I am attempted to extract data from a wiki fandom website using the rvest
package in R. However, I am running into several issues because the infobox is not structured as an HTML table. Please see below for my attempts at dealing with this issue:
library(tidyverse)
library(data.table)
library(rvest)
library(httr)
url <- c("https://starwars.fandom.com/wiki/Anakin_Skywalker")
#See here that the infobox information does not appear when checking for HTML tables in the page
df <- read_html(url) %>%
html_table()
#So now just extract data using the CSS selector
df <- read_html(url) %>%
html_element("aside")
html_text2()
The second attempt does succeed at extracting the raw data, but it is formatted in a way that is not easy to format into a clean dataframe. So, then I attempted to extract each element of the table individually, which might be easier to clean and structure into a dataframe. However, when I attempt to do so using the XPath, I get an empty result:
df <- read_html(url) %>%
html_nodes(xpath = '//*[@id="mw-content-text"]/div/aside/section[1]') %>%
html_text2()
So I suppose my question is primarily: does anyone know of a good way to automatically extract the infobox in a datarfame friendly format? If not, would someone be able to point me towards why my attempt to extract each panel individually is not working?
CodePudding user response:
If you target the div.pi-data
directly, you could do something like this:
bind_rows(
read_html(url) %>%
rvest::html_nodes("div.pi-data") %>%
map(.f = ~tibble(
label = html_elements(.x, ".pi-data-label") %>% html_text2(),
text= html_elements(.x, ".pi-data-value") %>% html_text2() %>% strsplit(split="\n")
) %>% unnest(text)
)
)
Output:
# A tibble: 29 x 2
label text
<chr> <chr>
1 Homeworld Tatooine[1]
2 Born 41 BBY,[2] Tatooine[3]
3 Died 4 ABY,[4]DS-2 Death Star II Mobile Battle Station, Endor system[5]
4 Species Human[1]
5 Gender Male[1]
6 Height 1.88 meters,[1] later 2.03 meters (6 ft, 8 in) in armor[6]
7 Mass 120 kilograms in armor[7]
8 Hair color Blond,[8] light[9] and dark[10]
9 Eye color Blue,[11] later yellow (dark side)[12]
10 Skin color Light,[11] later pale[5]
# ... with 19 more rows