Total pyspark noob here. I have a dataframe similar to this:

df = spark.createDataFrame([
  Row(ttype='C', amt='12.99', dt='2024/01/01'),
  Row(ttype='D', amt='21.99', dt='2024/02/15'),
  Row(ttype='C', amt='16.99', dt='2024/01/21'),
])

I want to find the average amt for the last 30, 60 and 90 days for ttype='C' and ttype='D'

I can do this one at a time but I am looking for a more elegant way to do this.