nb4. Query by scientific category

import numpy as np
from astropy.table import Table
import pyvo
import sys
import matplotlib.pyplot as plt
import pandas as pd
import sklearn.cluster

service = pyvo.dal.TAPService("https://almascience.eso.org/tap")      # for the EU ALMA TAP service

# service = pyvo.dal.TAPService("https://almascience.nao.ac.jp/tap")  # for the EA ALMA TAP service
# service = pyvo.dal.TAPService("https://almascience.nrao.edu/tap")   # for the NA ALMA TAP service

def query_scientific_category(service, scientific_category):
    """Query for all science observations of a given scientific category. To reduce the memory
       requirements, rather than using *, it is often useful to select the columns of interest.
    
       service               pyvo TAPService instance
       scientific_category   one of the categories shown at the top of this notebook
       
       returns               pandas table    
    """
    
    query = f"""  
            SELECT target_name, science_keyword, s_ra, s_dec, band_list
            FROM ivoa.obscore  
            WHERE scientific_category = '{scientific_category}'  
            AND science_observation = 'T'  
            GROUP BY target_name, science_keyword, s_ra, s_dec, band_list
            """

    return service.search(query).to_table().to_pandas()

def query_science_keyword(service, science_keyword):
    """ALMA has a long list of scientific keywords in the Observing Tool from whch PIs need to select
       one or two in their proposals. This query returns all science observations for a given science 
       keyword (or part of it).
       
       service               pyvo TAPService instance
       science_keyword       one of the science keywords of ALMA or a substring
       
       returns               pandas table       
       """
    
    query = f"""  
            SELECT s_ra, s_dec, target_name, band_list, t_exptime
            FROM ivoa.obscore  
            WHERE science_observation = 'T'  
            AND science_keyword like '%{science_keyword}%'  
            GROUP BY s_ra, s_dec, target_name, band_list, t_exptime
            """
    
    return service.search(query).to_table().to_pandas()

def query_science_keyword_datatype(service, science_keyword, datatype):
    """This function shows how to combine several constraints. Here the science keyword as well 
       as the datatype and science_observations
    
       service               pyvo TAPService instance
       science_keyword       one of the science keywords of ALMA or a substring
       datatype              "image" or "cube"
       
       returns               pandas table    
    """
    
    query = f"""   
            SELECT s_ra, s_dec, target_name, band_list, t_exptime
            FROM ivoa.obscore  
            WHERE science_keyword like '%{science_keyword}%'  
            AND science_observation = 'T'  
            AND dataproduct_type = '{datatype}'   
            GROUP BY s_ra, s_dec, target_name, band_list, t_exptime
            """
    
    return service.search(query).to_table().to_pandas()

output_agn = query_scientific_category(service, 'Active galaxies')

query = """
        SELECT s_ra, s_dec, target_name, t_exptime
        FROM ivoa.obscore
        WHERE proposal_abstract like '%SMG%'
        OR proposal_abstract like '%ub-mm galax%'
        AND science_observation = 'T'
        GROUP BY s_ra, s_dec, target_name, t_exptime
        """           

output_smgs_abstract = service.search(query).to_table().to_pandas()