What is Pyplot?

Pyplot is a Matplotlib library module that provides a MATLAB-like interface that can be used for creating and customizing plots and figures. This module offers a state-based, procedural interface for quickly and easily creating visualizations, which makes this module very useful for creating simple and quick plots. The key features of the Pyplot are a state-based interface, simple and intuitive, similar syntax like in MATLAB, comprehensive plotting capabilities, integration with numpy, customization, styling, saving, and exporting.

• State-based interface - The pyplot module maintains a state machine which means that you can incrementally build plots. This process is similar to MATLAB. Using new/additional functions you can create and modify the current plot. The Python keeps track of the figures and axes for you.
  The state-based interface has a couple of functions that will act on a currently defined state. This differs from the object-oriented approach, where object methods are used. For example, let's say that you have the following block of code

  import matplotlib.pyplot as plt
  plt.scatter(x,y)

  The previous block of code will call the pyplot.plt module from the matplotlib library and create a scatter plot. So this code puts pyplot in a state where a current figure and current aces are defined. If the next line of code is

  plt.title("the matplotlib tutorials")

  this will create a title of the current axes that is stored in the pyplot state. The final code line will display the plot and is written as

  plt.show()

  This code will show all the figures stored in the pyplot state.
  
• Simple and intuitive - The main goal when they were creating the pyplot module is that it is easy to use. Using this module the common tasks that can be achieved with a few lines of code are line plots, scatter plots, bar charts,...The simplicity of this module makes it favorable for beginners to use whi is enew in data visualization in PYthon.

The advantages of using the pyplot module are ease of use, quick prototyping, and education purposes. The state-based nature of Pyplot makes it very straightforward to create quick plots without needing to understand the underlying object-oriented structure of Matplotlib. Pyplot is excellent for prototyping and exploratory data analysis where you need to generate visualizations quickly to understand the data. The simplicity makes it an excellent tool for teaching data visualization concepts to beginners.