Efficiency in extracting data from webscraping in R - r

Question

This is no doubt very simple so apologies but I am new to webscraping and am trying to extract multiple datapoints in one call using rvest. Let's take for example the following code (NB I have not used the actual website which I have replaced in this code snippet with xxxxxx.com):
univsalaries <- lapply(paste0('https://xxxxxx.com/job/p', 1:20,'/key=%F9%80%76&final=1&jump=1&PGTID=0d3408-0000-24gf-ac2b-810&ClickID=2'),
function(url_base){
url_base %>% read_html() %>%
html_nodes('.salary') %>%
html_text()
})
Let's say there is another html node I want to scrape (.company). Obviously I can make a separate call and fetch that data, but I want to understand the syntax of how I could extract the information in the same call.
I tried to put it in the following structure, but the code sent me to the debugger
.... function(url_base){
url_base %>% read_html() %>%
Salary <- univsalaries %>%
html_nodes('.salary') %>% html_text()
Company <- univsalaries %>%
html_nodes('.company') %>% html_text()
dt<-tibble(Salary,Company)
})

Answer 1

Read the webpage once and then you can extract multiple values from the same page.
library(purrr)
library(rvest)
univsalaries <- map(paste0('https://xxxxxx.com/job/p', 1:20,'/key=%F9%80%76&final=1&jump=1&PGTID=0d3408-0000-24gf-ac2b-810&ClickID=2'),
function(url_base){
webpage <- url_base %>% read_html()
data.frame(Salary = webpage %>% html_nodes('.salary') %>% html_text(),
Company = webpage %>% html_nodes('.company') %>% html_text())
})
This would give you a list of dataframes (one for every link), if you need one combined dataframe then use map_df instead of map.