How can I customize the appearance of Pandas Dataframe HTML tables with styles and CSS?

Customize Pandas Dataframe HTML Table Appearance using Styles and CSS

In Python's Pandas library, you can manipulate and visualize dataframes. Sometimes, it's necessary to enhance the visual appeal of these dataframes by modifying their color schemes.

Problem: Coloration Customization for Dataframe Tables

Consider a Pandas dataframe where you need to color all values in rows labeled 'MOS' and alter the background color of specified header/index tables.

Solution: Employing Pandas Styling Functionalities

Pandas' styling capabilities (introduced in version 0.17.1) allow for flexible styling customization.

Highlighting MOS Rows:

To color the values in 'MOS' rows, define a function highlight_MOS(s) that checks for rows with the 'MOS' label and returns appropriate color codes.

<code class="python">def highlight_MOS(s):
    is_mos = s.index.get_level_values(1) == 'MOS'
    return ['color: darkorange' if v else 'color: darkblue' for v in is_mos]</code>

Apply Styles:

Use the style.apply() method to apply the highlight_MOS function, resulting in a styled dataframe s.

<code class="python">s = df.style.apply(highlight_MOS)</code>

Display the Styled Dataframe:

Printing s will display the dataframe with the color modifications applied.

<code class="python">print(s)</code>

This solution provides a concise and efficient method to customize the appearance of Pandas dataframes, making them more aesthetically appealing and informative.

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