Is there in pandas operation complementary (opposite) to groupby?

问题

I have a table (data frame) with many columns. Now I would like to average values in one of the columns. It means that I need to group by over all columns except the one over which I need to average. Of course I can write:

df.groupby(['col1', 'col2', 'col3', 'col4', 'col5'])['vals'].mean()

But it would be nice if I could do something like:

df.groupby(['col6'], something='reverse')['vals'].mean()

Is it possible in pandas?

回答1:

You are searching for the complementary columns to a list you have on hands. You can play with df.columns. It represents an Index object that allows some interesting manipulations.

df.columns.drop(['col6']) returns an Index with the list of columns passed as argument removed. You can convert it into a list and use it as the groupby argument:

df.groupby(df.columns.drop(['col6']).tolist())['vals'].mean()

来源：https://stackoverflow.com/questions/16808682/is-there-in-pandas-operation-complementary-opposite-to-groupby