How to use pandasticsearch - 10 common examples

def test_select_from_dict(self):
        select = Select.from_dict(create_hits())
        print(select)
        print(repr(select))

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

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 test_getitem(self):
        df = create_df_from_es()
        self.assertTrue(isinstance(df['a'], Column))
        self.assertTrue(isinstance(df['b'], Column))

        expr = df['a'] > 2
        self.assertTrue(isinstance(expr, BooleanFilter))
        self.assertTrue(isinstance(df[expr], DataFrame))
        self.assertEqual(df[expr]._filter.build(), {'range': {'a': {'gt': 2}}})

def test_agg_date_histogram(self):
        agg = Agg()
        agg._result_dict = {
            'took': 3,
            'aggregations': {
                'my_date_histogram': {
                    'buckets': [
                        {
                            'doc_count': 1,
                            'key': 1480392360000,
                            'key_as_string': '2016-11-29T04:06:00.000Z',
                            'f1': {'value': 0.1},
                        },
                        {
                            'doc_count': 1,
                            'key': 1480392420000,
                            'key_as_string': '2016-11-29T04:07:00.000Z',
                            'f1': {'value': 0.2},

def test_agg_buckets(self):
        agg = Agg()
        agg._result_dict = {
            'took': 1,
            'aggregations': {
                'agg_key': {
                    'buckets': [
                        {
                            'key': 'a',
                            'f1': {'value': 100},
                            'f2': {'value': 1},
                            "doc_count": 12
                        },
                        {
                            'key': 'b',
                            'f1': {'value': 200},
                            'f2': {'value': 2},
                            "doc_count": 13

def test_agg_nested_buckets(self):
        agg = Agg()
        agg._result_dict = {
            'aggregations': {
                'agg_key1': {
                    'buckets': [
                        {
                            'key': 'a',
                            'agg_key2': {
                                'buckets': [
                                    {
                                        'key': 'x',
                                        'f1': {'value': 100},
                                        'f2': {'value': 1},
                                        "doc_count": 934422
                                    },
                                    {
                                        'key': 'y',

def test_agg_buckets(self):
        agg = Agg()
        agg._result_dict = {
            'aggregations': {
                'agg_key': {
                    'buckets': [
                        {
                            'key': 'a',
                            'f1': {'value': 100},
                            'f2': {'value': 1},
                            "doc_count": 934422
                        },
                        {
                            'key': 'b',
                            'f1': {'value': 200},
                            'f2': {'value': 2},
                            "doc_count": 934422
                        },

def test_agg_nested_buckets(self):
        agg = Agg()
        agg._result_dict = {
            'took': 1,
            'aggregations': {
                'agg_key1': {
                    'buckets': [
                        {
                            'key': 'a',
                            'agg_key2': {
                                'buckets': [
                                    {
                                        'key': 'x',
                                        'f1': {'value': 100},
                                        'f2': {'value': 1},
                                        "doc_count": 11
                                    },
                                    {