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76 lines
3.4 KiB
Python
76 lines
3.4 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from typing import Optional
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from flask_babel import gettext as _
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from pandas import DataFrame
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from superset.exceptions import InvalidPostProcessingError
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from superset.utils.pandas_postprocessing.utils import (
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scalar_to_sequence,
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validate_column_args,
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)
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@validate_column_args("columns", "exclude", "rename")
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def select(
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df: DataFrame,
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columns: Optional[list[str]] = None,
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exclude: Optional[list[str]] = None,
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rename: Optional[dict[str, str]] = None,
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) -> DataFrame:
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"""
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Only select a subset of columns in the original dataset. Can be useful for
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removing unnecessary intermediate results, renaming and reordering columns.
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:param df: DataFrame on which the rolling period will be based.
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:param columns: Columns which to select from the DataFrame, in the desired order.
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If left undefined, all columns will be selected. If columns are
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renamed, the original column name should be referenced here.
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:param exclude: columns to exclude from selection. Applied after `columns` and
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before `rename`, so the original column name should be referenced
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here, and the column must survive the `columns` selection.
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:param rename: columns which to rename, mapping source column to target column.
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For instance, `{'y': 'y2'}` will rename the column `y` to
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`y2`.
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:return: Subset of columns in original DataFrame
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:raises InvalidPostProcessingError: If the request in incorrect
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"""
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df_select = df.copy(deep=False)
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if columns:
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df_select = df_select[columns]
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if exclude:
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# A bare column name is accepted as well as a sequence: `validate_column_args`
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# normalises through `scalar_to_sequence` to validate, then hands the original
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# value on. Normalise here too, so a string is not iterated character by
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# character.
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exclude = list(scalar_to_sequence(exclude))
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# `exclude` is validated against the incoming DataFrame by the decorator, but
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# a preceding `columns` selection may already have removed the column. Reject
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# that as a validation error instead of letting pandas raise a bare KeyError.
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if missing := [column for column in exclude if column not in df_select.columns]:
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raise InvalidPostProcessingError(
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_(
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"Referenced columns not available in DataFrame: %(columns)s",
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columns=", ".join(missing),
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)
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)
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df_select = df_select.drop(exclude, axis=1)
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if rename is not None:
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df_select = df_select.rename(columns=rename)
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return df_select
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