Having established the foundational components of a Matplotlib figure and axes in the previous chapter, we now turn to creating specific types of plots suited for common data analysis tasks. This section focuses on generating visualizations designed for comparing quantities and understanding data distributions.

You will learn to:

• Create vertical and horizontal bar charts using plt.bar() and plt.barh() for comparing categorical data.
• Generate histograms with plt.hist() to visualize the frequency distribution of a single numerical variable, including how to adjust the number of bins.
• Construct pie charts using plt.pie() to represent proportions within a whole, while also considering their limitations.
• Briefly touch upon stacking plots for visualizing component contributions.

By the end of this chapter, you will be able to select and implement appropriate basic Matplotlib plot types for different analytical scenarios.