Realize your creativity with Python: Master the language and start your journey of innovation

import pandas as pd
import matplotlib.pyplot as plt

data = {'Name': ['Alice', 'Bob', 'Cathy', 'David'],
        'Age': [25, 30, 35, 40]}
df = pd.DataFrame(data)

plt.bar(df['Name'], df['Age'])
plt.xlabel('Name')
plt.ylabel('Age')
plt.title('Age Distribution')
plt.show()

import requests
from bs4 import BeautifulSoup

url = 'http://example.com'
response = requests.get(url)
soup = BeautifulSoup(response.content, 'html.parser')
print(soup.prettify())

from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
from sklearn.metrics import accuracy_score

iris = load_iris()
X, y = iris.data, iris.target
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

model = RandomForestClassifier()
model.fit(X_train, y_train)
predictions = model.predict(X_test)

print('Accuracy:', accuracy_score(y_test, predictions))