{"version":"1.0","type":"rich","title":"Loading and Parsing diabetes risk CSV Data","description":"This example loads a diabetes risk prediction dataset from UCI’s machine learning repository, sourced from Sylhet Hospital in Bangladesh, and displays its size in kilobytes, row count, and column count. The visualization uses d3.csv to fetch and parse the CSV file, then d3.csvFormat to calculate the file size, with the summary rendered in a large-text <pre> element. It also includes commented-out alternatives using fetch, async/await, and d3.csvParse, demonstrating different ways to handle asynchronous data loading.","provider_name":"VizHub AI Studio","provider_url":"https://vizhub.com","html":"<iframe src=\"https://vizhub.com/viz/8e8dc29221e944fbbae17745889890be?mode=embed\" width=\"960\" height=\"500\" scrolling=\"no\" frameborder=\"0\"></iframe>","width":960,"height":500,"cache_age":3600}