Rvest: Scrape multiple URLs

Question

I am trying to scrape some IMDB data looping through a list of URLs. Unfortunately my output isn't exactly what I hoped for, never mind storing it in a dataframe.

I get URLs with

library(rvest)
topmovies <- read_html("http://www.imdb.com/chart/top")
links <- top250 %>%
  html_nodes(".titleColumn") %>%
  html_nodes("a") %>%
  html_attr("href")
links_full <- paste("http://imdb.com",links,sep="")
links_full_test <- links_full[1:10]

and then I could get content with

lapply(links_full_test, . %>% read_html() %>% html_nodes("h1") %>% html_text())

but it is a nested list and I don't know how to get it into a proper data.frame in R. Similarly, if I wanted to get another attribute, say

%>% read_html() %>% html_nodes("strong span") %>% html_text()

to retrieve the IMDB rating, I get the same nested-list output and most importantly I have to do read_html() twice ... which takes a lot of time. Is there a better way to do this? I guess for-loops, but I can't get it to work that way :(

Answer 1

Edit: now with rating as well

library(dplyr)
library(rvest)

s = "http://www.imdb.com/chart/top" %>% html_session

links =
  s %>%
  html_nodes(".titleColumn a") %>%
  html_attr("href") %>%
  data_frame(link = .) %>%
  slice(1:10) %>%
  rowwise %>%
  mutate(new_page = 
           s %>%
           jump_to(link) %>%
           list,
         title = 
           new_page %>%
           html_nodes("h1") %>% 
           html_text,
         rating = 
           new_page %>%
           html_nodes("strong span") %>% 
           html_text %>%
           as.numeric)

Answer 2

Here's one approach using purrr and rvest. The key idea is to save the parsed page, and then extract the bits you're interested in.

library(rvest)
library(purrr)

topmovies <- read_html("http://www.imdb.com/chart/top")
links <- topmovies %>%
  html_nodes(".titleColumn") %>%
  html_nodes("a") %>%
  html_attr("href") %>% 
  xml2::url_absolute("http://imdb.com") %>% 
  .[1:5] # for testing

pages <- links %>% map(read_html)

title <- pages %>% 
  map_chr(. %>% 
    html_nodes("h1") %>% 
    html_text()
  )
rating <- pages %>% 
  map_dbl(. %>% 
    html_nodes("strong span") %>% 
    html_text() %>% 
    as.numeric()
  )

Answer 3

Another approach would be to use sapply as follows:

library(rvest)

s = "http://www.imdb.com/chart/top" %>% html_session

title_links <- function(x) {x %>% html_nodes(".titleColumn a") %>% html_attr("href")}
h1_text <- function(x) {x %>% html_node("h1") %>% html_text(trim=TRUE)}

s %>% 
  title_links %>% 
  sapply(. %>% jump_to(s, .) %>% h1_text) %>% 
  data.frame(text = ., link = names(.), row.names=NULL)

Which results in:

                     text
1 Die Verurteilten (1994)
2         Der Pate (1972)
3       Der Pate 2 (1974)
4  The Dark Knight (2008)
5 Schindlers Liste (1993)
                                                                                                                                                 link
1 /title/tt0111161/?pf_rd_m=A2FGELUUNOQJNL&pf_rd_p=2398042102&pf_rd_r=109KYN8J6HW5TM5Y1P86&pf_rd_s=center-1&pf_rd_t=15506&pf_rd_i=top&ref_=chttp_tt_1
2 /title/tt0068646/?pf_rd_m=A2FGELUUNOQJNL&pf_rd_p=2398042102&pf_rd_r=109KYN8J6HW5TM5Y1P86&pf_rd_s=center-1&pf_rd_t=15506&pf_rd_i=top&ref_=chttp_tt_2
3 /title/tt0071562/?pf_rd_m=A2FGELUUNOQJNL&pf_rd_p=2398042102&pf_rd_r=109KYN8J6HW5TM5Y1P86&pf_rd_s=center-1&pf_rd_t=15506&pf_rd_i=top&ref_=chttp_tt_3
4 /title/tt0468569/?pf_rd_m=A2FGELUUNOQJNL&pf_rd_p=2398042102&pf_rd_r=109KYN8J6HW5TM5Y1P86&pf_rd_s=center-1&pf_rd_t=15506&pf_rd_i=top&ref_=chttp_tt_4
5 /title/tt0108052/?pf_rd_m=A2FGELUUNOQJNL&pf_rd_p=2398042102&pf_rd_r=109KYN8J6HW5TM5Y1P86&pf_rd_s=center-1&pf_rd_t=15506&pf_rd_i=top&ref_=chttp_tt_5