Understanding Matplotlib's Drawing Hierarchy: Plot, Axes, and Figure
When plotting with matplotlib, you encounter three key objects: plot, axes, and figure. The hierarchy and functionality of these objects can be confusing. Let's explore the differences and best practices.
Plot, Axes, and Figure: The Hierarchy
The figure is the container for the entire plot, representing the canvas on which the plot is drawn. It defines properties such as size, background color, and margins.
Axes are rectangular regions within the figure where data is plotted. Each axes object can contain multiple plots and has its own set of properties for configuring plot elements like labels, tick marks, and legends.
Plot is a graphical representation of data within an axes object. It can be a curve, scatter plot, histogram, or other visual representation.
Three Ways to Draw Plots
You can create plots in matplotlib using three different approaches:
Best Practices
The choice of which method to use depends on the nature of your plot and the level of customization required:
By understanding the hierarchy and functionality of plot, axes, and figure, you can effectively create customized and informative plots in matplotlib.
The above is the detailed content of Here are a few question-based titles that capture the essence of the article: * Matplotlib\'s Plotting Hierarchy: Figure, Axes, and Plot – What\'s the Difference? * How to Choose the Right Approach. For more information, please follow other related articles on the PHP Chinese website!