def test_time_series_dim(self):
result = CSV(mock_dataset.fields.wins) \
.transform(dimx1_date_df, [mock_dataset.fields.timestamp], [])
expected = dimx1_date_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp']
expected.columns = ['Wins']
expected = expected.applymap(format_float_raw)
self.assertEqual(expected.to_csv(**csv_options), result)
def test_dimx1_date(self):
result = Pandas(mock_dataset.fields.wins).transform(dimx1_date_df, [mock_dataset.fields.timestamp], [])
expected = dimx1_date_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_sort_value_greater_than_number_of_columns_is_ignored(self):
result = Pandas(mock_dataset.fields.wins, sort=[5]) \
.transform(dimx1_date_df, mock_dataset, [mock_dataset.fields.timestamp], [])
expected = dimx1_date_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
expected = expected.applymap(_format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_metricx2_sort_value_desc(self):
result = Pandas(mock_dataset.fields.wins, sort=[1], ascending=[False]) \
.transform(dimx1_date_df, mock_dataset, [mock_dataset.fields.timestamp], [])
expected = dimx1_date_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
expected = expected.sort_values(['Wins'], ascending=False)
expected = expected.applymap(_format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_metricx2_sort_index_and_value(self):
result = Pandas(mock_dataset.fields.wins, sort=[-0, 1]).transform(
dimx1_date_df, [mock_dataset.fields.timestamp], []
)
expected = dimx1_date_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
expected = (
expected.reset_index().sort_values(['Timestamp', 'Wins'], ascending=[True, False]).set_index('Timestamp')
)
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_metric_format(self):
import copy
votes = copy.copy(mock_dataset.fields.votes)
votes.prefix = '$'
votes.suffix = '€'
votes.precision = 2
# divide the data frame by 3 to get a repeating decimal so we can check precision
result = Pandas(votes).transform(dimx1_date_df / 3, [mock_dataset.fields.timestamp], [])
f_votes = f('votes')
expected = dimx1_date_df.copy()[[f_votes]]
expected[f_votes] = ['${0:,.2f}€'.format(x) for x in expected[f_votes] / 3]
expected.index.names = ['Timestamp']
expected.columns = ['Votes']
expected.columns.name = 'Metrics'
pandas.testing.assert_frame_equal(expected, result)
