superset cum 源码
superset cum 代码
文件路径：/superset/utils/pandas_postprocessing/cum.py
# 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 Dict
from flask_babel import gettext as _
from pandas import DataFrame
from superset.exceptions import InvalidPostProcessingError
from superset.utils.pandas_postprocessing.utils import (
_append_columns,
ALLOWLIST_CUMULATIVE_FUNCTIONS,
validate_column_args,
)
@validate_column_args("columns")
def cum(
df: DataFrame,
operator: str,
columns: Dict[str, str],
) -> DataFrame:
"""
Calculate cumulative sum/product/min/max for select columns.
:param df: DataFrame on which the cumulative operation will be based.
:param columns: columns on which to perform a cumulative operation, mapping source
column to target column. For instance, `{'y': 'y'}` will replace the column
`y` with the cumulative value in `y`, while `{'y': 'y2'}` will add a column
`y2` based on cumulative values calculated from `y`, leaving the original
column `y` unchanged.
:param operator: cumulative operator, e.g. `sum`, `prod`, `min`, `max`
:return: DataFrame with cumulated columns
"""
columns = columns or {}
df_cum = df.loc[:, columns.keys()]
operation = "cum" + operator
if operation not in ALLOWLIST_CUMULATIVE_FUNCTIONS or not hasattr(
df_cum, operation
):
raise InvalidPostProcessingError(
_("Invalid cumulative operator: %(operator)s", operator=operator)
)
df_cum = _append_columns(df, getattr(df_cum, operation)(), columns)
return df_cum
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