I and some of my new colleagues hopped on this side hustle where we started learning Data Analytics. First, we did a few weeks of internship and to get into the boot camp where we can effectively learn data analytics we had to pay for it.

Moving forward, we all paid and we were selected to form a team just to work on some project, as you know we'd have to get to know each other and get acquainted. Just after that, we had to choose a team lead (yours truly✌️) and an assistant lead (Simbiat).

Fast forward, we started late because it was kinda late before our team was complete. We had our first google meet session where discussed the project and what was required of us to do, it was super stressful.

But we had to do it anyways with a few members as most weren't online to join, we concluded what must be done and we had another Google meeting the following day, concluded some things and designated assignments for every team member.

Lo and behold we went straight into the action that same night and by the last day which was today, we concluded the project best according to our understanding of the project (not to say we weren't open to correction).

THE PROJECT: Data Analytics Perform a Nutrition Analysis on McDonald’s. Scrap, Clean and visualize with Power BI. This should include every menu item, including salads, beverages, and desserts. Categorize items according to factors like sugar and fiber content, ... Then you can model the results using bar and pie charts, scatter plots, and heatmaps.

We designed each visualization mentioned in the question using the category given from the dataset against all the nutritional values given in the dataset. This also included the food items and we used the average of nutritional value.

Mind you we also considered creating each visualization using the average of the nutrients instead of the sum, the reason is, we discovered that some category mentioned also has other food items under them.

Example: Dessert: Remember dessert has different types: Chocolate, strawberry, oatmeal etc. It's the reason we used the average.