def test_pivot_second_dimension_with_one_metric(self):
result = ReactTable(slicer.metrics.wins, pivot=[slicer.dimensions.state]) \
.transform(cont_uni_dim_df, slicer, [slicer.dimensions.timestamp, slicer.dimensions.state], [])
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{'Header': 'Texas', 'accessor': '1'},
{'Header': 'California', 'accessor': '2'}],
'data': [{
'$d$timestamp': {'raw': '1996-01-01'},
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}, {
'$d$timestamp': {'raw': '2000-01-01'},
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}, {
'$d$timestamp': {'raw': '2004-01-01'},
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}, {
'$d$timestamp': {'raw': '2008-01-01'},
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}, {
'$d$timestamp': {'raw': '2012-01-01'},
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}, {
'$d$timestamp': {'raw': '2016-01-01'},
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}]
}, result)
def test_pivot_single_dimension_as_rows_single_metric_and_transpose_set_to_true(self):
result = ReactTable(slicer.metrics.wins, pivot=[slicer.dimensions.candidate], transpose=True) \
.transform(uni_dim_df, slicer, [slicer.dimensions.candidate], [])
self.assertEqual({
'columns': [{'Header': '', 'accessor': '$d$metrics'},
{'Header': 'Bill Clinton', 'accessor': '1'},
{'Header': 'Bob Dole', 'accessor': '2'},
{'Header': 'Ross Perot', 'accessor': '3'},
{'Header': 'George Bush', 'accessor': '4'},
{'Header': 'Al Gore', 'accessor': '5'},
{'Header': 'John Kerry', 'accessor': '6'},
{'Header': 'Barrack Obama', 'accessor': '7'},
{'Header': 'John McCain', 'accessor': '8'},
{'Header': 'Mitt Romney', 'accessor': '9'},
{'Header': 'Donald Trump', 'accessor': '10'},
{'Header': 'Hillary Clinton', 'accessor': '11'}],
'data': [{
'$d$metrics': {'raw': 'Wins'},
'1': {'display': '2', 'raw': 2},
'10': {'display': '2', 'raw': 2},
'11': {'display': '0', 'raw': 0},
'2': {'display': '0', 'raw': 0},
'3': {'display': '0', 'raw': 0},
'4': {'display': '4', 'raw': 4},
'5': {'display': '0', 'raw': 0},
'6': {'display': '0', 'raw': 0},
'7': {'display': '4', 'raw': 4},
'8': {'display': '0', 'raw': 0},
'9': {'display': '0', 'raw': 0}
}]
}, result)
def test_time_series_ref(self):
result = ReactTable(slicer.metrics.votes) \
.transform(cont_uni_dim_ref_df,
slicer,
[
slicer.dimensions.timestamp,
slicer.dimensions.state
], [
ElectionOverElection(slicer.dimensions.timestamp)
])
self.assertIn('data', result)
result['data'] = result['data'][:2] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{'Header': 'State', 'accessor': '$d$state'},
{'Header': 'Votes', 'accessor': '$m$votes'},
{'Header': 'Votes (EoE)', 'accessor': '$m$votes_eoe'}],
'data': [{
'$d$state': {'display': 'Texas', 'raw': '1'},
'$d$timestamp': {'raw': '2000-01-01'},
'$m$votes': {'display': '6,233,385', 'raw': 6233385},
'$m$votes_eoe': {'display': '5,574,387', 'raw': 5574387}
}, {
'$d$state': {'display': 'California', 'raw': '2'},
'$d$timestamp': {'raw': '2000-01-01'},
'$m$votes': {'display': '10,428,632', 'raw': 10428632},
'$m$votes_eoe': {'display': '9,646,062', 'raw': 9646062}
}]
}, result)
def test_pivot_single_metric_time_series_dim(self):
result = ReactTable(slicer.metrics.wins) \
.transform(cont_dim_df, slicer, [slicer.dimensions.timestamp], [])
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{
'$d$timestamp': {'raw': '1996-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$timestamp': {'raw': '2000-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$timestamp': {'raw': '2004-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$timestamp': {'raw': '2008-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$timestamp': {'raw': '2012-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$timestamp': {'raw': '2016-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}]
}, result)
def test_multi_dims_with_all_levels_totals(self):
result = ReactTable(slicer.metrics.wins) \
.transform(cont_uni_dim_all_totals_df, slicer, [slicer.dimensions.timestamp.rollup(),
slicer.dimensions.state.rollup()], [])
self.assertIn('data', result)
result['data'] = result['data'][:3] + result['data'][-1:] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{'Header': 'State', 'accessor': '$d$state'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{
'$d$state': {'display': 'Texas', 'raw': '1'},
'$d$timestamp': {'raw': '1996-01-01'},
'$m$wins': {'display': '1', 'raw': 1}
}, {
'$d$state': {'display': 'California', 'raw': '2'},
'$d$timestamp': {'raw': '1996-01-01'},
'$m$wins': {'display': '1', 'raw': 1}
}, {
'$d$state': {'raw': 'Totals'},
'$d$timestamp': {'raw': '1996-01-01'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$state': {'raw': 'Totals'},
'$d$timestamp': {'raw': 'Totals'},
'$m$wins': {'display': '12', 'raw': 12}
}]
}, result)
def test_dim_with_hyperlink_depending_on_another_dim_included_if_other_dim_is_selected(self):
slicer = self.slicer
slicer.dimensions.political_party.hyperlink_template = 'http://example.com/candidates/{candidate}/'
result = ReactTable(slicer.metrics.wins) \
.transform(cat_uni_dim_df, slicer, [slicer.dimensions.political_party, slicer.dimensions.candidate], [])
self.assertIn('data', result)
result['data'] = result['data'][:2] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': 'Party', 'accessor': '$d$political_party'},
{'Header': 'Candidate', 'accessor': '$d$candidate'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{
'$d$candidate': {'display': 'Bill Clinton', 'raw': '1'},
'$d$political_party': {
'display': 'Democrat',
'hyperlink': 'http://example.com/candidates/1/',
'raw': 'd'
},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$candidate': {'display': 'Al Gore', 'raw': '5'},
'$d$political_party': {
'display': 'Democrat',
'hyperlink': 'http://example.com/candidates/5/',
'raw': 'd'
},
'$m$wins': {'display': '0', 'raw': 0}
}]
}, result)
def test_uni_dim_no_display_definition(self):
import copy
candidate = copy.copy(slicer.dimensions.candidate)
uni_dim_df_copy = uni_dim_df.copy()
del uni_dim_df_copy[fd(slicer.dimensions.candidate.display.key)]
del candidate.display
result = ReactTable(slicer.metrics.wins) \
.transform(uni_dim_df_copy, slicer, [candidate], [])
self.assertEqual({
'columns': [{'Header': 'Candidate', 'accessor': '$d$candidate'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{'$d$candidate': {'raw': '1'}, '$m$wins': {'display': '2', 'raw': 2}},
{'$d$candidate': {'raw': '2'}, '$m$wins': {'display': '0', 'raw': 0}},
{'$d$candidate': {'raw': '3'}, '$m$wins': {'display': '0', 'raw': 0}},
{'$d$candidate': {'raw': '4'}, '$m$wins': {'display': '4', 'raw': 4}},
{'$d$candidate': {'raw': '5'}, '$m$wins': {'display': '0', 'raw': 0}},
{'$d$candidate': {'raw': '6'}, '$m$wins': {'display': '0', 'raw': 0}},
{'$d$candidate': {'raw': '7'}, '$m$wins': {'display': '4', 'raw': 4}},
{'$d$candidate': {'raw': '8'}, '$m$wins': {'display': '0', 'raw': 0}},
{'$d$candidate': {'raw': '9'}, '$m$wins': {'display': '0', 'raw': 0}},
{
'$d$candidate': {'raw': '10'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$candidate': {'raw': '11'},
'$m$wins': {'display': '0', 'raw': 0}
}]
}, result)
def test_time_series_dim_with_operation(self):
result = ReactTable(CumSum(slicer.metrics.votes)) \
.transform(cont_dim_operation_df, slicer, [slicer.dimensions.timestamp], [])
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{'Header': 'CumSum(Votes)', 'accessor': '$m$cumsum(votes)'}],
'data': [{
'$d$timestamp': {'raw': '1996-01-01'},
'$m$cumsum(votes)': {'display': '15,220,449', 'raw': 15220449}
}, {
'$d$timestamp': {'raw': '2000-01-01'},
'$m$cumsum(votes)': {'display': '31,882,466', 'raw': 31882466}
}, {
'$d$timestamp': {'raw': '2004-01-01'},
'$m$cumsum(votes)': {'display': '51,497,398', 'raw': 51497398}
}, {
'$d$timestamp': {'raw': '2008-01-01'},
'$m$cumsum(votes)': {'display': '72,791,613', 'raw': 72791613}
}, {
'$d$timestamp': {'raw': '2012-01-01'},
'$m$cumsum(votes)': {'display': '93,363,823', 'raw': 93363823}
}, {
'$d$timestamp': {'raw': '2016-01-01'},
'$m$cumsum(votes)': {'display': '111,674,336', 'raw': 111674336}
}]
}, result)
def test_single_metric(self):
result = ReactTable(slicer.metrics.votes) \
.transform(single_metric_df, slicer, [], [])
self.assertEqual({
'columns': [{'Header': 'Votes', 'accessor': '$m$votes'}],
'data': [{'$m$votes': {'display': '111,674,336', 'raw': 111674336}}]
}, result)
def test_multiple_metrics_reversed(self):
result = ReactTable(slicer.metrics.wins, slicer.metrics.votes) \
.transform(multi_metric_df, slicer, [], [])
self.assertEqual({
'columns': [{'Header': 'Wins', 'accessor': '$m$wins'},
{'Header': 'Votes', 'accessor': '$m$votes'}],
'data': [{
'$m$votes': {'display': '111,674,336', 'raw': 111674336},
'$m$wins': {'display': '12', 'raw': 12}
}]
}, result)
def test_transpose(self):
result = ReactTable(slicer.metrics.wins, transpose=True) \
.transform(cat_dim_df, slicer, [slicer.dimensions.political_party], [])
self.assertEqual({
'columns': [{'Header': '', 'accessor': '$d$metrics'},
{'Header': 'Democrat', 'accessor': 'd'},
{'Header': 'Independent', 'accessor': 'i'},
{'Header': 'Republican', 'accessor': 'r'}],
'data': [{
'$d$metrics': {'raw': 'Wins'},
'd': {'display': '6', 'raw': 6},
'i': {'display': '0', 'raw': 0},
'r': {'display': '6', 'raw': 6}
}]
}, result)
def test_pivot_single_dimension_as_rows_multiple_metrics(self):
result = ReactTable(slicer.metrics.wins, slicer.metrics.votes,
pivot=[slicer.dimensions.candidate]) \
.transform(uni_dim_df, slicer, [slicer.dimensions.candidate], [])
self.assertEqual({
'columns': [{'Header': '', 'accessor': '$d$metrics'},
{'Header': 'Bill Clinton', 'accessor': '1'},
{'Header': 'Bob Dole', 'accessor': '2'},
{'Header': 'Ross Perot', 'accessor': '3'},
{'Header': 'George Bush', 'accessor': '4'},
{'Header': 'Al Gore', 'accessor': '5'},
{'Header': 'John Kerry', 'accessor': '6'},
{'Header': 'Barrack Obama', 'accessor': '7'},
{'Header': 'John McCain', 'accessor': '8'},
{'Header': 'Mitt Romney', 'accessor': '9'},
{'Header': 'Donald Trump', 'accessor': '10'},
{'Header': 'Hillary Clinton', 'accessor': '11'}],
'data': [{
'$d$metrics': {'raw': 'Wins'},
'1': {'display': '2', 'raw': 2},
'10': {'display': '2', 'raw': 2},
'11': {'display': '0', 'raw': 0},
'2': {'display': '0', 'raw': 0},
'3': {'display': '0', 'raw': 0},
'4': {'display': '4', 'raw': 4},
'5': {'display': '0', 'raw': 0},
'6': {'display': '0', 'raw': 0},
'7': {'display': '4', 'raw': 4},
'8': {'display': '0', 'raw': 0},
'9': {'display': '0', 'raw': 0}
}, {
'$d$metrics': {'raw': 'Votes'},
'1': {'display': '7,579,518', 'raw': 7579518},
'10': {'display': '13,438,835', 'raw': 13438835},
'11': {'display': '4,871,678', 'raw': 4871678},
'2': {'display': '6,564,547', 'raw': 6564547},
'3': {'display': '1,076,384', 'raw': 1076384},
'4': {'display': '18,403,811', 'raw': 18403811},
'5': {'display': '8,294,949', 'raw': 8294949},
'6': {'display': '9,578,189', 'raw': 9578189},
'7': {'display': '24,227,234', 'raw': 24227234},
'8': {'display': '9,491,109', 'raw': 9491109},
'9': {'display': '8,148,082', 'raw': 8148082}
}]
}, result)
def test_pivot_second_dimension_and_transpose_with_all_levels_totals(self):
state = slicer.dimensions.state.rollup()
result = ReactTable(slicer.metrics.wins, slicer.metrics.votes, pivot=[state], transpose=True) \
.transform(cont_uni_dim_all_totals_df, slicer, [slicer.dimensions.timestamp.rollup(),
state], [])
self.assertIn('data', result)
result['data'] = result['data'][:2] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': '', 'accessor': '$d$metrics'},
{'Header': 'State', 'accessor': '$d$state'},
{'Header': '1996-01-01', 'accessor': '1996-01-01'},
{'Header': '2000-01-01', 'accessor': '2000-01-01'},
{'Header': '2004-01-01', 'accessor': '2004-01-01'},
{'Header': '2008-01-01', 'accessor': '2008-01-01'},
{'Header': '2012-01-01', 'accessor': '2012-01-01'},
{'Header': '2016-01-01', 'accessor': '2016-01-01'},
{
'Header': 'Totals',
'accessor': 'Totals',
'className': 'fireant-totals'
}],
'data': [{
'$d$metrics': {'raw': 'Wins'},
'$d$state': {'display': 'Texas', 'raw': '1'},
'1996-01-01': {'display': '1', 'raw': 1},
'2000-01-01': {'display': '1', 'raw': 1},
'2004-01-01': {'display': '1', 'raw': 1},
'2008-01-01': {'display': '1', 'raw': 1},
'2012-01-01': {'display': '1', 'raw': 1},
'2016-01-01': {'display': '1', 'raw': 1},
'Totals': {'display': 'null', 'raw': None}
}, {
'$d$metrics': {'raw': 'Wins'},
'$d$state': {'display': 'California', 'raw': '2'},
'1996-01-01': {'display': '1', 'raw': 1},
'2000-01-01': {'display': '1', 'raw': 1},
'2004-01-01': {'display': '1', 'raw': 1},
'2008-01-01': {'display': '1', 'raw': 1},
'2012-01-01': {'display': '1', 'raw': 1},
'2016-01-01': {'display': '1', 'raw': 1},
'Totals': {'display': 'null', 'raw': None}
}]
}, result)
def test_pivot_first_dimension_and_transpose_with_all_levels_totals(self):
state = slicer.dimensions.state.rollup()
result = ReactTable(slicer.metrics.wins, slicer.metrics.votes, pivot=[state], transpose=True) \
.transform(cont_uni_dim_all_totals_df, slicer, [slicer.dimensions.timestamp.rollup(),
state], [])
self.assertIn('data', result)
result['data'] = result['data'][:6:3] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': '', 'accessor': '$d$metrics'},
{'Header': 'State', 'accessor': '$d$state'},
{'Header': '1996-01-01', 'accessor': '1996-01-01'},
{'Header': '2000-01-01', 'accessor': '2000-01-01'},
{'Header': '2004-01-01', 'accessor': '2004-01-01'},
{'Header': '2008-01-01', 'accessor': '2008-01-01'},
{'Header': '2012-01-01', 'accessor': '2012-01-01'},
{'Header': '2016-01-01', 'accessor': '2016-01-01'},
{
'Header': 'Totals',
'accessor': 'Totals',
'className': 'fireant-totals'
}],
'data': [{
'$d$metrics': {'raw': 'Wins'},
'$d$state': {'display': 'Texas', 'raw': '1'},
'1996-01-01': {'display': '1', 'raw': 1},
'2000-01-01': {'display': '1', 'raw': 1},
'2004-01-01': {'display': '1', 'raw': 1},
'2008-01-01': {'display': '1', 'raw': 1},
'2012-01-01': {'display': '1', 'raw': 1},
'2016-01-01': {'display': '1', 'raw': 1},
'Totals': {'display': 'null', 'raw': None}
}, {
'$d$metrics': {'raw': 'Votes'},
'$d$state': {'display': 'Texas', 'raw': '1'},
'1996-01-01': {'display': '5,574,387', 'raw': 5574387},
'2000-01-01': {'display': '6,233,385', 'raw': 6233385},
'2004-01-01': {'display': '7,359,621', 'raw': 7359621},
'2008-01-01': {'display': '8,007,961', 'raw': 8007961},
'2012-01-01': {'display': '7,877,967', 'raw': 7877967},
'2016-01-01': {'display': '5,072,915', 'raw': 5072915},
'Totals': {'display': 'null', 'raw': None}
}]
}, result)
def test_uni_dim(self):
result = ReactTable(slicer.metrics.wins) \
.transform(uni_dim_df, slicer, [slicer.dimensions.candidate], [])
self.assertEqual({
'columns': [{'Header': 'Candidate', 'accessor': '$d$candidate'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{
'$d$candidate': {'display': 'Bill Clinton', 'raw': '1'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$candidate': {'display': 'Bob Dole', 'raw': '2'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$candidate': {'display': 'Ross Perot', 'raw': '3'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$candidate': {'display': 'George Bush', 'raw': '4'},
'$m$wins': {'display': '4', 'raw': 4}
}, {
'$d$candidate': {'display': 'Al Gore', 'raw': '5'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$candidate': {'display': 'John Kerry', 'raw': '6'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$candidate': {'display': 'Barrack Obama', 'raw': '7'},
'$m$wins': {'display': '4', 'raw': 4}
}, {
'$d$candidate': {'display': 'John McCain', 'raw': '8'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$candidate': {'display': 'Mitt Romney', 'raw': '9'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$candidate': {'display': 'Donald Trump', 'raw': '10'},
'$m$wins': {'display': '2', 'raw': 2}
}, {
'$d$candidate': {'display': 'Hillary Clinton', 'raw': '11'},
'$m$wins': {'display': '0', 'raw': 0}
}]
}, result)
def test_multi_dims_time_series_and_uni(self):
result = ReactTable(slicer.metrics.wins) \
.transform(cont_uni_dim_df, slicer, [slicer.dimensions.timestamp, slicer.dimensions.state], [])
self.assertIn('data', result)
result['data'] = result['data'][:2] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{'Header': 'State', 'accessor': '$d$state'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{
'$d$state': {'display': 'Texas', 'raw': '1'},
'$d$timestamp': {'raw': '1996-01-01'},
'$m$wins': {'display': '1', 'raw': 1}
}, {
'$d$state': {'display': 'California', 'raw': '2'},
'$d$timestamp': {'raw': '1996-01-01'},
'$m$wins': {'display': '1', 'raw': 1}
}]
}, result)
def test_pivot_second_dimension_with_multiple_metrics(self):
result = ReactTable(slicer.metrics.wins, slicer.metrics.votes, pivot=[slicer.dimensions.state]) \
.transform(cont_uni_dim_df, slicer, [slicer.dimensions.timestamp, slicer.dimensions.state], [])
self.assertIn('data', result)
result['data'] = result['data'][:2] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{
'Header': 'Votes',
'columns': [{'Header': 'Texas', 'accessor': '$m$votes.1'},
{'Header': 'California', 'accessor': '$m$votes.2'}]
}, {
'Header': 'Wins',
'columns': [{'Header': 'Texas', 'accessor': '$m$wins.1'},
{'Header': 'California', 'accessor': '$m$wins.2'}]
}],
'data': [{
'$d$timestamp': {'raw': '1996-01-01'},
'$m$votes': {
'1': {'display': '5,574,387', 'raw': 5574387},
'2': {'display': '9,646,062', 'raw': 9646062}
},
'$m$wins': {
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}
}, {
'$d$timestamp': {'raw': '2000-01-01'},
'$m$votes': {
'1': {'display': '6,233,385', 'raw': 6233385},
'2': {'display': '10,428,632', 'raw': 10428632}
},
'$m$wins': {
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1}
}
}]
}, result)
def test_dim_with_hyperlink_hyperlink_is_always_included(self):
slicer = self.slicer
slicer.dimensions.political_party.hyperlink_template = 'http://example.com/{political_party}'
result = ReactTable(slicer.metrics.wins) \
.transform(cat_dim_df, slicer, [slicer.dimensions.political_party], [])
self.assertEqual({
'columns': [{'Header': 'Party', 'accessor': '$d$political_party'},
{'Header': 'Wins', 'accessor': '$m$wins'}],
'data': [{
'$d$political_party': {'display': 'Democrat', 'hyperlink': 'http://example.com/d', 'raw': 'd'},
'$m$wins': {'display': '6', 'raw': 6}
}, {
'$d$political_party': {'display': 'Independent', 'hyperlink': 'http://example.com/i', 'raw': 'i'},
'$m$wins': {'display': '0', 'raw': 0}
}, {
'$d$political_party': {'display': 'Republican', 'hyperlink': 'http://example.com/r', 'raw': 'r'},
'$m$wins': {'display': '6', 'raw': 6}
}]
}, result)
def test_pivot_multi_dims_with_all_levels_totals(self):
state = slicer.dimensions.state.rollup()
result = ReactTable(slicer.metrics.wins, slicer.metrics.votes, pivot=[state]) \
.transform(cont_uni_dim_all_totals_df, slicer, [slicer.dimensions.timestamp.rollup(),
state], [])
self.assertIn('data', result)
result['data'] = result['data'][:2] + result['data'][-1:] # shorten the results to make the test easier to read
self.assertEqual({
'columns': [{'Header': 'Timestamp', 'accessor': '$d$timestamp'},
{
'Header': 'Votes',
'columns': [{'Header': 'Texas', 'accessor': '$m$votes.1'},
{'Header': 'California', 'accessor': '$m$votes.2'},
{
'Header': 'Totals',
'accessor': '$m$votes.{}'.format(MAX_STRING),
'className': 'fireant-totals'
}]
}, {
'Header': 'Wins',
'columns': [{'Header': 'Texas', 'accessor': '$m$wins.1'},
{'Header': 'California', 'accessor': '$m$wins.2'},
{
'Header': 'Totals',
'accessor': '$m$wins.{}'.format(MAX_STRING),
'className': 'fireant-totals'
}]
}],
'data': [{
'$d$timestamp': {'raw': '1996-01-01'},
'$m$votes': {
'1': {'display': '5,574,387', 'raw': 5574387},
'2': {'display': '9,646,062', 'raw': 9646062},
MAX_STRING: {'display': '15,220,449', 'raw': 15220449}
},
'$m$wins': {
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1},
MAX_STRING: {'display': '2', 'raw': 2}
}
}, {
'$d$timestamp': {'raw': '2000-01-01'},
'$m$votes': {
'1': {'display': '6,233,385', 'raw': 6233385},
'2': {'display': '10,428,632', 'raw': 10428632},
MAX_STRING: {'display': '16,662,017', 'raw': 16662017}
},
'$m$wins': {
'1': {'display': '1', 'raw': 1},
'2': {'display': '1', 'raw': 1},
MAX_STRING: {'display': '2', 'raw': 2}
}
}, {
'$d$timestamp': {'raw': 'Totals'},
'$m$votes': {
'1': {'display': 'null', 'raw': None},
'2': {'display': 'null', 'raw': None},
MAX_STRING: {
'display': '111,674,336',
'raw': 111674336
}
},
'$m$wins': {
'1': {'display': 'null', 'raw': None},
'2': {'display': 'null', 'raw': None},
MAX_STRING: {'display': '12', 'raw': 12}
}
}]
}, result)
