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131 lines
4.9 KiB
Python
131 lines
4.9 KiB
Python
# Licensed to Elasticsearch B.V. under one or more contributor
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# license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright
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# ownership. Elasticsearch B.V. licenses this file to you under
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# the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# File called _pytest for PyCharm compatability
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import numpy as np
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import pytest
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from pandas.testing import assert_frame_equal, assert_series_equal
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from eland.tests.common import TestData
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class TestDataFrameAggs(TestData):
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def test_basic_aggs(self):
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pd_flights = self.pd_flights()
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ed_flights = self.ed_flights()
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pd_sum_min = pd_flights.select_dtypes(include=[np.number]).agg(["sum", "min"])
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ed_sum_min = ed_flights.select_dtypes(include=[np.number]).agg(
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["sum", "min"], numeric_only=True
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)
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# Eland returns all float values for all metric aggs, pandas can return int
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# TODO - investigate this more
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pd_sum_min = pd_sum_min.astype("float64")
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assert_frame_equal(pd_sum_min, ed_sum_min, check_exact=False)
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pd_sum_min_std = pd_flights.select_dtypes(include=[np.number]).agg(
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["sum", "min", "std"]
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)
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ed_sum_min_std = ed_flights.select_dtypes(include=[np.number]).agg(
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["sum", "min", "std"], numeric_only=True
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)
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print(pd_sum_min_std.dtypes)
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print(ed_sum_min_std.dtypes)
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assert_frame_equal(pd_sum_min_std, ed_sum_min_std, check_exact=False, rtol=True)
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def test_terms_aggs(self):
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pd_flights = self.pd_flights()
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ed_flights = self.ed_flights()
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pd_sum_min = pd_flights.select_dtypes(include=[np.number]).agg(["sum", "min"])
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ed_sum_min = ed_flights.select_dtypes(include=[np.number]).agg(
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["sum", "min"], numeric_only=True
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)
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# Eland returns all float values for all metric aggs, pandas can return int
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# TODO - investigate this more
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pd_sum_min = pd_sum_min.astype("float64")
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assert_frame_equal(pd_sum_min, ed_sum_min, check_exact=False)
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pd_sum_min_std = pd_flights.select_dtypes(include=[np.number]).agg(
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["sum", "min", "std"]
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)
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ed_sum_min_std = ed_flights.select_dtypes(include=[np.number]).agg(
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["sum", "min", "std"], numeric_only=True
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)
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print(pd_sum_min_std.dtypes)
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print(ed_sum_min_std.dtypes)
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assert_frame_equal(pd_sum_min_std, ed_sum_min_std, check_exact=False, rtol=True)
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def test_aggs_median_var(self):
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pd_ecommerce = self.pd_ecommerce()
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ed_ecommerce = self.ed_ecommerce()
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pd_aggs = pd_ecommerce[
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["taxful_total_price", "taxless_total_price", "total_quantity"]
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].agg(["median", "var"])
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ed_aggs = ed_ecommerce[
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["taxful_total_price", "taxless_total_price", "total_quantity"]
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].agg(["median", "var"], numeric_only=True)
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print(pd_aggs, pd_aggs.dtypes)
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print(ed_aggs, ed_aggs.dtypes)
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# Eland returns all float values for all metric aggs, pandas can return int
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# TODO - investigate this more
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pd_aggs = pd_aggs.astype("float64")
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assert_frame_equal(pd_aggs, ed_aggs, check_exact=False, check_less_precise=2)
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# If Aggregate is given a string then series is returned.
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@pytest.mark.parametrize("agg", ["mean", "min", "max"])
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def test_terms_aggs_series(self, agg):
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pd_flights = self.pd_flights()
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ed_flights = self.ed_flights()
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pd_sum_min_std = pd_flights.select_dtypes(include=[np.number]).agg(agg)
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ed_sum_min_std = ed_flights.select_dtypes(include=[np.number]).agg(
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agg, numeric_only=True
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)
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assert_series_equal(pd_sum_min_std, ed_sum_min_std)
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def test_terms_aggs_series_with_single_list_agg(self):
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# aggs list with single agg should return dataframe.
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pd_flights = self.pd_flights()
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ed_flights = self.ed_flights()
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pd_sum_min = pd_flights.select_dtypes(include=[np.number]).agg(["mean"])
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ed_sum_min = ed_flights.select_dtypes(include=[np.number]).agg(
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["mean"], numeric_only=True
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)
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assert_frame_equal(pd_sum_min, ed_sum_min)
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# If Wrong Aggregate value is given.
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def test_terms_wrongaggs(self):
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ed_flights = self.ed_flights()[["FlightDelayMin"]]
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match = "('abc', ' not currently implemented')"
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with pytest.raises(NotImplementedError, match=match):
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ed_flights.select_dtypes(include=[np.number]).agg("abc")
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