Create a mini IMDb database in R

Introduction

In a previous post we showed how to extract movie info R info using the imdbapi package. In this post we will create a mini imdb database using the same package.

Solution

If we use the free version, the maximum number of requests per day is 1,000. We need to request an API key here.

First we need a vector containing the movie titles or the IMDbIDs (e.g.: for Vertigo the last section of the url https://www.imdb.com/title/tt0052357/, the string tt0052357. In our example we will use the list containing the results from the Sight and Sound 2012 poll of 846 critics, these are the films receiving at least 3 votes.

library(imdbapi)
library(data.table)
library(tidyverse)
sight_sound <- read.csv("https://sites.google.com/site/nubededatosblogspotcom/Sight&Sound2012-CriticsPoll.txt", stringsAsFactors = FALSE)
glimpse(sight_sound)

Observations: 588
Variables: 17
$ const                          "tt0052357", "tt0033467", "tt004643...
$ position                       1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ...
$ created                        "Thu Aug 16 07:42:05 2012", "Thu Au...
$ description                    NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ modified                       "Thu Aug 16 07:42:05 2012", "Thu Au...
$ Title                          "Vertigo", "Citizen Kane", "Tôkyô m...
$ Directors                      "Alfred Hitchcock", "Orson Welles",...
$ Title.type                     "Feature Film", "Feature Film", "Fe...
$ IMDb.Rating                    8.5, 8.5, 8.2, 8.0, 8.3, 8.3, 8.0, ...
$ PeacefulAnarchy.rated          10, 9, 10, 9, 9, 6, 6, 10, 8, 9, 6,...
$ Runtime..mins.                 128, 119, 136, 110, 94, 160, 119, 6...
$ Genres                         "mystery, romance, thriller", "dram...
$ Year                           1958, 1941, 1953, 1939, 1927, 1968,...
$ Num.Votes                      153502, 205699, 16219, 14872, 19188...
$ Release.Date..month.day.year.  "1958-05-09", "1941-05-01", "1953-1...
$ Id                             1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ...
$ URL                            "http://www.imdb.com/title/tt005235...

We use the function lapply to extract the info for all IMDbIDs.

tt <-
  lapply(sight_sound$const, function(x) {
    return(tryCatch(
      find_by_id(
        x,
        type = NULL,
        year_of_release = NULL,
        plot = "full",
        include_tomatoes = TRUE,
        api_key = "12345678"
      ),
      error = function(e)
        NULL
    ))
  })
df_sight_sound <- rbindlist(tt, fill = TRUE)
df_sight_sound$Ratings <- as.character(df_sight_sound$Ratings)
df_sight_sound <- as.data.frame(df_sight_sound)
df_sight_sound %>% distinct(imdbID) %>% summarise(n= n())

    n
1 586

After running the code some titles may be missing. In our examples, two title. We will repeat the process until obtain all of them.

# Checking missing titles
m <- subset(sight_sound, !(const %in% df_sight_sound$imdbID))$const 
m

[1] "tt0115751" "tt0032551"

Finally, we keep distinct titles removing duplicates.

df_sight_sound <- df_sight_sound %>% 
  filter(grepl("Internet",Ratings)) %>% 
  group_by(imdbID) %>% 
  distinct()

# A tibble: 588 x 26
# Groups:   imdbID [588]
   Title Year  Rated Released   Runtime Genre Director Writer Actors Plot 
                       
 1 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
 2 Citi~ 1941  PG    1941-09-05 119 min Dram~ Orson W~ Herma~ Josep~ "A g~
 3 Toky~ 1953  NOT ~ 1972-03-13 136 min Drama Yasujir~ Kôgo ~ Chish~ An e~
 4 The ~ 1939  NOT ~ 1950-04-08 110 min Come~ Jean Re~ Jean ~ Nora ~ Avia~
 5 Sunr~ 1927  NOT ~ 1927-11-04 94 min  Dram~ F.W. Mu~ Carl ~ Georg~ "In ~
 6 2001~ 1968  G     1968-05-12 149 min Adve~ Stanley~ Stanl~ Keir ~ "\"2~
 7 The ~ 1956  PASS~ 1956-05-26 119 min Adve~ John Fo~ Frank~ John ~ Etha~
 8 Man ~ 1929  NOT ~ 1929-05-12 68 min  Docu~ Dziga V~ Dziga~ Mikha~ This~
 9 The ~ 1928  NOT ~ 1928-10-25 114 min Biog~ Carl Th~ Josep~ Maria~ The ~
10 8½    1963  NOT ~ 1963-06-25 138 min Drama Federic~ Feder~ Marce~ Guid~
# ... with 578 more rows, and 16 more variables: Language ,
#   Country , Awards , Poster , Ratings ,
#   Metascore , imdbRating , imdbVotes , imdbID ,
#   Type , DVD , BoxOffice , Production , Website ,
#   Response , totalSeasons 

To export the final results as a csv:

write.csv(df_sight_sound, "df_sight_sound.csv", row.names = FALSE)

Related posts

• Extract movie info using the OMDb API in R

References

• Package imdbapi manual
• ombapi

Extract movie info using the OMDb API in R

Problem

We want to extract movie information using the OMDb API in R.

Solution

We use the imdbapi package. If we use the free version, the maximum number of requests per day is 1,000. We need to request an API key here. The package allows:

• Retrieve info by imdb id

library(imdbapi)
find_by_id("tt0107692", type = NULL, year_of_release = NULL, plot = "full", include_tomatoes = FALSE, api_key = "12345678") # Ninja Scroll imdb id: tt0107692

# A tibble: 2 x 25
  Title Year  Rated Released   Runtime Genre Director Writer Actors Plot 
                      
1 Ninj~ 1993  NOT ~ 1993-06-05 94 min  Anim~ Yoshiak~ Yoshi~ Kôich~ A Jo~
2 Ninj~ 1993  NOT ~ 1993-06-05 94 min  Anim~ Yoshiak~ Yoshi~ Kôich~ A Jo~
# ... with 15 more variables: Language , Country , Awards ,
#   Poster , Ratings , Metascore , imdbRating ,
#   imdbVotes , imdbID , Type , DVD , BoxOffice ,
#   Production , Website , Response 

• Search by title

find_by_title("vertigo", type = NULL, year_of_release = NULL, plot = "full", include_tomatoes = FALSE, api_key = "12345678")

# A tibble: 3 x 25
  Title Year  Rated Released   Runtime Genre Director Writer Actors Plot 
                      
1 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
2 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
3 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
# ... with 15 more variables: Language , Country , Awards ,
#   Poster , Ratings , Metascore , imdbRating ,
#   imdbVotes , imdbID , Type , DVD , BoxOffice ,
#   Production , Website , Response 

• Additionally the package includes specific functions to extract info about actors, countries, directors, genres and writers.

get_actors(find_by_title("vertigo", api_key = "12345678"))

[1] "James Stewart"      "Kim Novak"          "Barbara Bel Geddes"
[4] "Tom Helmore"  

get_countries(find_by_title("vertigo", api_key = "12345678"))

[1] "USA"

get_directors(find_by_title("vertigo", api_key = "12345678"))

[1] "Alfred Hitchcock"

get_genres(find_by_title("vertigo", api_key = "12345678"))

[1] "Mystery"  "Romance"  "Thriller"

get_writers(find_by_title("vertigo", api_key = "12345678"))

[1] "Alec Coppel (screenplay by)"                                  
[2] "Samuel A. Taylor (screenplay by)"                             
[3] "Pierre Boileau (based on the novel \"D'Entre Les Morts\" by)" 
[4] "Thomas Narcejac (based on the novel \"D'Entre Les Morts\" by)"

Load poster image

library(RCurl)
df <- find_by_title("Batman Ninja", type = NULL, year_of_release = NULL, plot = "full", include_tomatoes = FALSE, api_key = "12345678")
plot(0:1,
     0:1,
     type = "n",
     ann = FALSE,
     axes = FALSE)
my_image <-  readJPEG(getURLContent(df$Poster[1]))
rasterImage(my_image, 0, 0, 1, 1)

Notes

By inspecting the previous functions starting with get, we can see that these are wrappers subetting the info returned by the functions find_by_title or find_by_id.

function (omdb) 
{
  if (!inherits(omdb, "omdb")) {
    message("get_actors() expects an omdb object")
    return(NULL)
  }
  if ("Actors" %in% names(omdb)) {
    str_split(omdb$Actors, ",[ ]*")[[1]]
  }
}

Every request returned by find_by_id o find_by_title, will generate a row for each rating availables. For instance, Vertigo will return 3 rating rows: IMDb, Rotten Tomatoes and Metacritic. Whereas Ninja Scroll or Batman Ninja will return only 2 available ratings: IMDb and Rotten Tomatoes. The variables are:

Classes ‘omdb’, ‘tbl_df’, ‘tbl’ and 'data.frame': 2 obs. of  25 variables:
 $ Title     : chr  "Batman Ninja" "Batman Ninja"
 $ Year      : chr  "2018" "2018"
 $ Rated     : chr  "PG-13" "PG-13"
 $ Released  : Date, format: "2018-04-24" "2018-04-24"
 $ Runtime   : chr  "85 min" "85 min"
 $ Genre     : chr  "Animation, Action" "Animation, Action"
 $ Director  : chr  "Junpei Mizusaki" "Junpei Mizusaki"
 $ Writer    : chr  "Kazuki Nakashima (screenplay), Leo Chu (English screenplay), Eric Garcia (English screenplay), Bob Kane (charac"| __truncated__ "Kazuki Nakashima (screenplay), Leo Chu (English screenplay), Eric Garcia (English screenplay), Bob Kane (charac"| __truncated__
 $ Actors    : chr  "Kôichi Yamadera, Wataru Takagi, Ai Kakuma, Rie Kugimiya" "Kôichi Yamadera, Wataru Takagi, Ai Kakuma, Rie Kugimiya"
 $ Plot      : chr  "Batman, along with a number of his allies and adversaries, finds himself transplanted from modern Gotham City to feudal Japan." "Batman, along with a number of his allies and adversaries, finds himself transplanted from modern Gotham City to feudal Japan."
 $ Language  : chr  "Japanese, English" "Japanese, English"
 $ Country   : chr  "Japan, USA" "Japan, USA"
 $ Awards    : chr  "N/A" "N/A"
 $ Poster    : chr  "https://m.media-amazon.com/images/M/MV5BYmFhYzZhYzgtZjZiYS00NWEwLWFhYTUtN2UxM2FmYzdhNDUyXkEyXkFqcGdeQXVyNDk2Nzc"| __truncated__ "https://m.media-amazon.com/images/M/MV5BYmFhYzZhYzgtZjZiYS00NWEwLWFhYTUtN2UxM2FmYzdhNDUyXkEyXkFqcGdeQXVyNDk2Nzc"| __truncated__
 $ Ratings   :List of 2
  ..$ :List of 2
  .. ..$ Source: chr "Internet Movie Database"
  .. ..$ Value : chr "5.7/10"
  ..$ :List of 2
  .. ..$ Source: chr "Rotten Tomatoes"
  .. ..$ Value : chr "79%"
 $ Metascore : chr  "N/A" "N/A"
 $ imdbRating: num  5.7 5.7
 $ imdbVotes : num  9759 9759
 $ imdbID    : chr  "tt7451284" "tt7451284"
 $ Type      : chr  "movie" "movie"
 $ DVD       : Date, format: "2018-05-08" "2018-05-08"
 $ BoxOffice : chr  "N/A" "N/A"
 $ Production: chr  "DC Comics" "DC Comics"
 $ Website   : chr  "N/A" "N/A"
 $ Response  : chr  "True" "True"

References

• Package imdbapi manual
• ombapi

Crear una pequeña base de datos de IMDb con R

Introducción

En una entrada anterior usamos la OMDb API para extraer con R información sobre películas o series de televisión. En esta ocasión queremos crear una pequeña base datos con el mismo paquete imdbapi.

Solución

Empleamos el paquete imdbapi que nos permite extraer dicha información. Si utilizamos la versión gratuita, tendremos una limitación de 1.000 peticiones al día.

Lo primero que necesitamos es un vector con títulos de películas o de IMDbIDs (por ejemplo: para Vértigo la parte final de la dirección https://www.imdb.com/title/tt0052357/, la cadena tt0052357. En nuestro ejemplo usamos la encuesta de los críticos Sight & Sound de 2012, que contiene la columna const con dichos IMDbIDs .

library(imdbapi)
library(data.table)
library(tidyverse)
sight_sound <- read.csv("https://sites.google.com/site/nubededatosblogspotcom/Sight&Sound2012-CriticsPoll.txt", stringsAsFactors = FALSE)
glimpse(sight_sound)

Observations: 588
Variables: 17
$ const                          "tt0052357", "tt0033467", "tt004643...
$ position                       1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ...
$ created                        "Thu Aug 16 07:42:05 2012", "Thu Au...
$ description                    NA, NA, NA, NA, NA, NA, NA, NA, NA,...
$ modified                       "Thu Aug 16 07:42:05 2012", "Thu Au...
$ Title                          "Vertigo", "Citizen Kane", "Tôkyô m...
$ Directors                      "Alfred Hitchcock", "Orson Welles",...
$ Title.type                     "Feature Film", "Feature Film", "Fe...
$ IMDb.Rating                    8.5, 8.5, 8.2, 8.0, 8.3, 8.3, 8.0, ...
$ PeacefulAnarchy.rated          10, 9, 10, 9, 9, 6, 6, 10, 8, 9, 6,...
$ Runtime..mins.                 128, 119, 136, 110, 94, 160, 119, 6...
$ Genres                         "mystery, romance, thriller", "dram...
$ Year                           1958, 1941, 1953, 1939, 1927, 1968,...
$ Num.Votes                      153502, 205699, 16219, 14872, 19188...
$ Release.Date..month.day.year.  "1958-05-09", "1941-05-01", "1953-1...
$ Id                             1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, ...
$ URL                            "http://www.imdb.com/title/tt005235...

Empleamos la función lapply para extraer la información de todos los IMDbIDs.

tt <-
  lapply(sight_sound$const, function(x) {
    return(tryCatch(
      find_by_id(
        x,
        type = NULL,
        year_of_release = NULL,
        plot = "full",
        include_tomatoes = TRUE,
        api_key = "12345678"
      ),
      error = function(e)
        NULL
    ))
  })
df_sight_sound <- rbindlist(tt, fill = TRUE)
df_sight_sound$Ratings <- as.character(df_sight_sound$Ratings)
df_sight_sound <- as.data.frame(df_sight_sound)
df_sight_sound %>% distinct(imdbID) %>% summarise(n= n())

    n
1 586

En una sola pasada suelen faltar algunos. En este caso nos faltan dos títulos. Repetiríamos el proceso hasta obtener todos los títulos.

# Comprobamos los titulos no encontrados
m <- subset(sight_sound, !(const %in% df_sight_sound$imdbID))$const 
m

[1] "tt0115751" "tt0032551"

Finalmente procesamos el data frame para eliminar duplicados.

df_sight_sound <- df_sight_sound %>% 
  filter(grepl("Internet",Ratings)) %>% 
  group_by(imdbID) %>% 
  distinct()

# A tibble: 588 x 26
# Groups:   imdbID [588]
   Title Year  Rated Released   Runtime Genre Director Writer Actors Plot 
                       
 1 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
 2 Citi~ 1941  PG    1941-09-05 119 min Dram~ Orson W~ Herma~ Josep~ "A g~
 3 Toky~ 1953  NOT ~ 1972-03-13 136 min Drama Yasujir~ Kôgo ~ Chish~ An e~
 4 The ~ 1939  NOT ~ 1950-04-08 110 min Come~ Jean Re~ Jean ~ Nora ~ Avia~
 5 Sunr~ 1927  NOT ~ 1927-11-04 94 min  Dram~ F.W. Mu~ Carl ~ Georg~ "In ~
 6 2001~ 1968  G     1968-05-12 149 min Adve~ Stanley~ Stanl~ Keir ~ "\"2~
 7 The ~ 1956  PASS~ 1956-05-26 119 min Adve~ John Fo~ Frank~ John ~ Etha~
 8 Man ~ 1929  NOT ~ 1929-05-12 68 min  Docu~ Dziga V~ Dziga~ Mikha~ This~
 9 The ~ 1928  NOT ~ 1928-10-25 114 min Biog~ Carl Th~ Josep~ Maria~ The ~
10 8½    1963  NOT ~ 1963-06-25 138 min Drama Federic~ Feder~ Marce~ Guid~
# ... with 578 more rows, and 16 more variables: Language ,
#   Country , Awards , Poster , Ratings ,
#   Metascore , imdbRating , imdbVotes , imdbID ,
#   Type , DVD , BoxOffice , Production , Website ,
#   Response , totalSeasons 

Y tendremos lista nuestra pequeña base de datos de IMDb. Si queremos exportar los resultados como csv:

write.csv(df_sight_sound, "df_sight_sound.csv", row.names = FALSE)

Entradas relacionadas

• Extraer información de la OMDb API con R
• Importar datos en R: tablas HTML
• Importar datos en R: tablas HTML gráficos ggplot2
• Importar HTML en R: Películas más taquilleras IMDb
• Cómo obtener (scrape) el presupuesto de una película IMDd con rvest

Referencias

• Manual de referencia de imdbapi
• ombapi

Extraer información de la OMDb API con R

Problema

Queremos extraer con R información sobre películas o series de televisión usando la OMDb API.

Solución

Empleamos el paquete imdbapi que nos permite extraer dicha información. Si utilizamos la versión gratuita, tendremos una limitación de 1.000 peticiones al día. El paquete imdbapi nos permite:

• Búsqueda por imdb id

library(imdbapi)
find_by_id("tt0107692", type = NULL, year_of_release = NULL, plot = "full", include_tomatoes = FALSE, api_key = "12345678")

# A tibble: 2 x 25
  Title Year  Rated Released   Runtime Genre Director Writer Actors Plot 
                      
1 Ninj~ 1993  NOT ~ 1993-06-05 94 min  Anim~ Yoshiak~ Yoshi~ Kôich~ A Jo~
2 Ninj~ 1993  NOT ~ 1993-06-05 94 min  Anim~ Yoshiak~ Yoshi~ Kôich~ A Jo~
# ... with 15 more variables: Language , Country , Awards ,
#   Poster , Ratings , Metascore , imdbRating ,
#   imdbVotes , imdbID , Type , DVD , BoxOffice ,
#   Production , Website , Response 

• Búsqueda por título

find_by_title("vertigo", type = NULL, year_of_release = NULL, plot = "full", include_tomatoes = FALSE, api_key = "12345678")

# A tibble: 3 x 25
  Title Year  Rated Released   Runtime Genre Director Writer Actors Plot 
                      
1 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
2 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
3 Vert~ 1958  PG    1958-07-21 128 min Myst~ Alfred ~ "Alec~ James~ "Joh~
# ... with 15 more variables: Language , Country , Awards ,
#   Poster , Ratings , Metascore , imdbRating ,
#   imdbVotes , imdbID , Type , DVD , BoxOffice ,
#   Production , Website , Response 

• Además cuenta con diferentes funciones para extraer una información específica: actores, países, directores, géneros o escritores.

get_actors(find_by_title("vertigo", api_key = "12345678"))

[1] "James Stewart"      "Kim Novak"          "Barbara Bel Geddes"
[4] "Tom Helmore"  

get_countries(find_by_title("vertigo", api_key = "12345678"))

[1] "USA"

get_directors(find_by_title("vertigo", api_key = "12345678"))

[1] "Alfred Hitchcock"

get_genres(find_by_title("vertigo", api_key = "12345678"))

[1] "Mystery"  "Romance"  "Thriller"

get_writers(find_by_title("vertigo", api_key = "12345678"))

[1] "Alec Coppel (screenplay by)"                                  
[2] "Samuel A. Taylor (screenplay by)"                             
[3] "Pierre Boileau (based on the novel \"D'Entre Les Morts\" by)" 
[4] "Thomas Narcejac (based on the novel \"D'Entre Les Morts\" by)"

Cargar la imagen del póster

library(RCurl)
df <- find_by_title("Batman Ninja", type = NULL, year_of_release = NULL, plot = "full", include_tomatoes = FALSE, api_key = "12345678")
plot(0:1,
     0:1,
     type = "n",
     ann = FALSE,
     axes = FALSE)
my_image <-  readJPEG(getURLContent(df$Poster[1]))
rasterImage(my_image, 0, 0, 1, 1)

Notas

Al inspeccionar las funciones anteriores que comienzan por get, podemos ver que simplemente extraen un subconjunto de datos del objeto omdb generado por la búsqueda por imdb id o título.

function (omdb) 
{
  if (!inherits(omdb, "omdb")) {
    message("get_actors() expects an omdb object")
    return(NULL)
  }
  if ("Actors" %in% names(omdb)) {
    str_split(omdb$Actors, ",[ ]*")[[1]]
  }
}

Cada petición con find_by_id o find_by_title, generará una fila por cada página de las valoraciones (Ratings) disponibles encontradas. Por ejemplo, Vértigo devolverá 3 filas con las valoraciones de IMDb, Rotten Tomatoes y Metacritic. En cambio Ninja Scroll o Batman Ninja solamente devolverá dos filas: IMDb y Rotten Tomatoes. Las variables extraídas son:

Classes ‘omdb’, ‘tbl_df’, ‘tbl’ and 'data.frame': 2 obs. of  25 variables:
 $ Title     : chr  "Batman Ninja" "Batman Ninja"
 $ Year      : chr  "2018" "2018"
 $ Rated     : chr  "PG-13" "PG-13"
 $ Released  : Date, format: "2018-04-24" "2018-04-24"
 $ Runtime   : chr  "85 min" "85 min"
 $ Genre     : chr  "Animation, Action" "Animation, Action"
 $ Director  : chr  "Junpei Mizusaki" "Junpei Mizusaki"
 $ Writer    : chr  "Kazuki Nakashima (screenplay), Leo Chu (English screenplay), Eric Garcia (English screenplay), Bob Kane (charac"| __truncated__ "Kazuki Nakashima (screenplay), Leo Chu (English screenplay), Eric Garcia (English screenplay), Bob Kane (charac"| __truncated__
 $ Actors    : chr  "Kôichi Yamadera, Wataru Takagi, Ai Kakuma, Rie Kugimiya" "Kôichi Yamadera, Wataru Takagi, Ai Kakuma, Rie Kugimiya"
 $ Plot      : chr  "Batman, along with a number of his allies and adversaries, finds himself transplanted from modern Gotham City to feudal Japan." "Batman, along with a number of his allies and adversaries, finds himself transplanted from modern Gotham City to feudal Japan."
 $ Language  : chr  "Japanese, English" "Japanese, English"
 $ Country   : chr  "Japan, USA" "Japan, USA"
 $ Awards    : chr  "N/A" "N/A"
 $ Poster    : chr  "https://m.media-amazon.com/images/M/MV5BYmFhYzZhYzgtZjZiYS00NWEwLWFhYTUtN2UxM2FmYzdhNDUyXkEyXkFqcGdeQXVyNDk2Nzc"| __truncated__ "https://m.media-amazon.com/images/M/MV5BYmFhYzZhYzgtZjZiYS00NWEwLWFhYTUtN2UxM2FmYzdhNDUyXkEyXkFqcGdeQXVyNDk2Nzc"| __truncated__
 $ Ratings   :List of 2
  ..$ :List of 2
  .. ..$ Source: chr "Internet Movie Database"
  .. ..$ Value : chr "5.7/10"
  ..$ :List of 2
  .. ..$ Source: chr "Rotten Tomatoes"
  .. ..$ Value : chr "79%"
 $ Metascore : chr  "N/A" "N/A"
 $ imdbRating: num  5.7 5.7
 $ imdbVotes : num  9759 9759
 $ imdbID    : chr  "tt7451284" "tt7451284"
 $ Type      : chr  "movie" "movie"
 $ DVD       : Date, format: "2018-05-08" "2018-05-08"
 $ BoxOffice : chr  "N/A" "N/A"
 $ Production: chr  "DC Comics" "DC Comics"
 $ Website   : chr  "N/A" "N/A"
 $ Response  : chr  "True" "True"

Entradas relacionadas

• Importar datos en R: tablas HTML
• Importar datos en R: tablas HTML gráficos ggplot2
• Importar HTML en R: Películas más taquilleras IMDb
• Cómo obtener (scrape) el presupuesto de una película IMDd con rvest

Referencias

• Manual de referencia de imdbapi
• ombapi