I’ve got an assignment to use a lambda function in agg to aggregate an imported dataframe returning the number of rows with a value greater than 1.5. So far I have the following, but I don’t think its exactly what I’m supposed to pull and further so, it doesn’t have the built in function.

print(df.iloc[:,:-1].agg([lambda x : [i for i in x if i> 1.5]]))

Your attempt is pretty close if your want it per column. Your lambda should be lambda x: len([i for i in x if i > 1.5]).

However, I don’t understand why the assignment says to use agg. It’s typically used for applying multiple independent operations to a DataFrame and aggregating the results. If all you want is a single result (“number of rows containing a value greater than 1.5”) apply is a better choice.

If you read it as “show, for each column, the number of rows where …”, then @abessman’s suggestion works very nicely.
If you want to count the number of rows where all columns need to be > 1.5 then it can be simplified: