def test_multi_dimx2_date_str(self):
query_dimensions = [mock_dataset.fields.timestamp, mock_dataset.fields.political_party]
result = CSV(mock_dataset.fields.wins) \
.transform(dimx2_date_str_df, mock_dataset, query_dimensions, [])
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp', 'Party']
expected.columns = ['Wins']
self.assertEqual(expected.to_csv(**csv_options), result)
def test_dimx2_date_str(self):
dimensions = [mock_dataset.fields.timestamp, mock_dataset.fields.political_party]
result = Pandas(mock_dataset.fields.wins).transform(dimx2_date_str_df, dimensions, [])
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp', 'Party']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_pivoted_multi_dimx2_date_str(self):
result = CSV(mock_dataset.fields.wins, pivot=[mock_dataset.fields.political_party]) \
.transform(dimx2_date_str_df,
[mock_dataset.fields.timestamp, mock_dataset.fields.political_party], [])
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected = expected.unstack(level=[1])
expected.index.names = ['Timestamp']
expected.columns = ['Democrat', 'Independent', 'Republican']
expected = expected.applymap(format_float_raw)
self.assertEqual(expected.to_csv(**csv_options), result)
def test_pivoted_dimx2_date_str(self):
result = Pandas(mock_dataset.fields.wins, pivot=[mock_dataset.fields.political_party]) \
.transform(dimx2_date_str_df, mock_dataset,
[mock_dataset.fields.timestamp, mock_dataset.fields.political_party], [])
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected = expected.unstack(level=[1])
expected.index.names = ['Timestamp']
expected.columns = ['Democrat', 'Independent', 'Republican']
expected.columns.names = ['Party']
expected = expected.applymap(_format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_hidden_dimx2_date_str(self):
dimensions = [
mock_dataset.fields.timestamp, mock_dataset.fields.political_party
]
result = CSV(mock_dataset.fields.wins, hide=[mock_dataset.fields.political_party]) \
.transform(dimx2_date_str_df, dimensions, [])
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected.reset_index('$political_party', inplace=True, drop=True)
expected.index.names = ['Timestamp']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
self.assertEqual(expected.to_csv(**csv_options), result)
def test_pivoted_dimx2_date_str_sort_index_level_1_desc(self):
result = Pandas(mock_dataset.fields.wins, sort=[1], ascending=[False]).transform(
dimx2_date_str_df, [mock_dataset.fields.timestamp, mock_dataset.fields.political_party], []
)
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected.index.names = ['Timestamp', 'Party']
expected.columns = ['Wins']
expected.columns.name = 'Metrics'
expected = expected.reset_index().sort_values(['Party'], ascending=[False]).set_index(['Timestamp', 'Party'])
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_fetch_only_dimx2_date_str(self):
dimensions = [mock_dataset.fields.timestamp, mock_dataset.fields.political_party]
dimensions[1].fetch_only = True
result = Pandas(mock_dataset.fields.wins).transform(dimx2_date_str_df, dimensions, [])
dimensions[1].fetch_only = False
expected = dimx2_date_str_df.copy()[[f('wins')]]
expected.reset_index('$political_party', inplace=True, drop=True)
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_use_pandas_default_for_ascending_when_arg_empty_list(self):
result = Pandas(
mock_dataset.fields.votes, pivot=[mock_dataset.fields.political_party], sort=[0, 2], ascending=[]
).transform(dimx2_date_str_df, [mock_dataset.fields.timestamp, mock_dataset.fields.political_party], [])
expected = dimx2_date_str_df.copy()[[f('votes')]]
expected = expected.unstack(level=[1])
expected.index.names = ['Timestamp']
expected.columns = ['Democrat', 'Independent', 'Republican']
expected.columns.names = ['Party']
expected = expected.reset_index().sort_values(['Timestamp', 'Democrat'], ascending=None).set_index('Timestamp')
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_pivoted_dimx2_date_str_with_sort_second_metric_desc(self):
result = Pandas(
mock_dataset.fields.votes, pivot=[mock_dataset.fields.political_party], sort=1, ascending=False
).transform(dimx2_date_str_df, [mock_dataset.fields.timestamp, mock_dataset.fields.political_party], [])
expected = dimx2_date_str_df.copy()[[f('votes')]]
expected = expected.unstack(level=[1])
expected.index.names = ['Timestamp']
expected.columns = ['Democrat', 'Independent', 'Republican']
expected.columns.names = ['Party']
expected = expected.reset_index().sort_values(['Democrat'], ascending=False).set_index('Timestamp')
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
def test_hide_data_frame_indexes_hides_found_aliases(self):
widget = Widget()
base_df = dimx2_date_str_df.copy()[[alias_selector('wins'), alias_selector('votes')]]
result = base_df.copy()
widget.hide_data_frame_indexes(
result,
[
alias_selector(mock_dataset.fields.political_party.alias),
alias_selector(mock_dataset.fields.votes.alias),
alias_selector('unknown'),
],
)
expected = base_df.copy()
expected.reset_index('$political_party', inplace=True, drop=True)
del expected['$votes']
pd.testing.assert_frame_equal(expected, result)
def test_pivoted_dimx1_metricx2(self):
result = Pandas(
mock_dataset.fields.votes, mock_dataset.fields.wins, pivot=[mock_dataset.fields.timestamp]
).transform(dimx2_date_str_df, [mock_dataset.fields.timestamp, mock_dataset.fields.political_party], [])
expected = dimx2_date_str_df.copy()[[f('votes'), f('wins')]]
expected = expected.unstack(level=0)
expected.index.names = ['Party']
expected.columns = pd.MultiIndex.from_product(
[
['Votes', 'Wins'],
pd.DatetimeIndex(['1996-01-01', '2000-01-01', '2004-01-01', '2008-01-01', '2012-01-01', '2016-01-01']),
],
names=['Metrics', 'Timestamp'],
)
expected = expected.applymap(format_float)
pandas.testing.assert_frame_equal(expected, result)
