Data visualization is a powerful tool for understanding and communicating patterns and insights from data. In Python development services, there are several libraries available for creating compelling visualizations, such as Matplotlib, Seaborn, Plotly, and Bokeh. In this comprehensive guide, we will explore the basics of data visualization in Python and learn how to create various types of visualizations.
1. Installation: Before getting started, make sure you have Python installed on your system. You can install the necessary libraries using pip, the Python package manager. Open a terminal or command prompt and run the following commands: