Matplotlib Online

Python with numpy, pandas, matplotlib, scipy and scikit-learn. Your charts appear next to the output. Free, no sign-up.

Try an example

main.py

Press Run and your chart appears here.

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2 * np.pi, 200)

plt.plot(x, np.sin(x), label="sin(x)")
plt.plot(x, np.cos(x), label="cos(x)", linestyle="--")
plt.title("Sine and cosine")
plt.xlabel("x (radians)")
plt.ylabel("y")
plt.legend()
plt.grid(alpha=0.3)
plt.show()

print(f"{len(x)} points from 0 to {x[-1]:.2f}")

Plot Python graphs online, no install needed

Write Python, press Run, and your chart appears next to the code. This free online playground runs real Python 3.12 with numpy, pandas, matplotlib, scipy and scikit-learn already installed, so you can go from a few lines of data to a finished plot without setting up Jupyter, pip or a virtual environment.

Pick an example to start: a line chart, a scatter plot with colored groups, a histogram, k-means clusters on the iris dataset or a pandas bar chart. Change a number, run it again and watch the plot change. It is a quick place to test a plt call, check what a groupby returns, or try a scikit-learn model on a bundled dataset.

What this online Python graph plotter does

Real Python with the data science stack: numpy, pandas, matplotlib, scipy and scikit-learn are ready to import.
Charts drawn on the page: every figure your code makes with plt.show() appears beside the output, sharp at any size, and opens larger with one click.
Several figures in one run show as thumbnails, and Python warnings are listed above the chart instead of hiding in the output.
Your code is saved in your browser as you type. Copy it or download main.py to keep working in Jupyter or your own editor.

What you can plot in the matplotlib playground

Line charts of a function or a time series with plt.plot, a legend and labelled axes.
Scatter plots and histograms of random data from numpy.random, to see a distribution take shape.
Bar charts straight from pandas: group rows with groupby, sum them and call .plot(kind="bar").
Machine learning on scikit-learn's bundled datasets such as load_iris, load_wine and load_digits: clusters, decision boundaries and model scores.

Matplotlib online FAQ

Is this matplotlib online editor free?

Yes. It is free and needs no account: open the page, edit the code and press Run.

Which Python libraries can I use?

Python 3.12 with numpy, pandas, matplotlib, scipy and scikit-learn, plus the standard library. You cannot pip install other packages here.

Do matplotlib charts really show up?

Yes. Call plt.show() after plotting, or just leave the figure open at the end, and the chart appears next to the output. Line, scatter, bar, histogram, image and contour plots are drawn natively; a few kinds of chart are shown as the picture matplotlib rendered instead. One run shows up to 8 figures.

Can I use scikit-learn online here?

Yes. Import from sklearn as usual and train models such as KMeans, KNeighborsClassifier or LinearRegression. Use the datasets that ship with scikit-learn, like load_iris(), or build your own with numpy and pandas. Datasets that need a download, such as fetch_openml, are not available.

What are the limits?

A run has about 10 seconds, the code can be up to about 14 KB, and the program cannot read input, open files you upload or reach the internet. That is plenty for plots and small models. For bigger projects, copy your code into Jupyter or a local Python install.

How do I learn machine learning after trying it?

Change the examples and see what happens to the chart. When you want a guided path, Coddy's Machine Learning course teaches numpy, pandas, plotting and scikit-learn in short lessons that draw their charts in the same way.

Useful tools for Matplotlib

Free, browser-based tools that pair well with the Matplotlib Playground - all part of Coddy.

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