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41 lines
1.3 KiB
Python
41 lines
1.3 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 __future__ import annotations
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import pandas as pd
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def rank(
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df: pd.DataFrame,
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metric: str,
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group_by: str | None = None,
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) -> pd.DataFrame:
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"""
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Calculates the rank of a metric within a group.
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:param df: N-dimensional DataFrame.
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:param metric: The metric to rank.
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:param group_by: The column to group by.
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:return: a flat DataFrame
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"""
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if group_by:
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gb = df.groupby(group_by, group_keys=False)
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df["rank"] = gb.apply(lambda x: x[metric].rank(pct=True))
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else:
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df["rank"] = df[metric].rank(pct=True)
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return df
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