Justin Kaplan

Assignment 3

movies <- read_csv(“https://gist.githubusercontent.com/tiangechen/b68782efa49a16edaf07dc2cdaa855ea/raw/0c794a9717f18b094eabab2cd6a6b9a226903577/movies.csv”)

1. Rename(): (4 points)

Rename the “Film” column to “movie_title” and “Year” to “release_year”.

rename <- movies %>%
rename(movie_title = Film, release_year = Year)

2. select(): (4 points)

Create a new dataframe with only the columns: movie_title, release_year, Genre, Profitability,

select <- rename %>% select(movie_title, release_year, Genre)

3. filter(): (4 points)

Filter the dataset to include only movies released after 2000 with a Rotten Tomatoes % higher than 80.

filter <- rename %>%
filter(release_year > 2000 & Rotten Tomatoes % > 80)

4. mutate(): (4 points)

Add a new column called “Profitability_millions” that converts the Profitability to millions of dollars.

profitability <- rename %>% mutate(profitability_millions = Profitability * 1000000)

5. arrange(): (3 points)

Sort the filtered dataset by Rotten Tomatoes % in descending order, and then by Profitability in descending order. five <- four %>% arrange(desc(Rotten Tomatoes %) , desc(Profitability_millions))

arrange <- profitability %>%
arrange(desc(Rotten Tomatoes %), profitability_millions )

6. Combining functions: (3 points)

Use the pipe operator (%>%) to chain these operations together, starting with the original dataset and ending with a final dataframe that incorporates all the above transformations.

rename2 <- movies %>%
rename(movie_title = Film, release_year = Year) select2 <- rename2 %>% select(movie_title, release_year, Genre) filter2 <- rename2 %>%
filter(release_year > 2000 & Rotten Tomatoes % > 80) profitability2 <- rename2 %>% mutate(profitability_millions = Profitability * 1000000) arrange2 <- profitability2 %>%
arrange(desc(Rotten Tomatoes %), profitability_millions )

7. Interpret question 6 (1 point)

From the resulting data, are the best movies the most popular?

The resulting data shows that the best movies are not always the most popular.This is shown by the contrasting results between profitability and audience score.