Pandas idiomatic way to do this custom copy row function?

I have a pd.DataFrame where each row represents a group of people. They have an id (I have several columns in my dataframe, but here is summarized by the columns of "id"my example dataframe ). Each of this group represents several people (columns "size").

I am trying to divide these groups into smaller groups of maximum size "max_size". For example, if max_size = 5the AND line "id" = "foo"and "size" = 13should consist of three lines, all are replaced "id" = "foo"with the respective "size" = 5, "size" = 5and"size" = 3

I've written a function that works, but I'm looking for a more pandas idiomatic way to do this, if it exists.

My function is

def custom_duplicating_function(df):
    def aux_custom_duplicating_function(row, max_size=5):
        row = row.to_dict()
        size = row["size"]
        L = [row.copy() for i in range((size // max_size + 1))]
        for i in range(len(L) - 1):
            L[i]["size"] = max_size 
        L[-1]["size"] = size%max_size
        return(pd.DataFrame.from_dict(L))

    temp = df.apply(aux_custom_duplicating_function, axis=1)
    result = pd.concat([temp[i] for i in range(len(temp.index))])
    return(result)

The following dataframe

test = pd.DataFrame.from_dict([{"id":"foo", "size":13},
                     {"id":"bar", "size":17},
                     {"id":"baz", "size":3}])
************
    id  size
0  foo    13
1  bar    17
2  baz     3
************

should be converted to

    id  size
0  foo     5
1  foo     5
2  foo     3
0  bar     5
1  bar     5
2  bar     5
3  bar     2
0  baz     3