📥 Step 1: Import Matplotlib

import matplotlib.pyplot as plt

📈 Step 2: Line Plot Example

x = [1, 2, 3, 4, 5]
y = [10, 20, 25, 30, 40]
plt.plot(x, y)
plt.title("Simple Line Chart")
plt.xlabel("X Axis")
plt.ylabel("Y Axis")
plt.show()

Line charts help show trends over time.

📊 Step 3: Bar Chart Example

categories = ['A', 'B', 'C']
values = [10, 15, 7]
plt.bar(categories, values)
plt.title("Category Distribution")
plt.show()

Use bar charts to compare categories.

📊 Step 4: Histogram

import numpy as np
data = np.random.randn(1000)
plt.hist(data, bins=20)
plt.title("Histogram of Random Data")
plt.show()

Histograms are useful for showing data distribution.

🎯 Your Task:

• Create a line plot with your own data
• Try a bar chart showing 4 category counts
• Use plt.savefig() to save your charts