Run Matplotlib Online – Free Matplotlib Online Compiler

Run a Matplotlib plot and charts in your browser with our free online Matplotlib compiler. No installation or signup required – Try It Now.

Start Plotting Now →See the Code

Try This Matplotlib Example

import matplotlib.pyplot as plt
import numpy as np

# Generate data
x = np.linspace(0, 2 * np.pi, 200)
y_sin = np.sin(x)
y_cos = np.cos(x)

# Create figure with two subplots
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))

# Sine wave
ax1.plot(x, y_sin, linewidth=2)
ax1.set_title('Sine Wave')
ax1.set_xlabel('x')
ax1.set_ylabel('sin(x)')
ax1.grid(True, alpha=0.3)

# Cosine wave
ax2.plot(x, y_cos, linewidth=2)
ax2.set_title('Cosine Wave')
ax2.set_xlabel('x')
ax2.set_ylabel('cos(x)')
ax2.grid(True, alpha=0.3)

plt.suptitle('Trigonometric Functions', fontsize=14, fontweight='bold')
plt.tight_layout()
plt.savefig('trig_functions.png', dpi=100, bbox_inches='tight')
plt.show()
print("Chart rendered successfully!")
Open in full editor →Loads instantly in your browser. No install.

What You Can Do With Matplotlib Online

Line, Bar & Scatter Charts

Create publication-quality plots using plt.plot(), plt.bar(), plt.scatter(), and plt.subplots(). Customise titles, labels, colours, and grids.

Charts Render Inline

Matplotlib output renders as an image directly in the output panel. No file downloads needed — see your chart the moment the code runs.

Full NumPy Integration

Use NumPy to generate and transform your data, then pass it straight to Matplotlib. Both libraries are pre-loaded and ready to use together.

How to Plot Your First Chart Online

Using our browser-based Python environment, you can generate data and visualize it instantly without setting up a local IDE. Here is a quick guide to getting started with the Matplotlib online compiler:

  1. Import the Library: Start by importing the required module: import matplotlib.pyplot as plt. (NumPy is also highly recommended for generating data).
  2. Prepare Your Data: Create your X and Y axis data points. For example, use np.linspace() to generate an array of numbers.
  3. Create the Plot: Call plt.plot(x, y) or plt.scatter(x, y) to define your chart type. You can easily customize labels, titles, and grids.
  4. Render the Image: Crucially, call plt.show() at the end of your script. Our compiler intercepts this call and securely renders the chart as an inline image right in your browser.

For advanced charting options, 3D plots, and custom styling, be sure to check out the official Matplotlib documentation.

Frequently Asked Questions

Can I run Matplotlib online without installing Python?

Yes. PythonHere runs Python in your browser via WebAssembly (Pyodide). Matplotlib is pre-loaded — just import matplotlib.pyplot as plt and run.

Will my charts actually display in the browser?

Yes. Matplotlib charts render as inline images in the output panel. You can see your plots immediately after running the code.

Is it free?

100% free, forever. No account required, no time limit, no credit card.

Can I use NumPy and pandas with Matplotlib?

Yes. NumPy, pandas, and Matplotlib are all pre-installed and available simultaneously. Build your data pipeline and visualise it in one script.

Plot Your First Chart in the Browser

Free forever. No install. No signup.

Open the Matplotlib Editor →