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The following commit(s) were added to refs/heads/master by this push:
new 73797b8 check for empty dataframes before processing results (#10361)
73797b8 is described below
commit 73797b8b6406ba9ca54fb603d6bd7a6c92ee4cd9
Author: bryanck <brya...@gmail.com>
AuthorDate: Sun Jul 19 07:19:30 2020 -0700
check for empty dataframes before processing results (#10361)
Co-authored-by: Bryan Keller <bkel...@netflix.com>
---
INTHEWILD.md | 1 +
superset/viz.py | 43 ++++++++++++++++++++++++++++---------------
tests/viz_tests.py | 10 +++++++++-
3 files changed, 38 insertions(+), 16 deletions(-)
diff --git a/INTHEWILD.md b/INTHEWILD.md
index c3dde1f..c716221 100644
--- a/INTHEWILD.md
+++ b/INTHEWILD.md
@@ -101,6 +101,7 @@ Join our growing community!
- [bilibili](https://www.bilibili.com) [@Moinheart]
- [Douban](https://www.douban.com/) [@luchuan]
- [Kuaishou](https://www.kuaishou.com/) [@zhaoyu89730105]
+- [Netflix](https://www.netflix.com/)
- [TME QQMUSIC/WESING](https://www.tencentmusic.com/)
- [Zaihang](http://www.zaih.com/)
diff --git a/superset/viz.py b/superset/viz.py
index 6e6f86d..8bceef6 100644
--- a/superset/viz.py
+++ b/superset/viz.py
@@ -661,21 +661,19 @@ class TableViz(BaseViz):
# Transform the data frame to adhere to the UI ordering of the columns
and
# metrics whilst simultaneously computing the percentages (via
normalization)
# for the percent metrics.
- if not df.empty:
- columns, percent_columns = self.columns, self.percent_columns
- if DTTM_ALIAS in df and self.is_timeseries:
- columns = [DTTM_ALIAS] + columns
- df = pd.concat(
- [
- df[columns],
- (
- df[percent_columns]
- .div(df[percent_columns].sum())
- .add_prefix("%")
- ),
- ],
- axis=1,
- )
+ if df.empty:
+ return None
+
+ columns, percent_columns = self.columns, self.percent_columns
+ if DTTM_ALIAS in df and self.is_timeseries:
+ columns = [DTTM_ALIAS] + columns
+ df = pd.concat(
+ [
+ df[columns],
+
(df[percent_columns].div(df[percent_columns].sum()).add_prefix("%")),
+ ],
+ axis=1,
+ )
return self.handle_js_int_overflow(
dict(records=df.to_dict(orient="records"),
columns=list(df.columns))
)
@@ -852,6 +850,9 @@ class CalHeatmapViz(BaseViz):
is_timeseries = True
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
+
form_data = self.form_data
data = {}
@@ -1074,6 +1075,8 @@ class BulletViz(NVD3Viz):
return d
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
df["metric"] = df[[utils.get_metric_name(self.metric)]]
values = df["metric"].values
return {
@@ -1665,6 +1668,8 @@ class SunburstViz(BaseViz):
)
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
fd = self.form_data
cols = fd.get("groupby") or []
cols.extend(["m1", "m2"])
@@ -1715,6 +1720,8 @@ class SankeyViz(BaseViz):
return qry
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
source, target = self.groupby
(value,) = self.metric_labels
df.rename(
@@ -1774,6 +1781,8 @@ class DirectedForceViz(BaseViz):
return qry
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
df.columns = ["source", "target", "value"]
return df.to_dict(orient="records")
@@ -1827,6 +1836,8 @@ class CountryMapViz(BaseViz):
return qry
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
fd = self.form_data
cols = [fd.get("entity")]
metric = self.metric_labels[0]
@@ -2915,6 +2926,8 @@ class PartitionViz(NVD3TimeSeriesViz):
]
def get_data(self, df: pd.DataFrame) -> VizData:
+ if df.empty:
+ return None
fd = self.form_data
groups = fd.get("groupby", [])
time_op = fd.get("time_series_option", "not_time")
diff --git a/tests/viz_tests.py b/tests/viz_tests.py
index 8290fbf..c6d0c80 100644
--- a/tests/viz_tests.py
+++ b/tests/viz_tests.py
@@ -825,8 +825,16 @@ class TestPartitionViz(SupersetTestCase):
)
def test_get_data_calls_correct_method(self):
+ raw = {}
+ raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
+ raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
+ raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
+ raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
+ raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
+ raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
+ raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
+ df = pd.DataFrame(raw)
test_viz = viz.PartitionViz(Mock(), {})
- df = Mock()
with self.assertRaises(ValueError):
test_viz.get_data(df)
test_viz.levels_for = Mock(return_value=1)
