I've always been a workout and fitness fanatic and now that I've learned about web scrapping, I want to try my new found skills in scrapping one of the biggest (if not THE biggest) online website for sports nutrition -- **bodybuilding.com** In this attempt, I would like to create a dataset that has **all Sports Nutrition and Workout Support** products. Specifically my aim is to select the following features from each product: - Product name - Brand name - Product description - Product category - Total price - Price per serving - Number of reviews - Overall rating - Number of overall reviewers - Verified buyer rating - Number of verified buyer reviews - Average flavor rating - Number of flavors - Top rated flavor rating - Top rated flavor name **To Note:** this data set can be further enhanced by including other product properties, such as: - Ingredients - Different servings sizes and their corresponding prices - etc... However, due to time constraints and this being the first time I attempt to scrape a website, I will stick to the list I have currently :) ## Potential questions to answer using this dataset - Which product categories are associated with the highest rating? As a potential product developer, which category should you focus on? - What flavor should the product you create make available? Does that make a difference? Do flavors affect overall product rating? - Does value affect overall product rating? Is price negatively correlated with overall product rating? These and other potential questuons could be answered and/or alluded to using the available dataset. Happy coding pythonistas!!!