• Use the EuStockMarkets data that contains the daily closing prices of major European stock indices: Germany DAX (Ibis), Switzerland SMI, France CAC, and UK FTSE. Then, create multiple lines that show changes of each index’s daily closing prices over time.

• Please use function gather from package tidyr to transform the data from a wide to a long format. For more info, refer to our lecture materials on dataformats (i.e., DS3003_dataformat_facets_note.pdf, DS3003_dataformat_facets_code.rmd, or DS3003_dataformat_facets_code.html

• Use function plot_ly from package plotly to create a line plot.

We chose to use the dataset “TV shows on Netflix, Prime Video, Hulu and Disney+” from Kaggle. Initially, the data had 12 variables: the Unique TV Show ID, the ID, Title, Year of production, Age restrictions, IMDb Ratings, Rotten Tomatoes Ratings, Netflix (1 or 0 indicating whether or not the show was on Netflix), Hulu (1 or 0 indicating whether or not the show was on Hulu), Prime Video (1 or 0 indicating whether or not the show was on Prime Video), Disney+ (1 or 0 indicating whether or not the show was on Disney+), and Type. We decided to focus on the variables: IMDb Ratings, Rotten Tomatoes Ratings, Age restrictions, and Year, which we broke into two century variables: 1900s and 2000s.