Choose one of David Robinson’s tidytuesday screencasts, watch the video, and summarise. https://www.youtube.com/channel/UCeiiqmVK07qhY-wvg3IZiZQ
You must follow the instructions below to get credits for this assignment.
The title of the screencast I chose is “Predicting wine ratings”.
The screencast I chose was published on May 31st 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 source of the data is github.com, and from the TidyTuesday project. There is 130,000 observations shown. Each row represents diffferent variables including country, description, designation, region, and taster name. These variables tell you information about each type of wine shown.
Hint: For example, importing data, understanding the data, data exploration, etc.
He started off by importing data and then slimming it down. He also created various graphs with the data and showed us a ggplot. I feel Dave did a very good job explaining the analysis and made each step very clear and easy to follow. He made it interesting to watch and seemed enthusiastic about it.
When he made graphs to represent data I recognized how he did it from other graphs we have made in class. I was able to understand parts of the video from topics we have already learned, such as importing data, running a code, and creating a ggplot.
A major finding from this analysis would be the rankings of the wines. In the end he shows the scores on each wine based on their different variables in a ggplot.
I really enjoyed how enthusiastic David was when approaching the data. He made everything very clear and elaborated making it easier to follow. You can tell that he is very passionate about what he does.