Choose one of David Robinson’s tidytuesday screencasts, watch the video, and summarise. https://www.youtube.com/channel/UCeiiqmVK07qhY-wvg3IZiZQ
Tidy Tuesday screecast: analyzing pizza ratings
Oct 1, 2019
Hint: What’s the source of the data; what does the row represent; how many observations?; what are the variables; and what do they mean? The data shows the ratings of different pizza places rated by critics and a guy named Dave from barstool. One graph shows the ratings of each pizza place by number of respondents and percentage of respondents per rating(ratings ranged from never again-excellent). Another graph showed how barstool’s Dave ratings compared to the ratings of critics and showed that Dave is a tougher rater. Dave would tend to rate lower by one or two points compared to critics. Lastly a graph showed the ratings by number of respondents compared to 3 cities plus a others group.
Hint: For example, importing data, understanding the data, data exploration, etc. Dave would use the correct taglines needed for each set of data he produced. He made sure the correct sections of data where used, such as barstool dave’s data analysis compared to critic’s pizza analysis. He would explore other ratings such as other barstool workers pizza ratings just to gain a idea of the data he was looking at. He also had to learn about what bartsool was and that it is a social media platform rather than actual barstools. Barstool is a sports analysis platform. Dave took each step slowly so that he fully understood his code and he also had many mistakes he had to change at the end. This helps the viewer also learn from his mistakes.
In the video Dave used box plots to create the relationship between cities and ratings percentage per respondents. We learned how to create box plots earlier in the year and I could relate it to that section in the video. He also used bar graphs as we did earlier in the year but he made it more specific having multiple bar graphs grouped next to one another which we havent gone over.
The major finding is that Flores is by far the most popular pizza place out of the 16 others because it had the most repondents and had mostly good ratings with a small few being negative. Another major finding is that Barstool Dave is more often than not tougher on ratings of pizza than the actual critics are.
I really liked how the scatterplot is used to compare the difference of ratings from Barstool Dave against critics. It was cool to see the pattern that Dave seemed to be more judgy than the critics because his ratings always seemed to be lower than the critics rating. I thought this was interesting because it almost seems that Dave is the more legit rater because he is more specific on why his rating is what it is.