Assign 4
Gunnar Leonard
2026-10-07
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library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(readr)
# Load the movies dataset
movies <- read_csv("https://gist.githubusercontent.com/tiangechen/b68782efa49a16edaf07dc2cdaa855ea/raw/0c794a9717f18b094eabab2cd6a6b9a226903577/movies.csv")## Rows: 77 Columns: 8## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (4): Film, Genre, Lead Studio, Worldwide Gross
## dbl (4): Audience score %, Profitability, Rotten Tomatoes %, Year
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.one <- movies %>%
rename(
movie_title = Film,
release_year = Year
)
head(one)## # A tibble: 6 × 8
## movie_title Genre `Lead Studio` `Audience score %` Profitability
## <chr> <chr> <chr> <dbl> <dbl>
## 1 Zack and Miri Make a Por… Roma… The Weinstei… 70 1.75
## 2 Youth in Revolt Come… The Weinstei… 52 1.09
## 3 You Will Meet a Tall Dar… Come… Independent 35 1.21
## 4 When in Rome Come… Disney 44 0
## 5 What Happens in Vegas Come… Fox 72 6.27
## 6 Water For Elephants Drama 20th Century… 72 3.08
## # ℹ 3 more variables: `Rotten Tomatoes %` <dbl>, `Worldwide Gross` <chr>,
## # release_year <dbl>two <- one %>%
select(
movie_title,
release_year,
Genre,
Profitability,
`Rotten Tomatoes %`,
`Audience score %`
)
head(two)## # A tibble: 6 × 6
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Zack and Miri Make a Por… 2008 Roma… 1.75 64
## 2 Youth in Revolt 2010 Come… 1.09 68
## 3 You Will Meet a Tall Dar… 2010 Come… 1.21 43
## 4 When in Rome 2010 Come… 0 15
## 5 What Happens in Vegas 2008 Come… 6.27 28
## 6 Water For Elephants 2011 Drama 3.08 60
## # ℹ 1 more variable: `Audience score %` <dbl>three <- two %>%
filter(
release_year > 2008,
`Rotten Tomatoes %` > 80
)
head(three)## # A tibble: 6 × 6
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Tangled 2010 Animation 1.37 89
## 2 My Week with Marilyn 2011 Drama 0.826 83
## 3 Midnight in Paris 2011 Romence 8.74 93
## 4 Jane Eyre 2011 Romance 0 85
## 5 Beginners 2011 Comedy 4.47 84
## 6 A Serious Man 2009 Drama 4.38 89
## # ℹ 1 more variable: `Audience score %` <dbl>four <- three %>%
mutate(
rating_gap = `Rotten Tomatoes %` - `Audience score %`
)
head(four)## # A tibble: 6 × 7
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Tangled 2010 Animation 1.37 89
## 2 My Week with Marilyn 2011 Drama 0.826 83
## 3 Midnight in Paris 2011 Romence 8.74 93
## 4 Jane Eyre 2011 Romance 0 85
## 5 Beginners 2011 Comedy 4.47 84
## 6 A Serious Man 2009 Drama 4.38 89
## # ℹ 2 more variables: `Audience score %` <dbl>, rating_gap <dbl>Question 5: arrange()
five <- four %>%
arrange(desc(`Rotten Tomatoes %`), desc(Profitability))
head(five)## # A tibble: 6 × 7
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Midnight in Paris 2011 Romence 8.74 93
## 2 A Serious Man 2009 Drama 4.38 89
## 3 Tangled 2010 Animation 1.37 89
## 4 (500) Days of Summer 2009 comedy 8.10 87
## 5 Jane Eyre 2011 Romance 0 85
## 6 Beginners 2011 Comedy 4.47 84
## # ℹ 2 more variables: `Audience score %` <dbl>, rating_gap <dbl>Question 6: Combining Functions
final_movies <- movies %>%
rename(
movie_title = Film,
release_year = Year
) %>%
select(
movie_title,
release_year,
Genre,
Profitability,
`Rotten Tomatoes %`,
`Audience score %`
) %>%
filter(
release_year > 2008,
`Rotten Tomatoes %` > 80
) %>%
mutate(
rating_gap = `Rotten Tomatoes %` - `Audience score %`
) %>%
arrange(desc(`Rotten Tomatoes %`), desc(Profitability))
head(final_movies)## # A tibble: 6 × 7
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 Midnight in Paris 2011 Romence 8.74 93
## 2 A Serious Man 2009 Drama 4.38 89
## 3 Tangled 2010 Animation 1.37 89
## 4 (500) Days of Summer 2009 comedy 8.10 87
## 5 Jane Eyre 2011 Romance 0 85
## 6 Beginners 2011 Comedy 4.47 84
## # ℹ 2 more variables: `Audience score %` <dbl>, rating_gap <dbl>Question 7
The movie with the highest critic score is Midnight in Paris with a 93% Rotten Tomatoes score, but it does not have the highest audience score because Tangled scored an 88% audience rating. The positive rating gap of 9 for Midnight in Paris reveals that critics rated the film higher than general audiences did. In contrast, A Serious Man shows an even larger gap of 25 points, meaning critics enjoyed the movie much more than audience members.