Scraping data from an HTML table into a pandas dataframe is advantageous because it enables quick and simple data manipulation and analysis utilizing pandas' robust data manipulation and analysis features.
Data analysis: If you need to perform data analysis on a table of data that is only available as HTML, scraping the table into a pandas dataframe can make it easier to perform operations like filtering, sorting, and aggregating the data.
Data visualization: Pandas has built-in functions for creating visualizations from dataframes, so scraping an HTML table into a dataframe can allow you to create visualizations of the data contained in the table.
Machine learning: If you want to use machine learning algorithms to analyze data from an HTML table, it may be necessary to scrape the table into a pandas dataframe so that you can manipulate the data in a way that is compatible with the machine learning libraries you are using.