Pyspark: orderby top 10 count descending breaking ties?

Question

I have the following dataframe where I am grouping by id1 and id2, then ordering by count in descending order. I want to break tie breakers by whichever has the higher rate value. Here is what I have for my code currently:

df.groupBy('ID1', 'ID2').agg((avg("amount")/avg("distance")).alias("rate"), count("*").alias("count")).orderBy(desc('count'), desc('rate')).limit(10).show()

and my output is:

Any help is greatly appreciated!