Q1: Consider the following df (copy paste the code to get the df): df=pd.DataFrame([[80,90,85],[70,50,60],[89,87,82],[90,90,75]],columns=['M ath','Physics','Arabic'), index=['Ali','Sara','Taha','Ala']) Math Physics Arabic Ali 80 90 85 Sara 70 50 60 Taha 89 87 82 Ala 90 90 75 A. Convert the given df to NumPy array. B. Using NumPx functions find the following: 1. The max mark of all results 2. The average mark for every subject 3. The worst mark for every student 4. Add 2 marks for Arabic subject for all students 5. Using array slicing print the results for Sara and Ala for Math and Arabic courses 6. Add(Append) a new student marks with values Math: 95, Physics:99, Arabic:99 7. Change the shape of the array so that every column represents a student instead of a subject. 8. After the change convert the array to Dataframe