1. File Handling

Q1. Log File Analyzer

with open("log.txt", "w") as f:
    f.write("""System started successfully
User logged in
ERROR: Invalid password
Connection established
ERROR: Database not found
User logged out
ERROR: Timeout occurred
System shutdown""")

error_count = 0

with open("log.txt", "r") as f:
    with open("errors.txt", "w") as out:
        for line in f:
            if "ERROR" in line:
                error_count += 1
                out.write(line)

print("Total errors:", error_count)

Total errors: 3

Q2. Student Record Cleaner

with open("students.txt", "w") as f:
    f.write("""Alice,85
Bob,abc
Charlie,90
David,78
Eva,9O
Frank,100
Grace,seven
Helen,88""")

with open("students.txt", "r") as f:
    with open("cleaned.txt", "w") as out:
        for line in f:
            name, mark = line.strip().split(",")
            if mark.isdigit():        # checks if all characters are numbers
                out.write(line)

Q3. Append vs Write Demonstration

# Step 1 — Create data.txt
with open("data.txt", "w") as f:
    f.write("Python\nJava\nC++")

# Step 2 — Append
with open("data.txt", "a") as f:
    f.write("\nJavaScript")

print("After append:")
with open("data.txt") as f:
    print(f.read())

# Step 3 — Overwrite
with open("data.txt", "w") as f:
    f.write("JavaScript")

print("\nAfter write:")
with open("data.txt") as f:
    print(f.read())

After append:
Python
Java
C++
JavaScript

After write:
JavaScript

2. Modules & PIP

Q4. stats.py Module

stats.py

def mean(numbers):
    return sum(numbers) / len(numbers)

def maximum(numbers):
    return max(numbers)

def minimum(numbers):
    return min(numbers)

with open("stats.py", "w") as f:
    f.write("""
def mean(numbers):
    return sum(numbers) / len(numbers)

def maximum(numbers):
    return max(numbers)

def minimum(numbers):
    return min(numbers)
""")

import stats

data = [12, 45, 23, 67, 34]

print("Mean:", stats.mean(data))
print("Max:", stats.maximum(data))
print("Min:", stats.minimum(data))

Mean: 36.2
Max: 67
Min: 12

Q5. Namespace Conflict

mathops.py

def add(a, b):
    return a + b

stringops.py

def add(a, b):
    return a + b

with open("mathops.py", "w") as f:
    f.write("""
def add(a, b):
    return a + b
""")

with open("stringops.py", "w") as f:
    f.write("""
def add(a, b):
    return a + b
""")

import mathops as m
import stringops as s

print(m.add(10, 5))          # 15
print(s.add("Hello ", "World"))   # Hello World

15
Hello World

Q6. External Package Example (using camelcase)

!pip install camelcase

Requirement already satisfied: camelcase in /usr/local/lib/python3.12/dist-packages (0.2)

import camelcase
c = camelcase.CamelCase()

print(c.hump("python is very powerful"))

Python is Very Powerful

3. Introduction to Numpy

Q7. Marks Matrix

import numpy as np

marks = np.array([
    [80, 70, 90, 60],
    [75, 85, 95, 65],
    [60, 70, 80, 90]
])

print("2nd student:", marks[1])
print("Subject 3:", marks[:, 2])
print("Highest mark:", np.max(marks))

2nd student: [75 85 95 65]
Subject 3: [90 95 80]
Highest mark: 95

Q8. Slice Even Positions

arr = np.array([10, 20, 30, 40, 50, 60, 70])
print(arr[1::2])

[20 40 60]

Q9. Copy vs Slice

arr = np.array([10, 20, 30, 40])

copy_arr = arr.copy()
slice_arr = arr[1:3]

arr[1] = 99

print(arr)        # [10 99 30 40]
print(copy_arr)   # unchanged
print(slice_arr)  # changed because slice is a view\

[10 99 30 40]
[10 20 30 40]
[99 30]

4. Introduction to Matplotlib

Q10. Weekly Temperature Plot

import matplotlib.pyplot as plt
import numpy as np

temps = np.array([22, 24, 19, 23, 25, 21, 20])
days = np.array([1,2,3,4,5,6,7])

plt.plot(days, temps)
plt.title("Weekly Temperature")
plt.xlabel("Day")
plt.ylabel("Temperature")
plt.show()

Q11. Compare Two Students

import matplotlib.pyplot as plt
import numpy as np

A = np.array([70, 75, 80, 85])
B = np.array([60, 65, 78, 88])
x = np.array([1, 2, 3, 4])

plt.plot(x, A)
plt.plot(x, B)
plt.title("Student Performance")
plt.xlabel("Test")
plt.ylabel("Marks")
plt.show()

Q12. Debugging the Graph

Wrong Code

x = np.array([1, 2, 3, 4])
y = np.array([10, 20, 30])
plt.plot(x, y)

Error: x and y must be the same length

x = np.array([1, 2, 3])
y = np.array([10, 20, 30])
plt.plot(x, y)
plt.show()

Q13. Kinematics

import matplotlib.pyplot as plt
import numpy as np

time = np.array([1,2,3,4])
speed = np.array([10,20,30,40])
distance = np.array([10,40,90,160])

plt.subplot(2,1,1)
plt.plot(time, speed)
plt.title("Speed vs Time")

plt.subplot(2,1,2)
plt.plot(time, distance)
plt.title("Distance vs Time")

plt.tight_layout()
plt.show()

Bonus: Mixed File Analyzer

with open("mixed.txt", "w") as f:
    f.write("""ERROR Disk full
User login
75
ERROR Network down
hello
100
ERROR Access denied
42""")

with open("mixed.txt", "r") as f, \
     open("errors.txt", "w") as e, \
     open("numbers.txt", "w") as n:

    for line in f:
        line = line.strip()
        if "ERROR" in line:
            e.write(line + "\n")
        elif line.isdigit():
            n.write(line + "\n")

import matplotlib.pyplot as plt
import numpy as np

xpoints = np.array([0, 6])
ypoints = np.array([0, 250])

plt.plot(xpoints, ypoints)
plt.show()

import matplotlib.pyplot as plt
import numpy as np

xpoints = np.array([1, 8])
ypoints = np.array([3, 10])

plt.plot(xpoints, ypoints, 'o')
plt.show()

import matplotlib.pyplot as plt
import numpy as np

xpoints = np.array([1, 2, 6, 8])
ypoints = np.array([3, 8, 1, 10])

plt.plot(xpoints, ypoints,"o")
plt.show()

import matplotlib.pyplot as plt
import numpy as np

ypoints = np.array([3, 8, 1, 10, 5, 7])

plt.plot(ypoints)
plt.show()

import matplotlib.pyplot as plt
import numpy as np

x = np.array([1,2,3,4])
temp = np.array([22, 24, 19, 23])
sales = np.array([200, 300, 250, 400])

plt.subplot(2, 1, 1)
plt.plot(x, temp)
plt.title("Temperature")

plt.subplot(2, 1, 2)
plt.plot(x, sales)
plt.title("Sales")

plt.tight_layout()
plt.show()