mirror of
https://github.com/apache/superset.git
synced 2026-04-10 11:55:24 +00:00
80 lines
3.2 KiB
Python
80 lines
3.2 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
|
|
# or more contributor license agreements. See the NOTICE file
|
|
# distributed with this work for additional information
|
|
# regarding copyright ownership. The ASF licenses this file
|
|
# to you under the Apache License, Version 2.0 (the
|
|
# "License"); you may not use this file except in compliance
|
|
# with the License. You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing,
|
|
# software distributed under the License is distributed on an
|
|
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
|
|
# KIND, either express or implied. See the License for the
|
|
# specific language governing permissions and limitations
|
|
# under the License.
|
|
from typing import List, Optional
|
|
|
|
import pandas as pd
|
|
from flask_babel import gettext as _
|
|
from pandas import DataFrame
|
|
|
|
from superset.constants import PandasPostprocessingCompare
|
|
from superset.exceptions import QueryObjectValidationError
|
|
from superset.utils.core import TIME_COMPARISION
|
|
from superset.utils.pandas_postprocessing.utils import validate_column_args
|
|
|
|
|
|
@validate_column_args("source_columns", "compare_columns")
|
|
def compare( # pylint: disable=too-many-arguments
|
|
df: DataFrame,
|
|
source_columns: List[str],
|
|
compare_columns: List[str],
|
|
compare_type: Optional[PandasPostprocessingCompare],
|
|
drop_original_columns: Optional[bool] = False,
|
|
precision: Optional[int] = 4,
|
|
) -> DataFrame:
|
|
"""
|
|
Calculate column-by-column changing for select columns.
|
|
|
|
:param df: DataFrame on which the compare will be based.
|
|
:param source_columns: Main query columns
|
|
:param compare_columns: Columns being compared
|
|
:param compare_type: Type of compare. Choice of `absolute`, `percentage` or `ratio`
|
|
:param drop_original_columns: Whether to remove the source columns and
|
|
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.
|
|
"""
|
|
if len(source_columns) != len(compare_columns):
|
|
raise QueryObjectValidationError(
|
|
_("`compare_columns` must have the same length as `source_columns`.")
|
|
)
|
|
if compare_type not in tuple(PandasPostprocessingCompare):
|
|
raise QueryObjectValidationError(
|
|
_("`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):
|
|
if compare_type == PandasPostprocessingCompare.DIFF:
|
|
diff_series = df[s_col] - df[c_col]
|
|
elif compare_type == PandasPostprocessingCompare.PCT:
|
|
diff_series = (
|
|
((df[s_col] - df[c_col]) / df[c_col]).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])
|
|
)
|
|
df = pd.concat([df, diff_df], axis=1)
|
|
|
|
if drop_original_columns:
|
|
df = df.drop(source_columns + compare_columns, axis=1)
|
|
return df
|