OneCompiler

Hslip3

109

Q1]

<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Company Information</title> <style> body { background-color: #f0f0f0; /* Light gray background */ font-family: 'Comic Sans MS', cursive; /* Comic Sans MS font for the heading */ margin: 0; padding: 0; } 
#companyName {
  background-color: green; /* Green background color */
  color: red; /* Red text color */
  padding: 10px;
  text-align: center;
}

h1 {
  font-size: 24pt; /* Large font size for the heading */
}

#companyDescription {
  color: blue; /* Blue text color for the description */
  margin: 20px;
}
</style> </head> <body> <div id="companyName"> <h1>Company XYZ</h1> </div> <div id="companyDescription"> <p> Welcome to Company XYZ! We are a leading company in the industry, dedicated to providing high-quality services and products to our clients. With a focus on innovation and customer satisfaction, we strive to exceed expectations and create lasting partnerships. </p> </div> </body> </html>

Q2]
a]
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

Load Iris data

iris_data = pd.read_csv('iris.csv')

Create box plots for each feature across the three species

plt.figure(figsize=(12, 8))
sns.boxplot(x='species', y='sepal_length', data=iris_data)
plt.title('Distribution of Sepal Length Across Species')
plt.show()

plt.figure(figsize=(12, 8))
sns.boxplot(x='species', y='sepal_width', data=iris_data)
plt.title('Distribution of Sepal Width Across Species')
plt.show()

plt.figure(figsize=(12, 8))
sns.boxplot(x='species', y='petal_length', data=iris_data)
plt.title('Distribution of Petal Length Across Species')
plt.show()

plt.figure(figsize=(12, 8))
sns.boxplot(x='species', y='petal_width', data=iris_data)
plt.title('Distribution of Petal Width Across Species')
plt.show()

B]
import pandas as pd

Assuming the dataset is named 'heights_weights.csv'

data = pd.read_csv('heights_weights.csv')

View basic statistical details

statistical_details = data.describe()
print(statistical_details)