在一列中查找重复项,比较另一列,修改数据帧中的第三列

你说总是有两个重复的条目,所以你可以简单地使用 idxmax + loc :

m = df.groupby('PlayerName')['Salary'].idxmax()
df.loc[m, 'Position'] = 'CPT' + df.loc[m, 'Position'].map(' ({})'.format)

  PlayerName  Salary   Position
0        Joe    3000        FWD
1        Joe    4500  CPT (FWD)
2       Bill    3200  CPT (CNT)
3       Bill    2000        CNT
4       Jill    1200        GRD
5       Jill    2200  CPT (GRD)

你可以找到每个玩家的“最高工资”列,然后你可以匹配索引(当你和玩家的最高工资在同一行时,这将为你提供真实的工资),并更新这些索引的职位字符串值。试试下面的:

player_df = pd.DataFrame(columns=["PlayerName", "Salary", "Position"], data=[
["Joe", 3000, "FWD"],
["Joe", 4500, "FWD"],
["Bill", 3200, "CNT"],
["Bill", 2000, "CNT"],
["Jill", 1200, "GRD"],
["Jill", 2200, "GRD"]])

player_df["top_sal"] = player_df.groupby("PlayerName")["Salary"].transform("max")
player_df.loc[player_df["top_sal"] == player_df["Salary"], "Position"] = "CPT (" + player_df["Position"] + ")"