Basic Plot Example

Using NumPy to create simple data and plot a line graph:

import numpy as np
import matplotlib.pyplot as plt
 
# Generate data
x = np.arange(0, 10)  # Array: 0 to 9
y = 2 * x  # y = 2 * x
 
# Plotting
plt.plot(x, y)  # Line plot
plt.xlabel('X Axis Label')  # X-axis label
plt.ylabel('Y Axis Label')  # Y-axis label
plt.title('Basic Line Plot')  # Title
plt.xlim(0, 6)  # Set X-axis range
plt.ylim(0, 12)
plt.show()  # Display the figure

🔍 Breakdown:

• plt.plot(x, y): Creates a line plot
• plt.xlabel('X Axis Label'): Adds a label to the X-axis
• plt.ylabel('Y Axis Label'): Adds a label to the Y-axis
• plt.title('Basic Line Plot'): Adds a title to the plot
• plt.show(): Displays the figure (essential for non-Jupyter environments)
• plt.xlim(0,6): Restricts the X-axis range to 0 to 6
• plt.ylim(0,12): Restricts the Y-axis range to 0 to 12

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Exporting a Plot

Matplotlib allows you to save plots in various formats:

plt.plot(x, y)
plt.savefig('example.png')  # Save as PNG

📌 Additional options:

• plt.savefig('example.png', dpi=300): Higher resolution (300 dpi)
• plt.savefig('example.pdf'): Save as PDF
• plt.savefig('example.svg'): Save as SVG (vector format)

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🎯 Summary:

• Matplotlib is a powerful, customizable library for data visualization
• Basic workflow: Import → Generate data → plt.plot() → Add labels/titles → plt.show()
• Customization: Adjust axis limits (xlim(), ylim()), labels (xlabel(), ylabel()), and title (title())
• Exporting: Use plt.savefig() to save in multiple formats