How to use the pandasticsearch.queries.Select function in pandasticsearch

def test_select_explain_result(self):
        select = Select()
        select._result_dict = create_hits()
        select.explain_result()
        print(select)
        print(repr(select))

        self.assertIsNotNone(select.result)
        self.assertEqual(len(select), 3)

def test_collect(self):
        query = Select()
        query._values = [{'a': 1}, {'a': 2}]
        self.assertEqual(query.collect(), [Row(a=1), Row(a=2)])

def test_select_explain_result(self):
        select = Select()
        select._result_dict = create_hits()
        select.explain_result()
        print(select)
        print(repr(select))

        self.assertIsNotNone(select.result)
        self.assertEqual(len(select), 3)

def __init__(self):
        super(Select, self).__init__()

def from_dict(d):
        query = Select()
        query.explain_result(d)
        return query

def _execute(self):
        if self._client is None:
            raise _unbound_index_err

        res_dict = self._client.post(data=self._build_query())
        if self._aggregation is None and self._groupby is None:
            query = Select()
            query.explain_result(res_dict)
        else:
            query = Agg.from_dict(res_dict)
        return query

def explain_result(self, result=None):
        super(Select, self).explain_result(result)
        rows = []
        for hit in self._result_dict['hits']['hits']:
            row = {}
            for k in hit.keys():
                if k == '_source':
                    solved_fields = self.resolve_fields(hit['_source'])
                    row.update(solved_fields)
                elif k.startswith('_'):
                    row[k] = hit[k]
            rows.append(row)
        self._values = rows

def result_as_tabular(self, cols, n, truncate=20):
        b = six.StringIO()
        widths = []
        tavnit = '|'
        separator = '+'

        for col in cols:
            maxlen = len(col)
            for kv in self.result[:n]:
                if col in kv:
                    s = Select._stringfy_value(kv[col])
                else:
                    s = '(NULL)'
                if len(s) > maxlen:
                    maxlen = len(s)
            widths.append(min(maxlen, truncate))

        for w in widths:
            tavnit += ' %-' + '%ss |' % (w,)
            separator += '-' * w + '--+'

        b.write(separator + '\n')
        b.write(tavnit % tuple(cols) + '\n')
        b.write(separator + '\n')
        for kv in self.result[:n]:
            row = []
            for col in cols: