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fix(explore): preserve metric column order in bar chart (#12417)

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* fix: Preserve Column Order in Bar chart

* Update tests/viz_tests.py to use f-strings style

Co-authored-by: Duy Nguyen <duy.nguyenhoang@global-fashion-group.com>
This commit is contained in:
Duy Nguyen Hoang
2021-01-28 15:39:00 +07:00
committed by GitHub
parent 5a3c5b1f54
commit 32f2c45f93
3 changed files with 107 additions and 13 deletions
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111
tests/viz_tests.py
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@@ -79,10 +79,10 @@ class TestBaseViz(SupersetTestCase):
datasource.type = "table"
test_viz = viz.BaseViz(datasource, form_data)
expect_metric_labels = [
u"sum__SP_POP_TOTL",
u"SUM(SE_PRM_NENR_MA)",
u"SUM(SP_URB_TOTL)",
u"count",
"sum__SP_POP_TOTL",
"SUM(SE_PRM_NENR_MA)",
"SUM(SP_URB_TOTL)",
"count",
]
self.assertEqual(test_viz.metric_labels, expect_metric_labels)
self.assertEqual(test_viz.all_metrics, expect_metric_labels)
@@ -500,6 +500,7 @@ class TestDistBarViz(SupersetTestCase):
{"x": "2.0", "y": 29},
{"x": NULL_STRING, "y": 3},
]
self.assertEqual(expected_values, data["values"])
def test_column_nulls(self):
@@ -531,6 +532,92 @@ class TestDistBarViz(SupersetTestCase):
]
self.assertEqual(expected, data)
def test_column_metrics_in_order(self):
form_data = {
"metrics": ["z_column", "votes", "a_column"],
"adhoc_filters": [],
"groupby": ["toppings"],
"columns": [],
}
datasource = self.get_datasource_mock()
df = pd.DataFrame(
{
"toppings": ["cheese", "pepperoni", "cheese", "pepperoni"],
"role": ["engineer", "engineer", None, None],
"votes": [3, 5, 1, 2],
"a_column": [3, 5, 1, 2],
"z_column": [3, 5, 1, 2],
}
)
test_viz = viz.DistributionBarViz(datasource, form_data)
data = test_viz.get_data(df)
expected = [
{
"key": "z_column",
"values": [{"x": "pepperoni", "y": 3.5}, {"x": "cheese", "y": 2.0}],
},
{
"key": "votes",
"values": [{"x": "pepperoni", "y": 3.5}, {"x": "cheese", "y": 2.0}],
},
{
"key": "a_column",
"values": [{"x": "pepperoni", "y": 3.5}, {"x": "cheese", "y": 2.0}],
},
]
self.assertEqual(expected, data)
def test_column_metrics_in_order_with_breakdowns(self):
form_data = {
"metrics": ["z_column", "votes", "a_column"],
"adhoc_filters": [],
"groupby": ["toppings"],
"columns": ["role"],
}
datasource = self.get_datasource_mock()
df = pd.DataFrame(
{
"toppings": ["cheese", "pepperoni", "cheese", "pepperoni"],
"role": ["engineer", "engineer", None, None],
"votes": [3, 5, 1, 2],
"a_column": [3, 5, 1, 2],
"z_column": [3, 5, 1, 2],
}
)
test_viz = viz.DistributionBarViz(datasource, form_data)
data = test_viz.get_data(df)
expected = [
{
"key": f"z_column, {NULL_STRING}",
"values": [{"x": "pepperoni", "y": 2}, {"x": "cheese", "y": 1}],
},
{
"key": "z_column, engineer",
"values": [{"x": "pepperoni", "y": 5}, {"x": "cheese", "y": 3}],
},
{
"key": f"votes, {NULL_STRING}",
"values": [{"x": "pepperoni", "y": 2}, {"x": "cheese", "y": 1}],
},
{
"key": "votes, engineer",
"values": [{"x": "pepperoni", "y": 5}, {"x": "cheese", "y": 3}],
},
{
"key": f"a_column, {NULL_STRING}",
"values": [{"x": "pepperoni", "y": 2}, {"x": "cheese", "y": 1}],
},
{
"key": "a_column, engineer",
"values": [{"x": "pepperoni", "y": 5}, {"x": "cheese", "y": 3}],
},
]
self.assertEqual(expected, data)
class TestPairedTTest(SupersetTestCase):
def test_get_data_transforms_dataframe(self):
@@ -1179,18 +1266,18 @@ class TestTimeSeriesViz(SupersetTestCase):
viz_data = test_viz.get_data(df)
expected = [
{
u"values": [
{u"y": 4, u"x": u"2018-02-20T00:00:00"},
{u"y": 4, u"x": u"2018-03-09T00:00:00"},
"values": [
{"y": 4, "x": "2018-02-20T00:00:00"},
{"y": 4, "x": "2018-03-09T00:00:00"},
],
u"key": (u"Real Madrid Basket",),
"key": ("Real Madrid Basket",),
},
{
u"values": [
{u"y": 2, u"x": u"2018-02-20T00:00:00"},
{u"y": 2, u"x": u"2018-03-09T00:00:00"},
"values": [
{"y": 2, "x": "2018-02-20T00:00:00"},
{"y": 2, "x": "2018-03-09T00:00:00"},
],
u"key": (u"Real Madrid C.F.\U0001f1fa\U0001f1f8\U0001f1ec\U0001f1e7",),
"key": ("Real Madrid C.F.\U0001f1fa\U0001f1f8\U0001f1ec\U0001f1e7",),
},
]
self.assertEqual(expected, viz_data)