Homework_3

Netflix <- read.csv("Netflix.csv")

Netflix_Actor <- Netflix %>%
  separate_rows(cast, sep = ", ") %>%
  drop_na(cast) %>%
  rename(actor = cast)

head(Netflix_Actor)

## # A tibble: 6 × 12
##    show_id type  title     director actor country date_added release_year rating
##      <int> <chr> <chr>     <chr>    <chr> <chr>   <chr>             <int> <chr> 
## 1 81145628 Movie Norm of … Richard… Alan… United… September…         2019 TV-PG 
## 2 81145628 Movie Norm of … Richard… Andr… United… September…         2019 TV-PG 
## 3 81145628 Movie Norm of … Richard… Bria… United… September…         2019 TV-PG 
## 4 81145628 Movie Norm of … Richard… Cole… United… September…         2019 TV-PG 
## 5 81145628 Movie Norm of … Richard… Jenn… United… September…         2019 TV-PG 
## 6 81145628 Movie Norm of … Richard… Jona… United… September…         2019 TV-PG 
## # ℹ 3 more variables: duration <chr>, listed_in <chr>, description <chr>

Top_Actors <- Netflix_Actor %>%
  select(type, actor) %>%
  filter(type == "TV Show") %>%
  group_by(actor) %>%
  summarise(appearances = n()) %>%
  arrange(desc(appearances)) %>%
  head(6)

Top_Actors

## # A tibble: 6 × 2
##   actor                appearances
##   <chr>                      <int>
## 1 ""                           210
## 2 "Takahiro Sakurai"            18
## 3 "Yuki Kaji"                   16
## 4 "Daisuke Ono"                 14
## 5 "David Attenborough"          14
## 6 "Ashleigh Ball"               12