Matplotlib.pyplot.axes() in Python (original) (raw)

Last Updated : 31 May, 2025

**axes() method in Matplotlib is used to create a new Axes instance (i.e., a plot area) within a figure. This allows you to specify the location and size of the plot within the figure, providing more control over subplot layout compared to plt.subplot(). It's key features include:

• Creates a new Axes at a specified position inside the figure.
• Allows precise control of the Axes position using normalized figure coordinates.
• Returns an Axes object for further customization and plotting.
• Supports multiple Axes in a single figure for complex layouts.

**Example:

Python `

import matplotlib.pyplot as plt import numpy as np

fig = plt.figure() ax = plt.axes([0.1, 0.1, 0.8, 0.8])

x = np.linspace(0, 10, 100) y = np.sin(x) ax.plot(x, y) plt.show()

`

**Output

Using Matplotlib.pyplot.axes()

**Explanation:

• **plt.figure() creates a blank figure and **plt.axes([0.1, 0.1, 0.8, 0.8]) adds a subplot positioned within it.
• **np.linspace(0, 10, 100) creates 100 points and np.sin(x) computes their sine values.
• **ax.plot(x, y) plots the sine wave.

Syntax

matplotlib.pyplot.axes(*args, **kwargs)

**Parameters: The parameters can be passed in different ways:

**1. Positional Argument rect: A list or tuple of 4 floats [left, bottom, width, height] and defines the position and size of the axes as fractions of the figure width and height, all values between 0 and 1.

• **left: The distance from the left side of the figure to the left side of the axes.
• **bottom: The distance from the bottom of the figure to the bottom of the axes.
• **width: The width of the axes.
• **height: The height of the axes.

**2. Keyword Arguments (kwargs): A dictionary of additional keyword arguments to customize the Axes object. Some common keyword arguments include:

• **polar: A boolean value (True or False). If True, creates a polar plot.
• **facecolor: A color value to set the background color of the axes.
• **projection: A string specifying the projection type (e.g., 'polar').
• Other Axes properties can also be passed as keyword arguments for further customization.

****Returns: (**Axes) An instance of matplotlib.axes.Axes (or a subclass like Axes3D) .The newly created Axes object which can be used to plot data and customize the plot.

Examples

**Example 1: In this example we are creating multiple axes in one figure.

Python `

import matplotlib.pyplot as plt import numpy as np

fig = plt.figure() ax1 = plt.axes([0.1, 0.1, 0.35, 0.8]) # Left small axes ax2 = plt.axes([0.55, 0.1, 0.35, 0.8]) # Right small axes

x = np.linspace(0, 10, 100) ax1.plot(x, np.sin(x)) ax2.plot(x, np.cos(x))

plt.show()

`

**Output

Using Matplotlib.pyplot.axes()

**Explanation:

• **plt.figure() initializes a blank figure and **plt.axes() adds two Axes objects (ax1 and ax2) with specified positions using normalized figure coordinates [left, bottom, width, height].
• **ax1 (left side) is 10% from left, 10% from bottom, 35% width, 80% height, and ax2 (right side) is 55% from left, 10% from bottom, 35% width, 80% height.
• **np.linspace(0, 10, 100) generates 100 evenly spaced x-values between 0 and 10.

**Example 2: In this example, we are creating 3d axes

Python `

import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D import numpy as np

fig = plt.figure() ax = plt.axes([0.1, 0.1, 0.8, 0.8], projection='3d')

x = np.linspace(-5, 5, 100) y = np.linspace(-5, 5, 100) X, Y = np.meshgrid(x, y) Z = np.sin(np.sqrt(X2 + Y2))

ax.plot_surface(X, Y, Z, cmap='viridis') plt.show()

`

**Output

Using Matplotlib.pyplot.axes()

**Explanation:

• **plt.axes() creates a 3D Axes at position [0.1, 0.1, 0.8, 0.8] with projection='3d'.
• **np.linspace(-5, 5, 100) generates 100 points for both x and **y and **np.meshgrid(x, y) creates a 2D grid.
• **np.sin(np.sqrt(X**2 + Y**2)) calculates height values as the sine of the distance from the origin.
• **ax.plot_surface() plots the 3D surface using the viridis colormap.