CODEWITHSUNDEEP
rweb-scrapingrvest
Rishan.RM
Rishan.RM

Reputation: 43

R Web Scraping Multiple Levels of a Website

I am a beginner to R web scraping. In this case first I have tried to do a simple web scraping with R. This is the work that I have done.

  1. sort out the staff member details from this website (https://science.kln.ac.lk/depts/im/index.php/staff/academic-staff), this is the code that I have used,
library(rvest)
url <- read_html("https://science.kln.ac.lk/depts/im/index.php/staff/academic-staff")
url %>% html_nodes(".sppb-addon-content") %>% html_text()

Above code is working and all the sorted data is showing.

  1. When u click on each staff member u can get another details as Research Interests, Areas of Specialization, Profile etc.... How can I get these data and show that data in the above data set according to each staff member?

Upvotes: 2

Views: 302

Answers (1)

setty
setty

Reputation: 447

The code below will get you all the links to each professor's page. From there, you can map each link to another set of rvest calls using purrr's map_df or map functions.

Most importantly, giving credit where it's due @hrbrmstr: R web scraping across multiple pages

The linked answer is subtly different in that it's mapping across a set of numbers, as opposed to mapping across a vector of URL's like in the code below.

library(rvest)
library(purrr)
library(stringr)
library(dplyr)

url <- read_html("https://science.kln.ac.lk/depts/im/index.php/staff/academic-staff")

names <- url %>%
  html_nodes(".sppb-addon-content") %>%
  html_nodes("strong") %>%
  html_text()
#extract the names

names <- names[-c(3,4)]
#drop the head of department and blank space

names <- names %>%
  tolower() %>%
  str_extract_all("[:alnum:]+") %>%
  sapply(paste, collapse = "-")
#create a list of names separated by dashes, should be identical to link names

content <- url %>% 
  html_nodes(".sppb-addon-content") %>%
  html_text()

content <- content[! content %in% "+"]
#drop the "+" from the content

content_names <- data.frame(prof_name = names, content = content)
#make a df with the content and the names, note the prof_name column is the same as below
#this allows for joining later on

links <- url %>% 
  html_nodes(".sppb-addon-content") %>%
  html_nodes("strong") %>% 
  html_nodes("a") %>%
  html_attr("href")
#create a vector of href links

url_base <- "https://science.kln.ac.lk%s"
urls <- sprintf(url_base, links)
#create a vector of urls for the professor's pages


prof_info <- map_df(urls, function(x) {
  #create an anonymous function to pull the data

  prof_name <- gsub("https://science.kln.ac.lk/depts/im/index.php/", "", x)
  #extract the prof's name from the url

  page <- read_html(x)
  #read each page in the urls vector

  sections <- page %>%
    html_nodes(".sppb-panel-title") %>%
    html_text()
  #extract the section title

  info <- page %>%
    html_nodes(".sppb-panel-body") %>%
    html_nodes(".sppb-addon-content") %>%
    html_text()
  #extract the info from each section

  data.frame(sections = sections, info = info, prof_name = prof_name)
  #create a dataframe with the section titles as the column headers and the
  #info as the data in the columns

}) 
#note this returns a dataframe. Change map_df to map if you want a list
#of tibbles instead

prof_info <- inner_join(content_names, prof_info, by = "prof_name")
#joining the content from the first page to all the individual pages

Not sure this is the cleanest or most efficient way to do this, but I think this is what you're after.

Upvotes: 4

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