更有效的方法来迭代 groupby Pandas 数据框？

Question

I have this snippet code that groupby column ID from a pandas dataframe and appends in a result dataframe all the top salaries from a unique ID. The code works but is kind of slow with larger files. I was wondering if someone could suggest a more efficient way.

groupe = df.groupby("ID")
t = (group.sort_values(by="Salary", ascending=False)[:1] for yr, group in groupe)
result = pd.DataFrame() 
     for i in t:
        result = result.append(i)

Answer 1

df.groupby('ID').max()

You can then select the salaries column.

Edit

If you want to retain all other columns, even the non-numerical, this should do the job:

df.sort_values(by="Salary", ascending=False).groupby('ID').first()