Web scraping with R and selector gadget - r

Question

I am trying to scrape data from a website using R. I am using rvest in an attempt to mimic an example scraping the IMDB page for the Lego Movie. The example advocates use of a tool called Selector Gadget to help easily identify the html_node associated with the data you are seeking to pull.
I am ultimately interested in building a data frame that has the following schema/columns:
rank, blog_name, facebook_fans, twitter_followers, alexa_rank.
My code below. I was able to use Selector Gadget to correctly identity the html tag used in the Lego example. However, following the same process and same code structure as the Lego example, I get NAs (...using firstNAs introduced by coercion[1] NA
). My code is below:
data2_html = read_html("http://blog.feedspot.com/video_game_news/")
data2_html %>%
html_node(".stats") %>%
html_text() %>%
as.numeric()
I have also experimented with: html_node("html_node(".stats , .stats span")), which seems to work for the "Facebook fans" column since it reports 714 matches, however only returns 1 number is returned.
714 matches for .//*[#class and contains(concat(' ', normalize-space(#class), ' '), ' stats ')] | .//*[#class and contains(concat(' ', normalize-space(#class), ' '), ' stats ')]/descendant-or-self::*/span: using first{xml_node}
<td>
[1] <span>997,669</span>

Answer 1

This may help you:
library(rvest)
d1 <- read_html("http://blog.feedspot.com/video_game_news/")
stats <- d1 %>%
html_nodes(".stats") %>%
html_text()
blogname <- d1%>%
html_nodes(".tlink") %>%
html_text()
Note that it is html_nodes (plural)
Result:
> head(blogname)
[1] "Kotaku - The Gamer's Guide" "IGN | Video Games" "Xbox Wire" "Official PlayStation Blog"
[5] "Nintendo Life " "Game Informer"
> head(stats,12)
[1] "997,669" "1,209,029" "873" "4,070,476" "4,493,805" "399" "23,141,452" "10,210,993" "879"
[10] "38,019,811" "12,059,607" "500"
blogname returns the list of blog names that is easy to manage. On the other hand the stats info comes out mixed. This is due to the way the stats class for Facebook and Twitter fans are indistinguishable from one another. In this case the output array has the information every three numbers, that is stats = c(fb, tw, alx, fb, tw, alx...). You should separate each vector from this one.
FBstats = stats[seq(1,length(stats),3)]
> head(stats[seq(1,length(stats),3)])
[1] "997,669" "4,070,476" "23,141,452" "38,019,811" "35,977" "603,681"

Answer 2

You can use html_table to extract the whole table with minimal work:
library(rvest)
library(tidyverse)
# scrape html
h <- 'http://blog.feedspot.com/video_game_news/' %>% read_html()
game_blogs <- h %>%
html_node('table') %>% # select enclosing table node
html_table() %>% # turn table into data.frame
set_names(make.names) %>% # make names syntactic
mutate(Blog.Name = sub('\\s?\\+.*', '', Blog.Name)) %>% # extract title from name info
mutate_at(3:5, parse_number) %>% # make numbers actually numbers
tbl_df() # for printing
game_blogs
#> # A tibble: 119 x 5
#> Rank Blog.Name Facebook.Fans Twitter.Followers Alexa.Rank
#> <int> <chr> <dbl> <dbl> <dbl>
#> 1 1 Kotaku - The Gamer's Guide 997669 1209029 873
#> 2 2 IGN | Video Games 4070476 4493805 399
#> 3 3 Xbox Wire 23141452 10210993 879
#> 4 4 Official PlayStation Blog 38019811 12059607 500
#> 5 5 Nintendo Life 35977 95044 17727
#> 6 6 Game Informer 603681 1770812 10057
#> 7 7 Reddit | Gamers 1003705 430017 25
#> 8 8 Polygon 623808 485827 1594
#> 9 9 Xbox Live's Major Nelson 65905 993481 23114
#> 10 10 VG247 397798 202084 3960
#> # ... with 109 more rows
It's worth checking that everything is parsed like you want, but it should be usable at this point.

Answer 3

This uses html_nodes (plural) and str_replace to remove commas in numbers. Not sure if these are all the stats you need.
library(rvest)
library(stringr)
data2_html = read_html("http://blog.feedspot.com/video_game_news/")
data2_html %>%
html_nodes(".stats") %>%
html_text() %>%
str_replace_all(',', '') %>%
as.numeric()