Example #1
0
    def test_arealist_query(self):

        # Test case AREALIST1
        area_level = "FRAC"
        variables = "PERSONA.CONDACT"

        area_filter = {"PROV": ["02", "03"]}
        universe_filter = "1 = 1"
        title = "El titulo"

        query = pyredatam.arealist_query(area_level, variables, area_filter,
                                         universe_filter, title)
        self.assertEqual(query, queries.AREALIST1.strip())

        # Test case AREALIST2
        variables = ["PERSONA.CONDACT"]
        query = pyredatam.arealist_query(area_level, variables)
        self.assertEqual(query, queries.AREALIST2.strip())

        # Test case AREALIST3
        area_filter = {"PROV": "02"}
        query = pyredatam.arealist_query(area_level, variables, area_filter)
        self.assertEqual(query, queries.AREALIST3.strip())
Example #2
0
def get_data(area_level, variable, universe_filter=None, redownload=False):
    path = get_data_path(area_level, variable, "censo", universe_filter)

    if not os.path.isfile(path) or redownload:
        query = pyredatam.arealist_query(area_level, variable, {"PROV": "02"}, universe_filter=universe_filter)

        df = cpv2010arg.make_arealist_query(query)
        if "Código" in df.columns:
            df = replace_index(df, AREAS_LENIDS[area_level])

        df.to_csv(path, encoding="utf-8")

    else:
        df = pd.read_csv(path, encoding="utf-8")
        if "Código" in df.columns:
            df = replace_index(df, AREAS_LENIDS[area_level])

    return df
Example #3
0
def get_data(area_level, variable, universe_filter=None, redownload=False):
    path = get_data_path(area_level, variable, "censo", universe_filter)

    if not os.path.isfile(path) or redownload:
        query = pyredatam.arealist_query(area_level, variable,
                                         {"PROV": "02"},
                                         universe_filter=universe_filter)

        df = cpv2010arg.make_arealist_query(query)
        if "Código" in df.columns:
            df = replace_index(df, AREAS_LENIDS[area_level])

        df.to_csv(path, encoding="utf-8")

    else:
        df = pd.read_csv(path, encoding="utf-8")
        if "Código" in df.columns:
            df = replace_index(df, AREAS_LENIDS[area_level])

    return df