QT/superset2
1
0
Fork 0
mirror of https://github.com/apache/superset.git synced 2026-04-21 09:04:38 +00:00
Code Issues Packages Projects Releases Wiki Activity

chore: upgrade black (#19410)

Browse Source
This commit is contained in:
Ville Brofeldt
2022-03-29 20:03:09 +03:00
committed by GitHub
parent 816a2c3e1e
commit a619cb4ea9
204 changed files with 2125 additions and 608 deletions
Download Patch File Download Diff File Expand all files Collapse all files

38
tests/unit_tests/pandas_postprocessing/test_pivot.py
View File

@@ -34,37 +34,49 @@ def test_flatten_column_after_pivot():
"""
# single aggregate cases
assert (
_flatten_column_after_pivot(aggregates=AGGREGATES_SINGLE, column="idx_nulls",)
_flatten_column_after_pivot(
aggregates=AGGREGATES_SINGLE,
column="idx_nulls",
)
== "idx_nulls"
)
assert (
_flatten_column_after_pivot(aggregates=AGGREGATES_SINGLE, column=1234,)
_flatten_column_after_pivot(
aggregates=AGGREGATES_SINGLE,
column=1234,
)
== "1234"
)
assert (
_flatten_column_after_pivot(
aggregates=AGGREGATES_SINGLE, column=Timestamp("2020-09-29T00:00:00"),
aggregates=AGGREGATES_SINGLE,
column=Timestamp("2020-09-29T00:00:00"),
)
== "2020-09-29 00:00:00"
)
assert (
_flatten_column_after_pivot(aggregates=AGGREGATES_SINGLE, column="idx_nulls",)
_flatten_column_after_pivot(
aggregates=AGGREGATES_SINGLE,
column="idx_nulls",
)
== "idx_nulls"
)
assert (
_flatten_column_after_pivot(
aggregates=AGGREGATES_SINGLE, column=("idx_nulls", "col1"),
aggregates=AGGREGATES_SINGLE,
column=("idx_nulls", "col1"),
)
== "col1"
)
assert (
_flatten_column_after_pivot(
aggregates=AGGREGATES_SINGLE, column=("idx_nulls", "col1", 1234),
aggregates=AGGREGATES_SINGLE,
column=("idx_nulls", "col1", 1234),
)
== "col1, 1234"
)
@@ -72,7 +84,8 @@ def test_flatten_column_after_pivot():
# Multiple aggregate cases
assert (
_flatten_column_after_pivot(
aggregates=AGGREGATES_MULTIPLE, column=("idx_nulls", "asc_idx", "col1"),
aggregates=AGGREGATES_MULTIPLE,
column=("idx_nulls", "asc_idx", "col1"),
)
== "idx_nulls, asc_idx, col1"
)
@@ -90,7 +103,11 @@ def test_pivot_without_columns():
"""
Make sure pivot without columns returns correct DataFrame
"""
df = pivot(df=categories_df, index=["name"], aggregates=AGGREGATES_SINGLE,)
df = pivot(
df=categories_df,
index=["name"],
aggregates=AGGREGATES_SINGLE,
)
assert df.columns.tolist() == ["name", "idx_nulls"]
assert len(df) == 101
assert df.sum()[1] == 1050
@@ -235,7 +252,10 @@ def test_pivot_eliminate_cartesian_product_columns():
df=mock_df,
index=["dttm"],
columns=["a", "b"],
aggregates={"metric": {"operator": "mean"}, "metric2": {"operator": "mean"},},
aggregates={
"metric": {"operator": "mean"},
"metric2": {"operator": "mean"},
},
drop_missing_columns=False,
)
assert list(df.columns) == [