Python 根据列表中给定的优先级保留重复行

我有一个数据帧

df = pd.DataFrame([["A","Q",98,56],["C","S",18,45], ["B","T",79,54], ["A","P",98,56],["C","R",18,45],["B","S",79,54], ["A","R",84,65],["B","Q",79,54],["C","Q",19,44]], columns=["id","prio","c1","c2"])

我有一份清单

Priority = ["P","R","Q","S","T"]

根据id、c1、c2选择重复的行。 如果我们发现重复的行，则根据prio列中列表中给定的优先级保留这些行

例如：对于id A的重复行，如果p和Q出现在列prio中，则优先考虑p并删除其他行，类似地，对于id B的重复行，T、S、Q出现在列prio中，因为在T、S中，Q排在列表的第一位。所以保留Q行

预期产出：

df_out = pd.DataFrame([["A","P",98,56],["C","R",18,45], ["A","R",84,65],["B","Q",79,54],["C","Q",19,44]], columns=["id","prio","c1","c2"]) 

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如何操作？

您可以将值转换为有序类别，然后与以下内容一起使用：

df['prio'] = pd.Categorical(df['prio'], categories=Priority, ordered=True)
df = df.sort_values('prio').drop_duplicates(['id','c1','c2'])
print (df)
  id prio  c1  c2
3  A    P  98  56
4  C    R  18  45
6  A    R  84  65
7  B    Q  79  54
8  C    Q  19  44