def test_boxplot_percentile_incorrect_params(self):
with pytest.raises(QueryObjectValidationError):
proc.boxplot(
df=names_df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.PERCENTILE,
metrics=["cars"],
)
with pytest.raises(QueryObjectValidationError):
proc.boxplot(
df=names_df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.PERCENTILE,
metrics=["cars"],
percentiles=[10],
)
with pytest.raises(QueryObjectValidationError):
proc.boxplot(
df=names_df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.PERCENTILE,
metrics=["cars"],
percentiles=[90, 10],
)
with pytest.raises(QueryObjectValidationError):
proc.boxplot(
df=names_df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.PERCENTILE,
metrics=["cars"],
percentiles=[10, 90, 10],
)
def test_boxplot_min_max(self):
df = proc.boxplot(
df=names_df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.MINMAX,
metrics=["cars"],
)
columns = {column for column in df.columns}
assert columns == {
"cars__mean",
"cars__median",
"cars__q1",
"cars__q3",
"cars__max",
"cars__min",
"cars__count",
"cars__outliers",
"region",
}
assert len(df) == 4
def test_boxplot_percentile():
df = boxplot(
df=names_df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.PERCENTILE,
metrics=["cars"],
percentiles=[1, 99],
)
columns = {column for column in df.columns}
assert columns == {
"cars__mean",
"cars__median",
"cars__q1",
"cars__q3",
"cars__max",
"cars__min",
"cars__count",
"cars__outliers",
"region",
}
assert len(df) == 4
def test_boxplot_type_coercion():
df = names_df
df["cars"] = df["cars"].astype(str)
df = boxplot(
df=df,
groupby=["region"],
whisker_type=PostProcessingBoxplotWhiskerType.TUKEY,
metrics=["cars"],
)
columns = {column for column in df.columns}
assert columns == {
"cars__mean",
"cars__median",
"cars__q1",
"cars__q3",
"cars__max",
"cars__min",
"cars__count",
"cars__outliers",
"region",
}
assert len(df) == 4
