Pandas DataFrame formatting and styling can help clients or stakeholders by presenting data in more visually appealing and easy to understand format.

I would like to provide you with multiple examples of how to customize and format Pandas DataFrame using styling and formatting techniques, in order to give you a more detailed understanding of how to work with and present data effectively.

What you will learn:

1.) How can you apply number formatting in Pivot and DataFrame?
2.) How do you set DataFrame background colors based on numbers?
3.) What is the method to highlight missing values in a specific color?
4.) What is the process to highlight the maximum or minimum from a specific column?
5.) How can you apply Conditional Bar formatting on quantitative columns and align data accordingly?
6.) What are the steps to set background gradient using cmap or seaborn?
7.) How can you highlight Pandas DataFrame cells based on hover?
8.) How can you use HTML and CSS to design or format the DataFrame?
9.) How do you export a DataFrame in Excel with formatting?
10.) How can you hide (not delete) rows and columns from a DataFrame?
11.) How to apply conditional formatting or border on DataFrame’s header and index?
12.) Examples…

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