Matplotlib Subplots

Last Updated :23 Dec, 2024

In Matplotlib,subplots() function simplifies the creation of multiple plots within a single figure for organized visualization of various datasets.

Before diving into subplots, let's start with a simple plot usingmatplotlib.pyplot.plot():

Python

importmatplotlib.pyplotaspltplt.plot([1,2,3,4],[16,4,1,8])plt.show()

Output:

Simple plot using Python matplotlib — Plot using Python matplotlib

What is matplotlib.pyplot.subplots()?

Thesubplots() function inmatplotlib.pyplot creates a figure with a set of subplots arranged in a grid. It allows you to easily plot multiple graphs in a single figure, making your visualizations more organized and efficient.

Syntax: matplotlib.pyplot.subplots(nrows=1, ncols=1)
This syntax creates a figure withnrowsrows andncolscolumns of subplots.

Creating Multiple Plots with subplots()

In this example, we will usesubplots()to create two plots in a single figure.

Python

importmatplotlib.pyplotaspltimportnumpyasnp# Plot 1:x1=np.array([1,2,3,4])y1=np.array([10,20,25,30])plt.subplot(1,2,1)plt.plot(x1,y1)# Plot 2:x2=np.array([1,2,3,4])y2=np.array([30,25,20,10])plt.subplot(1,2,2)plt.plot(x2,y2)plt.show()

Output:

Screenshot-2024-12-03-145841 — Two side-by-side plots displaying different datasets.

The subplots() function in Matplotlib allows plotting multiple plots using the same data or axes. For example, setting nrows=1 and ncols=2 creates two subplots that share the y-axis.

Python

importmatplotlib.pyplotaspltimportnumpyasnpx=np.array([0,1,2,3])y=np.array([3,8,1,10])fig,ax=plt.subplots(1,2)ax[0].plot(x,y)ax[0].set_title('Plot 1')ax[1].plot(x,y,'r')ax[1].set_title('Plot 2')plt.show()

Output:

Screenshot-2024-12-03-150429 — Two side-by-side plots displaying different datasets.

Stacking Subplots in Two Directions

You can stack subplots vertically and horizontally by adjusting the nrows and ncols parameters in subplots(). This example demonstrates a 2x2 grid layout.

Python

# Implementation of matplotlib functionimportnumpyasnpimportmatplotlib.pyplotasplt# First create some toy data:x=np.linspace(0,2*np.pi,400)y1=np.sin(x)y2=np.sin(x**2)y3=y1**2y4=y2**2fig,ax=plt.subplots(nrows=2,ncols=2)ax[0,0].plot(x,y1,c='red')ax[0,1].plot(x,y2,c='red')ax[1,0].plot(x,y3,c='blue')ax[1,1].plot(x,y3,c='blue')ax[0,0].set_title('Simple plot with sin(x)')ax[0,1].set_title('Simple plot with sin(x**2)')ax[1,0].set_title('Simple plot with sin(x)**2')ax[1,1].set_title('Simple plot with sin(x**2)**2')fig.suptitle('Stacked subplots in two direction')plt.show()

Output:

Stacking subplots in two directions — A 2x2 grid of plots, each displaying different mathematical functions.

Sharing Axes Between Subplots

In some cases, you may want your subplots to share axes. This is useful when comparing datasets with similar ranges. By setting thesharex orshareyparameter toTrue, the subplots will share their x or y axis.

Example Code for Shared Axis:

Python

importnumpyasnpimportmatplotlib.pyplotaspltx=np.linspace(0,2*np.pi,400)y1=np.sin(x)y2=np.sin(x**2)fig,(ax1,ax2)=plt.subplots(2,sharex=True)ax1.plot(x,y1,c='red')ax2.plot(x,y2,c='red')ax1.set_ylabel('Simple plot with sin(x)')ax2.set_ylabel('Simple plot with sin(x**2)')fig.suptitle('Subplots with shared axis')plt.show()

Output:

Creating Polar Plots

Matplotlib also supports polar plots. You can create them by passing a dictionary with projection='polar'to thesubplot_kw parameter insubplots().

Example Code for Polar Axis:

Python

importnumpyasnpimportmatplotlib.pyplotaspltx=np.linspace(0,1.5*np.pi,100)y=np.sin(x**2)+np.cos(x**2)fig,axs=plt.subplots(nrows=2,ncols=2,subplot_kw=dict(polar=True))axs[0,0].plot(x,y)axs[1,1].scatter(x,y)fig.suptitle('matplotlib.pyplot.subplots() Example')plt.show()