Python for Data Analysis: Step-By-Step with Projects - Distribution of One Feature

This lesson covers data visualization techniques for exploring the distribution of numerical and categorical features. It introduces methods like describe, histograms, box plots, and KDE plots for numerical data, and value counts and bar plots for categorical data. The lesson emphasizes understanding data distributions and the importance of visualizations in data analysis.

What is the purpose of using the value counts method for categorical features?

How can we visualize the distribution of categorical data?

What are the limitations of the plots created by the Pandas library?

What will be covered in the next lesson regarding data visualization?