Q.Store the Result data in a DataFrame called marksUT.
(Create the DataFrame from the case-study marks of the four students — Raman, Zuhaire, Ashravy and Mishti — across Unit Tests 1, 2 and 3 in the subjects Maths, Science, S.St, Hindi and Eng.)

import pandas as pd

marksUT = {'Name':['Raman','Raman','Raman','Zuhaire','Zuhaire','Zuhaire',
                    'Ashravy','Ashravy','Ashravy','Mishti','Mishti','Mishti'],
           'UT':[1,2,3,1,2,3,1,2,3,1,2,3],
           'Maths':[22,21,14,20,23,22,23,24,12,15,18,17],
           'Science':[21,20,19,17,15,18,19,22,25,22,21,18],
           'S.St':[18,17,15,22,21,19,20,24,19,25,25,20],
           'Hindi':[20,22,24,24,25,23,15,17,21,22,24,25],
           'Eng':[21,24,23,19,15,13,22,21,23,22,23,20]}
df = pd.DataFrame(marksUT)
print(df)

Output:

       Name  UT  Maths  Science  S.St  Hindi  Eng
0     Raman   1     22       21    18     20   21
1     Raman   2     21       20    17     22   24
2     Raman   3     14       19    15     24   23
3   Zuhaire   1     20       17    22     24   19
4   Zuhaire   2     23       15    21     25   15
5   Zuhaire   3     22       18    19     23   13
6   Ashravy   1     23       19    20     15   22
7   Ashravy   2     24       22    24     17   21 …

Why a dictionary-of-lists is the right constructor here

pd.DataFrame() accepts many input shapes, but when your source data is already organised as "one list of values per column," a dictionary of lists is the most direct fit: each key becomes a column name, each value (a list) becomes that column's data, top to bottom. Pandas aligns the lists by position — the 1st value in every list belongs to row 0, the 2nd value in every list belongs to row 1, and so on. So before writing any code, the real design question is: what does each row represent?

Here, each row must represent one student's marks in one unit test — not one student overall. Since there are 4 students × 3 unit tests, that's 12 rows, and each of the 7 lists (Name, UT, Maths, Science, S.St, Hindi, Eng) must therefore hold exactly 12 values, kept in the same student/test order throughout.

The real data (Table 3.1)

The code

import pandas as pd

marksUT = {
    'Name': ['Raman','Raman','Raman','Zuhaire','Zuhaire','Zuhaire',
              'Ashravy','Ashravy','Ashravy','Mishti','Mishti','Mishti'],
    'UT': [1,2,3,1,2,3,1,2,3,1,2,3],
    'Maths': [22,21,14,20,23,22,23,24,12,15,18,17],
    'Science': [21,20,19,17,15,18,19,22,25,22,21,18],
    'S.St': [18,17,15,22,21,19,20,24,19,25,25,20],
    'Hindi': [20,22,24,24,25,23,15,17,21,22,24,25],
    'Eng': [21,24,23,19,15,13,22,21,23,22,23,20]
}

df = pd.DataFrame(marksUT)
print(df)

Output:

       Name  UT  Maths  Science  S.St  Hindi  Eng
0     Raman   1     22       21    18     20   21
1     Raman   2     21       20    17     22   24
2     Raman   3     14       19    15     24   23
3   Zuhaire   1     20       17    22     24   19
4   Zuhaire   2     23       15    21     25   15
5   Zuhaire   3     22       18    19     23   13
6   Ashravy   1     23       19    20     15   22 …