Python color palettes are a powerful tool in the realm of data visualization and graphical design. Understanding the fundamental concepts, such as color models, and knowing how to use different libraries' color palettes, along with following common and best practices, can significantly enhance the quality of your visualizations.

The return value is an object that wraps a list of RGB tuples with a few useful methods, such as conversion to hex codes and a rich HTML representation. Calling color_palette() with no arguments will return the current default color palette that matplotlib (and most seaborn functions) will use if colors are not otherwise specified.

Picking colors manually often leads to a maze of unsuitable options. Luckily, the all-new PyPalettes package provides a collection of 2500+ palettes meticulously curated by hundreds of experts. This app lets you effortlessly explore various palettes and gives you two lines of code to use directly in your Matplotlib chart.

Hexadecimal: Another popular way to represent colors in Python is using hexadecimal codes. A hexadecimal color code starts with a # followed by six characters (0 - 9, A - F). For example, #FF0000 is pure red, #00FF00 is pure green, and #0000FF is pure blue. Matplotlib is a widely used library for data visualization in Python.