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In Matplotlib library a figure is the top-level container that holds all elements of a plot or visualization. It can be thought of as the window or canvas where plots are created. A single figure can contain multiple subplots i.e. axes, titles, labels, legends and other elements. The figure() function in Matplotlib is used to create a new figure.
Syntax
The below is the syntax and parameters of the figure() method.
plt.figure(figsize=(width, height), dpi=resolution)
Where,
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figsize=(width, height) − Specifies the width and height of the figure in inches. This parameter is optional.
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dpi=resolution − Sets the resolution or dots per inch for the figure. Optional and by default is 100.
Creating a Figure
To create the Figure by using the figure() method we have to pass the figure size and resolution values as the input parameters.
Example
import matplotlib.pyplot as plt # Create a figure plt.figure(figsize=(3,3), dpi=100) plt.show()
Output
Figure size 300x300 with 0 Axes
Adding Plots to a Figure
After creating a figure we can add plots or subplots (axes) within that figure using various plot() or subplot() functions in Matplotlib.
Example
import matplotlib.pyplot as plt # Create a figure plt.figure(figsize=(3, 3), dpi=100) x = [12,4,56,77] y = [23,5,7,21] plt.plot(x,y) plt.show()
Output
Displaying and Customizing Figures
To display and customize the figures we have the functions plt.show(),plt.title(), plt.xlabel(), plt.ylabel(), plt.legend().
plt.show()
This function displays the figure with all the added plots and elements.
Customization
We can perform customizations such as adding titles, labels, legends and other elements to the figure using functions like plt.title(), plt.xlabel(), plt.ylabel(), plt.legend() etc.
Example
In this example we are using the figure() method of the pyplot module by passing the figsize as (8,6) and dpi as 100 to create a figure with a line plot and includes customization options such as a title, labels and a legend. Figures can contain multiple plots or subplots allowing for complex visualizations within a single window.
import matplotlib.pyplot as plt
# Data
x = [1, 2, 3, 4, 5]
y = [2, 4, 6, 8, 10]
# Create a figure
plt.figure(figsize=(8, 6), dpi=100)
# Add a line plot to the figure
plt.plot(x, y, label=''Line Plot'')
# Customize the plot
plt.title(''Figure with Line Plot'')
plt.xlabel(''X-axis'')
plt.ylabel(''Y-axis'')
plt.legend()
# Display the figure
plt.show()
Output
Example
Here this is another example of using the figure() method of the pyplot module to create the subplots.
import matplotlib.pyplot as plt
# Create a figure
plt.figure(figsize=(8, 6))
# Add plots or subplots within the figure
plt.plot([1, 2, 3], [2, 4, 6], label=''Line 1'')
plt.scatter([1, 2, 3], [3, 5, 7], label=''Points'')
# Customize the figure
plt.title(''Example Figure'')
plt.xlabel(''X-axis'')
plt.ylabel(''Y-axis'')
plt.legend()
# Display the figure
plt.show()
Output
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