I used AI in order to help with the cleaning the code and figuring out why I could not upload it to RPUBS

The dataset used in this tutorial is food_stamps from the dslabs package. This data includes the annual number of participants (in millions) and the total cost (in billions of dollars) for the U.S. Supplemental Nutrition Assistance Program. I did a multivariable bubble plot with the help of ai to make the points look more like "bubbles". By mapping the number of participants to both the size and the color of the bubbles, add a third dimension to the standard Year vs. Cost scatter plot. I utilized the highcharter library to ensure the graph is interactive, allowing to hover over specific data points to see exact values. While the growth in costs and participants was relatively linear and gradual from the 1970s through the 1990s, there is a dramatic "explosion" in both variables starting around 2008. The bubbles not only move higher on the Y-axis (indicating skyrocketing costs) but also grow significantly larger and darker in color (indicating a massive increase in participants).

The data shows the total rate as well as rates based on sex, age, and race. Rates are also shown for three specific kinds of cancer: breast cancer, colorectal cancer, and lung cancer.​ This dataset comes from the CORGISD ( The collection of Really Great Interesting , Situated Data) where data is collected and posted onto this website. ​ https://corgis-edu.github.io/corgis/csv/cancer/​ AI WAS USED TO FIGURE OUT HOW TO RENDER AND CLEAN UP MY DATA SINCE THAT WAS THE ISSUE

Here are my two charts!