PySpark: Fill NAs with mode of column based on aggregation of other columns

Question

I have a dataframe with 4 columns:

# Compute the mode to fill NAs for Item
values = [(None, \'Red\', 3, 10), (None, \'Red\', 6, 20), (\'A\', \'Green\', 5, 30),