Q1]

<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Navigation Bar</title> <link rel="stylesheet" href="styles.css"> </head> <body> <nav class="navbar"> <div class="navbar-container"> <div class="logo">Your Logo</div> <ul class="nav-list"> <li><a href="#">Home</a></li> <li><a href="#">About</a></li> <li><a href="#">Services</a></li> <li><a href="#">Contact</a></li> </ul> </div> </nav> </body> </html> Q2] import pandas as pd from sklearn.preprocessing import LabelEncoder, OneHotEncoder

Load the dataset

df = pd.read_csv('Data.csv')

Display the original dataframe

print("Original DataFrame:")
print(df)

a. Apply OneHot coding on the 'Country' column

Using get_dummies method for simplicity

df_onehot = pd.get_dummies(df, columns=['Country'], prefix=['Country'])

Display the dataframe after OneHot coding

print("\nDataFrame after OneHot coding:")
print(df_onehot)

b. Apply Label encoding on the 'Purchased' column

label_encoder = LabelEncoder()
df['Purchased'] = label_encoder.fit_transform(df['Purchased'])

Display the dataframe after Label encoding

print("\nDataFrame after Label encoding:")
print(df)

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