Summarry of Data
str(df_netflix)
## spec_tbl_df [6,234 x 12] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ show_id : num [1:6234] 81145628 80117401 70234439 80058654 80125979 ...
## $ type : chr [1:6234] "Movie" "Movie" "TV Show" "TV Show" ...
## $ title : chr [1:6234] "Norm of the North: King Sized Adventure" "Jandino: Whatever it Takes" "Transformers Prime" "Transformers: Robots in Disguise" ...
## $ director : chr [1:6234] "Richard Finn, Tim Maltby" NA NA NA ...
## $ cast : chr [1:6234] "Alan Marriott, Andrew Toth, Brian Dobson, Cole Howard, Jennifer Cameron, Jonathan Holmes, Lee Tockar, Lisa Duru"| __truncated__ "Jandino Asporaat" "Peter Cullen, Sumalee Montano, Frank Welker, Jeffrey Combs, Kevin Michael Richardson, Tania Gunadi, Josh Keaton"| __truncated__ "Will Friedle, Darren Criss, Constance Zimmer, Khary Payton, Mitchell Whitfield, Stuart Allan, Ted McGinley, Peter Cullen" ...
## $ country : chr [1:6234] "United States, India, South Korea, China" "United Kingdom" "United States" "United States" ...
## $ date_added : chr [1:6234] "September 9, 2019" "September 9, 2016" "September 8, 2018" "September 8, 2018" ...
## $ release_year: num [1:6234] 2019 2016 2013 2016 2017 ...
## $ rating : chr [1:6234] "TV-PG" "TV-MA" "TV-Y7-FV" "TV-Y7" ...
## $ duration : chr [1:6234] "90 min" "94 min" "1 Season" "1 Season" ...
## $ listed_in : chr [1:6234] "Children & Family Movies, Comedies" "Stand-Up Comedy" "Kids' TV" "Kids' TV" ...
## $ description : chr [1:6234] "Before planning an awesome wedding for his grandfather, a polar bear king must take back a stolen artifact from"| __truncated__ "Jandino Asporaat riffs on the challenges of raising kids and serenades the audience with a rousing rendition of"| __truncated__ "With the help of three human allies, the Autobots once again protect Earth from the onslaught of the Decepticon"| __truncated__ "When a prison ship crash unleashes hundreds of Decepticons on Earth, Bumblebee leads a new Autobot force to protect humankind." ...
## - attr(*, "spec")=
## .. cols(
## .. show_id = col_double(),
## .. type = col_character(),
## .. title = col_character(),
## .. director = col_character(),
## .. cast = col_character(),
## .. country = col_character(),
## .. date_added = col_character(),
## .. release_year = col_double(),
## .. rating = col_character(),
## .. duration = col_character(),
## .. listed_in = col_character(),
## .. description = col_character()
## .. )
## - attr(*, "problems")=<externalptr>
Selecting Neccesary Clomns
df_filtered <- df_netflix %>% select(type,title,director,cast,country,release_year,rating,duration,listed_in)
df_filtered
## # A tibble: 6,234 x 9
## type title director cast country release_year rating duration listed_in
## <chr> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
## 1 Movie Norm ~ Richard ~ Alan~ United~ 2019 TV-PG 90 min Children~
## 2 Movie Jandi~ <NA> Jand~ United~ 2016 TV-MA 94 min Stand-Up~
## 3 TV Show Trans~ <NA> Pete~ United~ 2013 TV-Y7~ 1 Season Kids' TV
## 4 TV Show Trans~ <NA> Will~ United~ 2016 TV-Y7 1 Season Kids' TV
## 5 Movie #real~ Fernando~ Nest~ United~ 2017 TV-14 99 min Comedies
## 6 TV Show Apach~ <NA> Albe~ Spain 2016 TV-MA 1 Season Crime TV~
## 7 Movie Autom~ Gabe Ibá~ Anto~ Bulgar~ 2014 R 110 min Internat~
## 8 Movie Fabri~ Rodrigo ~ Fabr~ Chile 2017 TV-MA 60 min Stand-Up~
## 9 TV Show Fire ~ <NA> <NA> United~ 2017 TV-MA 1 Season Docuseri~
## 10 Movie Good ~ Henrik R~ Jame~ United~ 2014 R 90 min Action &~
## # ... with 6,224 more rows
Filtring Turkey
df_tr <- df_filtered %>% subset(., grepl("Turkey", country))
Türlerin ayrıştırılması
df_tr_plot <- df_tr %>%
mutate(listed_in = strsplit(as.character(listed_in), ",")) %>%
unnest(listed_in) %>% select(listed_in) %>% group_by(list_in = trimws(listed_in)) %>% summarise(total = n())
ggplot(df_tr_plot, aes(x = reorder(list_in, -total), y= total) ) +
geom_bar(stat='identity')+theme(axis.text.x = element_text(angle=45))
International Movies have most produced in Turkey in Netflix.
Filtring International Movies on Turkey
int_movies<- df_tr%>%subset(., grepl("International Movies", listed_in))
int_movies
## # A tibble: 60 x 9
## type title director cast country release_year rating duration listed_in
## <chr> <chr> <chr> <chr> <chr> <dbl> <chr> <chr> <chr>
## 1 Movie Act o~ Mahsun K~ Haluk ~ Turkey~ 2010 NR 112 min Action &~
## 2 Movie Delih~ Gupse Öz~ Gupse ~ Turkey 2018 TV-PG 102 min Comedies~
## 3 Movie Trave~ Bedran G~ Oguzha~ Turkey 2018 TV-14 111 min Comedies~
## 4 Movie Locke~ Kivanç B~ Ata De~ Turkey 2018 TV-14 105 min Comedies~
## 5 Movie Broth~ Onur Bil~ Cem Ge~ Turkey 2019 TV-14 110 min Comedies~
## 6 Movie Conse~ Ozan Açi~ Nehir ~ Turkey 2014 TV-MA 106 min Dramas, ~
## 7 Movie Love,~ Yilmaz E~ Aylin ~ Turkey 2017 TV-14 95 min Comedies~
## 8 Movie Clair~ Yesim Us~ Funda ~ Turkey~ 2016 TV-MA 102 min Dramas, ~
## 9 Movie Bygon~ Hakan Al~ Ata De~ Turkey 2017 TV-MA 104 min Comedies~
## 10 Movie Bana ~ Burak Ak~ Hande ~ Turkey 2015 TV-14 103 min Comedies~
## # ... with 50 more rows
Directors of International Movies
df_int_plot <- int_movies %>%
mutate(director = strsplit(as.character(director), ",")) %>%
unnest(director) %>% select(director) %>% group_by(director = trimws(director)) %>% summarise(total = n())
ggplot(df_int_plot, aes (x = reorder(director, -total), y = total))+
geom_bar(stat='identity')+theme(axis.text.x = element_text(angle=45))
Actors and Actresses in International Movies
df_int_cast_plot <- int_movies %>%
mutate(cast = strsplit(as.character(cast), ",")) %>%
unnest(cast) %>% select(cast) %>% group_by(cast = trimws(cast)) %>% summarise(total = n())%>%arrange(desc(total))%>%head(20)
df_int_cast_plot
## # A tibble: 20 x 2
## cast total
## <chr> <int>
## 1 Demet Akbag 11
## 2 Ata Demirer 7
## 3 Cezmi Baskin 7
## 4 Cem Yilmaz 6
## 5 Devrim Yakut 6
## 6 Tarik Ünlüoglu 6
## 7 Yilmaz Erdogan 6
## 8 Cengiz Bozkurt 5
## 9 Eda Ece 5
## 10 Erdal Tosun 5
## 11 Gupse Özay 5
## 12 Salih Kalyon 5
## 13 Altan Erkekli 4
## 14 Belçim Bilgin 4
## 15 Büsra Pekin 4
## 16 Ezgi Mola 4
## 17 Fatih Artman 4
## 18 Ibrahim Büyükak 4
## 19 Özge Borak 4
## 20 Tolga Çevik 4
ggplot(df_int_cast_plot, aes (x = reorder(cast, -total), y = total))+
geom_bar(stat='identity')+theme(axis.text.x = element_text(angle=45))
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