# Topic: Lists & Tuples
nums = [1,2,3]
nums.append(4)
print(nums)

# Topic: Web Scraping
import requests
from bs4 import BeautifulSoup
r = requests.get('https://example.com')
soup = BeautifulSoup(r.text, 'html.parser')
print(soup.title.string)

# Topic: NumPy
import numpy as np
a = np.array([1,2,3])
print …

# Quiz data as a list of dictionaries
quiz = [
    {"question": "What is the capital of France?", "options": ["Paris", "London", "Berlin", "Rome"], "answer": "Paris"},
    {"question": "Which planet is known as the Red Planet?", "options": ["Earth", "Mars", "Venus", "Jupiter"], "answer": "Mars"},
    {"question": "Who wrote '1984'?", "options": ["George Orwell", "Mark Twain", "J.K. Rowling …

# 1. Import required libraries
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# 2. Create a sample movie dataset
data = {
    "title": ["Inception", "Titanic", "Avengers", "Shrek", "Up", "Coco", "Joker", "Frozen", "Toy Story", "Tenet"],
    "genre": ["Sci-Fi", "Romance", "Action", "Animation", "Animation", "Animation", "Drama", "Animation", "Animation", "Sci-Fi"],
    "year": [2010, 1997 …

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

sns.set(style="whitegrid")

data = {
    "OrderID": [1001, 1002, 1003, 1004, 1005, 1006],
    "Product": ["Laptop", "Mouse", "Keyboard", "Monitor", "Laptop", "Mouse"],
    "Category": ["Electronics", "Accessories", "Accessories", "Electronics", "Electronics", "Accessories"],
    "Price": [70000, 500, 1500, 12000, 72000, 550],
    "Quantity": [1, 2, 1 …

# Topic: Matplotlib & Seaborn
import matplotlib.pyplot as plt
plt.plot([1,2],[3,4])
plt.show()

# Topic: Dictionaries & Sets
s = set([1, 2, 3, 2])
print(s)

# Topic: OOP
class Student:
    def __init__(self, name): self.name = name
s = Student('Fahd')
print(s.name)

# Topic: Loops
while True:
    print('Break …

# Block 1: Install required packages (if not already installed)
!pip install yfinance matplotlib --quiet

# Block 2: Import necessary libraries
import yfinance as yf
import matplotlib.pyplot as plt
import pandas as pd

# Block 3: Set display options for better visualization
pd.set_option("display.max_rows", 10)
pd.set_option("display.float_format", "{:.2f …

    pip install pandas

Collecting pandas
  Downloading pandas-2.3.0-cp312-cp312-win_amd64.whl.metadata (19 kB)
Requirement already satisfied: numpy>=1.26.0 in c:\users\hp\miniconda3\envs\py312\lib\site-packages (from pandas) (2.3.1)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users …

print("Hello World")

Hello World

pip install scikit-learn

Collecting scikit-learn
  Downloading scikit_learn-1.7.0-cp312-cp312-win_amd64.whl.metadata (14 kB)
Requirement already satisfied: numpy>=1.22.0 in c:\users\hp\miniconda3\envs\py312\lib\site-packages (from scikit-learn) (2.3.1)
Collecting scipy>=1.8.0 (from scikit-learn …

# Topic: Regex
import re
text = 'email: test@example.com'
print(re.findall(r'\S+@\S+', text))

# Topic: Functions
def square(x): return x*x
print(square(5))

# Topic: File I/O
with open('test.txt', 'r') as f:
    print(f.read())

# Topic: Basic ML
from sklearn.linear_model import LinearRegression
model …