{"id":18056,"date":"2021-06-15T04:30:30","date_gmt":"2021-06-14T23:00:30","guid":{"rendered":"http:\/\/www.fusioncharts.com\/blog\/?p=18056"},"modified":"2026-01-20T14:37:14","modified_gmt":"2026-01-20T09:07:14","slug":"visualizing-distributions-of-machine-learning-data-via-box-and-whiskers-plot","status":"publish","type":"post","link":"https:\/\/www.fusioncharts.com\/blog\/visualizing-distributions-of-machine-learning-data-via-box-and-whiskers-plot\/","title":{"rendered":"Visualizing of Machine Learning Data Via Box & Whiskers Plot 2026"},"content":{"rendered":"It is critical to get familiar with the data when conducting exploratory data analysis in machine learning. Automated systems for generating informative summaries and descriptive statistics are essential, especially when dealing with large datasets with numerous columns (also known as features).\u00a0<\/span>FusionCharts<\/span><\/a>\u00a0is a Javascript library that allows you to create beautiful and dynamic charts, maps, and plots to understand your data and its many aspects better.<\/span>\r\n\r\nA\u00a0<\/span>box and whiskers plot<\/span><\/a>\u00a0is a visualization of the\u00a0<\/span>five-number summary<\/span><\/a>\u00a0of a dataset, which includes the minimum, maximum, median, first quartile (center of the lower half of data), and the third quartile (center of the upper half of data). Plotting the five-number summary, therefore, gives not only a pretty good idea of the dispersion of data but also its skewness. This makes a box and whiskers plot a simple yet powerful tool for the statistics, data science, and machine learning community.<\/span>\r\n\r\nRead on to find out how to generate the box and whiskers plot for the various categories present in your machine learning dataset. We’ll use the well-known\u00a0<\/span>Iris dataset<\/span><\/a>\u00a0from the\u00a0<\/span>UCI Machine Learning Repository<\/span><\/a> for creating its corresponding box and whiskers plot in our powerful data visualization tool<\/a>.<\/span>\r\n
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