## Question 1: rename()
Rename Film → movie_title and Year → release_year
``` r
q1 <- movies %>%
rename(movie_title = Film,
release_year = Year)
head(q1, 6)## # 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>Keep only selected columns
q2 <- q1 %>%
select(movie_title, release_year, Genre, Profitability, `Rotten Tomatoes %`)
head(q2, 6)## # A tibble: 6 × 5
## 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 60Only movies released after 2000 with Rotten Tomatoes % above 80
q3 <- q2 %>%
filter(release_year > 2000, `Rotten Tomatoes %` > 80)
head(q3, 6)## # A tibble: 6 × 5
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 WALL-E 2008 Animati… 2.90 96
## 2 Waitress 2007 Romance 11.1 89
## 3 Tangled 2010 Animati… 1.37 89
## 4 Rachel Getting Married 2008 Drama 1.38 85
## 5 My Week with Marilyn 2011 Drama 0.826 83
## 6 Midnight in Paris 2011 Romence 8.74 93Add Profitability_millions
q4 <- q3 %>%
mutate(Profitability_millions = Profitability / 1000000)
head(q4, 6)## # A tibble: 6 × 6
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 WALL-E 2008 Animati… 2.90 96
## 2 Waitress 2007 Romance 11.1 89
## 3 Tangled 2010 Animati… 1.37 89
## 4 Rachel Getting Married 2008 Drama 1.38 85
## 5 My Week with Marilyn 2011 Drama 0.826 83
## 6 Midnight in Paris 2011 Romence 8.74 93
## # ℹ 1 more variable: Profitability_millions <dbl>Sort by rating and profitability (descending)
q5 <- q4 %>%
arrange(desc(`Rotten Tomatoes %`), desc(Profitability_millions))
head(q5, 6)## # A tibble: 6 × 6
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 WALL-E 2008 Animation 2.90 96
## 2 Midnight in Paris 2011 Romence 8.74 93
## 3 Enchanted 2007 Comedy 4.01 93
## 4 Knocked Up 2007 Comedy 6.64 91
## 5 Waitress 2007 Romance 11.1 89
## 6 A Serious Man 2009 Drama 4.38 89
## # ℹ 1 more variable: Profitability_millions <dbl>All transformations in one chain
q6 <- movies %>%
rename(movie_title = Film,
release_year = Year) %>%
select(movie_title, release_year, Genre, Profitability, `Rotten Tomatoes %`) %>%
filter(release_year > 2000, `Rotten Tomatoes %` > 80) %>%
mutate(Profitability_millions = Profitability / 1000000) %>%
arrange(desc(`Rotten Tomatoes %`), desc(Profitability_millions))
head(q6, 6)## # A tibble: 6 × 6
## movie_title release_year Genre Profitability `Rotten Tomatoes %`
## <chr> <dbl> <chr> <dbl> <dbl>
## 1 WALL-E 2008 Animation 2.90 96
## 2 Midnight in Paris 2011 Romence 8.74 93
## 3 Enchanted 2007 Comedy 4.01 93
## 4 Knocked Up 2007 Comedy 6.64 91
## 5 Waitress 2007 Romance 11.1 89
## 6 A Serious Man 2009 Drama 4.38 89
## # ℹ 1 more variable: Profitability_millions <dbl>From the resulting data, are the best movies the most popular?
Not necessarily. While the dataset shows movies with very high Rotten Tomatoes scores, profitability varies across those movies. This suggests that strong critical ratings (“best”) do not always translate to the highest profitability (“most popular”).
extra <- q6 %>%
group_by(Genre) %>%
summarize(
avg_rating = mean(`Rotten Tomatoes %`, na.rm = TRUE),
avg_profitability_millions = mean(Profitability_millions, na.rm = TRUE),
n_movies = n()
) %>%
arrange(desc(avg_rating))
head(extra, 6)## # A tibble: 6 × 4
## Genre avg_rating avg_profitability_millions n_movies
## <chr> <dbl> <dbl> <int>
## 1 Romence 93 0.00000874 1
## 2 Animation 92.5 0.00000213 2
## 3 Comedy 89.3 0.00000504 3
## 4 Romance 87 0.00000554 2
## 5 comedy 87 0.00000810 1
## 6 Drama 85.7 0.00000220 3