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feat(advanced analysis): support MultiIndex column in post processing stage (#19116)

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This commit is contained in:
Yongjie Zhao
2022-03-23 13:46:28 +08:00
committed by Ville Brofeldt
parent f8a92de75c
commit 9bc76337cf
55 changed files with 1272 additions and 772 deletions
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31
superset/utils/pandas_postprocessing/compare.py
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@@ -21,7 +21,7 @@ from flask_babel import gettext as _
from pandas import DataFrame
from superset.constants import PandasPostprocessingCompare
from superset.exceptions import QueryObjectValidationError
from superset.exceptions import InvalidPostProcessingError
from superset.utils.core import TIME_COMPARISION
from superset.utils.pandas_postprocessing.utils import validate_column_args
@@ -31,7 +31,7 @@ def compare( # pylint: disable=too-many-arguments
df: DataFrame,
source_columns: List[str],
compare_columns: List[str],
compare_type: Optional[PandasPostprocessingCompare],
compare_type: PandasPostprocessingCompare,
drop_original_columns: Optional[bool] = False,
precision: Optional[int] = 4,
) -> DataFrame:
@@ -46,31 +46,38 @@ def compare( # pylint: disable=too-many-arguments
compare columns.
:param precision: Round a change rate to a variable number of decimal places.
:return: DataFrame with compared columns.
:raises QueryObjectValidationError: If the request in incorrect.
:raises InvalidPostProcessingError: If the request in incorrect.
"""
if len(source_columns) != len(compare_columns):
raise QueryObjectValidationError(
raise InvalidPostProcessingError(
_("`compare_columns` must have the same length as `source_columns`.")
)
if compare_type not in tuple(PandasPostprocessingCompare):
raise QueryObjectValidationError(
raise InvalidPostProcessingError(
_("`compare_type` must be `difference`, `percentage` or `ratio`")
)
if len(source_columns) == 0:
return df
for s_col, c_col in zip(source_columns, compare_columns):
s_df = df.loc[:, [s_col]]
s_df.rename(columns={s_col: "__intermediate"}, inplace=True)
c_df = df.loc[:, [c_col]]
c_df.rename(columns={c_col: "__intermediate"}, inplace=True)
if compare_type == PandasPostprocessingCompare.DIFF:
diff_series = df[s_col] - df[c_col]
diff_df = c_df - s_df
elif compare_type == PandasPostprocessingCompare.PCT:
diff_series = (
((df[s_col] - df[c_col]) / df[c_col]).astype(float).round(precision)
)
# https://en.wikipedia.org/wiki/Relative_change_and_difference#Percentage_change
diff_df = ((c_df - s_df) / s_df).astype(float).round(precision)
else:
# compare_type == "ratio"
diff_series = (df[s_col] / df[c_col]).astype(float).round(precision)
diff_df = diff_series.to_frame(
name=TIME_COMPARISION.join([compare_type, s_col, c_col])
diff_df = (c_df / s_df).astype(float).round(precision)
diff_df.rename(
columns={
"__intermediate": TIME_COMPARISION.join([compare_type, s_col, c_col])
},
inplace=True,
)
df = pd.concat([df, diff_df], axis=1)