Programming in Python

Looping

Looping is the process of repeating a block of statements again and again until a given condition is satisfied. Examples: FOR, WHILE and DO...WHILE loops.

(a) def

In Python, a function is defined using the def keyword, followed by the function name and parentheses — for example, def add(a, b):. The other options are not Python keywords.

(a) Replace int() with float() and keep the same condition.

int("4.5") raises a ValueError because int() cannot directly convert a decimal string. Using float() accepts values like 4.5, and the condition num % 2 == 0 still correctly identifies whole even numbers.

def area_circle(r):
    return 3.14 * r * r

The function takes the radius r and returns the area $\pi r^2$ using $\pi = 3.14$. For example, area_circle(7) returns $3.14 \times 49 = 153.86$.

try:
    num = int(input("Enter a number: "))
    print("You entered:", num)
except ValueError:
    print("Invalid input! Please enter a numeric value.")

Explanation: The int() function raises a ValueError if the input cannot be converted to an integer (for example, "abc"). The except ValueError block catches this error and displays a friendly message instead of crashing the program.

Data visualization means presenting data in pictorial or graphical form — bar graphs, pie charts, line graphs — instead of plain tables of numbers. It can solve the teacher's problem in the following ways:

• Easy comparison: A bar graph of marks in each subject shows at a glance which subject is strong and which is weak, while in a table the student has to read and compare each number.
• Quick understanding of trends: A line graph of marks across several exams shows whether performance is improving or falling, which a table cannot show directly.
• Clear picture of the whole result: A pie chart shows each subject's share of the total marks, so the student instantly sees where most marks came from or were lost.
• Saves time and reduces confusion: Large amounts of data become simple and interesting, so students understand their performance faster and are motivated to improve.

So, by converting the result table into charts and graphs, the teacher makes performance easy to see, compare and act upon.

(a) Output

     Name  Marks
1  Bikash     72
2  Chandra    60

The condition df['Marks']>=60 keeps only the rows where Marks is 60 or more. Bikash (72) and Chandra (60) satisfy it, so those two rows are printed with their original index labels 1 and 2. Asha (45) is dropped.

(b) Modified code

import pandas as pd
data = {'Name':['Asha','Bikash','Chandra'],
'Marks':[45,72,60]}
df = pd.DataFrame(data)
print(df[df['Marks']<60])

Output:

   Name  Marks
0  Asha     45

Only the condition changes from >=60 to <60, so just Asha's row is displayed.