <td>278.416330</td>\n",
       "      <td>-21.061080</td>\n",
       "      <td>0.005418</td>\n",
       "      <td>Circle ICRS 278.416330 -21.061080 0.002709</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>56070.225109</td>\n",
       "      <td>56082.381661</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>6048.000</td>\n",
       "      <td>0.000984</td>\n",
       "      <td>0.000990</td>\n",
       "      <td>311889.659760</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>7</td>\n",
       "      <td>2.927369e+14</td>\n",
       "      <td>Bagdonaite, J.; Daprà, M.; Jansen, P.; Bethlem...</td>\n",
       "      <td>A limit on a possible cosmological variation o...</td>\n",
       "      <td>2013</td>\n",
       "      <td>The z=0.89 (sub)mm molecular absorber toward t...</td>\n",
       "      <td>PKS1830_CO5-4_b7_run_x3</td>\n",
       "      <td>Bethlem, Hendrick; Gerin, Maryvonne; Bottinell...</td>\n",
       "      <td>1.848243</td>\n",
       "      <td>0.068197</td>\n",
       "      <td>1.027013</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X36d874/X7e</td>\n",
       "      <td>uid://A002/X4122f3/X133</td>\n",
       "      <td>A survey of strong absorption lines at z=0.89 ...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>4.104185</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A004:DV04 A011:DV12 A021:DV08 A025:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-07-05T11:49:39.000</td>\n",
       "      <td>0.441708</td>\n",
       "      <td>[290.68..292.56GHz,976.56kHz,1.9mJy/beam@10km/...</td>\n",
       "      <td>298.550728</td>\n",
       "      <td>955.332153</td>\n",
       "      <td>Muller, Sebastien</td>\n",
       "      <td>A strong magnetic field in the jet base of a s...</td>\n",
       "      <td>Bagdonaite, J. Martí-Vidal, I. Martí-Vidal, Iv...</td>\n",
       "      <td>T</td>\n",
       "      <td>2013A&amp;A...558A.123M 2013PhRvL.111w1101B 2014A&amp;...</td>\n",
       "      <td>Galaxy structure &amp; evolution, Galaxy chemistry</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.665</td>\n",
       "      <td>261.72</td>\n",
       "      <td>263.60</td>\n",
       "      <td>262.66</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.111</td>\n",
       "      <td>8.262</td>\n",
       "      <td>22.748</td>\n",
       "      <td>191.363</td>\n",
       "      <td>5507.00</td>\n",
       "      <td>377.20</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006319</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003159</td>\n",
       "      <td>0.664926</td>\n",
       "      <td>56293.314401</td>\n",
       "      <td>56293.327148</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001137</td>\n",
       "      <td>0.001145</td>\n",
       "      <td>269951.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927348e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 12</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.507000</td>\n",
       "      <td>0.191363</td>\n",
       "      <td>2.751811</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>uid://A002/X590461/X17e6</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.261900</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-01-18T12:52:22.000</td>\n",
       "      <td>0.664926</td>\n",
       "      <td>[246.72..248.60GHz,976.56kHz,5.6mJy/beam@10km/...</td>\n",
       "      <td>255.972659</td>\n",
       "      <td>1103.737386</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.355</td>\n",
       "      <td>97.88</td>\n",
       "      <td>99.75</td>\n",
       "      <td>98.82</td>\n",
       "      <td>1.875</td>\n",
       "      <td>976.56</td>\n",
       "      <td>2.935</td>\n",
       "      <td>9.305</td>\n",
       "      <td>63.355</td>\n",
       "      <td>60.616</td>\n",
       "      <td>2862.27</td>\n",
       "      <td>120.59</td>\n",
       "      <td>uid://A002/X327408/X100</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X327408/X100</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.017599</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.008799</td>\n",
       "      <td>1.354752</td>\n",
       "      <td>56042.089628</td>\n",
       "      <td>56042.109167</td>\n",
       "      <td>332.640</td>\n",
       "      <td>332.640</td>\n",
       "      <td>0.003005</td>\n",
       "      <td>0.003063</td>\n",
       "      <td>102143.801200</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>2.927779e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B3 Setup 1: Run x 1</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>2.862267</td>\n",
       "      <td>0.060616</td>\n",
       "      <td>2.623814</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X327408/X100</td>\n",
       "      <td>uid://A002/X3e3a61/Xce</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>9.304600</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A003:DA41 A021:DV08 A025:DV14 A045:DV11 A046:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2013-06-15T09:26:34.000</td>\n",
       "      <td>1.354752</td>\n",
       "      <td>[84.07..85.94GHz,976.56kHz,3.2mJy/beam@10km/s,...</td>\n",
       "      <td>91.910024</td>\n",
       "      <td>2935.003931</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>251.60</td>\n",
       "      <td>253.47</td>\n",
       "      <td>252.54</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.155</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5492.90</td>\n",
       "      <td>368.94</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006240</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003120</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>56293.474235</td>\n",
       "      <td>56293.487242</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001183</td>\n",
       "      <td>0.001192</td>\n",
       "      <td>259583.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927352e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 13</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.492896</td>\n",
       "      <td>0.184788</td>\n",
       "      <td>3.761806</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>uid://A002/X590461/X1b27</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.158316</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-06-25T06:41:57.000</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>[249.97..251.85GHz,976.56kHz,5.5mJy/beam@10km/...</td>\n",
       "      <td>259.222672</td>\n",
       "      <td>1090.377424</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>266.60</td>\n",
       "      <td>268.47</td>\n",
       "      <td>267.53</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.090</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5382.61</td>\n",
       "      <td>372.08</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006240</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003120</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>56293.474235</td>\n",
       "      <td>56293.487242</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001117</td>\n",
       "      <td>0.001125</td>\n",
       "      <td>274943.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927352e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 13</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.382614</td>\n",
       "      <td>0.184788</td>\n",
       "      <td>3.761806</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>uid://A002/X590461/X1b27</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.158316</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-06-25T06:41:57.000</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>[249.97..251.85GHz,976.56kHz,5.5mJy/beam@10km/...</td>\n",
       "      <td>259.222672</td>\n",
       "      <td>1090.377424</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>249.97</td>\n",
       "      <td>251.85</td>\n",
       "      <td>250.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.162</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5505.70</td>\n",
       "      <td>368.62</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006240</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003120</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>56293.474235</td>\n",
       "      <td>56293.487242</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001190</td>\n",
       "      <td>0.001199</td>\n",
       "      <td>257919.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927352e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 13</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.505704</td>\n",
       "      <td>0.184788</td>\n",
       "      <td>3.761806</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>uid://A002/X590461/X1b27</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.158316</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-06-25T06:41:57.000</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>[249.97..251.85GHz,976.56kHz,5.5mJy/beam@10km/...</td>\n",
       "      <td>259.222672</td>\n",
       "      <td>1090.377424</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.657</td>\n",
       "      <td>264.97</td>\n",
       "      <td>266.85</td>\n",
       "      <td>265.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.097</td>\n",
       "      <td>8.158</td>\n",
       "      <td>22.463</td>\n",
       "      <td>184.788</td>\n",
       "      <td>5393.90</td>\n",
       "      <td>371.73</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006240</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003120</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>56293.474235</td>\n",
       "      <td>56293.487242</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001123</td>\n",
       "      <td>0.001131</td>\n",
       "      <td>273279.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927352e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 13</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.393897</td>\n",
       "      <td>0.184788</td>\n",
       "      <td>3.761806</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1ee</td>\n",
       "      <td>uid://A002/X590461/X1b27</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.158316</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-06-25T06:41:57.000</td>\n",
       "      <td>0.656589</td>\n",
       "      <td>[249.97..251.85GHz,976.56kHz,5.5mJy/beam@10km/...</td>\n",
       "      <td>259.222672</td>\n",
       "      <td>1090.377424</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.665</td>\n",
       "      <td>246.72</td>\n",
       "      <td>248.60</td>\n",
       "      <td>247.66</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.178</td>\n",
       "      <td>8.262</td>\n",
       "      <td>22.748</td>\n",
       "      <td>191.363</td>\n",
       "      <td>5623.83</td>\n",
       "      <td>374.09</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006319</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003159</td>\n",
       "      <td>0.664926</td>\n",
       "      <td>56293.314401</td>\n",
       "      <td>56293.327148</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001206</td>\n",
       "      <td>0.001215</td>\n",
       "      <td>254591.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927348e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 12</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.623833</td>\n",
       "      <td>0.191363</td>\n",
       "      <td>2.751811</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>uid://A002/X590461/X17e6</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.261900</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-01-18T12:52:22.000</td>\n",
       "      <td>0.664926</td>\n",
       "      <td>[246.72..248.60GHz,976.56kHz,5.6mJy/beam@10km/...</td>\n",
       "      <td>255.972659</td>\n",
       "      <td>1103.737386</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.665</td>\n",
       "      <td>248.35</td>\n",
       "      <td>250.22</td>\n",
       "      <td>249.29</td>\n",
       "      <td>1.874</td>\n",
       "      <td>976.56</td>\n",
       "      <td>1.170</td>\n",
       "      <td>8.262</td>\n",
       "      <td>22.748</td>\n",
       "      <td>191.363</td>\n",
       "      <td>5610.45</td>\n",
       "      <td>374.41</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2011.0.00820.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2011.0.00820.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>ngc4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.006319</td>\n",
       "      <td>Circle ICRS 186.727617 -0.877642 0.003159</td>\n",
       "      <td>0.664926</td>\n",
       "      <td>56293.314401</td>\n",
       "      <td>56293.327148</td>\n",
       "      <td>151.200</td>\n",
       "      <td>151.200</td>\n",
       "      <td>0.001198</td>\n",
       "      <td>0.001207</td>\n",
       "      <td>256255.750000</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>2.927348e+14</td>\n",
       "      <td>Costagliola, F.; Sakamoto, K.; Muller, S.; Mar...</td>\n",
       "      <td>Context. Extragalactic observations allow the ...</td>\n",
       "      <td>2015</td>\n",
       "      <td>A wide-band, high-quality, unbiased census of ...</td>\n",
       "      <td>ngc4418 B6 Setup 12</td>\n",
       "      <td>Garcia-Burillo, Santiago; Muehle, Stefanie; Aa...</td>\n",
       "      <td>5.610448</td>\n",
       "      <td>0.191363</td>\n",
       "      <td>2.751811</td>\n",
       "      <td></td>\n",
       "      <td>uid://A002/X314ea1/X1fa</td>\n",
       "      <td>uid://A002/X590461/X17e6</td>\n",
       "      <td>A 170 GHz-wide Complete Spectral Scan of an IR...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>8.261900</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DV01 A003:DA41 A004:DV04 A006:DV07 A007:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2014-01-18T12:52:22.000</td>\n",
       "      <td>0.664926</td>\n",
       "      <td>[246.72..248.60GHz,976.56kHz,5.6mJy/beam@10km/...</td>\n",
       "      <td>255.972659</td>\n",
       "      <td>1103.737386</td>\n",
       "      <td>Costagliola, Francesco</td>\n",
       "      <td>Abundance measurements of Titan's stratospheri...</td>\n",
       "      <td>Costagliola, F. Thelen, Alexander E.</td>\n",
       "      <td>T</td>\n",
       "      <td>2015A&amp;A...582A..91C 2019Icar..319..417T</td>\n",
       "      <td>Luminous and Ultra-Luminous Infra-Red Galaxies...</td>\n",
       "      <td>Galaxy evolution</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1335</th>\n",
       "      <td>1336</td>\n",
       "      <td>2018.1.01395.S</td>\n",
       "      <td>NGC_253</td>\n",
       "      <td>11.888058</td>\n",
       "      <td>-25.288800</td>\n",
       "      <td>0.019</td>\n",
       "      <td>217.98</td>\n",
       "      <td>219.85</td>\n",
       "      <td>218.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>1128.91</td>\n",
       "      <td>1.539</td>\n",
       "      <td>0.500</td>\n",
       "      <td>25.549</td>\n",
       "      <td>12.404</td>\n",
       "      <td>398.35</td>\n",
       "      <td>24.92</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2018.1.01395.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>97.364395</td>\n",
       "      <td>-87.964503</td>\n",
       "      <td>ADS/JAO.ALMA#2018.1.01395.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC_253</td>\n",
       "      <td>11.888058</td>\n",
       "      <td>-25.288800</td>\n",
       "      <td>0.007097</td>\n",
       "      <td>Polygon ICRS 11.888794 -25.292286 11.887323 -2...</td>\n",
       "      <td>0.018645</td>\n",
       "      <td>58640.446034</td>\n",
       "      <td>58674.467208</td>\n",
       "      <td>16003.008</td>\n",
       "      <td>16003.008</td>\n",
       "      <td>0.001364</td>\n",
       "      <td>0.001375</td>\n",
       "      <td>194758.820482</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>3.384169e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>We have used 0.2\" ALMA images of the HC3N vibr...</td>\n",
       "      <td>NGC_253_a_06_TM1</td>\n",
       "      <td>Martin-Pintado, Jesus; Martin, Sergio; Gonzale...</td>\n",
       "      <td>0.398353</td>\n",
       "      <td>0.012404</td>\n",
       "      <td>0.911870</td>\n",
       "      <td>uid://A001/X133d/X3024</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "      <td>uid://A002/Xdd4cf3/X33a6</td>\n",
       "      <td>Witnessing the early stages of the formation o...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>0.499517</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A015:DA64 A058:DA41 A069:DV16 A074:DV09 A082:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-02-12T18:33:55.000</td>\n",
       "      <td>0.018645</td>\n",
       "      <td>[217.98..219.85GHz,1128.91kHz,398.4uJy/beam@10...</td>\n",
       "      <td>227.913497</td>\n",
       "      <td>1434.115718</td>\n",
       "      <td>Rico Villas, Fernando</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1336</th>\n",
       "      <td>1337</td>\n",
       "      <td>2018.1.01395.S</td>\n",
       "      <td>NGC_253</td>\n",
       "      <td>11.888058</td>\n",
       "      <td>-25.288800</td>\n",
       "      <td>0.019</td>\n",
       "      <td>235.98</td>\n",
       "      <td>237.85</td>\n",
       "      <td>236.91</td>\n",
       "      <td>1.874</td>\n",
       "      <td>1128.91</td>\n",
       "      <td>1.434</td>\n",
       "      <td>0.500</td>\n",
       "      <td>25.549</td>\n",
       "      <td>12.404</td>\n",
       "      <td>382.31</td>\n",
       "      <td>24.78</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2018.1.01395.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>97.364395</td>\n",
       "      <td>-87.964503</td>\n",
       "      <td>ADS/JAO.ALMA#2018.1.01395.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC_253</td>\n",
       "      <td>11.888058</td>\n",
       "      <td>-25.288800</td>\n",
       "      <td>0.007097</td>\n",
       "      <td>Polygon ICRS 11.888794 -25.292286 11.887323 -2...</td>\n",
       "      <td>0.018645</td>\n",
       "      <td>58640.446034</td>\n",
       "      <td>58674.467208</td>\n",
       "      <td>16003.008</td>\n",
       "      <td>16003.008</td>\n",
       "      <td>0.001260</td>\n",
       "      <td>0.001270</td>\n",
       "      <td>209043.422558</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>6</td>\n",
       "      <td>3.384169e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>We have used 0.2\" ALMA images of the HC3N vibr...</td>\n",
       "      <td>NGC_253_a_06_TM1</td>\n",
       "      <td>Martin-Pintado, Jesus; Martin, Sergio; Gonzale...</td>\n",
       "      <td>0.382310</td>\n",
       "      <td>0.012404</td>\n",
       "      <td>0.911870</td>\n",
       "      <td>uid://A001/X133d/X3024</td>\n",
       "      <td>uid://A001/X133d/X3025</td>\n",
       "      <td>uid://A002/Xdd4cf3/X33a6</td>\n",
       "      <td>Witnessing the early stages of the formation o...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>0.499517</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A015:DA64 A058:DA41 A069:DV16 A074:DV09 A082:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-02-12T18:33:55.000</td>\n",
       "      <td>0.018645</td>\n",
       "      <td>[217.98..219.85GHz,1128.91kHz,398.4uJy/beam@10...</td>\n",
       "      <td>227.913497</td>\n",
       "      <td>1434.115718</td>\n",
       "      <td>Rico Villas, Fernando</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1337</th>\n",
       "      <td>1338</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>108.29</td>\n",
       "      <td>110.16</td>\n",
       "      <td>109.23</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.366</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>468.79</td>\n",
       "      <td>20.59</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.015529</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869878 186.729072 -...</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>58787.582055</td>\n",
       "      <td>58825.599964</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>0.002721</td>\n",
       "      <td>0.002768</td>\n",
       "      <td>55868.832936</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810830e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.468785</td>\n",
       "      <td>0.010485</td>\n",
       "      <td>2.368327</td>\n",
       "      <td>uid://A001/X1465/X389b</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>uid://A002/Xe2ada9/X15596</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>24.939648</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-17T19:10:59.000</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>[96.28..98.15GHz,1938.48kHz,511.7uJy/beam@10km...</td>\n",
       "      <td>104.161888</td>\n",
       "      <td>5274.300699</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1338</th>\n",
       "      <td>1339</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>91.70</td>\n",
       "      <td>93.57</td>\n",
       "      <td>92.63</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.210</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>508.68</td>\n",
       "      <td>20.77</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.016559</td>\n",
       "      <td>Polygon ICRS 196.371150 -49.461202 196.372949 ...</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>58830.525869</td>\n",
       "      <td>58831.619778</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>0.003204</td>\n",
       "      <td>0.003269</td>\n",
       "      <td>48272.592043</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811169e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.508682</td>\n",
       "      <td>0.010282</td>\n",
       "      <td>3.740537</td>\n",
       "      <td>uid://A001/X1465/X3887</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>uid://A002/Xe50c9e/X11047</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.131876</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-06T23:21:24.000</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>[89.90..91.77GHz,1938.48kHz,513.5uJy/beam@10km...</td>\n",
       "      <td>97.681492</td>\n",
       "      <td>5609.869359</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1339</th>\n",
       "      <td>1340</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>97.97</td>\n",
       "      <td>99.84</td>\n",
       "      <td>98.90</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.820</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>507.47</td>\n",
       "      <td>21.40</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.015529</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869878 186.729072 -...</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>58787.582055</td>\n",
       "      <td>58825.599964</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>0.003003</td>\n",
       "      <td>0.003060</td>\n",
       "      <td>51508.746588</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810830e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.507473</td>\n",
       "      <td>0.010485</td>\n",
       "      <td>2.368327</td>\n",
       "      <td>uid://A001/X1465/X389b</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>uid://A002/Xe2ada9/X15596</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>24.939648</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-17T19:10:59.000</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>[96.28..98.15GHz,1938.48kHz,511.7uJy/beam@10km...</td>\n",
       "      <td>104.161888</td>\n",
       "      <td>5274.300699</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1340</th>\n",
       "      <td>1341</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>96.28</td>\n",
       "      <td>98.15</td>\n",
       "      <td>97.21</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.920</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>511.67</td>\n",
       "      <td>21.39</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.015529</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869878 186.729072 -...</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>58787.582055</td>\n",
       "      <td>58825.599964</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>0.003054</td>\n",
       "      <td>0.003114</td>\n",
       "      <td>50638.217620</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810830e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.511673</td>\n",
       "      <td>0.010485</td>\n",
       "      <td>2.368327</td>\n",
       "      <td>uid://A001/X1465/X389b</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>uid://A002/Xe2ada9/X15596</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>24.939648</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-17T19:10:59.000</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>[96.28..98.15GHz,1938.48kHz,511.7uJy/beam@10km...</td>\n",
       "      <td>104.161888</td>\n",
       "      <td>5274.300699</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1341</th>\n",
       "      <td>1342</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>108.87</td>\n",
       "      <td>110.74</td>\n",
       "      <td>109.80</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.338</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>799.25</td>\n",
       "      <td>35.19</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.015447</td>\n",
       "      <td>Circle ICRS 196.363663 -49.467900 0.007723</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>58803.513052</td>\n",
       "      <td>58803.528983</td>\n",
       "      <td>876.960</td>\n",
       "      <td>876.960</td>\n",
       "      <td>0.002707</td>\n",
       "      <td>0.002754</td>\n",
       "      <td>56162.029463</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811359e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.799253</td>\n",
       "      <td>0.018936</td>\n",
       "      <td>3.860288</td>\n",
       "      <td>uid://A001/X1465/X388b</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>uid://A002/Xe37224/X14cf9</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>22.320877</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A004:DA56 A005:DV22 A006:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T20:54:34.000</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>[96.80..98.67GHz,1938.48kHz,984.3uJy/beam@10km...</td>\n",
       "      <td>104.713465</td>\n",
       "      <td>5246.997281</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1342</th>\n",
       "      <td>1343</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>110.76</td>\n",
       "      <td>112.63</td>\n",
       "      <td>111.69</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.247</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>792.83</td>\n",
       "      <td>35.21</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.015447</td>\n",
       "      <td>Circle ICRS 196.363663 -49.467900 0.007723</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>58803.513052</td>\n",
       "      <td>58803.528983</td>\n",
       "      <td>876.960</td>\n",
       "      <td>876.960</td>\n",
       "      <td>0.002662</td>\n",
       "      <td>0.002707</td>\n",
       "      <td>57136.004067</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811359e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.792833</td>\n",
       "      <td>0.018936</td>\n",
       "      <td>3.860288</td>\n",
       "      <td>uid://A001/X1465/X388b</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>uid://A002/Xe37224/X14cf9</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>22.320877</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A004:DA56 A005:DV22 A006:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T20:54:34.000</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>[96.80..98.67GHz,1938.48kHz,984.3uJy/beam@10km...</td>\n",
       "      <td>104.713465</td>\n",
       "      <td>5246.997281</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1343</th>\n",
       "      <td>1344</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>98.49</td>\n",
       "      <td>100.36</td>\n",
       "      <td>99.42</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.791</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>976.30</td>\n",
       "      <td>41.27</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.015447</td>\n",
       "      <td>Circle ICRS 196.363663 -49.467900 0.007723</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>58803.513052</td>\n",
       "      <td>58803.528983</td>\n",
       "      <td>876.960</td>\n",
       "      <td>876.960</td>\n",
       "      <td>0.002987</td>\n",
       "      <td>0.003044</td>\n",
       "      <td>51772.734587</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811359e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.976296</td>\n",
       "      <td>0.018936</td>\n",
       "      <td>3.860288</td>\n",
       "      <td>uid://A001/X1465/X388b</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>uid://A002/Xe37224/X14cf9</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>22.320877</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A004:DA56 A005:DV22 A006:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T20:54:34.000</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>[96.80..98.67GHz,1938.48kHz,984.3uJy/beam@10km...</td>\n",
       "      <td>104.713465</td>\n",
       "      <td>5246.997281</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1344</th>\n",
       "      <td>1345</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.309</td>\n",
       "      <td>96.80</td>\n",
       "      <td>98.67</td>\n",
       "      <td>97.73</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.890</td>\n",
       "      <td>22.321</td>\n",
       "      <td>55.608</td>\n",
       "      <td>18.936</td>\n",
       "      <td>984.33</td>\n",
       "      <td>41.26</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.015447</td>\n",
       "      <td>Circle ICRS 196.363663 -49.467900 0.007723</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>58803.513052</td>\n",
       "      <td>58803.528983</td>\n",
       "      <td>876.960</td>\n",
       "      <td>876.960</td>\n",
       "      <td>0.003038</td>\n",
       "      <td>0.003097</td>\n",
       "      <td>50901.751170</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811359e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.984333</td>\n",
       "      <td>0.018936</td>\n",
       "      <td>3.860288</td>\n",
       "      <td>uid://A001/X1465/X388b</td>\n",
       "      <td>uid://A001/X1465/X388c</td>\n",
       "      <td>uid://A002/Xe37224/X14cf9</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>22.320877</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A004:DA56 A005:DV22 A006:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T20:54:34.000</td>\n",
       "      <td>2.309410</td>\n",
       "      <td>[96.80..98.67GHz,1938.48kHz,984.3uJy/beam@10km...</td>\n",
       "      <td>104.713465</td>\n",
       "      <td>5246.997281</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1345</th>\n",
       "      <td>1346</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>103.38</td>\n",
       "      <td>105.26</td>\n",
       "      <td>104.32</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.621</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>461.89</td>\n",
       "      <td>19.82</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.016592</td>\n",
       "      <td>Polygon ICRS 40.669879 -0.021585 40.668325 -0....</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>58790.229826</td>\n",
       "      <td>58802.118198</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>0.002848</td>\n",
       "      <td>0.002900</td>\n",
       "      <td>53330.846587</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811652e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.461887</td>\n",
       "      <td>0.009858</td>\n",
       "      <td>2.751755</td>\n",
       "      <td>uid://A001/X1465/X388f</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>uid://A002/Xe2eefc/X31df</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>20.837939</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-10T20:24:07.000</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>[89.72..91.59GHz,1938.48kHz,494.6uJy/beam@10km...</td>\n",
       "      <td>97.487731</td>\n",
       "      <td>5621.370692</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1346</th>\n",
       "      <td>1347</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>101.58</td>\n",
       "      <td>103.45</td>\n",
       "      <td>102.51</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.721</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>459.66</td>\n",
       "      <td>19.55</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.016592</td>\n",
       "      <td>Polygon ICRS 40.669879 -0.021585 40.668325 -0....</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>58790.229826</td>\n",
       "      <td>58802.118198</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>0.002898</td>\n",
       "      <td>0.002951</td>\n",
       "      <td>52398.067385</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811652e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.459663</td>\n",
       "      <td>0.009858</td>\n",
       "      <td>2.751755</td>\n",
       "      <td>uid://A001/X1465/X388f</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>uid://A002/Xe2eefc/X31df</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>20.837939</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-10T20:24:07.000</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>[89.72..91.59GHz,1938.48kHz,494.6uJy/beam@10km...</td>\n",
       "      <td>97.487731</td>\n",
       "      <td>5621.370692</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1347</th>\n",
       "      <td>1348</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>91.51</td>\n",
       "      <td>93.39</td>\n",
       "      <td>92.45</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.223</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>480.47</td>\n",
       "      <td>19.59</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.016592</td>\n",
       "      <td>Polygon ICRS 40.669879 -0.021585 40.668325 -0....</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>58790.229826</td>\n",
       "      <td>58802.118198</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>0.003210</td>\n",
       "      <td>0.003276</td>\n",
       "      <td>48173.837781</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811652e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.480466</td>\n",
       "      <td>0.009858</td>\n",
       "      <td>2.751755</td>\n",
       "      <td>uid://A001/X1465/X388f</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>uid://A002/Xe2eefc/X31df</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>20.837939</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-10T20:24:07.000</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>[89.72..91.59GHz,1938.48kHz,494.6uJy/beam@10km...</td>\n",
       "      <td>97.487731</td>\n",
       "      <td>5621.370692</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1348</th>\n",
       "      <td>1349</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>1.609</td>\n",
       "      <td>89.72</td>\n",
       "      <td>91.59</td>\n",
       "      <td>90.65</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.345</td>\n",
       "      <td>20.838</td>\n",
       "      <td>59.730</td>\n",
       "      <td>9.858</td>\n",
       "      <td>494.60</td>\n",
       "      <td>19.97</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.016592</td>\n",
       "      <td>Polygon ICRS 40.669879 -0.021585 40.668325 -0....</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>58790.229826</td>\n",
       "      <td>58802.118198</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>9918.720</td>\n",
       "      <td>0.003273</td>\n",
       "      <td>0.003342</td>\n",
       "      <td>47246.711574</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811652e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.494603</td>\n",
       "      <td>0.009858</td>\n",
       "      <td>2.751755</td>\n",
       "      <td>uid://A001/X1465/X388f</td>\n",
       "      <td>uid://A001/X1465/X3890</td>\n",
       "      <td>uid://A002/Xe2eefc/X31df</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>20.837939</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-10T20:24:07.000</td>\n",
       "      <td>1.608789</td>\n",
       "      <td>[89.72..91.59GHz,1938.48kHz,494.6uJy/beam@10km...</td>\n",
       "      <td>97.487731</td>\n",
       "      <td>5621.370692</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1349</th>\n",
       "      <td>1350</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>89.43</td>\n",
       "      <td>91.30</td>\n",
       "      <td>90.36</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.364</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>466.81</td>\n",
       "      <td>18.82</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.016645</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869320 186.729177 -...</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>58810.445022</td>\n",
       "      <td>58842.573071</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>0.003284</td>\n",
       "      <td>0.003352</td>\n",
       "      <td>47103.985999</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810791e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.466810</td>\n",
       "      <td>0.009343</td>\n",
       "      <td>2.977325</td>\n",
       "      <td>uid://A001/X1465/X3897</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>uid://A002/Xe3f5bb/X3259</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.047713</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-07T00:23:33.000</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>[89.43..91.30GHz,1938.48kHz,466.8uJy/beam@10km...</td>\n",
       "      <td>97.175661</td>\n",
       "      <td>5638.752118</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1350</th>\n",
       "      <td>1351</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>101.78</td>\n",
       "      <td>103.65</td>\n",
       "      <td>102.72</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.710</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>475.79</td>\n",
       "      <td>20.26</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.016559</td>\n",
       "      <td>Polygon ICRS 196.371150 -49.461202 196.372949 ...</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>58830.525869</td>\n",
       "      <td>58831.619778</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>0.002892</td>\n",
       "      <td>0.002945</td>\n",
       "      <td>52507.569686</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811169e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.475794</td>\n",
       "      <td>0.010282</td>\n",
       "      <td>3.740537</td>\n",
       "      <td>uid://A001/X1465/X3887</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>uid://A002/Xe50c9e/X11047</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.131876</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-06T23:21:24.000</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>[89.90..91.77GHz,1938.48kHz,513.5uJy/beam@10km...</td>\n",
       "      <td>97.681492</td>\n",
       "      <td>5609.869359</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1351</th>\n",
       "      <td>1352</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>108.65</td>\n",
       "      <td>110.52</td>\n",
       "      <td>109.59</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.349</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>960.67</td>\n",
       "      <td>42.25</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.015477</td>\n",
       "      <td>Circle ICRS 40.669879 -0.013289 0.007739</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>58803.153086</td>\n",
       "      <td>58803.168742</td>\n",
       "      <td>846.720</td>\n",
       "      <td>846.720</td>\n",
       "      <td>0.002712</td>\n",
       "      <td>0.002759</td>\n",
       "      <td>56045.630140</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811774e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.960667</td>\n",
       "      <td>0.021996</td>\n",
       "      <td>5.121032</td>\n",
       "      <td>uid://A001/X1465/X3893</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>uid://A002/Xe37224/X12917</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>21.118095</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T21:54:54.000</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>[96.60..98.47GHz,1938.48kHz,1mJy/beam@10km/s,4...</td>\n",
       "      <td>104.505756</td>\n",
       "      <td>5257.484293</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1352</th>\n",
       "      <td>1353</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>110.54</td>\n",
       "      <td>112.42</td>\n",
       "      <td>111.48</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.257</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>1131.63</td>\n",
       "      <td>50.21</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.015477</td>\n",
       "      <td>Circle ICRS 40.669879 -0.013289 0.007739</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>58803.153086</td>\n",
       "      <td>58803.168742</td>\n",
       "      <td>846.720</td>\n",
       "      <td>846.720</td>\n",
       "      <td>0.002667</td>\n",
       "      <td>0.002712</td>\n",
       "      <td>57022.035883</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811774e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>1.131625</td>\n",
       "      <td>0.021996</td>\n",
       "      <td>5.121032</td>\n",
       "      <td>uid://A001/X1465/X3893</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>uid://A002/Xe37224/X12917</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>21.118095</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T21:54:54.000</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>[96.60..98.47GHz,1938.48kHz,1mJy/beam@10km/s,4...</td>\n",
       "      <td>104.505756</td>\n",
       "      <td>5257.484293</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1353</th>\n",
       "      <td>1354</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>98.29</td>\n",
       "      <td>100.16</td>\n",
       "      <td>99.23</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.802</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>1007.18</td>\n",
       "      <td>42.54</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.015477</td>\n",
       "      <td>Circle ICRS 40.669879 -0.013289 0.007739</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>58803.153086</td>\n",
       "      <td>58803.168742</td>\n",
       "      <td>846.720</td>\n",
       "      <td>846.720</td>\n",
       "      <td>0.002993</td>\n",
       "      <td>0.003050</td>\n",
       "      <td>51667.340290</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811774e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>1.007181</td>\n",
       "      <td>0.021996</td>\n",
       "      <td>5.121032</td>\n",
       "      <td>uid://A001/X1465/X3893</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>uid://A002/Xe37224/X12917</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>21.118095</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T21:54:54.000</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>[96.60..98.47GHz,1938.48kHz,1mJy/beam@10km/s,4...</td>\n",
       "      <td>104.505756</td>\n",
       "      <td>5257.484293</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1354</th>\n",
       "      <td>1355</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>103.05</td>\n",
       "      <td>104.92</td>\n",
       "      <td>103.99</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.639</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>436.95</td>\n",
       "      <td>18.72</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.016645</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869320 186.729177 -...</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>58810.445022</td>\n",
       "      <td>58842.573071</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>0.002857</td>\n",
       "      <td>0.002909</td>\n",
       "      <td>53166.454513</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810791e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.436953</td>\n",
       "      <td>0.009343</td>\n",
       "      <td>2.977325</td>\n",
       "      <td>uid://A001/X1465/X3897</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>uid://A002/Xe3f5bb/X3259</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.047713</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-07T00:23:33.000</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>[89.43..91.30GHz,1938.48kHz,466.8uJy/beam@10km...</td>\n",
       "      <td>97.175661</td>\n",
       "      <td>5638.752118</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1355</th>\n",
       "      <td>1356</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>91.20</td>\n",
       "      <td>93.07</td>\n",
       "      <td>92.13</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.243</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>459.55</td>\n",
       "      <td>18.71</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.016645</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869320 186.729177 -...</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>58810.445022</td>\n",
       "      <td>58842.573071</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>0.003221</td>\n",
       "      <td>0.003287</td>\n",
       "      <td>48017.332095</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810791e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.459546</td>\n",
       "      <td>0.009343</td>\n",
       "      <td>2.977325</td>\n",
       "      <td>uid://A001/X1465/X3897</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>uid://A002/Xe3f5bb/X3259</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.047713</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-07T00:23:33.000</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>[89.43..91.30GHz,1938.48kHz,466.8uJy/beam@10km...</td>\n",
       "      <td>97.175661</td>\n",
       "      <td>5638.752118</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1356</th>\n",
       "      <td>1357</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>2.537</td>\n",
       "      <td>101.24</td>\n",
       "      <td>103.11</td>\n",
       "      <td>102.18</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.740</td>\n",
       "      <td>27.048</td>\n",
       "      <td>59.922</td>\n",
       "      <td>9.343</td>\n",
       "      <td>437.00</td>\n",
       "      <td>18.56</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.016645</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869320 186.729177 -...</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>58810.445022</td>\n",
       "      <td>58842.573071</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>16632.000</td>\n",
       "      <td>0.002907</td>\n",
       "      <td>0.002961</td>\n",
       "      <td>52231.920422</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810791e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.436998</td>\n",
       "      <td>0.009343</td>\n",
       "      <td>2.977325</td>\n",
       "      <td>uid://A001/X1465/X3897</td>\n",
       "      <td>uid://A001/X1465/X3898</td>\n",
       "      <td>uid://A002/Xe3f5bb/X3259</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.047713</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-07T00:23:33.000</td>\n",
       "      <td>2.537301</td>\n",
       "      <td>[89.43..91.30GHz,1938.48kHz,466.8uJy/beam@10km...</td>\n",
       "      <td>97.175661</td>\n",
       "      <td>5638.752118</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1357</th>\n",
       "      <td>1358</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>2.247</td>\n",
       "      <td>96.60</td>\n",
       "      <td>98.47</td>\n",
       "      <td>97.53</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.902</td>\n",
       "      <td>21.118</td>\n",
       "      <td>55.719</td>\n",
       "      <td>21.996</td>\n",
       "      <td>1015.52</td>\n",
       "      <td>42.52</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>172.103977</td>\n",
       "      <td>-51.933584</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC1068</td>\n",
       "      <td>40.669879</td>\n",
       "      <td>-0.013289</td>\n",
       "      <td>0.015477</td>\n",
       "      <td>Circle ICRS 40.669879 -0.013289 0.007739</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>58803.153086</td>\n",
       "      <td>58803.168742</td>\n",
       "      <td>846.720</td>\n",
       "      <td>846.720</td>\n",
       "      <td>0.003045</td>\n",
       "      <td>0.003104</td>\n",
       "      <td>50793.714099</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811774e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC1068_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>1.015517</td>\n",
       "      <td>0.021996</td>\n",
       "      <td>5.121032</td>\n",
       "      <td>uid://A001/X1465/X3893</td>\n",
       "      <td>uid://A001/X1465/X3894</td>\n",
       "      <td>uid://A002/Xe37224/X12917</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>21.118095</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-05T21:54:54.000</td>\n",
       "      <td>2.246874</td>\n",
       "      <td>[96.60..98.47GHz,1938.48kHz,1mJy/beam@10km/s,4...</td>\n",
       "      <td>104.505756</td>\n",
       "      <td>5257.484293</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1358</th>\n",
       "      <td>1359</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>103.59</td>\n",
       "      <td>105.46</td>\n",
       "      <td>104.52</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.610</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>478.30</td>\n",
       "      <td>20.54</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.016559</td>\n",
       "      <td>Polygon ICRS 196.371150 -49.461202 196.372949 ...</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>58830.525869</td>\n",
       "      <td>58831.619778</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>0.002843</td>\n",
       "      <td>0.002894</td>\n",
       "      <td>53440.185286</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811169e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.478302</td>\n",
       "      <td>0.010282</td>\n",
       "      <td>3.740537</td>\n",
       "      <td>uid://A001/X1465/X3887</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>uid://A002/Xe50c9e/X11047</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.131876</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-06T23:21:24.000</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>[89.90..91.77GHz,1938.48kHz,513.5uJy/beam@10km...</td>\n",
       "      <td>97.681492</td>\n",
       "      <td>5609.869359</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1359</th>\n",
       "      <td>1360</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>2.523</td>\n",
       "      <td>89.90</td>\n",
       "      <td>91.77</td>\n",
       "      <td>90.84</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>6.332</td>\n",
       "      <td>27.132</td>\n",
       "      <td>59.612</td>\n",
       "      <td>10.282</td>\n",
       "      <td>513.50</td>\n",
       "      <td>20.76</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>305.271559</td>\n",
       "      <td>13.340115</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4945</td>\n",
       "      <td>196.363663</td>\n",
       "      <td>-49.467900</td>\n",
       "      <td>0.016559</td>\n",
       "      <td>Polygon ICRS 196.371150 -49.461202 196.372949 ...</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>58830.525869</td>\n",
       "      <td>58831.619778</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>10765.440</td>\n",
       "      <td>0.003267</td>\n",
       "      <td>0.003335</td>\n",
       "      <td>47345.641143</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.811169e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4945_a_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.513502</td>\n",
       "      <td>0.010282</td>\n",
       "      <td>3.740537</td>\n",
       "      <td>uid://A001/X1465/X3887</td>\n",
       "      <td>uid://A001/X1465/X3888</td>\n",
       "      <td>uid://A002/Xe50c9e/X11047</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>27.131876</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-04-06T23:21:24.000</td>\n",
       "      <td>2.522933</td>\n",
       "      <td>[89.90..91.77GHz,1938.48kHz,513.5uJy/beam@10km...</td>\n",
       "      <td>97.681492</td>\n",
       "      <td>5609.869359</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1360</th>\n",
       "      <td>1361</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>1.357</td>\n",
       "      <td>110.17</td>\n",
       "      <td>112.05</td>\n",
       "      <td>111.11</td>\n",
       "      <td>1.873</td>\n",
       "      <td>1938.48</td>\n",
       "      <td>5.274</td>\n",
       "      <td>24.940</td>\n",
       "      <td>55.903</td>\n",
       "      <td>10.485</td>\n",
       "      <td>465.01</td>\n",
       "      <td>20.60</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>http://almascience.org/aq?member_ous_id=uid://...</td>\n",
       "      <td>text/html</td>\n",
       "      <td>2019.1.00130.S</td>\n",
       "      <td>Public</td>\n",
       "      <td>290.048542</td>\n",
       "      <td>61.379017</td>\n",
       "      <td>ADS/JAO.ALMA#2019.1.00130.S</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>JAO</td>\n",
       "      <td>ALMA</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>cube</td>\n",
       "      <td>2</td>\n",
       "      <td>NGC4418</td>\n",
       "      <td>186.727617</td>\n",
       "      <td>-0.877642</td>\n",
       "      <td>0.015529</td>\n",
       "      <td>Polygon ICRS 186.727617 -0.869878 186.729072 -...</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>58787.582055</td>\n",
       "      <td>58825.599964</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>4898.880</td>\n",
       "      <td>0.002676</td>\n",
       "      <td>0.002721</td>\n",
       "      <td>56840.228703</td>\n",
       "      <td>/XX/YY/</td>\n",
       "      <td>phot.flux.density;phys.polarization</td>\n",
       "      <td>3</td>\n",
       "      <td>5.810830e+14</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>The 12C/13C isotopic ratio is a good tracer of...</td>\n",
       "      <td>NGC4418_b_03_TM1</td>\n",
       "      <td>Krips, Melanie; Garcia-Burillo, Santiago; Mueh...</td>\n",
       "      <td>0.465008</td>\n",
       "      <td>0.010485</td>\n",
       "      <td>2.368327</td>\n",
       "      <td>uid://A001/X1465/X389b</td>\n",
       "      <td>uid://A001/X1465/X389c</td>\n",
       "      <td>uid://A002/Xe2ada9/X15596</td>\n",
       "      <td>A decisive answer on the carbon isotopic ratio...</td>\n",
       "      <td>S</td>\n",
       "      <td>TARGET</td>\n",
       "      <td>T</td>\n",
       "      <td>24.939648</td>\n",
       "      <td>1.875000e+09</td>\n",
       "      <td>A001:DA48 A002:DA44 A003:DV23 A004:DA56 A005:D...</td>\n",
       "      <td>F</td>\n",
       "      <td>2021-03-17T19:10:59.000</td>\n",
       "      <td>1.356746</td>\n",
       "      <td>[96.28..98.15GHz,1938.48kHz,511.7uJy/beam@10km...</td>\n",
       "      <td>104.161888</td>\n",
       "      <td>5274.300699</td>\n",
       "      <td>Martin, Sergio</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>T</td>\n",
       "      <td></td>\n",
       "      <td>Starbursts, star formation, Galaxy chemistry</td>\n",
       "      <td>Active galaxies</td>\n",
       "      <td>2021-06-16T16:46:50.431</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1361 rows × 81 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Obs    project_code ALMA_source_name  ...                                    science_keyword  scientific_category             lastModified\n",
       "0        1  2011.0.00268.S  LESS J0332-2756  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "1        2  2011.0.00268.S  LESS J0332-2756  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "2        3  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "3        4  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "4        5  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "5        6  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "6        7  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "7        8  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "8        9  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "9       10  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "10      11  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "11      12  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "12      13  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "13      14  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "14      15  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "15      16  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "16      17  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "17      18  2011.0.00405.S      PKS1830-211  ...     Galaxy structure & evolution, Galaxy chemistry     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "18      19  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "19      20  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "20      21  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "21      22  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "22      23  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "23      24  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "24      25  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "25      26  2011.0.00820.S          ngc4418  ...  Luminous and Ultra-Luminous Infra-Red Galaxies...     Galaxy evolution  2021-06-16T16:46:50.431\n",
       "...    ...             ...              ...  ...                                                ...                  ...                      ...\n",
       "1335  1336  2018.1.01395.S          NGC_253  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1336  1337  2018.1.01395.S          NGC_253  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1337  1338  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1338  1339  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1339  1340  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1340  1341  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1341  1342  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1342  1343  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1343  1344  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1344  1345  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1345  1346  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1346  1347  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1347  1348  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1348  1349  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1349  1350  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1350  1351  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1351  1352  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1352  1353  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1353  1354  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1354  1355  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1355  1356  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1356  1357  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1357  1358  2019.1.00130.S          NGC1068  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1358  1359  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1359  1360  2019.1.00130.S          NGC4945  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "1360  1361  2019.1.00130.S          NGC4418  ...       Starbursts, star formation, Galaxy chemistry      Active galaxies  2021-06-16T16:46:50.431\n",
       "\n",
       "[1361 rows x 81 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alminer.explore(observations, allcols=True, allrows=False)\n",
    "# you can also set allrows=True to see all rows in the table but this may be slow for very large queries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 2.2 Summarize results <a name=\"summary\"></a>\n",
    "\n",
    "The `alminer.summary` function will print a summary of the observations. This is done by default when the query is run, but it's a useful function if the results are filtered further, as shown in the next section.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>summary</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Print a summary of the observations. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**summary**(_observations, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.2.1: print the summary of a given query result, including a list of unique ALMA target names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 47\n",
      "Number of observations = 339\n",
      "Number of unique subbands = 1162\n",
      "Total number of subbands = 1361\n",
      "63 target(s) with ALMA data = ['LESS J0332-2756', 'PKS1830-211', 'ngc4418', 'NGC7469', 'NGC_1097', 'Arp220', 'NGC_5253', 'M83', 'NGC253', 'NGC1266', 'vv114', 'Mystery_Object', 'Sgr_A_star', 'SDSS_J080430.99+360718.1', 'ngc_3256', 'NGC_3256', 'NGC_55', 'ngc3256', 'NGC4418', 'NGC_3627_BE', 'circinus', 'IRAS_F16399-0937', 'ngc6240', 'ngc613', 'n613', 'ngc253', 'N159-E', 'N159-W', 'N159-W_south', 'm83', 'IRAS_13120-5453', 'ngc4945', 'HE1353-1917', 'HE0108-4743', 'HE1108-2813', 'HE1029-1831', 'HE0433-1028', 'Y052343.48-680033.9', 'Y045406.43-664601.4', 'Y045358.57-691106.7', 'Y051912.27-690907.2', 'Y045100.16-691934.4', 'Y052210.08-673459.6', 'Y052423.39-693904.7', 'ST6', 'Y051916.87-693757.5', 'Y054826.21-700850.2', 'Y050953.89-685336.7', 'Y052333.40-693712.1', 'Y053952.11-710930.7', 'Y045622.61-663656.9', 'Y054248.90-694446.3', 'Y054629.32-693514.2', 'Y051344.99-693510.6', 'Y050355.87-672045.1', 'Y044854.41-690948.3', 'ST10', 'ngc4526', 'Cloverleaf', 'ngc7465', 'NGC_253', 'NGC4945', 'NGC1068']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "alminer.summary(observations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.2.2: print the summary of a given query result WITHOUT the list of target names\n",
    "\n",
    "For big tables, it is useful to avoid printing the list of target names in the summary. This can be done by setting *print_targets=False*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 47\n",
      "Number of observations = 339\n",
      "Number of unique subbands = 1162\n",
      "Total number of subbands = 1361\n",
      "Total number of targets with ALMA data = 63\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "alminer.summary(observations, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 2.3 Filter results <a name=\"filter\"></a>\n",
    "\n",
    "The search results can be further narrowed down by using [PANDAS DataFrame](https://pandas.pydata.org/pandas-docs/stable/reference/frame.html) functions. See also this [introduction to data structures](https://pandas.pydata.org/pandas-docs/stable/user_guide/dsintro.html#dataframe). For example, you can use `your_query.columns` to get a list of all columns in the DataFrame. \n",
    "\n",
    "To get the description and units of any column use the function `alminer.get_info('column_name')` where *column_name* is the name of the column. <br>\n",
    "<br>\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>get_info</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Print the description and units of a given column in the query results DataFrame.<br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**get_info**(_column_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **column (str)** : A column in the pandas.DataFrame query table.<br> \n",
    "***\n",
    "</details>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.3.1: simple selection - observations with angular resolutions < 0.5\"\n",
    "\n",
    "Let's first check what the description and units of *ang_res_arcsec* column are:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Column: ang_res_arcsec\n",
      "--------------------------------\n",
      "Description: typical spatial resolution\n",
      "Units: arcsec\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "alminer.get_info('ang_res_arcsec')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "Now we can do the some further filtering, say to only keep observations with angular resolutions < 0.5\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "selected = observations[observations['ang_res_arcsec'] < 0.5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "and print the summary:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 23\n",
      "Number of observations = 121\n",
      "Number of unique subbands = 367\n",
      "Total number of subbands = 484\n",
      "Total number of targets with ALMA data = 41\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "alminer.summary(selected, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.3.2: multiple selections - observations with angular resolution < 0.5\" & velocity resolution < 1 km/s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 9\n",
      "Number of observations = 48\n",
      "Number of unique subbands = 65\n",
      "Total number of subbands = 109\n",
      "Total number of targets with ALMA data = 26\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "selected = observations[(observations['ang_res_arcsec'] < 0.5) & \n",
    "                        (observations['vel_res_kms'] < 1.0)]\n",
    "alminer.summary(selected, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.3.3: observations containing a given frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 6\n",
      "Number of observations = 7\n",
      "Number of unique subbands = 7\n",
      "Total number of subbands = 7\n",
      "Total number of targets with ALMA data = 5\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "freq = 220.5  \n",
    "selected = observations[(observations[\"min_freq_GHz\"] < freq) & \n",
    "                        (observations[\"max_freq_GHz\"] > freq)]\n",
    "alminer.summary(selected, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 2.4 Line coverage <a name=\"line_coverage\"></a>\n",
    "\n",
    "An alternative to the last example in the previous section is the `alminer.line_coverage` function which determines how many targets were observed at a given frequency with the option to include a redshift for the line of interest to be taken into account. Some notes:\n",
    " * Line frequencies should be given in GHz \n",
    " * Redshift is by default assumed to be 0\n",
    " * The *line_name* keyword is the user's defined name for the frquency provided\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>line_coverage</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Determine how many observations were observed at a given frequency (+redshift). <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**line_coverage**(_observations, line_freq, z=0., line_name='', print_summary=True, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **line_freq (float64)** : Frequency of the line of interest in GHz. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequency given in 'line_freq' parameter should be shifted. <br>\n",
    " * **line_name (str, optional, default: '')** : Name of the line specified in 'line_freq'. <br>\n",
    " * **print_summary (bool, optional, default: True)** : Print a summary of the observations to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " * **pandas.DataFrame** containing all observations of line of interest.\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.4.1: search whether a given frequency is covered in the observations\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Summary of 'My favourite line' observations at 220.5 GHz\n",
      "--------------------------------\n",
      "Number of projects = 6\n",
      "Number of observations = 7\n",
      "Number of unique subbands = 7\n",
      "Total number of subbands = 7\n",
      "5 target(s) with ALMA data = ['Arp220', 'ngc_3256', 'IRAS_13120-5453', 'ngc253', 'NGC_253']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myline_obs = alminer.line_coverage(observations, \n",
    "                                   line_freq=220.5, \n",
    "                                   z=0, \n",
    "                                   line_name=\"My favourite line\", \n",
    "                                   print_targets=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.4.2: search whether a given frequency is observed for a target at a given redshift "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Summary of 'My favourite line' observations at 400.0 GHz (266.667 GHz at z=0.5)\n",
      "--------------------------------\n",
      "Number of projects = 8\n",
      "Number of observations = 10\n",
      "Number of unique subbands = 11\n",
      "Total number of subbands = 11\n",
      "6 target(s) with ALMA data = ['ngc4418', 'Arp220', 'ngc_3256', 'circinus', 'ngc4945', 'ngc253']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myline_obs = alminer.line_coverage(observations, \n",
    "                                   line_freq=400.0, \n",
    "                                   z=0.5, \n",
    "                                   line_name=\"My favourite line\", \n",
    "                                   print_targets=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 2.5 Coverage of CO, <sup>13</sup>CO, and C<sup>18</sup>O lines <a name=\"CO_lines\"></a>\n",
    "\n",
    "The `alminer.CO_lines` function determines how many CO, <sup>13</sup>CO, and C<sup>18</sup>O lines were observed in the provided DataFrame and returns a DataFrame containing all observations of these transitions.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>CO_lines</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Determine how many CO, <sup>13</sup>CO, and C<sup>18</sup>O lines were observed in the provided query DataFrame. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**CO_lines**(_observations, z=0., print_summary=True, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequency given in 'line_freq' parameter should be shifted. <br>\n",
    " * **print_summary (bool, optional, default: True)** : Print a summary of the observations to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " * **pandas.DataFrame** containing all observations of CO, <sup>13</sup>CO, and C<sup>18</sup>O\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.5.1: search whether any CO, <sup>13</sup>CO, and C<sup>18</sup>O lines were observed in the query results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Summary of 'CO (1-0)' observations at 115.271 GHz\n",
      "--------------------------------\n",
      "Number of projects = 4\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 4\n",
      "Total number of subbands = 5\n",
      "Total number of targets with ALMA data = 3\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (2-1)' observations at 230.538 GHz\n",
      "--------------------------------\n",
      "Number of projects = 10\n",
      "Number of observations = 13\n",
      "Number of unique subbands = 13\n",
      "Total number of subbands = 13\n",
      "Total number of targets with ALMA data = 8\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (3-2)' observations at 345.796 GHz\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 5\n",
      "Total number of subbands = 5\n",
      "Total number of targets with ALMA data = 4\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (4-3)' observations at 461.041 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (5-4)' observations at 576.268 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (6-5)' observations at 691.473 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (7-6)' observations at 806.652 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (8-7)' observations at 921.8 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (1-0)' observations at 110.201 GHz\n",
      "--------------------------------\n",
      "Number of projects = 18\n",
      "Number of observations = 23\n",
      "Number of unique subbands = 23\n",
      "Total number of subbands = 25\n",
      "Total number of targets with ALMA data = 17\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (2-1)' observations at 220.399 GHz\n",
      "--------------------------------\n",
      "Number of projects = 6\n",
      "Number of observations = 7\n",
      "Number of unique subbands = 7\n",
      "Total number of subbands = 7\n",
      "Total number of targets with ALMA data = 5\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (3-2)' observations at 330.588 GHz\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 5\n",
      "Total number of subbands = 5\n",
      "Total number of targets with ALMA data = 4\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (4-3)' observations at 440.765 GHz\n",
      "--------------------------------\n",
      "Number of projects = 1\n",
      "Number of observations = 1\n",
      "Number of unique subbands = 1\n",
      "Total number of subbands = 1\n",
      "Total number of targets with ALMA data = 1\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (5-4)' observations at 550.926 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (6-5)' observations at 661.067 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (7-6)' observations at 771.184 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (8-7)' observations at 881.273 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (1-0)' observations at 109.782 GHz\n",
      "--------------------------------\n",
      "Number of projects = 19\n",
      "Number of observations = 24\n",
      "Number of unique subbands = 25\n",
      "Total number of subbands = 27\n",
      "Total number of targets with ALMA data = 18\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (2-1)' observations at 219.56 GHz\n",
      "--------------------------------\n",
      "Number of projects = 7\n",
      "Number of observations = 9\n",
      "Number of unique subbands = 12\n",
      "Total number of subbands = 12\n",
      "Total number of targets with ALMA data = 6\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (3-2)' observations at 329.331 GHz\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 3\n",
      "Total number of subbands = 3\n",
      "Total number of targets with ALMA data = 2\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (4-3)' observations at 439.089 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (5-4)' observations at 548.831 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (6-5)' observations at 658.553 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (7-6)' observations at 768.252 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (8-7)' observations at 877.922 GHz\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "CO_obs = alminer.CO_lines(observations, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 2.5.2: search whether any redshifted CO, <sup>13</sup>CO, and C<sup>18</sup>O lines were observed in the query results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Summary of 'CO (1-0)' observations at 115.2712018 GHz (57.636 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (2-1)' observations at 230.538 GHz (115.269 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 4\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 4\n",
      "Total number of subbands = 5\n",
      "Total number of targets with ALMA data = 3\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (3-2)' observations at 345.7959899 GHz (172.898 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 3\n",
      "Total number of subbands = 3\n",
      "Total number of targets with ALMA data = 2\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (4-3)' observations at 461.0407682 GHz (230.52 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 10\n",
      "Number of observations = 13\n",
      "Number of unique subbands = 13\n",
      "Total number of subbands = 13\n",
      "Total number of targets with ALMA data = 8\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (5-4)' observations at 576.2679305 GHz (288.134 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 6\n",
      "Number of unique subbands = 6\n",
      "Total number of subbands = 6\n",
      "Total number of targets with ALMA data = 3\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (6-5)' observations at 691.4730763 GHz (345.737 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 5\n",
      "Total number of subbands = 5\n",
      "Total number of targets with ALMA data = 4\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (7-6)' observations at 806.651806 GHz (403.326 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'CO (8-7)' observations at 921.7997 GHz (460.9 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (1-0)' observations at 110.2013218 GHz (55.101 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (2-1)' observations at 220.3986195 GHz (110.199 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 18\n",
      "Number of observations = 23\n",
      "Number of unique subbands = 23\n",
      "Total number of subbands = 25\n",
      "Total number of targets with ALMA data = 17\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (3-2)' observations at 330.5878671 GHz (165.294 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 1\n",
      "Number of observations = 2\n",
      "Number of unique subbands = 2\n",
      "Total number of subbands = 2\n",
      "Total number of targets with ALMA data = 1\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (4-3)' observations at 440.7651735 GHz (220.383 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 6\n",
      "Number of observations = 7\n",
      "Number of unique subbands = 7\n",
      "Total number of subbands = 7\n",
      "Total number of targets with ALMA data = 5\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (5-4)' observations at 550.9262851 GHz (275.463 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 4\n",
      "Number of unique subbands = 4\n",
      "Total number of subbands = 4\n",
      "Total number of targets with ALMA data = 3\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (6-5)' observations at 661.0672766 GHz (330.534 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 5\n",
      "Number of unique subbands = 5\n",
      "Total number of subbands = 5\n",
      "Total number of targets with ALMA data = 4\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (7-6)' observations at 771.184125 GHz (385.592 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of '13CO (8-7)' observations at 881.272808 GHz (440.636 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 1\n",
      "Number of observations = 1\n",
      "Number of unique subbands = 1\n",
      "Total number of subbands = 1\n",
      "Total number of targets with ALMA data = 1\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (1-0)' observations at 109.7821734 GHz (54.891 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (2-1)' observations at 219.5603541 GHz (109.78 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 19\n",
      "Number of observations = 24\n",
      "Number of unique subbands = 25\n",
      "Total number of subbands = 27\n",
      "Total number of targets with ALMA data = 18\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (3-2)' observations at 329.3305525 GHz (164.665 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 1\n",
      "Number of observations = 2\n",
      "Number of unique subbands = 2\n",
      "Total number of subbands = 2\n",
      "Total number of targets with ALMA data = 1\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (4-3)' observations at 439.0887658 GHz (219.544 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 7\n",
      "Number of observations = 9\n",
      "Number of unique subbands = 12\n",
      "Total number of subbands = 12\n",
      "Total number of targets with ALMA data = 6\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (5-4)' observations at 548.8310055 GHz (274.416 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 3\n",
      "Total number of subbands = 3\n",
      "Total number of targets with ALMA data = 2\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (6-5)' observations at 658.5532782 GHz (329.277 GHz at z=1)\n",
      "--------------------------------\n",
      "Number of projects = 2\n",
      "Number of observations = 3\n",
      "Number of unique subbands = 3\n",
      "Total number of subbands = 3\n",
      "Total number of targets with ALMA data = 2\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (7-6)' observations at 768.2515933 GHz (384.126 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n",
      "--------------------------------\n",
      "Summary of 'C18O (8-7)' observations at 877.9219553 GHz (438.961 GHz at z=1)\n",
      "--------------------------------\n",
      "No observations found.\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "CO_obs = alminer.CO_lines(observations, z=1, print_targets=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "\n",
    "# 3. Plot results <a name=\"results\"></a>\n",
    "\n",
    "This section introduces all the plotting functions that help visualise the queried observations:<br>\n",
    "\n",
    "* [3.1 - Plot an overview of the observations (*alminer.plot_overview*)](#plot_overview)<br>\n",
    "* [3.2 - Plot an overview of a given line in the observations (*alminer.plot_line_overview*)](#plot_line_overview)<br>\n",
    "* [3.3 - Plot observed frequencies in each band (*alminer.plot_bands*)](#plot_bands)<br>\n",
    "* [3.4 - Plot observations in each band (*alminer.plot_observations*)](#plot_observations)<br>\n",
    "* [3.5 - Sky distribution (*alminer.plot_sky*)](#plot_sky)<br>\n",
    "\n",
    "#### General notes about the plotting functions:\n",
    " \n",
    "- Most of the plotting functions have the option to mark frequencies of CO, <sup>13</sup>CO, and C<sup>18</sup>O lines by toggling *mark_CO=True*. A redshift can be provided by setting the *z* parameter that will shift the marked frequencies accordingly. \n",
    "- Most of the plotting functions have the option to mark a list of frequencies. A redshift can be provided by setting the *z* parameter that will shift the marked frequencies accordingly. \n",
    "- Plots can be saved in PDF format by setting the *savefig* parameter to the desired filename. Figures are saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. \n",
    "- To avoid displaying the plot (for example to create and save plots in a loop), set *showfig=False*. \n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 3.1 Plot an overview of the observations <a name=\"plot_overview\"></a>\n",
    "\n",
    "The `alminer.plot_overview` function plots a summary of the observed frequencies, angular resolution, largest angular scales (LAS), and frequency and velocity resolutions.\n",
    "\n",
    "<u>Note</u>: The histogram of observed frequencies displays the distribution of central frequencies and also depends on the choice of binning. To get an overview plot for a specific frequency, use `alminer.plot_observations` and `alminer.plot_line_overview` (see examples below).\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_overview</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_overview**(_observations, mark_freq='', z=0., mark_CO=False, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.1.1: plot an overview of the observations and save the figure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
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\n",
      "text/plain": [
       "<Figure size 3600x4500 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_overview(observations, savefig='alma_galaxy_chemistry')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 3.2 Plot an overview of a given line in the observations <a name=\"plot_line_overview\"></a>\n",
    "\n",
    "The `alminer.plot_line_overview` function creates overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions for the input DataFrame, and highlights the observations of a give frequency (redshift if the *z* parameter is set) specified by the user. \n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_line_overview</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions, highlighting the observations of a give (redshifted) frequency with hatches on the bar plots. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_line_overview**(_observations, line_freq, z=0., line_name='', showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **line_freq (float64)** : Frequency of the line of interest in GHz. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequency given in 'line_freq' parameter should be shifted. <br>\n",
    " * **line_name (str, optional, default: '')** : Name of the line specified in 'line_freq'. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***   \n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.2.1: plot an overview of the observations and highlight observations at a particular frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3600x4500 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_line_overview(observations, line_freq=100.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.2.2: plot an overview of the observations and highlight observations at a redshifted frequency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1avpDxZXoDUjLEu+BEWtDMKe4t6DN9wMAAAAAYMrIyYCJU9wDAAAAAIAFs1DeG8UTRYcFiL3h5GqvNW+psBJYozYEc4p7C9p8P7Zs2ZKjR4+OfX0AAAAAgAmSkwETpbgHAAAAAAD9NjQ9wDpRh2xtuBZwAgcPHmw8mGtLce9Nb3rT0OOzFpSe6H5ceeWVY18fAAAAAGAdkpMBy6K4BwAAAAAAi83CL+95QifMqF27di36JbW2FMUmWdy76qqr8gd/8AeLjl922WUzFZSe7H6cffbZY58BAAAAAGDC5GTARCjudRw7dmzsawAAAAAAsL5Me3nvF5oeAGiO4t7SQWmSXHzxxROZoQ1B6XLux+HDh8c+BwAAAADABMnJgIm4+uqrs3fv3kXHZ624d/vtt2f37t1jXwcAAAAAgPVlqst7tVahJJCkfUWxSThRcW9S2hKUtuF+AAAAAABMkpwMmBTFvYU86sCBA2NfCwAAAACA9WVD0wMAjNssFsUU9zracj8AAAAAAABmxawW9wbzKAAAAAAASJT3gCnXhmBOcW/BLN4PAAAAAACAWaG4BwAAAAAA/ZT3gKm1ffv2xoO5thT3nvOc50xk/aTdQaniHgAAAAAAwHgo7gEAAAAAwGLKe8DU2rNnz0wVxZYq7r3whS/MM57xjInM0OagVHEPAAAAAABgPBT3OrZs2TL2tQEAAAAAWF+U94CptWnTprGv0Zai2ImKe4JSxT0AAAAAAIBxueyyy+RR6eRRV1555djXBwAAAABgfdnY9AAA61VbimKKex1tuR8AAAAAAACz5OKLL57IOushjzr77LPHPgMAAAAAAOuLX94DWIW2FMUU9zracj8AAAAAAAAYPXkUAAAAAADrlfIewAq1JZhT3Otoy/0AAAAAAABg9ORRAAAAAACsZ8p7ACvQlmBOca+jLfcDAAAAAACA0ZNHAQAAAACw3m1seoD1ppRy3yTbkzwgyWnd7S4ZbRGy1lqfN8LrASPQlmBOca+jLfcDAAAAAGBWyMmASZJHAQAAAAAwDZT3lqGU8rgkz07yzCSnj3u5JDWJUBJapC3BnOJeR1vuBwAAAADAtJOTAU2QRwEAAAAAMC2U906glPLwJL+d5JHzh5qbBmhKW4I5xb2OttwPAAAAAIBpJicDmiKPAgAAAABgmijvLaGU8jNJfjHJKVkII+sklp7AGsAytSWYU9zraMv9AAAAAACYZnIyoCnyKAAAAAAApo3y3hCllJckeXEmG0YCLdOWYE5xr6Mt9wMAAAAAYJrJyYCmyKMAAAAAAJhGynsDSilPTvKSdILIYWGkJ37CDGhLMKe419GW+wEAAAAAMM3kZEBT5FEAAAAAAEwr5b0epZQ7JXnVUh8nuS3Jnyd5a5KPJvlkkltrrbdNZkJgEtoSzCnudbTlfgAAAAAATDM5GdAUeRQAAAAAANNMea/fk5I8MP1PEi3d/Vck+YVa681DzgOmRFuCOcW9jrbcDwAAAACAGSAnAyZOHgUAAAAAwLRT3uv3zIH9+UDyebXWfZMfB5iktgRzinsdbbkfAAAAAAAzQk4GTJQ8CgAAAACAWbCh6QFa5pE97+cDydcKJGH6tSWYU9zraMv9AAAAAACYIXIyYGLkUQAAAAAAzArlvX73SCeI7PXfmhgEmJy2BHOKex1tuR8AAAAAADNGTgZMhDwKAAAAAIBZorzX74yB/UO11g83MgkwEW0J5hT3OtpyPwAAAAAAZpCcDBg7eRQAAAAAALNGea/f7QP7n2lkCmAi2hLMKe51tOV+AAAAAADMKDkZMFbyKAAAAAAAZpHyXr8vDOx/rZEpgLFrSzCnuNfRlvsBAAAAADDD5GTA2MijAAAAAACYVcp7/f45SenZP7upQYDxaUswp7jX0Zb7cfXVV09kHQAAAACAlpKTAWMhjwIAAAAAYJYp7/V7z8D+PUopc00MAoxHW4K5NhT3Dh48KCjtuuqqq7J3796JrAUAAAAA0FJyMmDkFPcAAAAAAJh1ynv9Xp+k9uxvSPIdDc0CjFhbgrk2FPeSZNeuXYLSLH0/AAAAAABmjJwMGCnFPQAAAAAAUN7rU2v9VJI3JilZCCd/urGBgJFpSzDXluJekhw9erRvfxaDUsU9AAAAAIAOORkwSop7AAAAAADQoby32M8luaP7viS5sJSys7lxgLVqSzDXpuLeoFkMShX3AAAAAAAWkZMBa6a4BwAAAAAAC5T3BtRaP5bkhVl4qmhJ8j9KKd/a6GDAqrQlmFPc62j7/QAAAAAAmGVyMmCtFPcAAAAAAKCf8t4Qtda9SX41C8Hk1yV5Synlp5ucC1iZY8eOtSKYa0Nx7/rrrx96fBaD0qXux2WXXTaR9QEAAAAA2kxOBqyW4h4AAAAAACymvLeEWuvuJP81yfF0gslTk/xGKeVDpZTnlFLu2uiAwEnt3r278WCuDcW96667Li960YsWHd++ffvMBaUnuh8XX3zxRGYAAAAAAGg7ORmwUop7AAAAAAAw3MamB2izWuuvlVI+kOTVSR6QzhNGvzHJ7yb5nVLKR5L8U5LDSW5O8rURrv3SUV0LZtWBAwf69ttUFJtkce/SSy/NbbfdtuizPXv2zFRQerL7cfjw4YnMAQAAAACwHsjJgOU6ePBgLr/8csW9JFdfffVE1gEAAAAAYP1Q3juJWus7Syn/Kcn/SXJ693BJcko6AeU3jGlpoSSMUNuKYpOw1BNO523atGnsM7QlKG3D/QAAAAAAWG/kZMBy7Nq1K0ePHu07NovFvauuuip79+6dyFoAAAAAAKwfG5oeoM1KKf+hlPIXSd6TTiBZuh/V7pbusVFvwAjNYlHsZMW9SWhTUNr0/QAAAAAAWG/kZMByKe4tnUcBAAAAAIBf3ltCKeWHk/xOkq9Lf1A4LJgc6dJjuCbMrLYEc4p7HbN4PwAAAAAA1hs5GbBainsAAAAAANDPL+8NUUr50SRXJTk1nZCwDtmAltuyZUsrgrk2FPce+tCHTmT9pP1BqeIeAAAAAMDS5GTAainuAQAAAADAYsp7A0opj07yqvSHkYNPFB3nBozIlVde2Xgw14bi3oUXXpgXvehFE5mh7UGp4h4AAAAAwNLkZMBqKe4BAAAAAMBwG5seoIVeleSU9D81dD6YrEnen+RtST6a5IYktya5LZ4yCq1z7rnnTmSdNhTFTlTce+UrX5nPfe5zY5+h7UGp4h4AAAAAwEnJyYAV2759u+Je12WXXZa9e/dOZAYAAAAAANYH5b0epZSLkmxPfwg5/5TPNyT5mVrrvzY0HtBCbSiKnay4JyhV3AMAAAAAOBk5GbBae/bskUelk0c97WlPU94DAAAAAKDPhqYHaJnv73nfG0y+uNb6fQJJoFcbimKKewvacD8AAAAAANYxORmwKps2bRr7GvIoAAAAAADWK+W9fo/qeT8fSP5lrfVlDc0DtFQbgjnFvQVtuB8AAAAAAOucnAxoJXkUAAAAAADrmfJev/ukE0T2+qUmBgHaqw3BnOLegjbcDwAAAACAKSAnA1pHHgUAAAAAwHqnvNdvbmD/5lrre5sYBGinNgRzinsL2nA/AAAAAACmxNzAvpwMaJQ8CgAAAACAaaC81+9LA/ufaWQKoJXaEMwp7i1ow/0AAAAAAJgicjKgNeRRAAAAAABMC+W9focG9m9vZAqgddoQzCnuLWjD/QAAAAAAmDJyMqAV5FEAAAAAAEwT5b1+H0tSevbPamoQoD3aEMwp7i1ow/0AAAAAAJhCcjKgcfIoAAAAAACmjfJev/cO7N+zlLKpkUmAVmhDMKe4t6AN9wMAAAAAYErJyYBGyaMAAAAAAJhGynv99g/s3ynJk5sYBGheG4I5xb0FbbgfAAAAAABTTE4GNEYeBQAAAADAtFLe61Fr/VCS98zvdl9/rJlpgCa1IZhT3FvQhvsBAAAAADDN5GRAU+RRAAAAAABMM+W9xX4mC4FkSfKUUspTG5wHmLA2BHOKewvacD8AAAAAAGaEnAyYKHkUAAAAAADTTnlvQK31vUl+NZ1AsnZfX1tK+cZGBwMmog3BnOLegjbcDwAAAACAWSEnAyZJHgUAAAAAwCxQ3hui1vpzSV6bhWDytCTvKKV8X6ODAWPVhmBOcW9BG+4HAAAAAMCskZMBkyCPAgAAAABgVijvLaHWekk6TxZNOsHk1iRXl1LeXEr5tuYmYxxKKfcqpTyzlPIrpZR3lFJuKaXUnu2GpmdkvNoQzCnuLWjD/QAAAAAAmFVyMmCc5FEAAAAAAMySjU0P0DallEt6dq9L8sdJ/mM6wWRJ8l1JvquUcijJ3yX5cJLDSW5O8rVRzVFrfc2orsVwpZTHJrk8yaOSnNPwODSoDcGc4t6CNtwPAAAAAIBZJCcDxk0eBQAAAADArFHeW2xfOgHkMPPBZJLcPcl3d7dxEEqO3wVJntn0EDSrDcGc4t6CNtwPAAAAAIAZti9yMmBM5FEAAAAAAMwi5b2llSX26wm+MypLhaJMzq1J7tr0EIxXG4I5xb0FbbgfAAAAAAAkkZMBIyaPAgAAAABgVinvLW2p8LE3nBxHeDiuoJOlHU3ywSR/n+QD3df7JfmbJodivNoQzCnuLWjD/Th48OBE1gEAAAAAWAfkZMDIyKMAAAAAAJhlynvL4wmf0+nNSd6W5F9qrcd7Pyil3K+ZkZiENgRzbSjuHTt2LFdccYWgNJ37sWvXromsBQAAAACwzsjJgFVT3AMAAAAAYNYp7w3nqZ4zoNb6r03PwOS1IZhrQ3EvSXbv3p0DBw70HZvFoHT+fhw9enQi6wEAAAAAtJycDBgJxT0AAAAAAFDeG+Zbmx4AGI82BHNtKe4lUdzL0vcDAAAAAGBGycmAkVDcAwAAAACADuW9AbXWa5qeARi9NgRzbSruDZrFoFRxDwAAAACgn5wMGAXFPQAAAAAAWLCh6QEAxq0NwZzi3oI23w8AAAAAAABWT3EPAAAAAAD6Ke8BU60NwVwbinvHjh0benwWg9Kl7sf27dsnsj4AAAAAAMA0UtwDAAAAAIDFNjY9AMC4XH311dm7d++i420oik2yuHf77bfnZS972aLjW7Zsmbmg9ET346UvfWme8pSnTGQOAACYBsePH1907MiRI5MfpKWG/VsM+zcDAACYBop7AAAAAAAwnPIetEQp5awkZ67wtAeMY5Zpobi3EJRee+21iz678sorZyooPdn9uOOOOyYyBwAATIujR48uOrZjx44GJlk/Dh8+nLPPPrvpMQAAAEbq2LFjueKKKxT3khw8eHAi6wAAAAAAsH4o70F7XJbkJU0PMc3aVBSbZHFvMCidd+655459hqQdQely7ofyHgAAAAAAjE8p5V5JLkzyqO7rI5Ns6fnKjbXWbQ2Mxhrt3r07Bw4c6Ds2i8W96667Lrt27ZrIWgAAAAAArB/Ke8BMaFtRbNxOVtyblLYEpU3fDwAAAAAAmEWllMcmuTydwt45DY/DmCjuLeRRw36lHgAAAACA2aa8B0y9WSuKKe4taMP9AAAAAACAGXZBkmc2PQSTM8vFvcE8CgAAAAAAEuU9aJO9SV6/wnMekPz/7P17mGTXWR/6f5csWx7JHRmDkbkEZMNgjA3xJEgkELAhJPEJEAsCTBJuUnAI9DmHpGObMEFgYwSThHAGwi8NBHw0SrikuSQ2mJBgCBgCnGCggQiPw2BZNsYB2wibtqbl6/r9UT2p7pqu7q7u2lWran8+zzOPtHdd1tKsWkv17ne9u/LyDvqyNFpIzLVQuHfTTTfl4Ycf7rz9q1pOlCrcAwCAbq2srOTChQs5ffr0TNrb2NjI+vr6NedXV1dz9uzZmfTh8uXLWVtb8wsLAAAwmXcmedy8O8H0KNwDAAAAAIBrKd6DRtRa35LkLZO8ppTSUW+Ww+rq6twTcy0U7t1888158YtfnLW1tc77kLSdKFW4BwAA3VpZWclLX/rSmW7U3K9wb9bxx/Of//xrCvfOnDmTzc3NmfQBAAAWwFaSX0/y6iS/uvPPJyf5uXl2iulRuAcAAAAAAPtTvDeilPIN8+5DktRaXzLvPsCim9UvLLRQKHZQ4d73fu/35oYbbui8D0nbiVKFewAA0L0LFy7YqJlB/PGSl7wkz3nOc2bSDwCAaZEnowM/keSnk7y21vr+3Q+UUp48ny4xbSsrKwr3driRCwAAAAAAoxTvXevFSeq8O5FEUhIWQAuFYocV7j3taU/LAw880Hk/Wk6UKtwDAIDZOH369EzaWYT445FHHplJPwAApuzFkSdjimqtr5t3H+ieG7kMuJELAAAAAAD7Ubw3Xplj2y0kRYFDtFAodpTCvVloPVGqcA8AAJbHosQfivcAgAUnTwYcmRu5uJELAAAAAADjKd4bb16JwXkmQ4EjaqFQTOHeUAvjAQAAdE/8AQAwM/JkQFMWJR5UvAcAAAAAwCjFe/Mxmnh0B1FYIC1s1FS4N9TCeAAAAN0TfwAALA15MmAi4kEAAAAAABaZ4r39dXlXz5phErKM/BNoXAuJOYV7Qy2MBwAA0D3xBwDATMmTAc0QDwIAAAAAsOgU713ryVN8r0cl+YAkT0jyzCSfkuSvJXlshonJmuT/TfLNcWdRaFoLiTmFe0MtjAcAANA98QcAwEzJkwHNWMR48P3vf/817/GOd7wjDz30UKf9XBSjf4/J/n9nsJ/9Pitvf/vbZ9+RRu33d2F+AQAAALRB8d6IWusbOnrrVyb51lLKE5N8dZIXJHlMBncT/XtJnpjkbK31XR21D5xACxs1Fe4NtTAeAABA98QfAACzJU/GsiulfHAGn7dJfFQXfeFgixoP/umf/uk15770S7+0sz4ugz/90z/NB33QB827GyyAra2ta84997nPnUNPFsdDDz2UW265Zd7dAAAAAOg9xXszVmt9a5KvL6X8WJIfziDZU5J8TpKfKKX8H7XW982zj8BeLWzUVLg31MJ4AAAA3RN/AAAsH3kyGrCa5EXz7gQHEw8CAAAAALBMFO/NSa31N0spn5nkV5I8KYPE5F9J8p0ZJI2YgVLKpyQ5tc9Df27k+LE747WfN9daXzPdnu1VSrkzyZ37PCQr1LEWEnMK94ZaGA8AAKB74g8AgOUmTwaMIx4EAAAAAGDZKN6bo1rrG0spfyfJzyepGSQm/0Ep5cdqrT871871xw8k+cgjPO+WJK8c89h92b+wbppuTfKsjttgRAuJOYV7Qy2MBwAA0D3xBwBAP8iTAaPEgwAAAAAALCPFe3NWa/2FUsorknx2honJ80lun2vHaM2DSV61z/kbk9w22670QwuJOYV7Qy2MBwAA0D3xBwBAv8iTMQfrSX5kwtd8VJKXd9AXdlnmePDlL395Hv/4xx/pudvb2zl37lw2Nzf3nF9ZWcmFCxdy+vTpY/VhUhsbG1lfX7/m/Orqas6ePXvs933729+e5z73uSfpGlxjWebHJC5fvpy1tbVsbW3NpD0AAAAATkbxXhu+L4Ok5FV/oZTyl2qtvzKvDtGWWuvFJBdHz5dSnp7k/ln3Z9m1sFFT4d5QC+MBAAB0T/wBANBb8mTMTK31LUneMslrSikd9Yarlj0efPzjH58nPOEJhz7vypUreeELX3hN4d488oP7FSbNcjzgqFZWVvLSl760V/Pj0qVLef7zn39N4d6ZM2euWT8AAAAAaMN18+4ASZKfTfLekXNuNzcDtdZba63lhH/unPd/B9PTwkZNhXtDLYwHAADQPfEHAECvyZNBj4kHB+QH4XguXLjQq/lx0Hp1/vz5mfQBAAAAgMkp3mtArfXhJP9r5PQnzaMv0GcSc0OtJx5snAUAgOUh/gAA6Dd5Mugv8eCA/CAc3+nTp2fSTgvz47D16tSpUzPpBwAAAACTU7zXjrcmKUnqzj8/Zr7dgX6RmBtahMSDjbMAALAcxB8AAOyQJ4OeEQ8OyA9C+1qYHy2sVwAAAAAcn+K9doyOxQfMpRfQQy1c6JaYG2phPAAAgO6JPwAA2EWeDHpEPDggPwjta2F+tLBeAQAAAHAyivfa8aQM7iYKzFALF7ol5oZaGA8AAKB74g8AAEbIk0FPiAcH5AehfS3MjxbWKwAAAABOTvFeA0oppzNISu721nn0BfqkhQvdEnNDLYwHAADQPfEHAAC7yZNBf4gHB+QHoX0tzI8W1isAAAAApkPxXhvu3PXvZeefkpLQoRYudEvMDbUwHtvb2523AQAAfSf+AABgH3fu+nd5MlhS4sEB+UFoXwvzo4X1CgAAAIDpUbw3Z6WUpydZS1J3na5Jfm0+PYLl18KFbom5oVbG49y5c523AwAAfSb+AABglDwZ9IN4cEB+ENrXwvxoYb0CAAAAYLqun3cH+qyUcluSH0/y2OxNSibJT82+R7D8WrjQ3UpibmNjI+vr69ec71vi4ep4bG5udt4WAAD0lY1PAACMkieDfhAPDrSSH2xhPKBVLcyPFtYrAAAAAKZP8d4clFL+YpLnJfmyJI/KtQnJP07yyln3C5ZdCxe6W0nMJVG4l/HjAQAATI+NTwAA7CZP1j+llE9Jcmqfh/7cyPFjSymfOeZt3lxrfc10e7ZXKeXOJHfu85CA4ZjEgwPb29t54QtfOPf8YAvjcfny5Zm0A5NqYX60sF4BAAAA0A3FeyNKKd8w7bdMclOSP5Pko5N8QpIP3PVYHXluTfKSWuuVKfcDeq2FC90tFe7tp2+JB4V7AADQPRufAAAWizwZHfmBJB95hOfdkvGFm/dl/8K6abo1ybM6bqM3xIND586dy+bm5p5zfSzcu3TpUtbW1mbSFkyilfnRwnoFAAAAQDcU713rxbn2Dp/TVHb9+37t/H9JvqvD9qF3WrjQrXBvqOXxAAAApsfGJwCAhfTiyJPRXw8medU+529Mcttsu7LYxIN7KdwbjsfW1tZM2oOjaml+tLBeAQAAANANxXvjlcOfcizjEp4lyW8l+Ru11vd11DYLqpRyZ/a/m6irtIdo4UK3wr2hlsdjZWVFwhAAAKbExicAgIUnT0bv1FovJrk4er6U8vQk98+6P4tKPHiwPhfujY4HzFvL86OF9QoAAACA6VG8N16XdxXd7Wry898l+Ye1Vles2c+tSZ41704smsuXL+f5z39+k4Vis07MvexlL9v3fN8SDweNx7d927flec97Xud9AACAZWfj08D29nbnbQAAdEiejKmptd467z4wG+LBgyncg3a0PD9aWK8AAAAAmC7Fe/NxNRH5/iQ/k+Rf1lpfOcf+0L4Hk7xqn/M3Jrlttl1ZHGtra9f8klorhWKzTszde++915xfXV3tVeLhsPG45ZZbOu8DAAAsu42Njayvr19zvm8bn65cuZJz58513g4AwIKSJ4MlpBBmYNyNXBTuQTtanh8K9wAAAACWk+K9/ZXDn3Is20len+TXk/xakpfVWn+/o7ZYIrXWi0kujp4vpTw9yf2z7s+iULg3PvGQJGfPnp1JH1pIPBxlPB566KHO+wEAAMtO4d4w/tjc3Oy8LQCAjsiTARNxI5eBK1eu5J577rnm/MrKShP5wRbG48yZM+Jl5qrl+aFwDwAAAGB5Kd671pOn/H41ycNJ3lFrfe+U3xs4otYKxWbhoMK9WWkh8dDKeAAAQB/1bePTuPgDAGCByJMBE1O4N4wH77//2vuuXrhwYe75wVbG4yUveUme85znzKQfMKr1+aFwDwAAAGB5Kd4bUWt9w7z7AExXCxs1Fe4N9XE8AACgj/q28UnhHgCwDOTJgGkQD+51+vTpzvuQLEZh0iOPPDKTfsCoRZgfCvcAAAAAltd18+4AQJdaSMwp3Bvq43gAAEAf9W3jk8I9AACAAfHgfChMgvHMDwAAAADmTfEesLTOnDkz98RcK4V7d91110zaT9pIPLQyHgAA0Ed92/g0Lv5YWVnpvG0AAICWiAfnQ2ESjGd+AAAAANACxXvA0jp//nyvCsUOSjzccccdM+lDC4mHVsYDAAD6aHV1tVcbnw6KPy5cuNB5+wAAAK3oWyHMuHjwpptu6rzt3RQmwXjmBwAAAACtULwHLK1Tp0513kYrhWISDwOtjAcAAPTV2bNnZ9LOIsQfp0+f7rwPAAAALXAjl4Gbb74599xzT+ftXyU/COOZHwAAAAC05Pp5dwBgUbVSKCbxMNDKeAAAAN1alPjjoYce6rwfAAAALXAjl2E8eMMNN3Teh0R+EA5ifgAAAADQGr+8B3AMrRSKSTwMtDIeAABAt8QfAAAA/SQeHJIfhPHMDwAAAABa5Jf3ACYkMTfUQuKhlfEAAAC6Jf4AAAC6VEq5M8md+zykymLOxIND8oMwnvkBAAAAQKsU7wFMQGJuqIXEQyvjAQAAdEv8AQAAzMCtSZ41706wl3hwSH4QxjM/AAAAAGiZ4j2AI5KYG2oh8dDKeAAAAN0SfwAAADPyYJJX7XP+xiS3zbYrJOLB3eQHYTzzY2B7e7vzNgAAAAA4nqUv3iul/It59+E4aq1fM+8+AEMSc0MtJB5aGQ8AAKBb4g8AgJORJ4Ojq7VeTHJx9Hwp5elJ7p91f/pOPDgkPwjjbWxsZH19/ZrzfZsfV65cyblz5zpvBwAAAIDjWfrivSQvSFLn3YljkJSERkjMDbWSeGhhPAAAgG6JPwAApkKeDFg44sEh+UE4mMK94Xq1ubnZeVsAAAAAHE8fiveuKvPuwAQWMYkKS0libqilxMO8xwMAAOiW+AMAYOrkyYCFIB4ckh+EyfVtfoxbrwAAAABoS5+K9xYl0bdIyVNmpJRyZ5I793lINqRDEnNDLScebJwFAIDlIv4AAOiEPBnQPPHgkPwgTK5v80PhHgAAAMDi6FPxXotGE5CLkjhl9m5N8qx5d6JPJOaGWk482DgLAADLRfwBANAr8mTA/yYeHJIfhMn1bX4o3AMAAABYLH0p3nOXThbdg0letc/5G5PcNtuuLD+JuaGWEw82zgIAwHIRfwAAdEaeDGiaeHBIfhAm17f5MW69WllZydbWVuftAwAAADC5PhTv3TXvDuzj1iT/KMmf2TmWNOVAtdaLSS6Oni+lPD3J/bPuzzKTmBtqOfFg4ywAACwX8QcAQGfkyYCmiQeH5Adhcqurq72aHwetV9/2bd+W5z3veZ33AQAAAIDJLX3xXq31vnn34apSygcn+fokz0vymKun59cjYDeJuaHWEw82zgIAwPIQfwAAdEeeDGiZeHBIfhCO5+zZszNpp4X5cdh6dcstt3TeBwAAAACOZ+mL91pQSvkzSb4myT9McmOuTUTWkeO3zqJfwJDE3NAiJB5snAUAgOUg/gAAWH7yZMB+xIND8oPQthbmx1HWq4ceeqjzfgAAAABwPNfNuwPLrJTy2FLKP0ny+iTnktyUQUKyjvzJzvmtJC9K8lGz7y30l8Tc0KIkHgAAgMUn/gAAWG7yZMA44sEh+UFoWwvzo5X1CgAAAIDj88t7HSilXJ/kK5J8XZInZXgH0dE7h2bnsUeS/Osk52utboUFM9TKhW6JuYFWxgMAAOiW+AMAYHnJkwEHEQ8OyQ9C21qYH62sVwAAAACcjOK9KSulfHGSb0xyaw5PRr43yf+b5CW11jfPpIPA/9bKhW6JuYFWxgMAAOiW+AMAYHnJkwEHEQ8OyQ9C21qYH62sVwAAAACcnOK9KSmlPDfJPUk+LocnI2uSH0ryDbXW182mh8BurVzolpgbaGU8AACAbok/AACWkzwZcBjx4JD8ILSthfnRynoFAAAAwHQo3juhUsqnJ/mWJLfn8GRkkvxkkq+rtf72DLoH7KOVC90ScwOtjMfGxsZM2gEAgL4SfwAALB95MuAoxIND8oPQthbmRyvrFQAAAADTo3jvmEopt2WQjPyMq6d2/jmakLx6/heS/NNa6y/PoHvAGK1c6G4hMXf58uU8//nPl3jIYDzW19dn0hYAAPSRjU8AAMtFnoxlVEq5M8md+zykkukExINDLeQHWxgPaFUL86OV9QoAAACA6VK8N6FSytOS3JPkjqundv45Lhn5GxncQfS/dN874CCtXOhuITGXJGtra9na2tpzro+Jh3HjAQAATIeNTwAAy0OejCV3a5JnzbsTy0Q8ONRCfrCF8dje3u68DTiOFuZHK+sVAAAAANOneO+ISikfmeQbk3xRkusyPhmZncf+Z5Kvr7X+6Gx6CByklQvdLSTmrlK4p3APAAC6ZuMTAMBykCejJx5M8qp9zt+Y5LbZdmXxiQeHNjY2sr6+fs35vhXuXblyJefOneu8HZhUK/OjhfUKAAAAgG4o3jtEKeWDk9yd5CuSPDqHJyN/P4Pk5cVa6/tn0kngQK1c6G6pcG9UHxMPCvcAAKBbNj4BACw+eTL6pNZ6McnF0fOllKcnuX/W/Vlk4sG9FO4Nx2Nzc7PztmASLc2PFtYrAAAAALqheG+MUsrNSb4myVdncDfFw5KRb03yLUm+q9b67pl0EjhUKxe6Fe4NtD4eAADAdNj4BACw2OTJgOMSDx6ur4V7o+MB89by/GhlvQIAAABgOq6bdwdaU0o5VUr52iQPJPnaJDdlkHSsuTYhWZJsJXlRkqfUWr9DQhLasb293cSF7hYK9x544IF9z/cx8TBuPFZXV2fSPgAALDsbnwAAFpc8GXAS4sHDKdyDNrQ8P1pZrwAAAACYHsV7O0op15dSVpO8Lsk3J/mAHJyMfFeSf5lBMvKbaq0Pz7K/wOHOnTs39wvdLRTuXbp0KXffffc158+cOdO7xMNB43H27NmZ9AEAAJbZ5cuXbXzasbGxMZN2AACmQZ4MOCmFMIdTuAdtaHl+tLJeAQAAADBdiveSlFK+JMn/TPKdSZ6Ug5OR70vyPUk+utb6NbXWh2bZV+DoNjc39xy3VCg268Tcww9fu2/i/PnzvUo8tDAeAACw7NbW1mx8yiD+WF9fn0lbAAAnJU8GnJQbuQy97GUv2/e8wr2BlZWVztuGg7Q8PxTuAQAAACyvXhfvlVKeW0r5H0kuJnlyDk5GJskPJXlarfWraq1vnllHgRPrY6HYuMTDVadOneq8D60kHloYDwAA6IOtra09x33c+DQu/gAAaI08GTAtbuQycN999+Xee++95vzq6urc84OtjMeFCxc6bx/GaX1+KNwDAAAAWF7Xz7sD81BK+Ywk35LktgwTjqOJyOx67BVJvq7W+j9m0D1gylrZqNlS4d4stJJ4aGE8AACgj/q48UnhHgCwCOTJgGlzI5eD48GzZ8/OpA+LUJh0yy23dN4H2M8izA+FewAAAADLq1fFe6WU2zJIRn7G1VM7/xx3B9FfSHKu1vorM+gejFVKuTPJnfs81P0V5AXXSmJO4d5AH8cDAAD6qI8bnxTuAQCtkycDZkE8OB+LUpj00EMPdd4PGLUo8wMAAACA5dWL4r1SytOSfHOS5149tfPPccnI30jyT2utPz2D7sFR3JrkWfPuxKJZWVlpIjHXQuHeM57xjNx///0z6UMriYcWxgMAAPqojxufWtioCQAwjjwZMCviwflQmATjmR8AAAAAtOC6eXega6WU+5L8dgYJybLzp2b/hORrk3xhrfUTJSRpzINJXrXPn1fPsU/Nu3DhwtwTcy0U7t1+++25++67Z9KHVhIPLYwHAAD00ZkzZ3q38Wlc/LG6ujqT9gEADiJPBsxKHwthFO4NtDIeMMr8AAAAAKAVS1+8l+RLkjwqe5ORV+8cejVJ+aYkX57kGbXWH51HJ+EgtdaLtdZnj/5Jcte8+9ay06dPz6SdFgrFDks8nDp1qvM+tJJ4aGE8AACgr86fP9+rjU8HxR9nz56dSR8AAA4hTwZ0zo1chu66a3bpW4VJMJ75AQAAAEBLrp93B2bk6t1DRxOTb0/yL5N8V5J3JXlsKWW/189crfXKvPsAHK6FQjGJh6EWxgMAAPrMjUOG8cdDDz00k34AAByBPBnQKTdyGXjBC16QT/3UT829997beR/kB2E88wMAAACA1vSleC/ZexfRq25O8k07f1pS06+xgYXUQqGYxMNQC+MBAAB0S/wBAHBs8mRAZ9zIZRgPPvDAA533QX4QxjM/AAAAAGhR3xNfbdw+FFg4LWzUlHgYamE8AACAbok/AACmTp4MWAjiwSH5QRjP/AAAAACgVX0v3qvz7sA+JEqhcRJzA60kHloYDwAAoFviDwCATsiTAc0TDw7JD8J45gcAAAAALetT8V6LCUhgwUjMDbSSeGhhPAAAgG6JPwAApkKeDFg44sEh+UEYz/wAAAAAoHXXzbsDAItCYm6glcRDC+MBAAB0S/wBAADQT+LBIflBGO/y5cvmx46NjY2ZtAMAAADA5Prwy3tvjLuJAickMTfQSuKhhfEAAAC6Jf4AAJgKeTI4olLKnUnu3Oeh7hMw7CEeHJIfhIOtra1la2trz7k+zo/77rsv6+vrM2kLAAAAgMktffFerfXWefcBWGwScwMtJR7mPR4AAEC3xB8AANMhTwYTuTXJs+bdib4TDw7JD8LhFO6NX68AAAAAaMfSF+8BnITE3EDriQcbZwEAYHmIPwAAgDl5MMmr9jl/Y5LbZtuVfhIPDskPwuT6OD8U7gEAAAAsBsV7AGNIzA20nniwcRYAAJaH+AMAAJiXWuvFJBdHz5dSnp7k/ln3p2/Eg0PygzC5Ps4PhXsAAAAAi+O6eXcAoEUScwOtJx5snAUAgOUh/gAAAOgn8eCQ/CBMro/zQ+EeAAAAwGJRvAcwQmJuoPXEg42zAACwPMQfAAAA/SQeHJIfhMmdOXOmd/Nj3Hq1uro6k/YBAAAAmJziPYBdJOYGWk882DgLAADLQ/wBAADQT+LBIflBOJ7z58/3an4ctF6dPXt2Jn0AAAAAYHKK9wB2SMwNLELiwcZZAABYDuIPAACAfhIPDskPwvGdOnWq8zZamR8trFcAAAAAHI/iPYC0caFbYm6ohfEAAAC6Jf4AAADoJ/HgkPwgtK2V+dHCegUAAADA8SneA3qvhQvdEnNDLYwHAADQLfEHAABAP4kHh+QHoW2tzI8W1isAAAAATkbxHtBrLVzolpgbamE8AACAbok/AAAA+kk8OCQ/CG1rZX60sF4BAAAAcHKK94DeauFCt8TcUAvjAQAAdEv8AQAA0E/iwSH5QWhbK/OjhfUKAAAAgOlQvAf0UgsXuiXmhloYj8uXL8+kHQAA6CvxBwAAQD+JB4fkB6FtrcyPFtYrAAAAAKZH8R7QOy1c6G4hMbe9vS3xsOPSpUtZW1ubSVsAANBHNj4BAAD0k3hwqIX8YCvjAS1qZX60sF4BAAAAMF3Xz7sDALPUwoXuFhJzSXLu3Llsbm7uOdfHxMPV8dja2ppJewAA0Dc2PgEAAPSTeHCohfxgK+MBLWplfrSwXgEAAAAwfYr3YAGUUu5Mcuc+D82mymtJtHChu4XE3FUK98aPBwAAMB02PgEAAPSTeHDo8uXLef7zn69wL8nGxsZM2oFJtDI/WlivAAAAAOiG4j1YDLcmeda8O7HIWrjQ3VLh3qg+Jh4U7gEAQLdsfAIAAOgn8eBea2tr2dra2nOuj4V79913X9bX12fSFhxVS/OjhfUKAAAAgG4o3oPF8GCSV+1z/sYkt822K4unhQvdCveGWh4PAABgOmx8AgAA6Cfx4LUU7o0fD5in1ueH61cAAAAAy0PxHiyAWuvFJBdHz5dSnp7k/ln3Z5G0cKG7hcK97e3tfc/3MfEwbjzOnDmTzc3NmfQBAACWmY1PAAAA/SQePJzCPWhD6/OjhfUKAAAAgOm5bt4dAOjKxsbG3C90t1C4d+XKldxzzz3XnF9ZWeld4uGg8Th//vxM+gAAAMtse3vbxqcdly9fnkk7AAAALVAIcziFe9CG1udHC+sVAAAAANOleA9YWuvr69eca6VQbNaJufvvv/YHGi9cuNCrxMNh43Hq1KmZ9AMAAJbZuXPnbHzKIP5YW1ubSVsAAADz5kYuQw888MC+5xXuQRtanx8K9wAAAACWk+I9oDdaKhSbZ2LuqtOnT3feh6SNxEML4wEAAH2wubm557iPG5+uxh9bW1szaQ8AAGDe3Mhl4NKlS7n77ruvOX/mzJm55wdbGY/V1dWZtA/7aX1+KNwDAAAAWF6K94Be6Fuh2GGFe7PSQuKhhfEAAIA+6uPGp3HxBwAAwDJzI5dhPPjwww9f89j58+cV7mUwHmfPnp1JH2DUIswPhXsAAAAAy0vxHrD0WtioqXBvqG/jAQAAfdTHjU8K9wAAAMSD+zl16lTnfVCYBOOZHwAAAADM2/Xz7gBAl1pIzLVQuHfTTTfte6fPrrSQeGhhPAAAoI/6uPFJ4R4AACy+UsqdSe7c5yEJhSMSD86HwiQYz/wAAAAAoAV+eQ9YWqurq3NPzLVQuHfzzTfnnnvu6bz9q1pIPLQwHgAA0EcrKyu92/g0Lv44c+bMTNoHAACm5tYkz9rnz21z7NPC6GMhjMK9oRbGA0aZHwAAAAC0QvEesLTOnj07k3ZaKBQ7LPHwlKc8pfM+JG0kHloYDwAA6KsLFy70auPTQfHH+fPnZ9IHAABgah5M8qp9/rx6jn1aCG7kMvSMZzxjJu0nCpPgIOYHAAAAAC1RvAdwAi0Uikk8DLUwHgAA0GenT5+eSTuLEH+cOnVqJv0AAACmo9Z6sdb67NE/Se6ad99a50YuA7fffnvuvvvumfRBfhDGMz8AAAAAaI3iPYBjaqFQTOJhqIXxAAAAuif+AAAAaIsbucz2Ri7ygzCe+QEAAABAixTvARxDCxs1JR6GWhgPAACge+IPAACAfhIPDsgPwnjmBwAAAACtUrwHMCGJuaEWEg8tjAcAANA98QcAAEA/iQcH5AdhPPMDAAAAgJYp3gOYgMTcUAuJhxbGAwAA6J74AwAAoJ/EgwPygzCe+QEAAABA6xTvARyRxNxQC4mHFsYDAADonvgDAACgn8SDA/KDMN729rb5sePy5cszaQcAAACAyV0/7w4ALAKJuaEWEg8tjAcAANA98QcAAEA/iQcH5AfhYOfOncvm5uaec32cH5cuXcra2tpM2gIAAABgcn55D+AQEnNDrSQe5j0eAABA98QfAAAA/SQeHJAfhMMp3BuuV1tbWzNpDwAAAIDJKd4DOIDE3FBLiQcbZwEAYLmJPwAAAPpJPDggPwiT6+P8GLdeAQAAANAWxXsAY0jMDbWceLBxFgAAlov4AwAAoJ/EgwPygzC5Ps4PhXsAAAAAi0PxHsA+JOaGWk482DgLAADLRfwBAADQT+LBAflBmFwf54fCPQAAAIDFongPYITE3FDLiQcbZwEAYLmIPwAAAPpJPDggPwiTW1lZ6d38GLdenTlzZibtAwAAADA5xXsAu0jMDbWceLBxFgAAlov4AwAAoJ/EgwPyg3A8Fy5c6NX8OGi9On/+/Ez6AAAAAMDkrp93BwBaITE31HriwcZZAABYHuIPAACAfhIPDsgPwvGdPn16Ju20MD8OW68eeeSRmfQDAAAAgMn55T2ASMzttgiJBxtnAQBgOYg/AAAA+kk8OCA/CO1rYX60sF4BAAAAcHyK94Dea+FCt8TcUAvjAQAAdE/8AQAA0E/iwQH5QWhfC/OjhfUKAAAAgJNRvAf0WgsXuiXmhloYDwAAoHviDwAAgH4SDw7ID0L7WpgfLaxXAAAAAJyc4j2gt1q40C0xN9TCeAAAAN0TfwAAAPSTeHBAfhDa18L8aGG9AgAAAGA6rp93B4DDlVLuTHLnPg+5GntMLVzolpgbamE8tre3O28DAAD6TvwBAADQT+LBAflBaF8L86OF9QoAAACA6VG8B4vh1iTPmncnlkULF7ol5oZaGY9z58513g4AAPSZ+AMAAKCfxIMD8oPQvhbmRwvrFQAAAADTpXgPFsODSV61z/kbk9w2264sthYudLeSmNvY2Mj6+vo15/uWeLg6Hpubm523BQAAfWXjEwAAQD+JBwdayQ+2MB7QqhbmRwvrFQAAAADTp3gPFkCt9WKSi6PnSylPT3L/rPuzqFq40N1KYi6Jwr2MHw8AAGB6bHwCAADoJ/HgwPb2dl74whfOPT/Ywnhcvnx5Ju3ApFqYHy2sVwAAAAB0Q/Ee0AstXOhuqXBvP31LPCjcAwCA7tn4BAAA0E/iwaFz585lc3Nzz7k+Fu5dunQpa2trM2kLJtHK/GhhvQIAAACgG9fNuwMAXWvhQrfCvaGWxwMAAJgeG58AAAD6STy4l8K94XhsbW3NpD04qpbmRwvrFQAAAADdULwHLLUWLnQr3BtqeTxWVlY6bxsAAPrCxicAAIB+Eg8erM+Fe6PjAfPW8vxoYb0CAAAAYHoU7wFL6/Lly3O/0N1K4d7LXvayfc/3LfFw0HhcuHCh8/YBAKAPbHwa2N7e7rwNAABgekopd5ZSfn70T5J75923RSEePJjCPWhHy/OjhfUKAAAAgOm6ft4dAOjK2tpatra29pxrpVBs1om5e++9Nq+8urraq8TDYeNxyy23dN4HAABYdhsbG1lfX7/mfN82Pl25ciXnzp3rvB0AAGCqbk3yrHl3YlEphBkYdyMXhXvQjpbnh8I9AAAAgOWkeA9YWgr3xicekuTs2bMz6UMLiYejjMdDDz3UeT8AAGDZKdwbxh+bm5udtwUAAEzVg0letc/5G5PcNtuuLBY3chm4cuVK7rnnnmvOr6ysNJEfbGE8zpw5I15mrlqeHwr3AAAAAJaX4j2gF1orFJuFgwr3ZqWFxEMr4wEAAH3Ut41P4+IPAACgfbXWi0kujp4vpTw9yf2z7s8iUbg3jAfvv//aj8qFCxfmnh9sZTxe8pKX5DnPec5M+gGjWp8fCvcAAAAAlpfiPWDptbBRU+HeUB/HAwAA+qhvG58U7gEAAAyIB/c6ffp0531IFqMw6ZFHHplJP2DUIswPhXsAAAAAy+u6eXcAoEstJOYU7g31cTwAAKCP+rbxSeEeAADAgHhwPhQmwXjmBwAAAADzpngPWFpnzpyZe2KulcK9u+66aybtJ20kHloZDwAA6KO+bXwaF3+srKx03jYAAEBLxIPzoTAJxjM/AAAAAGiB4j1gaZ0/f75XhWIHJR7uuOOOmfShhcRDK+MBAAB9tLq62quNTwfFHxcuXOi8fQAAgFb0rRBmXDx40003dd72bgqTYDzzAwAAAIBWKN4DltapU6c6b6OVQjGJh4FWxgMAAPrq7NmzM2lnEeKP06dPd94HAACAFriRy8DNN9+ce+65p/P2r5IfhPHMDwAAAABacv28OwCwqFopFJN4GGhlPAAAgG4tSvzx0EMPdd4PAACAFriRyzAevOGGGzrvQyI/CAcxPwAAAABojV/eAziGVgrFJB4GWhkPAACgW+IPAACAfhIPDskPwnjmBwAAAAAtUrwHMCGJuaEWEg+tjAcAANAt8QcAAEA/iQeH5AdhPPMDAAAAgFYp3gOYgMTcUAuJh1bGAwAA6Jb4AwAAoJ/Eg0PygzCe+QEAAABAyxTvARyRxNxQC4mHVsYDAADolvgDAACgn8SDQ/KDMJ75MbC9vd15GwAAAAAcz/Xz7gDAIpCYG2oh8dDKeAAAAN0SfwAAAPSTeHBIfhDG29jYyPr6+jXn+zY/rly5knPnznXeDgAAAADH45f3AA4hMTfUSuKhhfEAAAC6Jf4AAADoJ/HgkPwgHEzh3nC92tzc7LwtAAAAAI5H8R7AASTmhlpKPMx7PAAAgG6JPwAAAPpJPDgkPwiT69v8GLdeAQAAANAWxXsAY0jMDbWceLBxFgAAlov4AwAAoJ/Eg0PygzC5vs0PhXsAAAAAi0PxHsA+JOaGWk482DgLAADLRfwBAADQT+LBIflBmFzf5ofCPQAAAIDFongPYITE3FDLiQcbZwEAYLmIPwAAAPpJPDgkPwiT69v8GLderaysdN42AAAAAMejeA9gF4m5oZYTDzbOAgDAchF/AAAA9JN4cEh+ECa3urraq/lx0Hp14cKFztsHAAAA4Hiun3cHAFohMTfUeuLBxlkAAFge4g8AAIB+Eg8OyQ/C8Zw9e3Ym7bQwPw5br2655ZbO+wAAAADA8fjlPYBIzO22CIkHG2cBAGA5iD8AAAD6STw4JD8IbWthfrSyXgEAAABwPIr3gN5r5UK3xNxAK+MBAAB0S/wBAADQT+LBIflBaFsL86OV9QoAAACA41O8B/RaKxe6JeYGWhkPAACgW+IPAACAfhIPDskPQttamB+trFcAAAAAnIziPaC3WrnQLTE30Mp4AAAA3RJ/AAAA9JN4cEh+ENrWwvxoZb0CAAAA4OQU7wG91MqFbom5gVbGAwAA6Jb4AwAAoJ/Eg0Pyg9C2FuZHK+sVAAAAANOheA/onVYudEvMDbQyHhsbGzNpBwAA+kr8AQAA0E/iwSH5QWhbC/OjlfUKAAAAgOlRvAf0SisXultIzF2+fFniYcd9992X9fX1mbQFAAB9ZOMTAABAP4kHh1rID7YwHtCqFuZHK+sVAAAAANN1/bw7ADArrVzobiExlyRra2vZ2trac66PiYdx4wEAAEyHjU8AAAD9JB4caiE/2MJ4bG9vd94GHEcL86OV9QoAAACA6VO8B/RCKxe6W0jMXaVwT+EeAAB0zcYnAACAfhIPDm1sbGR9ff2a830r3Lty5UrOnTvXeTswqVbmRwvrFQAAAADdULwHC6CUcmeSO/d5qPurxEuglQvdLRXujepj4kHhHgAAdMvGJwAAgH4SD+6lcG84Hpubm523BZNoaX60sF4BAAAA0A3Fe7AYbk3yrHl3YhG1cqFb4d5A6+MBAABMh41PAAAA/SQePFxfC/dGxwPmreX50cp6BQAAAMB0XDfvDgBH8mCSV+3z59Vz7FPztre3m7jQ3ULh3gMPPLDv+T4mHsaNx+rq6kzaBwCAZWfjEwAAQD+JBw+ncA/a0PL8aGW9AgAAAGB6FO/BAqi1Xqy1Pnv0T5K75t23lp07d27uF7pbKNy7dOlS7r777mvOnzlzpneJh4PG4+zZszPpAwAALLPLly/b+LRjY2NjJu0AAAC0QCHM4RTuQRtanh+trFcAAAAATJfiPWBpbW5u7jluqVBs1om5hx9++JrHzp8/36vEQwvjAQAAy25tbc3Gpwzij/X19Zm0BQAAMG9u5DL0spe9bN/zCvcGVlZWOm8bDtLy/FC4BwAAALC8FO8BvdDHQrFxiYerTp061XkfWkk8tDAeAADQB1tbW3uO+7jxaVz8AQAAsKzcyGXgvvvuy7333nvN+dXV1bnnB1sZjwsXLnTePozT+vxQuAcAAACwvK6fdwcAutbKRs2WCvdmoZXEQwvjAQAAfdTHjU8K9wAAgD5yI5eD48GzZ8/OpA+LUJh0yy23dN4H2M8izA+FewAAAADLS/EesNRaScwp3Bvo43gAAEAf9XHjk8I9AABYbKWUO5Pcuc9D3Qc2S0Q8OB+LUpj00EMPdd4PGLUo8wMAAACA5aV4D1haKysrTSTmWijce8YznpH7779/Jn1oJfHQwngAAEAf9XHjUwsbNQEAgBO7Ncmz5t2JRSYenA+FSTCe+QEAAABAC66bdwcAunLhwoW5J+ZaKNy7/fbbc/fdd8+kD60kHloYDwAA6KMzZ870buPTuPhjdXV1Ju0DAABT82CSV+3z59Vz7NPC6GMhjMK9gVbGA0aZHwAAAAC0QvEesLROnz49k3ZaKBQ7LPFw6tSpzvvQSuKhhfEAAIC+On/+fK82Ph0Uf5w9e3YmfQAAAKaj1nqx1vrs0T9J7pp331rnRi5Dd901u4+LwiQYz/wAAAAAoCWK9wBOoIVCMYmHoRbGAwAA+syNQ8QfAABA/7iRy8ALXvCC3HHHHTPpg/wgjGd+AAAAANAaxXsAx9TCRk2Jh6EWxgMAAOiW+AMAAKA9buQiP3iVwiTmzfwAAAAAoEWK9wCOQWJuoJXEQwvjAQAAdEv8AQAA0E/iwSH5QRjP/AAAAACgVYr3ACYkMTfQSuKhhfEAAAC6Jf4AAADoJ/HgkPwgjGd+AAAAANAyxXsAE5CYG2gl8dDCeAAAAN0SfwAAAPSTeHBIfhDGMz8AAAAAaJ3iPYAjkpgbaCXx0MJ4AAAA3RJ/AAAA9JN4cEh+EMa7fPmy+bFjY2NjJu0AAAAAMLnr590BgEUgMTfQSuKhhfEAAAC6Jf4AAADoJ/HgkPwgHGxtbS1bW1t7zvVxftx3331ZX1+fSVsAAAAATM4v7wEcQmJuoKXEw7zHAwAA6Jb4AwAAoJ/Eg0Pyg3A4hXvj1ysAAAAA2qF4D+AAEnMDrScebJwFAIDlIf4AAADoJ/HgkPwgTK6P80PhHgAAAMBiULwHMIbE3EDriQcbZwEAYHmIPwAAAPpJPDgkPwiT6+P8ULgHAAAAsDgU7wHsQ2JuoPXEg42zAACwPMQfAAAA/SQeHJIfhMn1cX4o3AMAAABYLIr3AEZIzA20nniwcRYAAJaH+AMAAKCfxIND8oMwuTNnzvRufoxbr1ZXV2fSPgAAAACTU7wHsIvE3EDriQcbZwEAYHmIPwAAAPpJPDgkPwjHc/78+V7Nj4PWq7Nnz86kDwAAAABMTvEewA6JuYFFSDzYOAsAAMtB/AEAANBP4sEh+UE4vlOnTnXeRivzo4X1CgAAAIDjUbwHkDYudEvMDbUwHgAAQLfEHwAAAP0kHhySH4S2tTI/WlivAAAAADg+xXtA77VwoVtibqiF8QAAALol/gAAAOgn8eCQ/CC0rZX50cJ6BQAAAMDJKN4Deq2FC90Sc0MtjAcAANAt8QcAAEA/iQeH5Aehba3MjxbWKwAAAABOTvEe0FstXOiWmBtqYTwAAIBuiT8AAAD6STw4JD8IbWtlfrSwXgEAAAAwHYr3gF5q4UK3xNxQC+Nx+fLlmbQDAAB9Jf4AAADoJ/HgkPwgtK2V+dHCegUAAADA9CjeA3qnhQvdLSTmtre3JR52XLp0KWtrazNpCwAA+sjGJwAAgH4SDw61kB9sZTygRa3MjxbWKwAAAACm6/p5dwBgllq40N1CYi5Jzp07l83NzT3n+ph4uDoeW1tbM2kPAAD6xsYnAACAfhIPDrWQH2xlPKBFrcyPFtYrAAAAAKbPL+8BvdHChe4WEnNXKdwbPx4AAMB02PgEAADQT+LBocuXL889P9jKeGxsbMykHZhEK/OjhfUKAAAAgG745T2gF1q40N1S4d6oPiYeFO4BAEC3bHwCAADoJ/HgXmtra9na2tpzro+Fe/fdd1/W19dn0hYcVUvzo4X1CgAAAIBu+OU9YOm1cKFb4d5Qy+MBAABMh41PAAAA/SQevJbCvfHjAfPU+vxw/QoAAABgeSjeA5ZaCxe6Wyjc297e3vd8HxMP48bjzJkzM2kfAACWnY1PAAAA/SQePJzCPWhD6/OjhfUKAAAAgOlRvAcsrY2Njblf6G6hcO/KlSu55557rjm/srLSu8TDQeNx/vz5mfQBAACW2fb2to1POy5fvjyTdgAAAFqgEOZwCvegDa3PjxbWKwAAAACmS/EesLTW19evOddKodisE3P333//NY9duHChV4mHw8bj1KlTM+kHAAAss3Pnztn4lEH8sba2NpO2AAAA5s2NXIYeeOCBfc8r3IM2tD4/FO4BAAAALCfFe0BvtFQoNs/E3FWnT5/uvA9JG4mHFsYDAAD6YHNzc89xHzc+XY0/tra2ZtIeAADAvLmRy8ClS5dy9913X3P+zJkzc88PtjIeq6urM2kf9tP6/FC4BwAAALC8FO8BvdC3QrHDCvdmpYXEQwvjAQAAfdTHjU/j4g8AAIBl5kYuw3jw4Ycfvuax8+fPK9zLYDzOnj07kz7AqEWYHwr3AAAAAJaX4j1g6bWwUVPh3lDfxgMAAPqojxufFO4BAACIB/dz6tSpzvugMAnGMz8AAAAAmDfFe8BSayEx10Lh3k033dR527u1kHhoYTwAAKCP+rjxSeEeAACAeHBeFCbBeOYHAAAAAC1QvAcsrdXV1bkn5loo3Lv55ptzzz33dN7+VS0kHloYDwAA6KOVlZXebXwaF3+cOXNmJu0DAAC0oI+FMAr3hloYDxhlfgAAAADQCsV7wNI6e/bsTNppoVDssMTDU57ylM77kLSReGhhPAAAoK8uXLjQq41PB8Uf58+fn0kfAAAA5s2NXIae8YxnzKT9RGESHMT8AAAAAKAlivcATqCFQjGJh6EWxgMAAPrs9OnTM2lnEeKPU6dOzaQfAAAA8+ZGLgO333577r777pn0QX4QxjM/AAAAAGiN4j2AY2qhUEziYaiF8QAAALon/gAAAGiLG7nM9kYu8oMwnvkBAAAAQIsU7wEcQwsbNSUehloYDwAAoHviDwAAgH4SDw7ID8J45gcAAAAArVK8BzAhibmhFhIPLYwHAADQPfEHAABAP4kHB+QHYTzzAwAAAICWKd4DmIDE3FALiYcWxgMAAOie+AMAAKCfxIMD8oMwnvkBAAAAQOsU7wEckcTcUAuJhxbGAwAA6J74AwAAoJ/EgwPygzDe9va2+bHj8uXLM2kHAAAAgMldP+8OACwCibmhFhIPLYwHAADQPfEHAABAP4kHB+QH4WDnzp3L5ubmnnN9nB+XLl3K2traTNoCAAAAYHJ+eQ/gEBJzQ60kHuY9HgAAQPfEHwAAAP0kHhyQH4TDKdwbrldbW1szaQ8AAACAySneAziAxNxQS4kHG2cBAGC5iT8AAAD6STw4ID8Ik+vj/Bi3XgEAAADQFsV7AGNIzA21nHiwcRYAAJaL+AMAAKCfxIMD8oMwuT7OD4V7AAAAAItD8R7APiTmhlpOPNg4CwAAy0X8AQAA0E/iwQH5QZhcH+eHwj0AAACAxXL9vDsAHK6UcmeSO/d5yI7BDkjMDbWceLBxFgAAlov4AwAAoJ/EgwPygzC5lZWV3s2PcevVmTNnsrm5OZM+AAAAADAZxXuwGG5N8qx5d6IPJOaGWk482DgLAADLRfwBAADQT+LBAflBOJ4LFy70an4ctF695CUvyXOe85yZ9AMAAACAySjeg8XwYJJX7XP+xiS3zbYry0tibqj1xIONswAAsDzEHwAAAP0kHhyQH4TjO3369EzaaWF+HLZePfLIIzPpBwAAAACTU7wHC6DWejHJxdHzpZSnJ7l/1v1ZRhJzQ4uQeLBxFgAAloP4AwAAoJ/EgwPyg9C+FubHUdYrxXsAAAAA7VK8B/SexNzQoiQeAACAxSf+AAAAWlJKuTPJnfs8JDCYMvHggPwgtK+F+dHCegUAAADAySjeA3qthQvdEnNDLYwHAADQPfEHAADQoFuTPGvenVh24sEB+UFoXwvzo4X1CgAAAICTU7wH9FYLF7ol5oZaGA8AAKB74g8AAKBRDyZ51T7nb0xy22y7spzEgwPyg9C+FuZHC+sVAAAAANOheA/opRYudEvMDbUwHtvb2523AQAAfSf+AAAAWlVrvZjk4uj5UsrTk9w/6/4sG/HggPwgtK+F+dHCegUAAADA9Fw37w4AzFoLF7ol5oZaGY9z58513g4AAPSZ+AMAAKCfxIMD8oPQvhbmRwvrFQAAAADT5Zf3gF5p4UJ3K4m5jY2NrK+vX3O+b4mHq+OxubnZeVsAANBXNj4BAAD0k3hwoJX8YAvjAa1qYX60sF4BAAAAMH1+eQ/ojRYudLeSmEuicC/jxwMAAJgeG58AAAD6STw4sL293UR+sIXxuHz58kzagUm1MD9aWK8AAAAA6IZf3gN6oYUL3S0V7u2nb4kHhXsAANA9G58AAAD6STw4dO7cuWxubu4518fCvUuXLmVtbW0mbcEkWpkfLaxXAAAAAHTDL+8BS6+FC90K94ZaHg8AAGB6bHwCAADoJ/HgXgr3huOxtbU1k/bgqFqaHy2sVwAAAAB0Q/EesNRauNCtcG+o5fFYWVnpvG0AAOgLG58AAAD6STx4sD4X7o2OB8xby/OjhfUKAAAAgOlRvAcsrcuXL8/9QncrhXsve9nL9j3ft8TDQeNx4cKFztsHAIA+sPFpYHt7u/M2AAAAWiIePJjCPWhHy/OjhfUKAAAAgOm6ft4dAOjK2tpatra29pxrpVBs1om5e++995rzq6urvUo8HDYet9xyS+d9AACAZbexsZH19fVrzvdt49OVK1dy7ty5ztsBAABohUKYgXE3clG4B+1oeX4o3AMAAABYTn55D1haCvfGJx6S5OzZszPpQwuJh1bGAwAAlp3CvWH8sbm52XlbAAAALdjY2FAIk0E8eM8991xzfmVlpYn8YAvjcebMmZm0D+O0PD8U7gEAAAAsL8V7QC/0sVDsoMK9WWkh8dDKeAAAQB/1bePTuPgDAABgmbmRyzAevP/++6957MKFC3PPD7YyHufPn59JH2A/rc8PhXsAAAAAy+v6eXcAoGstbNRUuDfUx/EAAIA+6tvGJ4V7AAAAA+LBvU6fPt15H5LFKEx65JFHZtIPGLUI80PhHgAAAMDy8st7wFJrITGncG+oj+MBAAB91LeNTwr3AAAABsSD86EwCcYzPwAAAACYN8V7wNI6c+bM3BNzrRTu3XXXXTNpP2kj8dDKeAAAQB/1bePTuPhjZWWl87YBAABaIh6cD4VJMJ75AQAAAEALFO8BS+v8+fO9KhQ7KPFwxx13zKQPLSQeWhkPAADoo9XV1V5tfDoo/rhw4ULn7QMAALSib4Uw4+LBm266qfO2d1OYBOOZHwAAAAC0QvEesLROnTrVeRutFIpJPAy0Mh4AANBXZ8+enUk7ixB/nD59uvM+AAAAtMCNXAZuvvnm3HPPPZ23f5X8IIxnfgAAAADQkuvn3QGARdVKoZjEw0Ar4wEAAHRrUeKPhx56qPN+AAAAtMCNXIbx4A033NB5HxL5QTiI+QEAAABAa/zyHsAxtFIoJvEw0Mp4AAAA3RJ/AAAA9JN4cEh+EMYzPwAAAABokeI9gAlJzA21kHhoZTwAAIBuiT8AAAD6STw4JD8I45kfAAAAALRK8R7ABCTmhlpIPLQyHgAAQLfEHwAAAP0kHhySH4TxzA8AAAAAWqZ4D+CIJOaGWkg8tDIeAABAt8QfAAAA/SQeHJIfhPHMj4Ht7e3O2wAAAADgeK6fdwcAFoHE3FALiYdWxgMAAOiW+AMAAKCfxIND8oMw3sbGRtbX168537f5ceXKlZw7d67zdgAAAAA4Hr+8B3AIibmhVhIPLYwHAADQLfEHAABAP4kHh+QH4WAK94br1ebmZudtAQAAAHA8ivcADiAxN9RS4mHe4wEAAHRL/AEAANBP4sEh+UGYXN/mx7j1CgAAAIC2KN4DGENibqjlxIONswAAsFzEHwAAAP0kHhySH4TJ9W1+KNwDAAAAWByK9wD2ITE31HLiwcZZAABYLuIPAACAfhIPDskPwuT6Nj8U7gEAAAAsFsV7ACMk5oZaTjzYOAsAAMtF/AEAANBP4sEh+UGYXN/mx7j1amVlpfO2AQAAADgexXsAu0jMDbWceLBxFgAAlov4AwAAoJ/Eg0PygzC51dXVXs2Pg9arCxcudN4+AAAAAMdz/bw7ANAKibmh1hMPNs4CAMDyEH8AAAD0k3hwSH4Qjufs2bMzaaeF+XHYenXLLbd03gcAAAAAjscv7wFEYm63RUg82DgLAADLQfwBAADQT+LBIflBaFsL86OV9QoAAACA41G8B/ReKxe6JeYGWhkPAACgW+IPAACAfhIPDskPQttamB+trFcAAAAAHJ/iPaDXWrnQLTE30Mp4AAAA3RJ/AAAA9JN4cEh+ENrWwvxoZb0CAAAA4GQU7wG91cqFbom5gVbGAwAA6Jb4AwAAoJ/Eg0Pyg9C2FuZHK+sVAAAAACeneA/opVYudEvMDbQyHgAAQLfEHwAAAP0kHhySH4S2tTA/WlmvAAAAAJgOxXtA77RyoVtibqCV8djY2JhJOwAA0FfiDwAAgH4SDw7JD0LbWpgfraxXAAAAAEyP4j2gV1q50N1CYu7y5csSDzvuu+++rK+vz6QtAADoIxufAAAA+kk8ONRCfrCF8YBWtTA/WlmvAAAAAJiu6+fdAYBZaeVCdwuJuSRZW1vL1tbWnnN9TDyMGw8AAGA6bHwCAADoJ/HgUAv5wRbGY3t7u/M24DhamB+trFcAAAAATJ/iPaAXWrnQ3UJi7iqFewr3AACgazY+AQAA9JN4cGhjYyPr6+vXnO9b4d6VK1dy7ty5ztuBSbUyP1pYrwAAAADoxnXz7gBA11q50N1S4d6oPiYeFO4BAEC3bHwCAADoJ/HgXgr3huOxubnZeVswiZbmRwvrFQAAAADdULwHLLVWLnQr3BtofTwAAIDpsPEJAACgn8SDh+tr4d7oeMC8tTw/WlmvAAAAAJgOxXvA0tre3m7iQncLhXsPPPDAvuf7mHgYNx6rq6szaR8AAJadjU8AAAD9JB48nMI9aEPL86OV9QoAAACA6VG8Byytc+fOzf1CdwuFe5cuXcrdd999zfkzZ870LvFw0HicPXt2Jn0AAIBldvnyZRufdmxsbMykHQAAgBYohDmcwj1oQ8vzo5X1CgAAAIDpUrwHLK3Nzc09xy0Vis06Mffwww9f89j58+d7lXhoYTwAAGDZra2t2fiUQfyxvr4+k7YAAADmzY1chl72spfte17h3sDKykrnbcNBWp4fCvcAAAAAlpfiPaAX+lgoNi7xcNWpU6c670MriYcWxgMAAPpga2trz3EfNz6Niz8AAACWlRu5DNx333259957rzm/uro69/xgK+Nx4cKFztuHcVqfHwr3AAAAAJbX9fPuAEDXWtmo2VLh3iy0knhoYTwAAKCP+rjxSeEeAADQR27kcnA8ePbs2Zn0YREKk2655ZbO+wD7WYT5oXAPAAAAYHn55T1gqbWSmFO4N9DH8QAAgD7q48YnhXsAAADiwXlRmATjmR8AAAAAzJviPWBpraysNJGYa6Fw7xnPeMZM2k/aSTy0MB4AANBHfdz41MJGTQAAgHkTD86HwiQYz/wAAAAAoAWK94CldeHChbkn5loo3Lv99ttz9913z6QPrSQeWhgPAADoozNnzvRu49O4+GN1dXUm7QMAALSgj4UwCvcGWhkPGGV+AAAAANAKxXvA0jp9+vRM2mmhUOywxMOpU6c670MriYcWxgMAAPrq/Pnzvdr4dFD8cfbs2Zn0AQAAYN7cyGXorrvumkn7icIkOIj5AQAAAEBLFO8BnEALhWISD0MtjAcAAPSZG4eIPwAAgP5xI5eBF7zgBbnjjjtm0gf5QRjP/AAAAACgNYr3AI6phY2aEg9DLYwHAADQLfEHAABAe9zIRX7wKoVJzJv5AQAAAECLFO8BHIPE3EAriYcWxgMAAOiW+AMAAKCfxIND8oMwnvkBAAAAQKsU7wFMSGJuoJXEQwvjAQAAdEv8AQAA0E/iwSH5QRjP/AAAAACgZYr3ACYgMTfQSuKhhfEAAAC6Jf4AAADoJ/HgkPwgjGd+AAAAANA6xXsARyQxN9BK4qGF8QAAALol/gAAAOgn8eCQ/CCMd/nyZfNjx8bGxkzaAQAAAGBy18+7AwCLQGJuoJXEQwvjAQAAdEv8AQAA0E/iwSH5QTjY2tpatra29pzr4/y47777sr6+PpO2AAAAAJicX94DOITE3EBLiYd5jwcAANAt8QcAAEA/iQeH5AfhcAr3xq9XAAAAALRD8R7AASTmBlpPPNg4CwAAy0P8AQAA0E/iwSH5QZhcH+eHwj0AAACAxaB4D2AMibmB1hMPNs4CAMDyEH8AAAD0k3hwSH4QJtfH+aFwDwAAAGBxKN4D2IfE3EDriQcbZwEAYHmIPwAAAPpJPDgkPwiT6+P8ULgHAAAAsFgU7wGMkJgbaD3xYOMsAAAsD/EHAABAP4kHh+QHYXJnzpzp3fwYt16trq7OpH0AAAAAJqd4D2AXibmB1hMPNs4CAMDyEH8AAAD0k3hwSH4Qjuf8+fO9mh8HrVdnz56dSR8AAAAAmJziPYAdEnMDi5B4sHEWAACWg/gDAACgn8SDQ/KDcHynTp3qvI1W5kcL6xUAAAAAx6N4DyBtXOiWmBtqYTwAAIBuiT8AAAD6STw4JD8IbWtlfrSwXgEAAABwfIr3gN5r4UK3xNxQC+MBAAB0S/wBAADQT+LBIflBaFsr86OF9QoAAACAk1G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\n",
      "text/plain": [
       "<Figure size 3600x4500 with 5 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_line_overview(observations, line_freq=400.0, z=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 3.3 Plot observed frequencies in each band <a name=\"plot_bands\"></a>\n",
    "\n",
    "The `alminer.plot_bands` function creates detailed plots of observed frequencies in each band.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_bands</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview and detailed plots of observed frequencies in each band. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_bands**(_observations, mark_freq='', z=0., mark_CO=False, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.3.1: plot observed frequencies in each band and mark redshifted CO lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3600x5400 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_bands(observations, mark_CO=True, z=0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.3.2: plot observed frequencies in each band and mark frequencies of choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3600x5400 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_bands(observations, mark_freq=[106.5, 245.0, 366.3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 3.4 Plot observed frequencies in each band <a name=\"plot_observations\"></a>\n",
    "\n",
    "The `alminer.plot_observations` function creates a detailed plot of observations in each band showing the exact observed frequency ranges. Observation numbers are the input DataFrame's index values. \n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_observations</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create detailed plots of observations in each band. The x-axis displays the observation number 'Obs' column in the input DataFrame. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_observations**(_observations, mark_freq='', z=0., mark_CO=False, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.4.1: plot observed frequencies in each band and mark CO lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
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+aEmwHsD4mlHaZ+2gjbMb6Z1EfgMwRaWURyf58Ub2U2qtLxyzibbzQ3NuGNXmNPoZ1Zd5CNh3Sik3Tf9ki1N+d7MAjBZm9ZltbgCYns0+/3631np8q4qDk5J+JKdvbFyc5J5j9GOOAFgQpZRuKeVPkjwryU0H2R9N8qQkd09yg/Q/b2+W5H5J/l/6DwdJkhsmubyU8tQtupjXHLGTvswRAJNbxrWAdQfADJVSbpTkL5PcaCj7A0keVGsdFdzWtEhzxLh76ADL7hfSD6RI+icGPWqLsju1SPPDJH0BLKtRn3trSX6s1lpHvPYFtdbXJmkGfT9yzH7MDxMSrAcwvk810qOePrudZpR2s00AZqiU8pAkT2tkPzfJ4ydopu38MOoJHqPmB/MQwHT8nyTnD35/f5L/vgt9zOoz29wAMD2bff79zjiVa61XJ3lVI3tUsJ45AmBxPSvJdwylr0hyx1rrE2utr6+1frzW2qu1vq/W+rJa64OSPCCnbwj/ZCnloZu0P685Yid9mSMAJreMawHrDoAZKaVcL/1AvdsPZX8iyTfXWk+O2cwizRHj7qEDLK1Sylcn+YmhrCfVWk/sQleLND9M0hfAshr1ufeKWus1Y9b/7Ub6UCllVHCc+aElwXoA42t+aF+nlFJGltzcedu0CcCMlFLum+R5SYY/y/80ySO2e8JIQ/OzvPlZv51m+bVa66inerTtZ1Qd8xCwr5RSvivJA4eyHlNr/fgudNXqM3uwztjJzVfWKAA7VGv9bJL1RvZ/JPnHCZp5TSP9NSPKmCMAFlAp5bIkDx/K+mCS+9Za379VvVrrS5P8WCP7qaWUcW483ZVrP5vMeW2vZ5kjALa3jGuBWb0ngH2tlHJOkpfm9GtNn0lyn1rrmydoapb7zbPaQwdYSqWU1SS/l2RlkPVPSX5tl7qzhgBYLKM+95r71Ft5ffqntZ5yTpI7j9GP+WFCgvUAxvfhJMPBG90kN56wjZs30h9sNSIAdqSU8g1JXpRkdSj7lUm+t9bavFlpO83P8ltMWL85N3xozH6a9XbSl3kI2G+eOvT7y2utf7xL/bSdG740p89RG+mvR5qsUQCmq/kZeFWtdWOC+m9rpEd9JpsjABbToxvpp9VaN7uG0/TcJG8fSl+Q5EEjyrWdI5LkZtu0eUpz7G2vZ5kjALa3jGuBWb0ngH2rlNJN8sdJLhvKvjbJg2qtRydsbpb7zbPaQwdYVt+f5CsHv28keWStdW2X+rKGAFgsHxiR9/YReSMN5pPmSa2jPvfNDy0J1gMY0+Bps+9uZN9qwmaa5d+68xEBsBOllEPpP3lw+Kjs1yV5YK312h002bwhd7fmhquTDF94O7eUcuEu9QWwrM4f+v0+pZS63U+SVzfauPWIcndplJn23PCuUU+MtUYBmLp/a6Q/OWH9ZvkbjChjjgBYMIMnst6rkf2ycesPAr9f3sj++hFFW80RpZQb5/TrXdemfz1plFldzwLgi5ZxLTCT9wSwX5VSOkmen+Tbh7LXkzyk1vpXO2hylvvN1hwA7Zw/9HsnybEx97bv2WjnOY0yf9bsyBoCYOE097STXdjXNj+0J1gPYDLNSeLLJ6x/h23aA2AXlVK+IslfJrnuUPY/Jvm2Wuund9jsTOaGWmsvZz7RZOy+SilnJ7lonL4AaG2W6wZrFIDpeUsjffaE9c9ppD8zoow5AmDx3CDJ9Rt5Jydso1l+1AkWzc/Zg6WUsyboo/m5fWKLJ66bIwBmbxnXAuYTgF0yeGjIbyf5nqHsmuQRtdYX76TNGe83myMAFos1BMDiaO5pJ7uzr52YH1oRrAcwmSsb6XuMW7GUctMktxnK6mX0hAnALiilXJzklTn9KSD/luSba62faNH0lY303Uopq6MKbuKSbdrb6rWx56Ekd83pi7L31Vo3O1YcgHb+Nf3v+6fcZrAeGNdM5gZrFIAzvKmR/tIJ69+4kf7IiDLmCIDFM2qTe7MguM30GumVZoFa6/uTvL/R710n6GNWc8RqkrtP0BcAfcu4FpjlewLYb34zycMbeY+utT63ZbtXNtK7td/c7Gc399ABaO/KRtoaAmCPqrV+JGeeeLcb+9qJ+aEVwXoAk/nzRvreg6dZjeM/NdKvrrV+agpjAmAbpZRbJ3lVTl9knEzyTbXWD7Vpu9b61pz+BMLzMuaipJRyXpKvHW4uZ841w5qvfdM4/WxS9mUT1AVYFvdP//Nwkp+fbLTxgRFlrhouUGv9jySvbdQb6zN7sL64dyN7q89saxSA6Xl5ko2h9IFSyg0nqN8MqHhbs4A5AmAhjdqkvtmEbTRP0tvsetTLG+nduvbT7Oceg+tU47gkyXWG0m+vtb59zLoA+9YyrgVm/J4A9o1Syi8meUwj+wm11v89heZnst884z10gGX04ky+r/1NSf6p0c5TG6//3Cb9WUMALJaXNtJjP/ivlPKlSW7RyN7sGr/5oQXBegCTeV2SDw+lL0py2Zh1m0+8esk0BgTA1gZP2Pj/2bvvOOnOsn78nysJKQSSEKSEGkJAWgIKAtISukoRkCpIswBf5SeIgKBCkG5DEQEFJRQBBZUASlMgCChKCb2TYAihJiGQQtr1++NMZLOZmd3ZM7v7PE/e79drXq/sfZ9z3dezOzMnszOfvf89F32BcVKSO3b3SUtaZvWLn9XP+bM8IMllVnz94e7++pzj/zUX/cvtR1bVIWstMnlB8vBVw65DwCVOdx/b3f+2yC3JR1aVOXvKcdN+mbTRa8Ptk1xrxdffTPKhOcd7jQKwJJO/BP6BVcP3Wc+5k78Mfu9Vw++dcbhrBMBOpLvPSXLyquE7LFjmjqu+/vLUoy5+jXjEet74rqprJzlixdC5GX6PNFV3n5jkYyuGLpPk/mutM+EaAbBxu+Jrga36NwFcIlTVE5P83qrh53b3c5e0xFa+37xV76ED7HK6+8RF39eevLd96qpSn1l1zOow34W8hgDYufzzqq/vVVXrzYbdd9XXn+3ub8441vVhBGE9gAV09wVJjl41/PS13iyvqjsmue2Koe8n+YfldgfAapNdMN6V5Norhr+dYUe945e41N9m+It+F3pgVV1/jd72TvI7q4b/Zt453X1KkjetLJPkqHX098hcdEvxr2bYaRCAzfP6JGes+Pp2VTX3A72T1xVPXzX8isnrkKm8RgFYur9a9fUTq2qvdZz3q0muvOLr05O8Y8axrhEAO59/X/X14yZB7TVV1RG56K4Q0+pd6B1Jvrbi64OTPGIdyxyV4fdEF/rH7v7eGues/j3U70x+XzXT5PddD1gxNO1aA8Bsu+JrgS35NwFcElTVo5L84arhF3X3U5e1xha/37wl76EDMJ7XEAA7nWOTfH7F19dI8rC1TqqqSyd5wqrhmc/brg/jCOsBLO75SVbunHFEkifPOriqrprk5auG/7y7vzPteACWo6oum+TtSW64Yvi0JHfp7s8uc63u/lQu+mJizySvrKr9ZvRWSf4syXVWDH8lwxsWa3l6hg9CXeiXqupBsw6uqhsk+eNVw8+c/FV4ADbJZHemF60afnlVXWXOaU9JcrsVX38vyR+tYzmvUQCW53VJPrni6+sm+at5f4mwqm6Ri3+Q6sWzQhKuEQA7pdes+vpGSV681l+qrapDk7x21fAXk/zntOO7+4dJnr1q+I8nv9+ZtcYvJnnIiqHzc/E3p6d5WZL/XfH1dZO8YNab7JPfc70qw++9LvTa7v7MOtYCILvma4Et/jcB7LIm/1//4lXDr0jy/23CclvyfvMWv4cOwHheQwDsJLr7/Fx8R+4XVNVPzjqnqnbP8IcwVu5Cd0aSv1hjOdeHDaruXvsoAC6iqp6S5Dmrhl+S5Fnd/fXJMbsluWeSP8+QWL/Q15PcsLtP24JWAS6xquo9ufiW20/LjA9DreEj3X3qGusdmuTjSS69YvjjSR7X3e9dcdx1kzw3yX1Wlbh/d79hPc1U1V8l+bUVQxdk+CDXCy7ss6ouleTBSf40yeVWHPuJJDft7vPWsxbAJV1VHZnkPSuGvtrdB6/z3AOTfDoX3WnpqxneXH9LT34pU1VXy/BLtEetKvGk7l7XL5G8RgFYnslf+ntXLrpD0b8l+Z3u/siK4/ZP8stJnpHkMiuO/UKSm3X39+es4RoBsJOpqncnuf2q4fdn2IXi2JW/a6mqyyd5eJLfT7L/qnPu191vnLPOpZJ8LBf9A1SnJHl8hnDceZPjDpyMPTUX/QOtL+7uX1/nv+lBuXiY8I1JntrdX1xx3B2SvCDJ4SuO+0GSw7v7+PWsBbAzqKpbJ9lnytSNc9GQwjdz0aD0Sl+fF2TeFV8LbOW/CWC7bOY1oqrulORtSVbu3v25JI/L8Mc4FnHqyt9fzbJV7zdv5XvoANthK15DLNjPezOEKC70iO4+eoHzvYYAWIKtuj5Med4/PcNnZF/R3aevOO5mGUJsR64q8aju/ut5a0zOd33YAGE9gA2YXFCOSXL3VVPnZ7gofC9D8vyAVfNnJblzd39gs3sEuKSrqmX+j+7tV75ZMGfNB2b4gNPqv0D+7Qx/qfyKSa42Zf4vunvdfxVxsh35sUlutmrqnCTHJ/lhkkNy0Q8MJ8l3kty6u7+w3rUALunGhPUm598uyTuS7L1q6rQMz9kHZPgl1e6r5o9Jcu9e5y9uvEYBWK6qenKS502Z+kaSryXZN8m1c9HdhZLkuxleP3xy9YlT1nCNANiJVNWVk3wwF/2rsxf6QYbn7rOSXD7D72Wm7VD3J9392+tY6/oZgoAHTlnnyxne5L9Wkkutmv/vJEd291lrrbFirRcnecyq4U5yYobfaV0zyY+tmr8gyQPmhQ4BdkZVdUKG570xXtndD19jnV3utcBW/ZsAtstmXiOq6qisb3fs9Ti2u49c66CtfL95q95DB9gOW/UaYr2WENbzGgJgCbbwd0wHJflALv6+xTkZ3ks4I8P/a185F/ey7v61KePT1nF92IDd1j4EgNW6+4Ik90vy+lVTu2f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WzDVhvHUDYDG78dxhJY8JgLkdm3OfJ3SS180Yv8pr3c5TAFaoqn4myX3WND24u09fQlznHQDsOIr1ADbvYklqzf0zk3x9zhhfGrt/iYUyAmBlRm8g3WKs+bh1Dht/nf/inNOOrxsXnzjqvPOMH7eZuaxRAJP9dpIbj/7/jCS/2t29hLiLrhlfS3LWmvv7JLnohHHOawBWZ/wbwc9J8rac90tAJjk4ycOS/EdVXWjGOOsHwC7S3e9I8psZPsyaDB9YPa6q3l1Vf1xVd62qn6qq+1bVP2T4NvI7rgnxxiT3njHFoutGknx5nZh7jL+Ptej7YtYNgMXsxnOHVT0mADZo9IWHTxhrfl13f3XGYau81r2q6/cA53ujaxtPX9P0vO5+05LCO+8AYMfZb/0hAExxwbH7p23iQ7nfXycmADtQVR2e5B/Hml/R3e9e59Dx1/nxdWA94+P3r6oDu/uHS55n0jHWKIAxVXWlJI9b0/SE7v74ksIv9Fre3V1VpydZW9Ax6bXceQ3ACow+mDReZPf3SX589P+d5DUZduv+YpJDRn2/mOQya465TYYvCfm5KVNZPwB2me5+WlV9IsO6cc1R8w1y3h1b1/pskr9I8s/dfc6McSt5D2n07eb7LjiXdQNguXbjucOqHhMAG/cHSW605v45SR6xzjGrvNa9quv3ACRPSnL50f9/M8nvLTG28w4Adhw76wFs3vg/kH+wiRjjW3j7RzfADjf6kO3zk1xuTfMpGXZWWs+ia8f4ujEp5jLmmTSXNQrgvP4pQzFFknw8yeOXGHtVr+XWDIDVuHDO/a2uSfITo/9+K8kx3X2n7n56d7+mu1/c3X+c5KpJXjB23N2q6pemzGP9ANiFuvvNGYrz/jLJ2esM/8Jo3AvWKdRLtm/d2Mxc1g2A5dqN5w7OUwB2kKq6eZI/H2v+2+5+/zqH7k1rx0av3wOcr43WhAevafr97v7mEqfYm9aOeeYCYC+mWA9g8w4au3/GJmKMf5PSwZvMBYDVeXKSnx5r+7XuPmkDxy66dkz6Br5Ja4c1CmCLVdWDMuxulAy7If1qd2/m9XaaVb2WWzMAVmPahdazk9yhu98+qbO7v5dhd703jHU9vKrGi/8S6wfArlRVD07ymQy7UozvUDfuCkmemuRzVfXAdcZu17qxmbmsGwDLtRvPHZynAOwQVXVkkpcn2W9N8wlJHr6Bw/emtWOj1+8Bzreq6qAkz8yPvtDwTd393CVPszetHfPMBcBeTLEewOaNfyPGAZuIceA6MQHYQarqt5P83ljzX3T3izcYYtG1Y3zdmBRzGfNMmssaBTBSVZfOsFPFHs+YVmSxgFW9llszAFZj2mvjM7r7f2YdONoV6deTrN0d6apJjtnAPNYPgL1YVe1fVS9L8rQklx41fzvJY5LcMMlFMrwGXybJnZL8W4YvE0mSw5M8s6qePGOK7Vo3NjOXdQNguXbjuYPzFIAdoKouluS1SS62pvlrSe7W3ZOK28btTWvHRq/fA5yfPTrJVUb/f3rOvcPesuxNa8c8cwGwF1OsB7B53xu7P+mbYdcz/o0Y4zEB2CGq6heS/O1Y83FJ/niOMIuuHZO+SWnS2mGNAtha/y/JYaP//2qSh27BHKt6LbdmAKzGtNfGf97Iwd392SRvGmueVKxn/QDYXZ6W5OfW3H93kmt29yO7+3+7++TuPrO7v9Ldr+7uuyW5S879AZ8/qKoHTIm/XevGZuaybgAs1248d3CeArDNqupCGQr1fmxN8ylJbt/dJ24wzN60dmz0+j3A+VJV/USS31/T9Jju/swWTLU3rR3zzAXAXkyxHsDmjf8D+QJVVRNHTnfIOjEB2AGq6o5JnpNk7ev8y5P8cnf35KMmGn+dH18H1jM+/qzunvTtSovOM+kYaxRAkqq6R5K7rmn6ne4+eQumWui1fHRuspkPTDmvAdgC3X16krPHmr+b5P1zhDl+7P71J4yxfgDsElV1bJIHrWn6epI7dvdXZx3X3a9K8htjzU+uqo18iHRL3kOasg4u+r6YdQNgMbvx3GFVjwmACarqoCSvyrnfszotyR26+wNzhFrlte5VXb8HON+pqv2SPCvJvqOmDyb5yy2aznkHADuOYj2AzftmkrUFGvsnucScMS47dv/rC2UEwNJV1S2TvDTJfmua35jk3t09/iGj9Yy/zl9uzuPH141vbHCe8eM2M5c1CmDw5DX//+/d/ZItmmfRNeOSOffadU6Gc5hxzmsAVmf89fHT3X3OHMd/Yuz+pNdr6wfA7vHbY/f/trunvRc07rgkn1xz/6JJ7jZh3KLrRpJcZp2Ye4znvuj7YtYNgMXsxnOHVT0mAMZU1f5JXpLk2DXNZyS5W3e/c85wq7zWvarr9wDnR/dNcp3R/5+T5Fe7+6wtmst5BwA7jmI9gE0afRPsF8aarzBnmPHxH998RgAsW1XdKMO3/x20pvldSe7a3WdsIuT4h2u3at34bJK1b3AdXFUX36K5AM5vDlvz/3eoql7vluQtYzGuOGHcdcfGLHvN+Pykb3N1XgOwUh8bu3/qnMePj7/IhDHWD4BdYPQN27caa371Ro8fFYP/+1jzLSYMXWjdqKpL5Nzvm52R4X2pSVb1vhgAG7Mbzx1W8pgAOLeq2ifJc5P87Jrms5P8Qne/fhMhV3mt23kKwNY5bM3/75Pkvzd4bf2YsTjPHhvzivGJnHcAsBMp1gNYzPg/yK8x5/FXXyceANukqo5O8tokF1zT/P4kP9Pd399k2JWsG919ZpLPbHauqjowyZEbmQuALbPKcw3nNQCr8dGx+wfOefxBY/dPmzDG+gGwO1wkyYXH2k6cM8b4+Em7UYy/9l65qg6YY47x1/LPzPiGdOsGwM6yG88drDUAKzb6opF/SnKvNc2d5Je7+183E3PF17qtHQC7h/MOAHYUxXoAizlh7P5NNnpgVV06yRFrms7MeT+0BcA2qKqrJnljzr1TxceS3L67T1kg9Alj929QVfvNcfxN14k3q2/Da1SS6+XcHxz+Snd/fY7jAVjcRzKcI+xxxOgcYqNWsmY4rwGYy/vG7l9yzuMvMXb/WxPGWD8AdodJBd3TiuCmOXPs/r7jA7r7q0m+Ojbv9eaYY1Xrxn5JbjjHXACsbzeeO6zyMQEw+JskDxpr++3uPm7BuCeM3d+qa93j82zl9XsAttYJY/eddwCwrRTrASzmNWP3bzP61qiNuN3Y/bd09/eWkBMAC6iqKyZ5U879QdgTk9y2u7+xSOzu/njO/S2Ah2SDbw5V1SFJfnJtuJx3HVprvO+2G5lnythXz3EswG535wyvk/Pc/mAsxtcmjPn02gHd/d0kbxs7bkOv5aNzktuMNc96LXdeA7Aa/57knDX3r1RVh89x/HjxxCfGB1g/AHaNSQXZl5kzxvhOetPe1/r3sftb9R7S+Dw3Gb3ftRE3TXKBNfc/2d2f3OCxAEywG88dVvyYAM73quqxSX5nrPnh3f2UJYRfybXuFV+/Bzi/+dfMf139tkk+OBbnyWP9fzZlPucdAOwoivUAFvOuJN9cc//IJMdu8Njxb5Z65TISAmDzRt909J9JLrem+UtJbt3dX1rSNK8auz++Hkzz80kuuOb+e7r7yzPG/0fO/Y3rx1bVketNMnpj6P5jzdYogJHuPr673zTPLcl7x8L8YMK4SW/2b3bNuGWSK625/7Uk/zNjvPMagBUYfYP3O8ea77aRY0ff6H3Xsea3Thlu/QDYy3X3GUm+MtZ8qznD3Hrs/mcmjjrvuvGAjXyQqaqunOSYNU1nZng/aqLuPinJ+9c0XTDJPdebZ8S6AbA1duO5w6oeE8D5WlX9YZI/GWt+Qnc/YUlTrPJa96qu3wOcr3T3SfNeVx9dW//OWKiPjo0ZL+bbw3kHADuKYj2ABXT3OUmOG2t+5HoXsqvq1kluvqbpu0lestzsAJjHaEeLNya58prmb2TYUe/EJU71rAzfqrfHvarq6uvkdlCSPx5rfuasY7r720lesTZMkkdtIL8HJjlizf3PZ9hpEIDVe1GS76+5f4uqmvkB3dG5yCPHmp89OneZyHkNwEr949j9P6yqAzdw3K8kudSa+6cmef2UsdYPgN3hP8fuP2RUvL2uqjom597hYVK8PV6f5Itr7h+R5AEbmOZRGd5v2uNfu/uUdY4Zfz/rj0fve001et/s59c0TVp/ANic3XjusJLHBHB+VlW/luQvxpqf0t0PX9YcK77WvZLr9wBsLecdAOw0ivUAFvekJGt3wTgmyR9NG1xVl03yjLHmv+vub04aD8DWq6oLJXldkmuuaT45ye26+2PLnKu7P5xzv6lzQJLnVNWhU3KrJH+b5Cprmj+b4aLBeh6Z4QNMe/xiVd172uCqukaSvxxrfuzo29wBWLHRDkxPGWt+RlVdZsZhD0tyizX3T0ny5A1M57wGYDVemORDa+7/WJJ/rKqp79VX1Y1y3g9APXVaQYT1A2DXeP7Y/WsleeqsNSNJquqoJC8Ya/5Ukv+aNL67f5jkz8ea/3L0PtG0OX4hyX3XNJ2d837YaJJ/TvKFNfd/LMnfTPvQ1Oj9sudmeP9sjxd090c3MBcA69iN5w4rfkwA5zujc4GnjjU/O8lvb8F0K7nWveLr9wBsLecdAOwY1d3rjwJgpqp6WJLHjzU/LcnjuvvLozH7JLlTkr9LcoU1476c5JrdffIKUgVggqp6S5Jjx5r/LFM+xLSO93b3d9aZ76gkH0hygTXNH0jykO5+65pxP5bkCUnuNhbint390o0kU1X/mORX1zSdk+EDWH+zJ8+q2j/JfZL8dZKLrBn7wSTX6+6zNjIXAJNV1bFJ3rKm6fPdfcQGjz08yUdy7t2UPp/hwvere/TGTlVdLsmfJPm1sRAP7e4NvcnvvAZgNUbf0vrGnHs3ojcl+ePufu+acRdO8qAkj05ywTVjP5nk+t393RlzWD8AdoGqenOSW441vyPDjhLHr33PpqoumuT+Sf40yYXHjrlHd79sxjz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3s/8Ke/OyleaTacYCYI4k6wGs7YLe9qg3ua6l/yaKfp8AbFKttQcneU6v+NQkvzNFN7POJaPeaDRqLjFnASzHXyU5ZvD/5yR5/AaMsahjvLkEYDnGHSv/ZpLGVfXZJG/uFY9K1jOfABwcXpDkp4a235fkhlX15Kr6z6raVVUXV9VXq+q1VXVKkvtk/wd1fqu19vAx/S9rPlnPWOYTgI23Hc8znNMAbDKttaPTJepdd6h4d5J7VNXZE3azleaSSZ8RAGCgtXaLJL85VPS0qvrMBgy1leaTacYCYI4k6wGsrf+H6aVaa21kzfEuvUafAGxCrbWTk7wkyfBx//Qkj6qqGt1qpP5xvz8vrKVf//tVNeotR7OOM6qNOQtgFa21+ye571DRr1XVrg0YaqZj/OAcZj0PPTn/AViAqvpukkt6xd9K8sEpunl7b/tWI+qYTwC2udbaiUkeOVR0bpKTq+qc1dpV1WuS/HKv+NmttUkeEN2Qa1Bj5sdZr6uZTwDmbzueZyzqMwEwgdbakUlek/2vd30nyb2q6kNTdLXI++mLekYAgCSttUOT/F2SQwZFH07ypxs0nHMTANYkWQ9gbeclGU7IOCzJsVP2cdXe9rkzRQTAhmut3TnJq5IcOlT8piQPqqr+Q0Jr6R/3rzZl+/488vUJx+m3W89Y5iyA1T176P9fV1Wv3KBxZp1LrpT957S96c51+pz/ACxP/3j56araO0X7/+ltjzp+m08Atr/H9rafU1XjriX1nZrkk0Pbl09yyoh6s84nSXKVNfrcpx/7rNfVzCcA87cdzzMW9ZkAWENr7bAkr0xy4lDxRUlOqap3T9ndIu+nL+oZAQA6P5vkpoP/35vk0VX1/Q0ay7kJAGuSrAewhsGbW7/QK77GlN30639i/REBsNFaa7dN92a+I4eK35PkvlV10Tq67D80u1HzyGeTDF9oOqq1dsUNGguAzjFD/3+v1lqt9S/JW3t9XHNEvZv16sx7Lvn8qDewOv8BWKqP97b3TNm+X/+yI+qYTwC2scGbsu/SK37tpO0HSeKv6xXfcUTVmeaT1tqx2f+620XprmuNsqjragCs33Y8z1jIZwJgda21lSQvTfJ/hoovSfLgqnrjOrpc5P105zIAi3XM0P+vJPmPCe/d36nXz4t7df6lP5BzEwAmIVkPYDL9P4RvMGX766/RHwCbRGvtJklen+QyQ8UfTHLPqvr2OrtdyDxSVRcn+cx6x2qtHZHkhEnGAmDhFnlO4vwHYDk+1ts+Ysr2R/a2vzOijvkEYHu7bJKdvbKzp+yjX3/UShP9Y/K1W2uHTzFG/xj/mVXedG4+Adj8tuN5hvkHYMkGLyP5/5I8cKi4kjyqqv55PX0u+H66uQRge3NuAsCqJOsBTOas3vbtJm3YWrtykuOHii7OgQ9fAbAJtNaul+RN2X8Fio8nuUdV7Z6h67N627durR06Rfvbr9HfavsmnrOS3DL7PxD81ao6d4r2AGyc/053LrHP8YNzjUktZC5x/gMwk//qbV9pyvbH9ra/MaKO+QRgexuV6D0uCW6ci3vbh/QrVNU5Sc7pjXvLKcZY1HxyaJLbTDEWAOuzHc8zFvmZABjtL5I8slf22Ko6dcZ+z+ptb9T99P44G/mMAACLd1Zv27kJAPuRrAcwmTN623cdvMFpEnfvbb+1qi6YQ0wAzFFr7ZpJ3pz9H3A9O8ndqurrs/RdVZ/I/m/ou3QmvEjTWrt0kh8d7i4HzkvD+vvuNsk4Y+q+doq2AAern0x3/Jzm32/1+vjaiDqfHq5QVd9K8o5eu4mO8YNzl7v2ilc7xjv/AViO1yXZO7R9rdba5aZo30+S+J9+BfMJwLY3KlH7KlP20V9Jb9x1sdf1tjfqGlR/nNsNrpdN4vZJLjW0/cmq+uSEbQGY0HY8z1jwZwKgp7X2h0l+rVf8xKp63hy6X8j99AU/IwBA8s+Z/r793ZJ8uNfPs3v7/2DMeM5NAFiVZD2AybwnyXlD2yckOXHCtv23PL16HgEBMD+DNw6dmeRqQ8VfTnJSVX15TsO8prfdnx/G+ekklxnafn9VfWWV+v+a/d+YfmJr7YS1BhlcoHlYr9icBbCGqnp7Vb15mn9JPtDr5sIR9UZdjF/vXHLnJNca2v5akveuUt/5D8ASDN7C/e5e8SmTtB28lfu+veK3jaluPgHYpqrqoiRf7RXfZcpuTuptf2ZkrQPnk4dP8kBSa+3aSe40VHRxuutZI1XVF5N8cKjoMkkesNY4A+YTgMXZjucZi/pMAAxprf12kt/rFf9xVf3xnIZY5P30RT0jAHDQq6ovTnvffnDv/vxeVx/r1ekn8+3j3ASAVUnWA5hAVe1Ncmqv+Mlr3XhurZ2U5A5DRd9K8sr5RgfALAYrVbwpybWHir+ebkW9s+c41N+le+PdPg9srV1/jdiOTPI7veK/Xa1NVX0zyb8Md5PkKRPE94gkxw9tfz7dSoMAbB7/mOTbQ9t3bK2t+uDt4Jzlyb3iFw/OcUZy/gOwVH/d2/7t1toRE7T7+STHDW3vSfLGMXXNJwDb25m97ccNkrrX1Fq7U/ZfvWFUf/u8McmXhraPT/LwCYZ5SrrrVfv8c1XtXqNN/3rY7wyum401uO7200NFo+YlAOZnO55nLOQzAfADrbVfSPInveLnVdUT5zXGgu+nL+QZAQAWz7kJAGuRrAcwuWclGV7d4k5JnjCucmvtqkle1Ct+blWdN6o+AIvXWjs6yRuS3HCoeFeSu1fVx+c5VlV9NPtfXDk8yUtaazvGxNaSPCfJDw0VfzbdBf21PDndA0j7/Fxr7UHjKrfWbpDkT3vFfzh4GzsAm8RgxaXn9Ypf1Fq7yirNfjfJHYe2dyd59gTDOf8BWI6XJ/nI0PZ1k/x1a23stfzW2m1z4ENMzx+X+GA+Adj2/r63faMkz19tLkmS1tp1kpzWK/5Ukn8fVb+qvpfkj3rFfzq4zjRujAcn+dmhokty4ENDo/xNki8MbV83yV+Me/hpcL3tpemuv+1zWlV9bIKxAFiH7XieseDPBHDQG5wvPL9X/OIkj92A4RZyP33BzwgAsHjOTQAYq1XV2rUASJK01n43yTN6xS9I8vSq+sqgzkqSeyd5bpJrDNX7SpIbVtWuBYQKwARaa29NcmKv+A8y5iGkNXygqs5fY7zrJPlQkksNFX8oyeOq6m1D9a6b5I+TnNLr4gFV9apJgmmt/XWSRw8V7U33ANVf7IuztXZYkp9J8udJLjtU98NJbllV359kLACm01o7Mclbh4o+X1XHT9j2ckn+O/uvnvT5dDerX1uDCz2ttasl+b0kv9Dr4vFVNdFFeOc/AMsxeKvqm7L/qkNvTvI7VfWBoXo7kzwyyVOTXGao7ieT3KqqvrXKGOYTgG2stfaWJHfuFb8r3WoRbx++5tNau3yShyX5/SQ7e23uX1X/tMo4hyX5YPZ/EdY3k/x6uuS47w/qXW5Q9sTs/zLZ51fVL0/4mR6UA5MJ/ynJE6vqU0P17pLkL5LcZKjeBUluUlVnTzIWwHbUWrt9kqNG7Lpp9k8++Fr2T6we9pXVEp+343nGIj8TwGa3kXNJa+2uSV6fZHhV8E8keVy6l3xM4/zha2jjLOp++iKfEQDYChZxbjJlPG9Ll2S3z8Or6tQp2js3AWAkyXoAUxj80fzqJCf3dl2S7g/f3UmuleSY3v7vJrlbVb17o2MEYHKttXn+MXzn4Yvpq4z5wHQPFvXf/P31dG8IPzbJ1Ubs/79VNfFbA1trl0ry9iS36u26KMnZSb6X5ITs/1BvkpyX5PZV9clJxwJgOrMk6w3a3zHJG5Mc2du1K90x/ph0F/kP6e1/dZL71oQXg5z/ACxPa+0JSZ45Ytc5Sb6U5NJJrp39VwxKkm+kOzf5SL/hiDHMJwDbVGvtuCTvSXd87bsg3XH+u0kun+760KgV6v6sqn5rgrGuny4R8HIjxvlMuoevrpXksN7+9yU5saq+u9YYQ2M9P8kv9ooryRfTXVu7ZpIr9PbvTfLTqyUdAhwMWmufS3ecnMVLqupha4yz7c4zFvWZADa7jZxLWmtPyWSrbk/i7VV14lqVFnk/fVHPCABsBYs6N5nUHJL1nJsAMNLK2lUA2Keq9ia5f5J/7O06JN0FmpvnwD+qv5Hknh4sAiBJquof0719r/8g0hWT3DLJ1XPgRfg/TfJrU47znST3SPKW3q7Dk1wv3dvF+zcWPpfkLhL1ADa3qnpHknulW7Fi2DHpzkmulQMvwJ+W7gHViS/AO/8BWJ6qela6t6Fe3Nt1XLoHiK6fAxP1/ifJj06SqDcYw3wCsE1V1TnpHjJ624jdl0ly4yS3SZf43b8OdXGS30ny2xOO9fEkd0n38FF/nJsmuW4OTNR7c5J7TJOoN/Ar6VbNG9bSPYR0yxyYqPedJA+SqAewONvxPGNRnwmAxVrk/fRFPSMAwOI5NwFgHMl6AFOqqgur6kFJ7pfkrFWqfjvJ85PcYJKVlgA4eFTVy5PcKN0Fkf7Dt8Peke4N47+9nosmVfXNJHdL8ugkn16l6jeTPCPJjSd9sBeA5aqqtyS5QZIXpHsAdZwPJvmpqvqZqvreOsZx/gOwJFX1f9M9FPSKrH7ecHa6B3duUlWfmnIM8wnANlVVX0xyUpIHpEva27tGk93p5oMbV9WzpkyY+FC6BMA/TnL+KlU/leTnk9y9qnZN2v/QOHur6jfSJQe+c5WqFyX5hyQ3qqpXTjsOALPZjucZi/pMACzWIu+nL+oZAQAWz7kJAKM0f88DzKa1dp0kt01y1XRvV9qV5ONJ3l1VFy4xNAC2gNbajiQ/luSHkhyd5MIkX0g3j3x5zmPdOMktklw53ZuUvpHko0neW1Wr3RAAYBNrrR2V5HbpVlk6Jt2DqV9Od3xf7ebyesZy/gOwBIPzhtulO2/YmeSCJF9L8l9V9T9zGsN8ArCNtdaOTrc66wnpjvNHJtmT7vrQh5N8bPAm8FnHOSzdMf5GSS6f5JIkX00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fSwMfALaLiOdn5l192roXSZJqlRnGl68Uf4FHAvUSOBH4GcUFPMuWda8B1urpszPFjR1f0jCVe5EkqbWICGDvSvHMIbt7zYIkaaDMPDIiLqF4X/TksvjpzJ+RvNcVwKeAr2bmnD7tvHZBkjSfzLwiIq5j3s/aXg4cPqhvRCwH7F5TNcznZr4n0tAWmeoFSJK0MCu/sP0WsE5P8e0U2ScGqf6hdN+I0987xJhdzFM3l3/kSdKC5wfAx4YI1IPJ2xvqytrud+5BkjR5/pfiolOAi4HDOhx7qvYi3w9J0vSSwNnA+4BdKD6DWwZYClgbeD7FTbSq5/cdge9GRPUCnF7uRZKkJisybyY6gH8r/3sLsENm7pGZX87MEzPze5n5HuCJwLGVfi+OiGoAxVzuRZKkLuwErNtz/ADz70dNvGZBkjSUzPw1RXDeZ4CHBzT/R9nu2AGBeuC1C5KkZj+pHL8nIlYaot97gRVqyifivYrviR7FDNaTJGlifRp4bqXsvzLz6iH6LlU5fmDEuat3XoDi7uFdz1M3V908kqSp9TLgzIg4PSI2HNB2svaG6jzjzOUeJElTICJeS5EFAopAif/MzHH2iyZTtRf5fkiSpo9fAE/KzG0z87DM/GVmXpuZ92bm/Zl5XRkgcQCwEXBWpf9uFFnKm7gXSZKaNF3o8jCwW2aeUVdZZnR9DcUe1uvgMutRlXuRJKkL+1SOT8zMW4bs6zULkqShRMQBwOXAO5k/Q13VusARwFURsf+Atl67IElq8jmgN+h7beD/ImLZhvZExGuAgxqqJ+K9iu+JHsUM1pMkaYJExFuAt1eKP5WZ3xtyiOqdEZYYcQlLDjFmF/PUzTXOXR0kSWPKzAMzM+Y+KDJJPA7YHfg68945ZzvgjxGxZZ8hJ2tvqCtru9+5B0nSBIuINSnueDrX15ouRm1hqvYi3w9J0jSRmWdn5t+GbHsNRZD5bytV74+IZRq6uRdJkpo0nWe/lpm/79exzBrxBua9kOiJwA5DzONeJEkaSUQsB7y4UjxzhCG8ZkGS1FdELB4RPwSOBNYsi28FPgxsBaxMcV5fC9gD+DHFTSABVgG+HhGf7jOF1y5Ikmpl5mXAJyrFOwEXRcQBETEjIpaIiJUj4tkR8X3gGIqg8gRur/S9q2Ya3xNpbAbrSZI0ASLilcDnK8UzgfeMMEz1D7+6O/j0U3dXhLo/JtvOUzdX3TySpElSZpK4JjN/mpmvAzYHZvU0WQn4SUSs1DDEZO0NdWVt9zv3IEmaeF+i2EsAbgDePQFzTNVe5PshSVpIZeZ9wN7AQz3FqwG7NnRxL5IkNWk6z351mM6ZeQXwy0pxXbCee5Ekqa09gd6sEjcCJ43Q32sWJEmDHAm8pOf4D8CTM/OQzPxjZs7OzAcz8/rMPCEzXwy8kHkDCN4ZEfs1jO+1C5Kkfj4InFApW49if7qSItvcrRSfxe3Z0+YQ4LJKv9k14/ueSGMzWE+SpI5FxO7A0UD0FP8IeF1mZn2vWtU/lBpTMzeotn+ovCip63nq+vhHniQtQMo7Ce0CXN1TvDbwroYuk7I3ZOa9wMMt53IPkqRJFBF7Ai/qKXprZs6egKla7UUREYz35esyZd9RuBdJ0jRRvjc6vlI8bLCee5EkCWj8TOtO4E8jDHNa5XjLmjbuRZKktvatHH87Mx+qa9jAaxYkSY0iYkfgtT1FNwG7Z+YN/fpl5vHAGyvFn46IYQIavHZBkvQvmfkwxfULn2P+83idB4GDM/MjwHKVutk17X1PpLEZrCdJUoci4lnAD4DFeopPAfYq/ygcxU2V43VG7L925fifQ85T7TfOXNUxJUlTLDNvprgrUK99G5q33YMA1how5lzV/antfuceJEkT69M9///TzPz+BM3Tdi9anXnfl80Bbq5pdzPQe1OVxSmyLI3CvUiSppdfVY6f2NDOvUiS1E/1XHtZZs4Zof8lleO6c797kSRpbBGxPrBdpXjmiMN4zYIkqZ+3VI4/n5lN5/qqmcDfeo5XBV5c085rFyRJfWXmw5n5dmBT4OvAdTXN7gaOAbbKzI+XZatW2lQz7YHvidSCwXqSJHUkIramuDN3b/rhs4EXZeYDYwxZ/aJ23RH7V9tf3NDuCqD37nlLR8RjJ2guSdLU+jHzXnizVkSsV9Ou1R4UEasx7374AMV+U2ey9jtJUjdW6vn/3SIiBz2A31TGWK+m3RaVNl3vD3+vu0NdeafUf3Q8l3uRJC3Yrq4cN30O5l4kSernr5XjO0bsX22/ck0b9yJJUht7A72ZUs/LzAtGHMNrFiRJtcps3DtVik8Ytn95s5OfVoq3r2nqtQuSpKFk5sWZ+brMXBt4HPA0ihuYbAiskpn7ZOYsgPL9xmN6ut/N/J/3ge+J1ILBepIkdSAiNgdOYt60yH8CnpeZd485bPUPpU1G7L/xgPEAyMwHgcvHnSsilgTWH2YuSdLUyszZwK2V4jVqmlbP4xtExBIjTFXdgy7PzIdqW07SfidJmnYmc39wL5KkR5cHK8eLN7RzL5Ik9fOXyvGSI/ZfqnJ8T00b9yJJ0ljKAIq9K8VHjTGU1yxIkpqsDKxYKbtyxDGq7euyCHntgiRpZJl5TWael5lnZublNQlXNqscz8rMh2uG8j2RxmawniRJLUXEE4FTmPeup38F/iMzb28x9KzK8dMjYrER+m87YLx+dduMMM/TmPdL6Osz0/TJkjR9VC9UJTNvAG7oKVqS4nw/rEnZg8p9casR5pIkTR8XMe8eNSMi1hyh/2TtRWsCM3qKHmT+i3YlSQuW6g1L/tnQzr1IktTPeZXj1Ufsv1rl+JaaNu5FkqRx7QA8vuf4AeDYMcaZVTn2mgVJ0lx1NyxpCoJrUr1WYdFqA69dkCRNkN0qxyc1tJtVOfY9kYZmsJ4kSS1ExHrAL5n3S9UrgV0ys+lCn6Fk5sXMe6eEZRnyj6+IWBb4997hgBP7dKnW7TLMPA1tTxihryRpEkXE8sAqleIbG5r/tHI8UXtDdZ5tyn1sGNsCy/Qc/y0z/zZkX0nSeF5AcZ4f5fHOyhg31rS5rLdBZt4JnF7pN9ReVN45fOdKcb+9qPp+aOdyjGHsWjn+TWbeNWRfSdLUeGbl+Oq6Ru5FkqQBfgrM6Tl+fERUP3frp3px6SXVBu5FkqQW9qkcn5CZt446iNcsSJL6qLvhyFojjlHNpNd0rZ3XLkiSOhMRiwJ79hQ9TEMmct8TqQ2D9SRJGlN5p9BfAev0FF8LPDszr+1omuMrx68dst/LgeV6js/JzOv6tP8Z897daMeIqKZEnk/5Re2+leLjhlyjJGny7Qb0XmTzT+D6hrbVPWi/YS7QiYgNKO7YOteDFPtMrcy8GvhTT9FywMsGzVOq7ovuQZI0wTLztMz85SgP4NzKMPfVtKu7kHPc90PPYt47h98I/L5P+7OBm3uO1wd2HHIu9yJJmkYiYiXgJZXiX/Xp4l4kSapV3pn6rErxi4fpW959+0WV4lMbmrsXSZJGUl4Q+tJK8cwWQ3rNgiRpPpn5APNfa7DTiMM8u3J8eW0rr12QJHXrP4HH9Rz/bMB7Fd8TaSwG60mSNIby7qinABv0FP+TIqPelR1O9Q2KuynM9YqI2HjA2pYC3lMp/nq/PuVd9H7SOwxw6BDr2x+Y0XP8d4pMg5KkBUxELA18qFJ8YmbOqWsPnAxc03M8A9hviKkOZd6AwP/LzNsH9KnuU+8p97NG5X748p6iObT7slmStOD5LnB3z/H2EdH3i97yg+hDKsVH9dnvKOtmVooPGfRFb0Q8G9iup+hO4Pv9+kiSptxngJV6jh8ATurT3r1IktTPVyrH74qIJYfo93pgjZ7jOyg+i6vjXiRJGtVLmPeC0BuAn7cYz2sWJElNqjfBOrC8OclAEbED82YbqhtvLq9dkCR1ogzk/khP0YPM/96lyvdEGovBepIkjSgilqf4MPvJPcWzgV0z869dzpWZFzLvl5pLAEdHxAoNawvg88BGPcVXUPyxOMghFB8WzPWaiNirqXFEbEJxgVOvj5R3TpIkTZCI+FREPH3EPqtQ3OXnCT3FDwOfa+qTmfcDH6sUf6Y8/zfN80rg1ZU5qhcG1fkq8I+e4ycAn2u6GKjcB4+h2BfnOjYz/zLEXJKkaaLMVHF4pfhrEbFWn27vBbbvOb4d+PQQ030S6M3utwNwUFPjiFgb+Fql+H8y8+a69pKkbkXEeyLiaSO0XywiPsv8dzv9cmY2ZRt3L5IkDfId4IKe4ycAX4mIxuswImJr4FOV4iOaLhh1L5IkjWHfyvG3M/OhuobD8JoFSVIf36ocbwoc0e89EUBEbAgcWym+FPhtXXuvXZAkNYmIdSNimSHbbkwRGL5qT/GnB52zfU+kcRmsJ0nS6I4HqkES/w08JiJ2HvGx8hDzvR+4p+f46cDpEbFjb6OIeALwQ+C/Kv3fk5kPDpqk/IOz+qXqtyLiw73rjIjFI2Jf4EzmvRP5n4GjB80jSWptV+APEfH7iHh7RGwREYtXG0XhSRHxAeASYOdKk89l5gXVfhVfBy7qOV4ZOCMi9u69I15ErBIRHwG+Wen/lcz826B/UPkBQfVuQgcA34+I3g8uKO8cfgawZU/xXcAHB80jSZqWPkVx9++5Hg+cHRF79H4xGhHrRMSXmf/L2o+Vd6Drq7yY9LBK8ccj4ojei2AjYpGIeCFwNvPene464LND/HskSd14DnBORJwVEW+NiE3r7todESuWX2L+EXh7pfpy4MNDzOVeJEmqVWajexvz3ll7H+DkalB5uSe9neKu1r3Zjv7G/Of/KvciSdJQImI9YMdK8cwOhvaaBUnSfDLzZOA3leLXA6dFxLOrn9dFxKoR8Q7gHKB6A5KDM/PhPtN57YIkqc4ewD8i4vMRsUNELF1tEBGbRcSngFnAej1Vv2XeLHv9+J5II4vMHNxKkiT9S0R0uXk+KzNPHWLOV1DcUah6l55/UtzNZzVgnZr6L2bmW4ZdTHmHidOY90MEgAeAK4H7gfWZ94tkgJuBbYf5UEOS1E5EzAKeUil+ALiWItPrA8DywOPK/9Y5Gti/vKBo0HwbU7yxX6VSdRfFxa1LU1wgVA0Y/AOwY2beO2iOnrmOAN5QKU7gaoo9bz3gMZX6OcDLM/OHw84jSZpc5QfUvV/W/j0zZ4zQf3vgZGCpStVsivcpKwHrAotW6o8DXpRDfgBa3un1OGD3StXDwN8pslE8nnk/7Aa4F9glM88aZh5JUnsRcSpFtp9e9wPXUJyvH6a4M+oM6m9ceQOwfWZeOuR87kWSpEYRcRDwiZqqGyj2pmWBDZg30wLALRTfEw26oZZ7kSRpKOUNHHtvSnJuZla/+x93bK9ZkCTNJyLWoLiRx+Nrqu+iOHffS/FZ3frMv08AfDYz3znEXF67IEmaR0S8CfhiT9HDFHvPbRT7wprMm0lvrj8Cz83MW0aYy/dEGonBepIkjWgqgvXKefeiuEvQfHd+aPAZ4N3DfgHbM88qwA+AnYbschWwxzBfJkuS2msI1hvWHRR3gfvyKPtDRDyF4iKd9Qa1Lf0S2DMzZ4+yuPJioM9Q3JF8GPcA+2Xm90eZR5I0udoG65Vj7ETxPqX6BWyTYykC0+8fcZ6lgKOAVwzZ5RbgpcO+r5MkdaMhWG9YP6N4H3HTiHO6F0mSGkXEmymyylUvCm1yCfD8YQPHyznciyRJfUXEZRQB4nO9OTMP73B8r1mQJM0nIh4HHMP82V0HeRD4APCpEW4w4rULkqR/qQnWGyQp3tMcmJl3jzGf74k0tLq7iUqSpAVQZn4H2JTiy9V+6ZBPp7gb0LtG/QOvnOdWYBfgP4HL+jS9FTgM2Mw/8CRpUu0FHETxofIdQ7RPihT37wI2zMwjR90fMvN8YDPg4xR3HmpyKfB6YNdRP+wu55mTmW+n+KDhjD5NHwC+DWzqh92S9OiQmb8GNgGOpPjCs8mfgJdk5qtGvSC1nOe+zNwLeCkwq0/Tu4EjgE28IFWSpsTHgC8DF1HcJXWQuyi+1NwhM3cbNVAP3IskSf1l5heBzYHv0f87nCuBtwKbjxKoV87hXiRJahQRz2TeQL0HKK4t6IzXLEiS6mTm1cCzgZcBp1JkmOvndor3NZtl5idH2Su8dkGSVHEqcDRww4B29wP/BzwjM18/TqAe+J5IozGzniRJ01BErAA8E9gIWB64jyKN8lmZeW3Hc20G/BtFOuhFKe6QeiHw+8zs98emJGmClXdz2wjYEFgXWIHi7t13UnzAfRVwXmYOE9Q37JyLA1tTfPCwKsWFsdeX83T6pj8i1gG2ofi3LUXx77oUOLPLf5MkaXqJiKUp9oeNgZUovgi9luI9Sr8PqseZa0OKfW9tYAlgNvBXivde93U5lyRpPBGxDEXgwgyKz6+Wo7hZ5WyKC3b+AlyQmcME9Q07p3uRJKlR+R3ONhSf261IETR+I8XnZ5d0NId7kSRpSnnNgiSpSUQsD2wJrE/xfmUpihsR30Jxo+G/ZOaggL5h5vHaBUnSv0TE+hR7wtxr6KAIZruE4r1Dv5tfjTOf74nUl8F6kiRJkiRJkiRJkiRJkiRJkiRJkiS1tMhUL0CSJEmSJEmSJEmSJEmSJEmSJEmSpOnOYD1JkiRJkiRJkiRJkiRJkiRJkiRJkloyWE+SJEmSJEmSJEmSJEmSJEmSJEmSpJYM1pMkSZIkSZIkSZIkSZIkSZIkSZIkqSWD9SRJkiRJkiRJkiRJkiRJkiRJkiRJaslgPUmSJEmSJEmSJEmSJEmSJEmSJEmSWjJYT5IkSZIkSZIkSZIkSZIkSZIkSZKklgzWkyRJkiRJkiRJkiRJkiRJkiRJkiSpJYP1JEmSJEmSJEmSJEmSJEmSJEmSJElqyWA9SZIkSZIkSZIkSZIkSZIkSZIkSZJaMlhPkiRJkiRJkiRJkiRJkiRJkiRJkqSWDNaTJEmSJEmSJEmSJEmSJEmSJEmSJKklg/UkSZIkSZIkSZIkSZIkSZIkSZIkSWrJYD1JkiRJkiRJkiRJkiRJkiRJkiRJkloyWE+SJEmSJEmSJEmSJEmSJEmSJEmSpJYM1pMkSZIkSZIkSZIkSZIkSZIkSZIkqSWD9SRJkiRJkiRJkiRJkiRJkiRJkiRJaslgPUmSJEmSJEmSJEmSJEmSJEmSJEmSWjJYT5IkSZIkSZIkSZIkSZIkSZIkSZKklgzWkyRJkiRJkiRJkiRJkiRJkiRJkiSpJYP1JEmSJEmSJEmSJEmSJEmSJEmSJElqyWA9SZIkSZIkSZIkSZIkSZIkSZIkSZJaMlhPkiRJkiRJkiRJkiRJkiRJkiRJkqSWDNaTJEmSJEmSJEmSJEmSJEmSJEmSJKklg/UkSZIkSZIkSdJCIyJ2jIiseew71WuTNL+IuKrm9XrqVK9L0tRwH5ckSZIkSZIkTXeLTfUCJEmSJEmSJEnS9BQRiwNPB7YDngpsAKwDLAcsDdwP3A1cD1wOXAicAZyVmfdMxZolSRMjImYC+/RpcgXwpMx8sKP5ZgBX1lSdm5lbdjGHJEmSJEmSJEnSqAzWkyRJkiRJkiRJI4mIzYE3AHsCq/Zpukz5eCywOfCisvzuiDge+Gpm/mYi1ypJWmCsD7wOOHKqFyJJkiRJkiRJkjRRFpnqBUiSJEmSJEmSpOkhIp4QEccBs4AD6B+o18+ywF7AryPizIj4946WKKlDEXFoRGTNY8ZUr03T1gciYumpXoQkSZIkSZIkSdJEMVhPkiRJkiRJkiT1FYWDgT8DewDR4fDbAmdGxOERsVSH40qSFjxrAm+Z6kVIkiRJkiRJkiRNFIP1JEmSJEmSJElSo4hYATge+Biw5BBdbgYuAH4HnA9cO0SfRYA3AmdExDpjLlWSND28OyJWnOpFSJIkSZIkSZIkTQSD9SRJkiRJkiRJUq2IWAn4FbB7n2YPAN8F9gQem5mPzczNM/PfM3OLzFwHWB54LvBl4I4+Y21JkWVvRhfrlyQtkFYB3jXVi5AkSZIkSZIkSZoIButJkiRJkiRJkqT5RMTSwMkUAXRNZgLrZ+ZemfnDzLy5rlFm3pWZP8/MNwCPAz4BPNgw5nrAbyJitfFXL2m6yMwZmRmVx45TvS5NuAM9z0uSJEmSJEmSpIWRwXqSJEmSJEmSJKnO14CtGuruAPbIzP0y89pRBs3MOzLzvcC2wD8ams0AfhgRi48ytiRpgXR7TdmywPsmeyGSJEmSJEmSJEkTzWA9SZIkSZIkSZI0j4jYH3hlQ/UtwA6ZeUKbOTLzjxQBe5c2NNkOOKTNHJKkBcJngawpPyAi1pvsxUiSJEmSJEmSJE0kg/UkSZIkSZIkSdK/RMQaFIEVde6nyKg3q4u5MvMa4LkUAYB13h0Rm3cxlyRpyvwJ+EFN+RLAoZO7FEmSJEmSJEmSpIllsJ4kSZIkSZIkSep1KLBSQ91hmXl2l5Nl5uXAgQ3ViwOf7nI+SdKU+ADwcE35ayJi48lejCRJkiRJkiRJ0kRZbKoXIEmSJEmSJEmSFgwRsR6wf0P1xcAnJmLezPxWROwD7FxTvWtEbNN1kOBcEbE1sAewNfBEYGVgKeAu4CpgFnAScFxm3jdBa3gKxb99C2AzYFVgBWBZ4AHgHuBO4Grg78ClwB+A32fmbROwntWA5wHbAk8GZgArUvxc7gVuBq4o13AycFpmzul6HQPWuBjFz2xXip/bhjzyu7uN4md0cGaeNpnr6lJEPBbYHngKsDHF83Puc2Mp4HbgVorMlBcApwOnZ+Y/pmTBC6iICIrn8s4Ur/MNgNUoXl8P8chr66/AmcAJmXntFK11K+AFwDOAJ1E8pxcB/lk+zgN+DvwiM++YijWOKzP/FhFHAa+rVC0KfAR46eSvauETEY8DXgjsBGwCrE7xXL8buAE4B/gp8KPMvH+EcVcsx92Z4py0FsW56M5y3IuB4yheP53vSwPWNuX7eGU9i1Ccc54FPJ1if1qD4veQ5bquBv5Ccd7+SWbeMNHrqlnnDGA3YAeKn9vawPIU58VrKfaT6utVkiRJkiRJkjSEyMypXoMkSZIkSZIkSVoARMQngIMaqnfJzF9O4NwbUVzsv0hN9fcy8xVDjrMj8Juaqv0yc2ZPu52BjwNbDrnEW4BPAZ/PzAeG7NOovJj/dcCbKAL0xpHAH4HvA9/MzJtarmkH4N3Af1AE0AzrGuAzwJFtfjYRMRPYp1qemdHTZnGKTIwHUgSL9LNfZs6MiHdSn6Hx0Mz80LjrrRMRHwXeV1N1YGb+zxD9twReDjyHIlAy+veodQpFFsxTR+3Y9Dto6bTM3LHPnFcB643SZxgRsTTwX8DbgHVH6DoH+CXw0cw8o+UaDgUOqal6fGZe1dNuJ4rz0VZDDn0b8FHg8C7OR13p8/x5fmaeWAaSXQosWdPm6Zl5zojzzQCurKk6NzOHPbdP2HOwq7Ejou4L/aMzc9+eNusAnwRexnA37L0ReHdmHjNg7lWA9wJvBJYeYtw7gPcDR2RmXSbFgabLPl4VEStR/Jz+H4P3p14PA8dT7El/bjH/DOpfDx/KzEN72m0OfIwiKL/ub665/p6ZM8ZdjyRJkiRJkiQ9mvX78FWSJEmSJEmSJD1KlJnKmoJ0LpnIQD2AzLwU+EVD9QsjYtUu5omIRSPiixQBTUMHc1BkNPsk8IeIeELLNWwM/B74CuMH6kERyLUVRaDcy1qsZ+2I+AlwKsXF+6ME6gGsA3wemBURTxt3HYOUP/c/UQRbjBII8U2KTEFVe5dZ1zpRBmC+pqbqQeDbA/puHBGXUQRfvhPYlPEC9QB2AX4TET8rg0cedcpgnwuBzzFaoB4U35/uCpweEd+KiJW7Xd0jImLxiDgC+BXDB+pBkTnss8BZXZ0bJ0NmXg0c0VB92GSuZWESES+hyNL2SoYL1IMi497REfGNMgi6btztgT9TnJOGCdSDItveF4CfRkRdUGZrC8I+XrOmfSgCUT/KaPsTFHvui4DzIuKT5d9jnYvCBykydO6O14pIkiRJkiRJ0oTxA1hJkiRJkiRJkgSwDbBGQ903JmkNTfMsCezWdvAymOr7FNnsxvUUigCZsYLSImIL4HRGCzCYMBHxLIoAuBd0MNzGwBkR8eIOxppHRDwV+B1FtrmRZOaNwM9rqtYHtm+5tF47UR8YdmJm3jyg7+rABh2uBeC5FEEpT+x43AVaRLyZIjPe+h0M9yrg92Xmz06Vmf9+DryhxTBbAqdNp4A9iqC8O2vKdymDLDWCiHg98ANg+TGH2A/4cs24e1AEw6095rj/AfwoIkYN/u5rQdjHK+tZKiK+CcwEHtNyuEUpstueHBHLtV1brzIw/RvAhxg9IF+SJEmSJEmSNCKD9SRJkiRJkiRJEhSBPXXmAMdM0hqOA25tqHtOB+N/GmgKJLsZOJ8iG9dtA8Z5DPDziBgpuCoiVgROYvAF/XcAfwXOAf4AXAJcT/G76ExE7F6u57EDmt5aruEPFJmD7urTdmngexHxvE4WSZH5j2KddRnOHgCuAc6lyBZ0XcMwRzWU79t2fUOMNbODsR8CbuCR38Ms4EqKrH39bAT8LCJW6GANC7yIOJAiq1e/YJQ5FD/L8yheZ3cMGHYj4NSI6CL4b665AUc71dQ9RPGcPo8iq9lNA8Z6MvA/Ha5tQpWBq59rqDa73gjK8+yRzJ+FMyme4+dTnCtuHDDU/hGxX8+42wI/BJaoaXszcBHFOfeaAeM+D3jzgDajmtJ9vFcZcHsi8OoBTR8Erqb4XfyJYp/KPu13Ak5syng4pg/TvEfdBlxMkfH3L8B9Hc4rSZIkSZIkSY9Ki031AiRJkiRJkiRJ0gJhh4byv2bmDZOxgMx8ICJ+S30Wvab1DWtHYO9K2bUUQS7fycx5gg4i4gnAK4G3AivVjPcY4LsR8YzMfHjINXyM5uyFv6IIKPtV0887IpahCMz5N4ogiJ2BZYacuzrW1hTZmJZsaPJn4Evlei6v9F0UeAZF1rHXM//3TYsBR0fE5pl5/Tjrq/g6Rea5uRL4LvDtcn3zBBZExBrAnhTBKnOdCNwCVDOQvTQi3pSZd7dZYEQsD7yopupG4GdjDDkb+CnF8+J84KLMvL9m3iWBzSmCV/al/vm1PvBV4OVDzPs34Kye43WBx9W0OweYbz0NLhiyXSsR8Vzgvwes43Dgh5k5T1BwRDyF4vX+RmDZmr5rAceVr/dWz5XS+4HdK2XH8cg5YJ6A2DI74n7AgdS/Zl8VEd/MzJM7WNtk+CzFz7r6evz3iNgjM4+fgjVNN2sARzNvYOrFFD/bE6v7SERsDBxA8XOvC2b9ZET8H7AURaBeb6DYtcBngOMz84rKuOtSPDffU/at+nBEfK+jvWBHpn4fnzt2AN8Cnt3Q5D6K1/OPgLMy895K/9Up9vF3A0+q6b8DcCjwvlHW1WCbmnVeTRE0e0JmXlZZ26LAtsAeHcwtSZIkSZIkSY9Kkdnvpm2SJEmSJEmSJGlhFxGLUGSXqgtSOSYz95nEtXwI+GBD9eqZ2TfLVETsCPxmiKm+A/y/zJw9YLy1KTKj7dzQ5B2Z2S9AaO44S1Nk/akG190LvDozfzRojJoxl6IISnsrMDMzDx+y30oUmZHWqqmeDfxXZn5/yLGeRBGMsHFN9S+A5+SQX0ZFxExg0HPtcuBVmfn7YcasjP8/wFtqqvbNzKNHHa8y9muBr9VU/XdmvmOI/jtSPG9Pogg8+XVmDsqaVx1jGeAjwNuYP9MWwLMz89cjjnkocEhN1eMz86pRxuozx1XAepXi0zJzxxHGWIUiUKkuS2QCHwIOG/QzLbNsHUMR3FLniMx84wjrOpT6n1+va4FXZOaZQ4y3GfBLYLWa6lMyc9dh1zYR+ryGn5+ZJ1bavoMiAKzqAmCLzByYSTQiZlBkmKw6NzO3HLjgR8a5ipbPwYkcOyIGnUOTYt/8RGY+NGCsXYATqA/6fBvwdIoAt7kOBw7KzHsGjLsFxTlspZrqQzLzw/36V8bakQVwH6+M+S7gUw3VPwbekJmDMhoSEYsBB1Gcu6vn7TnAjpl5xpBrmkH966Hq0xS/k3sHtpQkSZIkSZIkjWWRqV6AJEmSJEmSJEmacutTH6gHRQatyXRun7rNO5rjmxQBX7MHNczMaykyYDUFDnw4ItYZYs5dqc+C97ZxAvXKtd2Xmd8sg1JmjtD1M9QH6l0FPG3YQL1yDRcDzwT+VFO9K91m5rkE2H6cQL3SUQ3l+4453jBjNM1ZdTmwWWY+LzNPHjVQDyAz7ykDA5uCyeoCFRcWH6Y+UA/gzZn5oWF+pmUWyV2A3zU0OSAinjrmGuv8DXjGMIF6AJl5AcVrqi6Q7dlllrPp4ksUgYpVmwF7TfJaprvXZuZHBwXqAWTmKcC7Gqo/wLyBeh/MzDcPCtQrx51F83mwmg2vC1OxjwMQERtSnHPqfCgzXzxMoF65tocy82PA/jXViwBfGHZdQ3pnZr7bQD1JkiRJkiRJmlgG60mSJEmSJEmSpH4BHhdM2ioKf+5T97gOxj+XIrBhqGxvAJl5P/BC4Jqa6mWBA4YYZtOastsZPpirr8y8a5h2EbEJsF/DWnbLzCvGmPtWigx/d9ZUHzjqeA0eBF6amdeNO0AZTHJ+TdUOZUaisZTZ2J5ZU3VuZl445NquHrbtEGMdSRHIUvX8aRbMNZSIWBN4XUP14Zn5pVHGKwOTdgNuqKlehCKgqQv3A3tmZt15pVEZrHpMTdUiFOepaSEz76M54OnDEbH4ZK5nGvtyZo66jxxJfQa2VXr+/8TM/Mgog2bmccDZNVUbRMRTRhlrgKnax+f6KLBUTflXM/PQEcb5l8ycSfF7qdoiInYYZ8wa383Mz3Y0liRJkiRJkiSpD4P1JEmSJEmSJEnS2n3qbpm0VRRu7VM3dOabPt4yZtayO4CDGqr3j4jFBgyxRk3Z3zLzgVHX0tK7qf9+6H2Z+ZdxBy0zkn2ipmrHjoI0PttRMFtdUEsA+7QYs6lvJ4GYYzoYqAayLALsNAVrmWivBZasKb8BeN84A5YBqO9uqN4jIuoyU47qk5nZLzi5n681lD9t3MVMkW8Al9WUr09zAKYecTPwzlE7lRn4+mVQfQD4rzHX9O2G8n8bc7w6U7WPExHrAy+rqbqa9tlL3wXcVlP+1pbjAtzR0TiSJEmSJEmSpCEYrCdJkiRJkiRJklbuU3f7pK2icCcwp6FupZZjn5SZdVl/hpKZxwJ/ralakyITVz91QQBLjLuWcUTEChQZ8KouB77SwRRHAvfUlL+o5bgPA4e3HGOub1Nk6avaOyJi1MHKPnvXVN0PfGfU8bpSZmv7Y03VMyZ7LZNgr4byT5TBOeP6FlAXILponzmHdR8tntOZeRb1gdRdBkRNuDJorClT4fsjYunJXM809NXMvHvMvr/oU/eDFllMT24of+qY41VN5T4OsD9FgHfVIWW2yLGVv8sv11Q9LyLqApJH8Z3MvKnlGJIkSZIkSZKkIRmsJ0mSJEmSJEmS+gVETGqwXmYmRcBenbaBG00Zf0ZxbEP5oIxldYE1m0ZEv6yGXXsOsExN+bfKoJlWMvM24PSaqm1aDv3LzLy25RgAZObNwIk1VesD240x5LOA9WrKjy+zs02lC2rKtp70VUygiHgcsElN1UM0v1aHUp6Ljmmo/o82YwO/yMx/thyj7ve7fssxp8L3gPNrytcC3jzJa5lu2gQE98uk+t0W414J3FtTvkGLMXtN5T4O8OKasnsonsddOK6mbEnaZ82c2bK/JEmSJEmSJGkEButJkiRJkiRJkqR+GVvumrRVDJ6zTWaZB4GftOg/1w8ayrca0K8usGZRYOYkZo/ataH8Rx3OcWZN2dYR0eY7qdNa9K1zVEP5vmOM1dRn5hhjde3GmrIZk72ICfbMhvJfdxAMB83BUNu2fE7XvU5GdVlN2TIRUZfFc4FVBkW+r6H6oIhYcTLXM43cDlw0bufMvIEiA+h8VcBvW4w7B/hHTVUXv8cp3ccjYh1g45qqkzOzLqvsOM6jPtixTdD7vdRnWpUkSZIkSZIkTZBp9WWNJEmSJEmSJEmaEHUX7M+1LHDHZC2kZ846/dY5yMWZeXeL/nP9jSLz3/KV8i0iYvHMfLCh368psn1Vv5vZGfhzRBwK/DAz2/wbB9mypux+WgR81Ph7TdkKFEFiV4w55rljr6beSRSBbKtXyl8aEW8aNugiIpajPsvS9cDJ7ZY4zzwzgM2AzYF1KX6ey5ePRft0XbembIWIiDJAamGweUP577sYPDOviYjrKLK89VoG2JDifDCOukxyo2o6L68ATHVWx5Fk5k8j4ixg20rVKsA7gQ9M/qoWeBeWgXFt3MX8QfDXZWZdJthRx63qIlhvqvfxuj0UigC7TmTmg+U5p5qJsOlcN4xZmflwi/6SJEmSJEmSpBGZWU+SJEmSJEmSJN3Xp26lyVoEQEQERbBJnX7rHGRWi77/UgY5/bmmain6ZC0rs3wd01C9IfAt4PqIOCYiXhERa7Zda68yC1hdRqDLOr6IvynIY9UWY9ZlEBtbZj5E8fOuWh546QhD7Ul9YOk32/5MI2KTiDgsIq4ErgSOBz4K/CfwCmA3YHuK4Kamx+Nqhl6E5tfXdLRhQ/mfOpyjaaxqMM0o2gZDQXMG0uU6GHsqHNxQfmBErDapK5keugjIrAt8m6hxm4LwRzGrgzHG3seBTRvKL267poq688MCs4dKkiRJkiRJkgYzWE+SJEmSJEmSJN3Wp66LbDijWJ7m7y9mtxj3qhZ9q65sKF95QL+DgWv71K8MvAb4DnBdRFwaEd+MiAMi4oljrLPX6sASNeVPjojs6gH8rM+/bVy3t+jbZGZD+b4jjNHU9qhRFtIrIlaPiKOBC4H30j9wZFwLU7BeU1DruFkc6zQFulSz7Y1idou+czVlR5yW3/9m5unAz2uqlgPeN8nLmQ66OC/WPYcmatwunpdXdTDGXOPs43UB0AA/6Hgf3WrEdQ0yEXuoJEmSJEmSJKmPaflljSRJkiRJkiRJ6lS/ALJVJm0Vg+e7psW4d7ToW3VnQ3nfi+kz80aKjGjD/js2BF4NHAlcHBHXRcSREbFtmYFwFFOdmarN86jL3x0AmXkhcE5N1Y4Rsd6g/hGxPrBdTdXvM3OsLEsRsR1wCbA3MOrvdxSLTuDYk63pNdflc6ZprJVajNllNsuFycHUB3odEBHrTvZiFnAT9RxakJ+bU72PT+U+ukDtoZIkSZIkSZKk/gzWkyRJkiRJkiRJV/ep22zSVjF4vn+0GLfLi9WbstSsNKhjZp4PPI0ie15TZqwmawIHAGcCF0XEy0cI2ltmxLm6ttS4HTPzwS4X0qMuA14A+wzRtymgbuY4C4mIHYCTmPxMltPdkg3lXWaSahpr7Oe06mXmn4Af1FQtARw6uavRAmiq9/Gp3EfbnG8mag+VJEmSJEmSJDUwWE+SJEmSJEmSJF0O3NNQt+VkLoQikK3JBZO2igmUmTdl5iuBfwO+xngBCBsD3wVOjYi1hmi/2BhzLOy+A9xfU753vyDIsm7vmqr7KH4nI4mIFcp+yzY0eRg4HfgYsBfwDODxFJmWlgQWycyoPoAPjbqWhUiXmQknMsuh5vcB6rO77R0RT5rsxUg93EclSZIkSZIkSUPxA2VJkiRJkiRJkh7lMvPhiPgzRRBQ1WQH6zXNd31m3thi3BVa9B12rNmjDJKZs4DXR8Sbge2BnYAdKAIWFx9ymO2BcyLiGZnZL/PgfQ3ldzA5QZBtfncTIjNvi4jjgJdVqjYAtqMIkKuzA0WwXNVPMnP2GEs5BFijoe4I4KOZef0Y4w77HJrO6oItoXiN3tLRHE2v96bXlFrIzL9FxEzgtZWqRYGPAi+d9EVpQTHV+3jTa/5Cus3mWWecPUCSJEmSJEmSNEUM1pMkSZIkSZIkSVAEJtUF6z0pIlZvGSg3lIhYAvj3hurTWg4/GRf53zbOYJl5H/CL8kFELA1sRRGIN/exRJ8h1gSOj4inZWZdRipoDiS4LDOfOc66FxIzmT9YD2AfmoP19m0oP2rUycvn/OsbqvfPzJHH7LFKi77TRdNrboF9vWsoHwJeTZE5steLy/PcuVOwpnEtOtULWIhM9eu6aR89ODNPaLkeSZIkSZIkSdJCZJGpXoAkSZIkSZIkSVognNRQviiw9ySt4QU0Bxj9vOXYM1r271WXVQ06Ct7JzHsz87TM/Ehm7gKsShFQ9ss+3Z5CEWDW5OqG8lXHXObC4hfAdTXle0bEMtXCiFgWeElN+2vo//tp8ixg+ZryY1sG6sGjI1iv7ncHsH6Hc2zYUG6mqwmSmVcDR9ZUBXDYREzZMFcXVu5oHE39Pu4+KkmSJEmSJEkaisF6kiRJkiRJkiQJ4Ezgpoa6/SdpDU3zPACc2HLsLVr2ByAiAti8puo+4Kou5qjKzLsy8wdl4N6OwA0NTffrM8a91AcarB4Ri7Vf5fRUZiL8Zk3V8tQH5b0UWK6m/JjMnDPGEnZoKK8LVBrVZh2MsaC7rKH8qR3OsUVD+aUdzqH5HQbcVVO+a0Q0vW7GdXdN2bJtB42IJbsYR/+yRReDtNjHL2koX6ftmiRJkiRJkiRJCxeD9SRJkiRJkiRJEpn5EHBMQ/WTIuLZEzl/RGwE7NpQ/ZPMvKXlFE8qs6K1tRH1mdBmZeaDHYzfV2aeBuwB1AWGPWPAv/EPNWVLAVt1sbZpbGZD+b5DlvUbY5A1a8oeBn475ngARMTKwJPajDFN/LmhvJPndESsDaxdU3UXcHkXc6heZv4T+O+G6q6z691eU7ZCB+M+pYMx9Iip3sfr9lCA7dsvSZIkSZIkSZK0MDFYT5IkSZIkSZIkzXUk8FBD3RcjYokJnPsImr+3+EIH4y8OvKCDcfZsKG+6iL9zmflH4Dc1VYvRP8PPLxvKd269qGksMy+mPjjuWRGx7tyDiJhBfSa8szJz3Cxrq9WU/bPM+NfG7kC0HAPg/obyiTwXjOKMhvKdImLVDsZ/RUP5WZmZHYyv/j4L1AVqbxMRz+9wnrpgvfU6yDq6bcv+mtdU7+MXAdfXlG8bEUu3W5IkSZIkSZIkaWFisJ4kSZIkSZIkSQIgM6+gOUPYxsB7JmLeiHg1zQFjv8jMszqa6lUdjPHKhvJfdzD2KGY1lK/Sp89PKLK2VR0QEUu1XdA0N7OmLIB9eo73pj4Arq7vsOrG6+J38dYOxgC4o6G8i+xWrWXmtcCFNVWL0xxoN4rXNJT/vIOxNUBm3gF8oqH6Y3T3XfeVNWVLUOx7bTQ9fzS+KdvHywDdH9dULQP8Z9tFSZIkSZIkSZIWHgbrSZIkSZIkSZKkXofSHKBzcERs0+VkEbEB8PmG6oeAd3c43XMj4hnjdo6IVwCb1FRdD/x07FWNp+k7ntlNHTLzBuC4mqo1gTd2sKbp7HvAvTXl+wBERFAE61XdA3y/xbw315StFBGrjztgRLwYeNr4S5pH07ngcR2N34VjG8oPjojlxh20fL0/pabqYeC7446rkR0OXFtTvhmwV0dznNtQPnb2voh4NvDUcfur0VTv419uKD8oIpYfd12SJEmSJEmSpIWLwXqSJEmSJEmSJOlfykxV72qoXhI4LiLqAlhGFhHrACcBqzY0+WRmnt/FXHOnBL4QEYuN3LG4CP+TDdVHZeZDrVY2uqZgrLqgll4fB7Km/LCI2L7dkqavzLyd+oxJG0TEdsB2wAY19T8qs3+N6x8N5S8dZ7CIWAP4yvjLmc9lDeVbdjhHW0cB99WUr0URfDyyiFgR+HRD9Y/KwFdNgsy8D/hwQ3XTXjWqcxrK92mxX3T5OtQjpnQfz8wLgBNrqtYEvhMRXn8hSZIkSZIkSTJYT5IkSZIkSZIkzSsz/5fmbGGPAU6LiN3bzBERTwPOAjZqaHIG8KE2czR4OvC1MlPaUCJiCeBHwLo11ffQnGmnd4zjI2KfiFh86JU2j7UDRfBY1axBgWOZeQ5wTE3VEsCPI2KntuubKyI2jIgvTqNsQ0c1lO9bPkbpM6xfN5S/PyIeO8pAZTa+kyleo105H5hTU/6qiFiqw3nGVgbONQVGvSMiXjfKeOW/6wRgnZrqOcBHR1uhOvAN6gNHV+xo/Asaxn8C8LZRBiqfP9+mPrhX3ZiSfbzHu4D7a8p3A46JiGVGGKtRRCweEa+KiNd3MZ4kSZIkSZIkafIYrCdJkiRJkiRJkursB5zbULcicEJEfD0i1hpl0IhYPiI+BvyW+ovmAa4C9szMB0cZewT7UFxQPzDQIyLWBI4Hdm5o8sHMvHqIOTcHZgJXRsQhEbHxsIutrGcn4P8osgtVHTvkMAdSn9FtFeCUiDgsIlYec33LRMQLI+InwCXAm4BFxxlrCvya+p/LntRnuvs78JuWc54J3FZTvgZw0rCvr4jYliLAdfOe4roMiiPJzHuAP9ZUrQ/8PCKeuYBkkjoUuLGh7ssRcfAwmbgiYgZFwGNdMCzA4Zn557FWqLGVGc8+OIHjJ82Btx+PiL2GGad8/pwCPL+jpanZVOzjAGTmxcB7G6pfBfyxDKofS0Q8KSLeD1wJfAt48rhjSZIkSZIkSZKmxoLw5ZkkSZIkSZIkSVrAlEE6uwJ/6tNsf4rgs2Mj4sURsWpdo4hYNiJ2iYgvAVcDBwNNGeb+DjwrM5sCb8Z1NPMGL70auDAi3hERa9esecOI+CBwEfAfDWOeB3x+xHWsTRFY9JeIuDAiPhERLymDPGpFxMplm+OAXwF1P+e/M2RmoMycDbwAqMvCtwhFEMLVEXFEROzR9Hst17ZKROwYEQeWAXo3Az8ux59W30Nl5hzqsw4uXz6qji6DfNrM+QDwmYbqpwEXRMT7I2K9amVELF3+fr5PEfTXm6XyDornfBe+1lC+A0WA4F0RcVFE/C4izqx5fLGjdTQqn9P7UJ8FcFHgYxQBNK+tC0SNiE0j4uMUGda2b5jmzzQH6GjifZci0+NE+Rowu6Z8UeDYiPheRPx7NTg1IhaLiO3K5/klwDN7qk+h2PPUjQVlHyczP0f9fgGwCXBqRJwTEW+KiC2agpojYtGI2DgiXhERn4mIi4G/Ah+h+HtBkiRJkiRJkjQNDbyDpCRJkiRJkiRJenTKzFvLTG7fAZ7T0GwJYK/yQUTcBNwA3A0sBTyW4oLzukxwVecCLxolw80ITqUIJHtHT9k6FIFSn46IfwLXUQRmrE2RZa6fW4C9MvPhFmt6Mj0ZcyLibuDW8nEvsAywevno5yFg/8y8c9iJM3NWROwGnACsVNNkWeAN5SMj4uZyXbMpfq8rlv3q+k5nM4H3D9Eu6S4Y7n8oMlluWFO3CkXQxkci4gaK19bDwGoU2ffqgl4TeC2waUfr+zbwdqApG+TSFMEpTR7qaB19ZebJEfE2ip9nnS0oArL+NyJuBK6neC6vxeDn8bXAC8sgZk2BzMwy29gJEzT+TRHxDuDrDU1eVj5uj4hrgbuAx1C8DpepaX8VRTDZH7pf7aPWqSxY+/hrKc7BTZkXn1Y+AO4t13cr8ACwAsV5ZxWKv6MkSZIkSZIkSQsRg/UkSZIkSZIkSVKjzJxdBnW9jyKIadBF5auVj5GmAY4E3pGZ942+yqG9G5gBvKRSHoy27luB52Xm37pbGlAEyC0LPG6EPvcCL8vMX486WWaeGRHPBH5AcyAWFD+fx5aPhVpmXh4RZwDbDWh6emZe0dGcd0fE7sDv6B80tkb56Dsc8ObM/GFEdBKsl5n3RsRLgd8w+mt7UmXmFyJiDkWmrEUbmi0CrFk+hnEpsFtmXtl+hWojM0+MiLOBbSZo/G9ExI7Aa/o0W7F89HMNsHMZANjR6lRaYPbxzHwoIl4FXEbxN1K/bLJLA+uWD0mSJEmSJEnSQq7fB8aSJEmSJEmSJElk5pzM/AjwFOCnHQ//W2C7zHzjBAfqkZlzgJcDh7cY5gJg28wcNVvS0FnvRnAOxc/uxHEHyMyLKDL/fBK4v6uFlW4FjgCmWzayo4ZoM7PLCTPzEmB7iqCPcc0GXpyZX+pkUT0y8y/AZsCxFFmhFliZeTiwM9BFMOW3ga0y89IOxlI33jvB4+9DETw+rrMpnjOXd7Qe9ZjifbxuPZmZH6Q4f/+p7Xg1zqb7v7skSZIkSZIkSRPMYD1JkiRJkiRJkjSUzLw4M3cHngr8L0Uw1jjuAb4LPDszt8nMs7pa4yCZ+XBmvhnYhSLYbVi3AgcDT8/Mi8eYeguKbG2foLig/+ExxpjrbGBfYOvMPLfFOECROS0z3wNsBHwKuKnFcNcD36LIerRmGYS5QAd31fgBcHef+ruBH3Y9aWZeAGwJ/PeA+avuBb4CPDEzf9L1uubKzJsy81XAWsDryznPBv4B3AY8OFFzjyozTwU2Bd5Osb5RzAFOBrbPzFdn5uxuV6c2MvN04OcTOH5m5v8Ddgf+MkLX64A3UwRQXz8hixMwpft4vzWdRXH+fgnwa4rzyDgeojivHgJslJnbZuYp3axSkiRJkiRJkjRZIjOneg2SJEmSJEmSJGkaiojFgWdQBKFtAWwArA0sByxNkantbuAG4HLgQuBM4IzMHCUYacJExNbAC4CtgScCKwNLUqz77xSBdScDP87Mezucd1lgK+DpwBOADYF1gRUofn6LUGTju4MiAO58YBbwi8y8sqt1NKxtEWAbYAeKrHvr88jvdQmKn82dwO0U2csuBv4K/LbMwKaWImIV4EXAs4B/Ax5D8dx8iOI5cRVwEUVQyE8z87aaMZaj+J1V/TMz2wSLTisREcAzKQJ7tqJ4ra0GLEMRNHsncDVFYNZZwPGZec3UrFYLkohYlOK581yKzGlrAI+l2CPuBK4EzgN+BvxsGgYmLxSmah8fsKbVgOeUa3oysB6wKsXfRnN4ZH+/iWIPvZhinz8zMyciE68kSZIkSZIkaRIZrCdJkiRJkiRJkiRJkiRJkiRJkiRJUkuLTPUCJEmSJEmSJEmSJEmSJEmSJEmSJEma7gzWkyRJkiRJkiRJkiRJkiRJkiRJkiSpJYP1JEmSJEmSJEmSJEmSJEmSJEmSJElqyWA9SZIkSZIkSZIkSZIkSZIkSZIkSZJaMlhPkiRJkiRJkiRJkiRJkiRJkiRJkqSWDNaTJEmSJEmSJEmSJEmSJEmSJEmSJKklg/UkSZIkSZIkSZIkSZIkSZIkSZIkSWrJYD1JkiRJkiRJkiRJkiRJkiRJkiRJkloyWE+SJEmSJEmSJEmSJEmSJEmSJEmSpJYM1pMkSZIkSZIkSZIkSZIkSZIkSZIkqSWD9SRJkiRJkiRJkiRJkiRJkiRJkiRJaslgPUmSJEmSJEmSJEmSJEmSJEmSJEmSWjJYT5IkSZIkSZIkSZIkSZIkSZIkSZKklgzWkyRJkiRJkiRJkiRJkiRJkiRJkiSpJYP1JEmSJEmSJEmSJEmSJEmSJEmSJElqyWA9SZIkSZIkSZIkSZIkSZIkSZIkSZJaMlhPkiRJkiRJkiRJkiRJkiRJkiRJkqSWDNaTJEmSJEmSJEmSJEmSJEmSJEmSJKklg/UkSZIkSZIkSZIkSZIkSZIkSZIkSWrJYD1JkiRJkiRJkiRJkiRJkiRJkiRJkloyWE+SJEmSJEmSJEmSJEmSJEmSJEmSpJYM1pMkSZIkSZIkSZIkSZIkSZIkSZIkqSWD9SRJkiRJkiRJkiRJkiRJkiRJkiRJaslgPUmSJEmSJEmSJEmSJEmSJEmSJEmSWjJYT5IkSZIkSZIkSZIkSZIkSZIkSZKklgzWkyRJkiRJkiRJkiRJkiRJkiRJkiSpJYP1JEmSJEmSJEmSJEmSJEmSJEmSJElqyWA9SZIkSZIkSZIkSZIkSZIkSZIkSZJaMlhPkiRJkiRJkiRJkiRJkiRJkiRJkqSWDNaTJEmSJEmSJEmSJEmSJEmSJEmSJKklg/UkSZIkSZIkSZIkSZIkSZIkSZIkSWrJYD1JkiRJkiRJkiRJkiRJkiRJkiRJkloyWE+SJEmSJEmSJEmSJEmSJEmSJEmSpJYM1pMkSZIkSZIkSZIkSZIkSZIkSZIkqSWD9SRJkiRJkiRJkiRJkiRJkiRJkiRJaslgPUmSJEmSJEmSJEmSJEmSJEmSJEmSWjJYT5IkSZIkSZIkSZIkSZIkSZIkSZKklgzWkyRJkiRJkiRJkiRJkiRJkiRJkiSpJYP1JEmSJEmSJEmSJEmSJEmSJEmSJElqyWA9SZIkSZIkSZIkSZIkSZIkSZIkSZJaMlhPkiRJkiRJkiRJkiRJkiRJkiRJkqSW/j+qtnASbYY2DQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 3600x9000 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_observations(observations, mark_CO=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.4.2: plot observed frequencies and mark frequencies of choice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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7U+/9SlV9eqvhvdVxb0wyPBnm7280Zsb3dmZyvwoAmN33K9v0ykH7zAnGzOrZ2Vk+DwwzIcAHAMzCLQftL6x51dr+atC++QbXPmHQftlmN16T0T+Qkrx3rOtGSX54vetXjxt/4FjXVUlet9k6q35/0B7WDADMWGvtjCS3G+u6LskfTTJ2NeT35kH3k9e6dtUwKDjcG6zntUmuHms/qLV2hw2uf1yS5bH2e6rqs5stsvqF8fALzydOWCMAsPsMv3eYdO/x7iSfG2vfLsnf2+D6hyY5daz92YxOkJnEsKYnbnL9rD4TALC32K8AALP2J4P2XTa5fpb3dmZ1vwoA2N0uG7RvvdHFM352dibPA8MsCfABALPwzUH7xlsYO7z2axtc+7hB+21bWOftg/aPbGGd/1lVV6955fH+Z5Jvj7XPaK3dc8KxAEAfwxuml1bVt9e8cm2XDNrDm55J/i4oOH6a8NVJ/nSSBVb3GuPXthy/Jxk3q30RALBLtdZOSfLIQfdEe4LVG6DvGHRv5buSt09yE/XotYP2ua21m6514Yw/EwCwt9ivAACzduWgvdnJLzO5tzPj+1UAwO528qD9jU2un+Wzs557Yc8R4AMAZuHPB+0z17uxuYZzBu0PrnVRa+22OfbknO8l+ciEaySjfxyMO2uDa4e/m+iLzCSpqpUc/xk2WgsA6O9Wg/bXtzj+ikH7rHWuG/Z/cHVvMKmZ7FeSXJzRXuqoO7TWTl3vYgBg17pvRm8VPepzVfXlLYyf1XclX0ry+bGuE5PcZ53LZ/mZAIC95axB234FAOjtjoP28H7S0FmDdq97O8N1et6vAgB2twcP2hdvcv1Zg3aXZ2dn/DwwzIwAHwDQXVV9Mcdu1E9K8k82G9daOynJLw26h8doH3XmoH1pVV0zaY1JPjlo36O1tjzhWsOxW11rOB8AMFvXD9onbHH8jQbt72utDW/KJjPaQ7TWbpRj35y6pbWq6ntJLptkLQBgV5vl9xezWst3MgDAdtmvAAAz01prSR4+6P70BtfP8t6O/QoAkNbajZNcOOh++SbD5vX9Ss/ngWFmBPgAgFl5To59OP55rbXz1ru4tXbzJP89x27E31RVb1pnyBmD9he2UlxVfTXJd8e6Tkxy1x5rrXH9cD4AYLaGJ+7dZovj17p+rS8ZZ7WHuFuS8S8ev1NVX+u0FgCwe01773Faa+3k4UWrN3jvMuW11tt7zOQzAQB7i/0KADAH5+bYZ04qyR9vcP0s7+145gUA9rnVl1L/UZJ7jXW/J8lrNxk6q33ELJ8HhpmRIgUAZqKq3t9a+8Uk/zFJy2gfcri19n/Yu+8waa+yfuDfO70RklBDJwQl9CYgCAldpYgICCJS1J8oFhRFwUJvAoqKYEEJiIiASJPeqyAlVOmhBQglCSGNtPv3xzORzWRmtkzZ910+n+ua63rnnPPc5+zu7M7zzjPfOQ9J8rIkn05yZpJLZtiW+xeSHLamxBuT3GfGFONvnP/qFpb5tQwviq6t+dkJ4y4151wnjN3fbEgAAFisL4zdv0pVXWr0gt5G3HhC22UmtM17vjJ+DjF+TjJtnvHjtjKX8xUA2P3Me+5xYpJz84NrSXskuUQuep5wyQyv9VzgnCTf3ORcGz33WNXXBADsLM5XAICVqao9kjxprPl13f2NGYet8trOqq5XAQDbZLTb3DFjzQcluUKGXYLvmmT/NX3/neTu3d3rlF7Ve2dX+X5gWBkBPgBgZbr72VX16SR/neRao+YfG92m+UKSP0/yj919/oxxB43dP30LSxw/ZrzmBZ/Suuecc607DwCwOt39har6WpLLrWn++STPXO/YqjooyZ0ndE16fp/3fGV8/N5VtW93f3/B80w6xvkKAOx+5jon6O6uqjOTXGxGzUltZ2zgAu+4jZ57rOprAgB2FucrAMAq/X6GD66+wPlJ/nidY1Z5bWdV16sAgO1zUIZNM9ZzYpKnJ3lGd58za+CK3zvrfS/sSHts9wIAgB8u3f2WDIG9pyU5b53hXx6Ne+E64b3koifXZ00cNduZ69Sc1rbZuTYyDwCwWi8fu/9HVXXIBo57RJKDJ7Rv5Dxi3nOIZc0zaS7nKwCw+9mu10qWee7hPAcA2ArnKwDASlTVLZM8Yaz5Gd394XUO3Z3OVzZ6vQoA2LWdmOG85R/XC++NrPK9s15fYUcS4AMAVqqqHpzk8xk+cWz80zjGXSnJs5J8saoetM7Y/cbun72F5Y1/Gtj+E8aMz7OVuTYyDwCwWn+Z4RNQL3D5JP9RVQdOO6Cq7pfkD6d0b+Q8Yt5ziGXNM2ku5ysAsPvZrtdKlnnu4TwHANgK5ysAwNJV1RFJXpZkrzXNxyV55AYO353OVzZ6vQoA2LVdJslfJ/lyVT2sqmqd8at876zXV9iRBPgAgJWoqr2r6qVJnp3k8FHzSUkem+QmSQ5Nsk+SyyW5a5L/TNKjcYcl+aeqeuqMKcY/YWOfLSxz33VqTmvb7FwbmQcAWKHu/lySJ4813ybJJ6rqwVV1larap6oOrarbVtWLkzw/wwcSdJLvjh172oRp5j1fGT+HmFRzEfNMmsv5CgDsfrbrtZJlnns4zwEAtsL5CgCwVFV1ySSvTXLJNc0nJrl7d08KvI3bnc5XNnq9CgDYJt19SnfXBbcM7205LMkNk/x2ko+tGX6xJE9L8ryqmpUvWuV7Z72+wo4kwAcArMqzk/zcmvvvT3Kt7n5Ud//P6D8M53T317v7Vd199yR3y4VPmn+/qh44pf74m+QnfdrHesY/YWPSG+8ntW12ro3MAwCs3p8ledVY25UznMccn+HTuU5K8qYk91wz5lFJPjd23CkT6s97vjLp08A2cr6yrPMiAGDXtl2vlSzz3MN5DgCwFc5XAIClqaqLZQjv/cia5u8muWN3H7/BMrvT+cpGr1cBALuI7j6/u0/u7g93998kuV6S388PNtlIkvslediMMqt876zXV9iRBPgAgKWrqmOS/PKapm8muXN3f2PWcd39yiQPGWt+alVt5MXAAze5zEnHXOSEvbvPTHLenHOtOw8AsHrdfV6Sn03yl7no8/0k5yR5ZHc/LslBY32nTBg/7/nK+Phzu3vSJ4St5LwIANjlzXVOUFWVrQX4DhgduxkbPfdY1dcEAOwszlcAgKWoqv2SvDLJjdc0n5HkTt39kU2UWuW1nVVdrwIAdlE9eHqSR4x1PaqqDp1yzCrfO+t9L+xIAnwAwCr89tj9Z3T3tzZ47LFJPrPm/iWS3H3CuG+O3b/CBuuvdbl1al5gfO2bnevyG5wHAFix7j6vu38vybWT/FOSr00YdnqS5ye5SXc/adR2ibEx4zvyJfOfr4yfQ0w7nxqfZ/y4rczlfAUAdj/znntcJslea+6fn+TbE8Z9Oxf+hNa9k1x6k3Nt9NxjVV8TALCzOF8BABauqvZO8uIkx6xpPjvJ3bv73Zsst8prO6u6XgUA7PqenuQLa+4fmOQeM8av6r2zq3w/MKyMAB8AsFSjTwq9zVjzqzZ6fHefn+S/xppvNWHop8fuX2mjcyRJVV06F95m++xc+D8mC5trwvhPbfJ4AGDJuvtT3f0r3X35JFdMcqMkt0xyZJLDuvv+3X1cklTVpZJccs3hpyf53wllV3UO8YUk5665v/9ojcuYCwDYdS363ONLkz5NffSJq19e8FzTzj1W8jUBADuL8xUAYNGqao8MH/Z4lzXN5yX5he5+/RZKrvLajve8AABJku4+N8NuwmvdfMYhqzqPWOX7gWFlBPgAgGU7NMnFx9qO32SN8fGTPmls/ET+alW1zybmOGrs/udH/zmZZHyua25inklzeTETAHZh3f3V7v5Qd7+ruz/f3WePDbnO2P3juvu8CaVWcg7R3eck+fxW56qqfZMcsZG5AIBd2ipfv1jVXF6TAQC2yvkKALAQow+y/ock917T3El+pbv/Yys1V3xtx/kKALDW+DnIZWeM3a7XV5b5fmBYGQE+AGDZ9p3QttkT4XPG7u85PqC7v5HkG2Pz3mgTc9xi7P5xM8aO9836xJELqaq9ktxkE3MBALu+O43df+2UcceN3f+x0bnBRq3kfCXDOdTac7ivd/c3N3E8ALBr+EQu/JrKVarq8E0cv6rXSg5PcpU1Teck+eSU4av8mgCAneW4sfvOVwCArfrLJL881vbb3X3snHWPG7u/rGs74/Ms83oVALD7GX+/7lrHjd1fyntnV/x+YFgZAT4AYNm+M6HtcpusMb7j3remjPuvsfu338Qc42NfNWPs+Dw3r6oDNzjPLZIcsOb+Z7r7Mxs8FgDYxVTVnknuuabpvCTPnTS2uz+VC39y2YHZ4IuZo3ONH19bLsmrZxwy3res8yIAYBfV3d9L8o6x5g2dE4w+Sf52Y82zzgnGzz1uN6qxEXcYu//W7j5t0sAVf00AwM7ifAUAmFtVPS7J74w1P7K7n7mA8iu5trPi61UAwK7vymP3T5wxdpXvnV3V+4FhZQT4AICl6u6zk3x9rPk2myxz27H741t2X+CVY/cfuJGLr1V1tSRHr2k6J8lrpo3v7q8k+fCapoOS3Gu9eUbGP4XtFRs8DgDYNf2/JFdcc/813f21GePHz1fGzw2m+fkM5xwX+MA687wmF971+JiqOmK9SUbnTg8Ya3a+AgC7r62ee9w6yVXX3D8xyftmjH9Pkm+vuX9EkmM2ONdmXytZ1dcEAOwszlcAgLlU1R8k+ZOx5id195MWNMUqr+2s6noVALALG51H3Hms+aPTxq/4vbMreT8wrJIAHwCwCm8eu//Q0XbY66qqo3PhT++aVO8Cr0/y1TX3r5LkgRuY5tFJ1p7Y/0d3f3edY/5p7P4fVdV+sw6oqqMyvJh5gfOTHLuB9QEAu6DRi36PW9N0TpI/Wuewf87waaQXuPfoHGHWPPtNqDt+LnIh3X1SkpevLZPhnGc9D8pwDnWBLyV50waOAwB2TS9Kcvqa+7eqqpkfrDS6+Pmosebndvf5044Z9R071vy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\n",
      "text/plain": [
       "<Figure size 3600x9000 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_observations(observations, mark_freq=[106.5, 245.0, 366.3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 3.5 Plot sky distribution <a name=\"plot_sky\"></a>\n",
    "\n",
    "The `alminer.plot_sky` function creates a plot of the distribution of targets on the sky.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_sky</code> function</summary>\n",
    "    \n",
    "* <u>Description</u>: Plot the distribution of the targets on the sky. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_sky**(_observations, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***  \n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 3.5.1: plot sky distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 3600x1500 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "alminer.plot_sky(observations)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "# 4. Create reports <a name=\"reports\"></a>\n",
    "\n",
    "This section introduces different ways to save query results:<br>\n",
    "\n",
    "* [4.1 - Export results as a table (*alminer.save_table*)](#save_table)<br>\n",
    "* [4.2 - Save overview plots for each target (*alminer.save_source_reports*)](#save_source_reports)<br>\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 4.1 Export results as a table <a name=\"save_table\"></a>\n",
    "\n",
    "The `alminer.save_table` function writes the provided DataFrame to a table in CSV format in the 'tables' folder within the current working directory. If the 'tables' folder does not exist, it will be created.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>save_table</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Write the DataFrame with the query results to a table in CSV format. The table will be saved in the 'tables' subdirectory within the current working directory. If the directory doesn't exist, it will be created. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**save_table**(_observations, filename=\"mytable\"_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    "     * **filename (str)** : Name of the table to be saved in the 'tables' subdirectory. <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 4.1.1: save query results as a table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "alminer.save_table(observations, filename=\"galaxy_chemistry\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 4.2 Save overview plots <a name=\"save_source_reports\"></a>\n",
    "\n",
    "The `alminer.save_source_reports` function creates overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions for each source in the provided DataFrame and saves them in PDF format in the 'reports' folder in the current working directory. If the 'reports' folder does not exist, it will be created. The reports are named after the target names. \n",
    "\n",
    "<u>Note</u>: Currently, the grouping is done based on ALMA target names, so the same source with a slighly different naming schemes will be treated as separate targets.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>save_source_reports</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions for each source in the provided DataFrame and save them in PDF format in the 'reports' subdirectory.\n",
    "    If the directory doesn't exist, it will be created. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**save_source_reports**(_observations, mark_freq='', z=0., mark_CO=False_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 4.2.1: save overview plots of each target with CO lines marked"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "Let's first narrow down our large query to a smaller subset to only a range of frequencies (Band 3) and angular resolutions < 0.5\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 8\n",
      "Number of observations = 21\n",
      "Number of unique subbands = 81\n",
      "Total number of subbands = 81\n",
      "8 target(s) with ALMA data = ['NGC7469', 'NGC1266', 'Arp220', 'ngc6240', 'IRAS_F16399-0937', 'n613', 'NGC4418', 'Cloverleaf']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "selected = observations[(observations[\"min_freq_GHz\"] > 80.0) & \n",
    "                        (observations[\"max_freq_GHz\"] < 115.0) & \n",
    "                        (observations[\"ang_res_arcsec\"] < 0.5)]\n",
    "alminer.summary(selected)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "Now we can create and save plots for each source, with CO and its isotopologues marked:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "alminer.save_source_reports(selected, mark_CO=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "# 5. Download data <a name=\"download\"></a>\n",
    "\n",
    "The `alminer.download_data` function allows the user to download the data from the archive directly to a location on the local disk. \n",
    "\n",
    "#### General notes about the download function:\n",
    " * The default download location is the 'data' subdirectory in the current working directory. The desired location can be changed by setting the *location* parameter to the desired path.\n",
    " * To check the amount of disk space needed, the *dryrun* parameter can be toggled to *True* which will only stage the data and write to the terminal how much space is required.\n",
    " * By default, tar files (including both raw and FITS data products) associated with uids in the provided DataFrame will be downloaded.\n",
    " * To download only the FITS data products, the *fitsonly* parameter can be toggled to *True*.\n",
    " * It is possible to provide a list of strings (to the *filename_must_include* parameter) that the user wants to be included in the filenames that are downloaded. This is useful to restrict the download further, for example, to data that have been primary beam corrected ('.pbcor') or that have the science target ('_sci' or the ALMA target name). The choice is largely dependent on the cycle and type of reduction that was performed, and data products that exist on the archive as a result.\n",
    " * A list of URLs (files) to be downloaded from the archive can be printed to the terminal by setting *print_urls=True*.\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>download_data</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Download ALMA data from the archive to a location on the local machine. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**download_data**(_observations, fitsonly=False, dryrun=False, print_urls=False, filename_must_include='', location='./data'_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **fitsonly (bool, optional, default: False)** : Download individual fits files only (*fitsonly=True*). This option will not download the raw data (e.g. 'asdm' files), weblogs, or README files. <br>\n",
    " * **dryrun (bool, optional, default: False)** : Allow the user to do a test run to check the size and number of files to download without actually downloading the data (*dryrun=True*). To download the data, set *dryrun=False*. <br>\n",
    " * **print_urls (bool, optional, default: False)** : Write the list of urls to be downloaded from the archive to the terminal. <br>\n",
    " * **filename_must_include (list of str, optional, default: '')** : A list of strings the user wants to be contained in the url filename. This is useful to restrict the download further, for example, to data that have been primary beam corrected ('.pbcor') or that have the science target or calibrators (by including their names). The choice is largely dependent on the cycle and type of reduction that was performed and data products that exist on the archive as a result. In most recent cycles, the science target can be filtered out with the flag '_sci' or its ALMA target name. <br>\n",
    " * **location (str, optional, default: './data')** : directory where the downloaded data should be placed. <br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "# This step is not necessary, but currently pyvo.dal.query contains \n",
    "# an Astropy deprecation warning that we prefer to ignore\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\") "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 5.1: download all data products (raw + products)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "This is a dryrun. To begin download, set dryrun=False.\n",
      "================================\n",
      "Download location = ./data\n",
      "Total number of Member OUSs to download = 21\n",
      "Selected Member OUSs: ['uid://A002/X6444ba/X17d', 'uid://A001/X121/X3d8', 'uid://A001/X121/X3d5', 'uid://A001/X121/X3d2', 'uid://A001/X121/X3cf', 'uid://A001/X2fe/Xcce', 'uid://A001/X2fe/Xcda', 'uid://A001/X2fe/Xcd6', 'uid://A001/X2fe/Xcde', 'uid://A001/X2fe/Xcd2', 'uid://A001/X2fe/X728', 'uid://A001/X2fe/X724', 'uid://A001/X2fe/X738', 'uid://A001/X2fe/X734', 'uid://A001/X5a4/X155', 'uid://A001/X87d/X1f5', 'uid://A001/X87d/X1fb', 'uid://A001/X87d/X207', 'uid://A001/X1290/X17', 'uid://A001/X1288/X6c2', 'uid://A001/X1288/X6be']\n",
      "Number of files to download = 114\n",
      "Needed disk space = 3991.3 GB\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "alminer.download_data(selected, fitsonly=False, dryrun=True, location='./data', print_urls=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 5.2: download only continuum FITS images for the science target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "This is a dryrun. To begin download, set dryrun=False.\n",
      "================================\n",
      "Download location = ./data\n",
      "Total number of Member OUSs to download = 21\n",
      "Selected Member OUSs: ['uid://A002/X6444ba/X17d', 'uid://A001/X121/X3d8', 'uid://A001/X121/X3d5', 'uid://A001/X121/X3d2', 'uid://A001/X121/X3cf', 'uid://A001/X2fe/Xcce', 'uid://A001/X2fe/Xcda', 'uid://A001/X2fe/Xcd6', 'uid://A001/X2fe/Xcde', 'uid://A001/X2fe/Xcd2', 'uid://A001/X2fe/X728', 'uid://A001/X2fe/X724', 'uid://A001/X2fe/X738', 'uid://A001/X2fe/X734', 'uid://A001/X5a4/X155', 'uid://A001/X87d/X1f5', 'uid://A001/X87d/X1fb', 'uid://A001/X87d/X207', 'uid://A001/X1290/X17', 'uid://A001/X1288/X6c2', 'uid://A001/X1288/X6be']\n",
      "Number of files to download = 19\n",
      "Needed disk space = 0.3 GB\n",
      "File URLs to download = https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_Xcda.Arp220_sci.spw25_27_29_31.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_Xcda.Arp220_sci.spw25_27_29_31.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_X728.ngc6240_sci.spw19_25_27_29.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_X728.ngc6240_sci.spw19_25_27_29.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_X724.ngc6240_sci.spw25_27_29_31.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_X724.ngc6240_sci.spw25_27_29_31.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_X738.IRAS_F16399-0937_sci.spw25_27_29_31.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X2fe_X738.IRAS_F16399-0937_sci.spw25_27_29_31.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X5a4_X155.n613_sci.spw25_27_29_31_33.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X5a4_X155.n613_sci.spw25_27_29_31_33.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X87d_X1f5.NGC4418_sci.spw25_27_29_31.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X87d_X1f5.NGC4418_sci.spw25_27_29_31.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X87d_X1fb.NGC4418_sci.spw25_27_29_31.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X87d_X1fb.NGC4418_sci.spw25_27_29_31.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X87d_X207.NGC4418_sci.spw25_27_29_31.cont.I.tt0.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X87d_X207.NGC4418_sci.spw25_27_29_31.cont.I.tt1.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X1290_X17.NGC7469_sci.spw19_21.cont.I.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X1288_X6c2.Cloverleaf_sci.spw22_24_26.cont.I.pbcor.fits\n",
      "https://almascience.eso.org/dataPortal/member.uid___A001_X1288_X6be.Cloverleaf_sci.spw22_24_26.cont.I.pbcor.fits\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "alminer.download_data(selected, fitsonly=True, dryrun=True, location='./data', \n",
    "                 filename_must_include=['_sci', '.pbcor', 'cont'], print_urls=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "# 6. Advanced query features <a name=\"advanced\"></a>\n",
    "\n",
    "This Section introduces:<br>\n",
    "\n",
    "* [6.1 - Create and run your own TAP query](#own_query)<br>\n",
    "* [6.2 - Convert results to ALminer format (*alminer.filter_results*)](#filter_results)<br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 6.1 Create and run your own TAP query <a name=\"create_query\"></a>\n",
    "\n",
    "You can use [Astronomical Data Query Language (ADQL)](https://www.ivoa.net/documents/ADQL/20180112/PR-ADQL-2.1-20180112.html) to create more complex queries relevant for your work. \n",
    "\n",
    "The ALminer querying functions provide an option to print the query string that was used to search the ALMA archive for the user by setting *print_query* parameter to *True*. \n",
    "\n",
    "Once you have created the query string of interest, you can run it using the `alminer.run_query` function.<br>\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>run_query</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Run the TAP query through PyVO service.<br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**run_query**(_query_str_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **query_str (str)** : ADQL query to send to the PyVO TAP service <br> \n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 6.1.1: Retrieve the ADQL query string used in ALminer query functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\n",
      "alminer.keysearch results \n",
      "================================\n",
      "Your query is: SELECT * FROM ivoa.obscore WHERE ((LOWER(proposal_abstract) LIKE '%planet%' AND LOWER(proposal_abstract) LIKE '%forming%' AND LOWER(proposal_abstract) LIKE '%disk%')) AND (LOWER(data_rights) LIKE '%public%') AND (LOWER(scan_intent) LIKE '%target%') ORDER BY proposal_id\n",
      "--------------------------------\n",
      "Number of projects = 116\n",
      "Number of observations = 1776\n",
      "Number of unique subbands = 974\n",
      "Total number of subbands = 8686\n",
      "Total number of targets with ALMA data = 1234\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "obs = alminer.keysearch({'proposal_abstract': ['planet forming disk']}, \n",
    "                   print_targets=False, print_query=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 6.1.2: Modify the query string and run the query\n",
    "\n",
    "In the previous example, we searched the ALMA archive for projects with the words 'planet' AND 'forming' AND 'disk' in their abstracts. But let's say you want to search for the *phrase* 'planet forming disk' rather than the words individually. \n",
    "\n",
    "You can modify the query string accordingly:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "query_str = \"SELECT * FROM ivoa.obscore WHERE ((LOWER(proposal_abstract) LIKE '%planet forming disk%')) AND (LOWER(data_rights) LIKE '%public%') AND (LOWER(scan_intent) LIKE '%target%') ORDER BY proposal_id\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "And run the query"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "outputs": [],
   "source": [
    "myquery = alminer.run_query(query_str)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "## 6.2 Convert your own query results into ALminer format <a name=\"filter_results\"></a>\n",
    "\n",
    "To make use of other `alminer` functions, the resulting DataFrame returned from running your query has to be converted to `alminer` format where a few useful columns are added to the DataFrame. This can be done through the `alminer.filter_results` function. <br>\n",
    " <br>\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>filter_results</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Add a few new useful columns to the pandas.DataFrame with the query results from the PyVO TAP service and return the full query DataFrame and optionally a summary of the results. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**filter_results**(_TAP_df, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **TAP_df (pandas.DataFrame)** : This is likely the output of `run_query` function. <br> \n",
    " * **print_targets (bool, optional)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.<br>\n",
    "***\n",
    "</details>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "### Example 6.2.1: Convert query results to ALminer format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "deletable": false,
    "editable": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--------------------------------\n",
      "Number of projects = 3\n",
      "Number of observations = 6\n",
      "Number of unique subbands = 13\n",
      "Total number of subbands = 28\n",
      "6 target(s) with ALMA data = ['Sz_91', 'AA_Tau', 'L1448-mm', 'HH211', 'B1-c', 'B5-IRS1']\n",
      "--------------------------------\n"
     ]
    }
   ],
   "source": [
    "myquery_obs = alminer.filter_results(myquery)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "Now you can use all the analysis and plotting routines presented before on these observations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": false,
    "editable": false
   },
   "source": [
    "***\n",
    "\n",
    "# 7. Glossary of functions <a name=\"glossery\"></a>\n",
    "\n",
    "### Query Functions\n",
    "\n",
    "<br>\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>catalog</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query the ALMA archive for a list of coordinates or a catalog of sources based on their coordinates. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**catalog**(_target_df, search_radius=1., point=True, public=True, published=None, print_query=False, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **target_df (pandas.DataFrame)** : DataFrame with source names and coordinates; it must have at least the following three columns: \"*Name*\", \"*RAJ2000*\", \"*DEJ2000*\". \"*Name*\" describes the target name (can be numbers or dummy names), \"*RAJ2000*\" is the right ascension in degrees (ICRS), \"*DEJ2000*\" is the declination in degrees (ICRS) <br>\n",
    " * **search_radius (float, optional, default: 1 arcmin)** : Search radius (in arcmin) around the source coordinates. <br>\n",
    " * **point (bool, optional, default: True)** : Search whether the phase center of the observations is contained within the search_radius (*point=True*) or whether any part of the observed region overlaps with the cone extending the search_radius (*point=False*). Note that *point=True* is much faster than *point=False* but the latter should be used if one is interested in searching for mosaics.<br>\n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>  \n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>conesearch</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query the ALMA archive for a given position and radius around it.<br>\n",
    "    <br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**conesearch**(_ra, dec, search_radius=1., point=True, public=True, published=None, print_targets=True, print_query=False_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **ra (float)** : Right ascension in degrees (ICRS). <br>\n",
    " * **dec (float)** : Declination in degrees (ICRS). <br>\n",
    " * **search_radius (float, optional, default: 1 arcmin)** : Search radius (in arcmin) around the source coordinates. <br>\n",
    " * **point (bool, optional, default: True)** : Search whether the phase center of the observations is contained within the search_radius (*point=True*) or whether any part of the observed region overlaps with the cone extending the search_radius (*point=False*). Note that *point=True* is much faster than *point=False* but the latter should be used if one is interested in searching for mosaics.<br>\n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>  \n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>keysearch</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Query the ALMA archive for any (string-type) keywords defined in ALMA TAP system. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**keysearch**(_search_dict, public=True, published=None, print_query=False, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **search_dict (dict[str, list of str])** : Dictionary of keywords in the ALMA archive and their values. Values must be formatted as a list of strings. For a list of valid keywords see [table](#TAP_table) below. <br> \n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>target</code> function</summary>\n",
    "    \n",
    "* <u>Description</u>: Query targets by name. <br>\n",
    " * This is done by using the astropy SESAME resolver to get the target's coordinates and then the ALMA archive is queried for those coordinates and a search_radius around them. The SESAME resolver searches multiple databases (Simbad, NED, VizieR) to parse names commonly found throughout literature and returns their coordinates. If the target is not resolved in any of these databases, consider using the `keysearch` function and query the archive using the 'target_name' keyword (e.g. `keysearch({'target_name': sources})`).<br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**target**(_sources, search_radius=1., point=True, public=True, published=None, print_query=False, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **sources (list of str)** : list of sources by name. (IMPORTANT: sources names must be identified by at least one of Simbad, NED, or Vizier) <br> \n",
    " * **search_radius (float, optional, default: 1 arcmin)** : Search radius (in arcmin) around the source coordinates. <br>\n",
    " * **point (bool, optional, default: True)** : Search whether the phase center of the observations is contained within the search_radius (*point=True*) or whether any part of the observed region overlaps with the cone extending the search_radius (*point=False*). Note that *point=True* is much faster than *point=False* but the latter should be used if one is interested in searching for mosaics.<br>\n",
    " * **public (bool, optional, default: True)** : Search for public data (*public=True*), proprietary data (*public=False*), or both public and proprietary data (*public=None*). <br>\n",
    " * **published (bool, optional, default: None)** : Search for published data only (*published=True*), unpublished data only (*published=False*), or both published and unpublished data (*published=None*). <br>\n",
    " * **print_query (bool, optional, default: False)** : Print the ADQL TAP query to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.\n",
    "***\n",
    "</details>\n",
    "\n",
    "\n",
    "### Analysis Functions\n",
    "\n",
    "<br>\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>CO_lines</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Determine how many CO, <sup>13</sup>CO, and C<sup>18</sup>O lines were observed in the provided query DataFrame. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**CO_lines**(_observations, z=0., print_summary=True, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequency given in 'line_freq' parameter should be shifted. <br>\n",
    " * **print_summary (bool, optional, default: True)** : Print a summary of the observations to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " * **pandas.DataFrame** containing all observations of CO, <sup>13</sup>CO, and C<sup>18</sup>O\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>explore</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Control how much of the pandas.DataFrame with the query results is presented in the displayed table. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**explore**(_observations, allcols=False, allrows=False_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **allcols (bool, optional, default: False)** : Show all 81 columns (*allcols=True*), or the first 18 columns (*allcols=False*). <br>\n",
    " * **allrows (bool, optional, default: False)** : Show all rows in the DataFrame (*allrows=True*), or just a summary (*allrows=False*). <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results displayed to the user interface as specified by the user.\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>get_info</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Print the description and units of a given column in the query results DataFrame.<br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**get_info**(_column_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **column (str)** : A column in the pandas.DataFrame query table.<br> \n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>line_coverage</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Determine how many observations were observed at a given frequency (+redshift). <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**line_coverage**(_observations, line_freq, z=0., line_name='', print_summary=True, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations** : pandas.DataFrame (This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions.) <br> \n",
    " * **line_freq (float64)** : Frequency of the line of interest in GHz. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequency given in 'line_freq' parameter should be shifted. <br>\n",
    " * **line_name (str, optional, default: '')** : Name of the line specified in 'line_freq'. <br>\n",
    " * **print_summary (bool, optional, default: True)** : Print a summary of the observations to the terminal. <br>\n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "* <u>Returns</u>:<br>\n",
    " * **pandas.DataFrame** containing all observations of line of interest.\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>summary</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Print a summary of the observations. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**summary**(_observations, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **print_targets (bool, optional, default: True)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    " <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "### Plotting Functions\n",
    "\n",
    "<br>\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_bands</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview and detailed plots of observed frequencies in each band. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_bands**(_observations, mark_freq='', z=0., mark_CO=False, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_line_overview</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions, highlighting the observations of a give (redshifted) frequency with hatches on the bar plots. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_line_overview**(_observations, line_freq, z=0., line_name='', showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **line_freq (float64)** : Frequency of the line of interest in GHz. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequency given in 'line_freq' parameter should be shifted. <br>\n",
    " * **line_name (str, optional, default: '')** : Name of the line specified in 'line_freq'. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***   \n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_observations</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create detailed plots of observations in each band. The x-axis displays the observation number 'Obs' column in the input DataFrame. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_observations**(_observations, mark_freq='', z=0., mark_CO=False, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_overview</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_overview**(_observations, mark_freq='', z=0., mark_CO=False, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>plot_sky</code> function</summary>\n",
    "    \n",
    "* <u>Description</u>: Plot the distribution of the targets on the sky. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**plot_sky**(_observations, showfig=True, savefig=None_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **showfig (bool, optional, default: True)** : Display the plot (*showfig=True*) or not (*showfig=False*). <br>\n",
    " * **savefig (str, optional, default: None)** : Filename (without an extension) for the plot to be saved as. Default file extension is PDF. Figure is saved in a subdirectory called 'reports' within the current working directory. If the directory doesn't exist, it will be created. Default quality is dpi=300. <br>\n",
    " <br>\n",
    "***  \n",
    "</details>\n",
    "\n",
    "### Writing Files & Plots\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>save_source_reports</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Create overview plots of observed frequencies, angular resolution, LAS, frequency and velocity resolutions for each source in the provided DataFrame and save them in PDF format in the 'reports' subdirectory.\n",
    "    If the directory doesn't exist, it will be created. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**save_source_reports**(_observations, mark_freq='', z=0., mark_CO=False_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **mark_freq (list of float64, optional, default: '')** : A list of frequencies to mark on the plot with dashed lines. <br>\n",
    " * **z (float64, optional, default: 0)** : Redshift by which the frequencies given in 'mark_freq' and 'mark_CO' parameters should be shifted. Currently only one redshift can be given for all targets. <br>\n",
    " * **mark_CO (bool, optional, default: False)** : mark CO, <sup>13</sup>CO, and C<sup>18</sup>O frequencies on the plot with dashed lines. <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>save_table</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Write the DataFrame with the query results to a table in CSV format. The table will be saved in the 'tables' subdirectory within the current working directory. If the directory doesn't exist, it will be created. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**save_table**(_observations, filename=\"mytable\"_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations** : pandas.DataFrame (This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions.) <br> \n",
    "     * **filename (str)** : Name of the table to be saved in the 'tables' subdirectory. <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "### Downloading ALMA Data\n",
    "\n",
    "<br>\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>download_data</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Download ALMA data from the archive to a location on the local machine. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**download_data**(_observations, fitsonly=False, dryrun=False, print_urls=False, filename_must_include='', location='./data'_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **observations (pandas.DataFrame)** : This is likely the output of e.g. `conesearch`, `target`, `catalog`, and `keysearch` functions. <br> \n",
    " * **fitsonly (bool, optional, default: False)** : Download individual fits files only (*fitsonly=True*). This option will not download the raw data (e.g. 'asdm' files), weblogs, or README files. <br>\n",
    " * **dryrun (bool, optional, default: False)** : Allow the user to do a test run to check the size and number of files to download without actually downloading the data (*dryrun=True*). To download the data, set *dryrun=False*. <br>\n",
    " * **print_urls (bool, optional, default: False)** : Write the list of urls to be downloaded from the archive to the terminal. <br>\n",
    " * **filename_must_include (list of str, optional, default: '')** : A list of strings the user wants to be contained in the url filename. This is useful to restrict the download further, for example, to data that have been primary beam corrected ('.pbcor') or that have the science target or calibrators (by including their names). The choice is largely dependent on the cycle and type of reduction that was performed and data products that exist on the archive as a result. In most recent cycles, the science target can be filtered out with the flag '_sci' or its ALMA target name. <br>\n",
    " * **location (str, optional, default: './data')** : directory where the downloaded data should be placed. <br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "\n",
    "### Advanced Query Functions\n",
    "\n",
    "<br>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>filter_results</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Add a few new useful columns to the pandas.DataFrame with the query results from the PyVO TAP service and return the full query DataFrame and optionally a summary of the results. <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**filter_results**(_TAP_df, print_targets=True_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **TAP_df (pandas.DataFrame)** : This is likely the output of `run_query` function. <br> \n",
    " * **print_targets (bool, optional)** : Print a list of targets with ALMA data (ALMA source names) to the terminal. <br>\n",
    "* <u>Returns</u>:<br>\n",
    " *  **pandas.DataFrame** containing the query results.<br>\n",
    "***\n",
    "</details>\n",
    "\n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code>run_query</code> function</summary>\n",
    "\n",
    "* <u>Description</u>: Run the TAP query through PyVO service.<br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.**run_query**(_query_str_)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **query_str (str)** : ADQL query to send to the PyVO TAP service <br> \n",
    "***\n",
    "</details>\n",
    "\n",
    "<!-- \n",
    "<details>\n",
    "<summary style=\"display:list-item\">Details of <code></code> function</summary>\n",
    "\n",
    "* <u>Description</u>: <br>\n",
    "<br>\n",
    "* <u>Command</u>:<br>\n",
    " * alminer.****(__)<br>\n",
    "<br>\n",
    "* <u>Parameters</u>:<br>\n",
    " * **** :  <br> \n",
    " * **** :  <br>\n",
    " * **** :  <br>\n",
    " * **** :  <br>\n",
    "***\n",
    "</details> -->"
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    "***\n",
    "\n",
    "# 8. Workstation <a name=\"workstation\"></a>\n",
    "\n",
    "You can create your own examples below. Happy mining 😉"
   ]
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