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.
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.
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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