R Webscraping: How to feed URLS into a function - r

My end goal is to be able to take all 310 articles from this page and its following pages and run it through this function:
library(tidyverse)
library(rvest)
library(stringr)
library(purrr)
library(lubridate)
library(dplyr)
scrape_docs <- function(URL){
doc <- read_html(URL)
speaker <- html_nodes(doc, ".diet-title a") %>%
html_text()
date <- html_nodes(doc, ".date-display-single") %>%
html_text() %>%
mdy()
title <- html_nodes(doc, "h1") %>%
html_text()
text <- html_nodes(doc, "div.field-docs-content") %>%
html_text()
all_info <- list(speaker = speaker, date = date, title = title, text = text)
return(all_info)
}
I assume the way to go forward would be to somehow create a list of the URLs I want, then iterate that list through the scrape_docs function. As it stands, however, I'm having a hard time understanding how to go about that. I thought something like this would work, but I seem to be missing something key given the following error:
xml_attr cannot be applied to object of class "character'.
source_col <- "https://www.presidency.ucsb.edu/advanced-search?field-keywords=%22space%20exploration%22&field-keywords2=&field-keywords3=&from%5Bdate%5D=&to%5Bdate%5D=&person2=&items_per_page=100&page=0"
pages <- 4
all_links <- tibble()
for(i in seq_len(pages)){
page <- paste0(source_col,i) %>%
read_html() %>%
html_attr("href") %>%
html_attr()
tmp <- page[[1]]
all_links <- bind_rows(all_links, tmp)
}
all_links

You can get all the url's by doing
library(rvest)
source_col <- "https://www.presidency.ucsb.edu/advanced-search?field-keywords=%22space%20exploration%22&field-keywords2=&field-keywords3=&from%5Bdate%5D=&to%5Bdate%5D=&person2=&items_per_page=100&page=0"
all_urls <- source_col %>%
read_html() %>%
html_nodes("td a") %>%
html_attr("href") %>%
.[c(FALSE, TRUE)] %>%
paste0("https://www.presidency.ucsb.edu", .)
Now do the same by changing the page number in source_col to get remaining data.
You can then use a for loop or map to extract all the data.
purrr::map(all_urls, scrape_docs)
Testing the function scrape_docs on 1 URL
scrape_docs(all_urls[1])
#$speaker
#[1] "Dwight D. Eisenhower"
#$date
#[1] "1958-04-02"
#$title
#[1] "Special Message to the Congress Relative to Space Science and Exploration."
#$text
#[1] "\n To the Congress of the United States:\nRecent developments in long-range
# rockets for military purposes have for the first time provided man with new mac......

Related

Loop with rvest

I'm very new to all this and am trying to work through some examples on stackoverflow to build up my confidence.
I found this answer by #RonakShah
Using rvest to scrape data that is not in table
and thought I'd use it because I'm familiar with HTML to build up my confidence with loops.
My issue is that I can't make the loop work.
Could someone please point out where I'm going wrong? It's bits and pieces of code I've found through the messageboards, but I'm not getting anywhere!
library(rvest)
page<- (0:2)
urls <- list()
for (i in 1:length(page)) {
url<- paste0("https://concreteplayground.com/sydney/bars?page=",page[i])
urls[[i]] <- url
}
tbl <- list()
j <- 1
for (j in seq_along(urls)) {
tbl[[j]] <- urls[[j]] %>% read_html()
name <- tbl[[j]] %>% html_nodes('p.name a') %>%html_text() %>% trimws()
address <- tbl[[j]] %>% html_nodes('p.address') %>% html_text() %>% trimws()
links <- tbl[[j]] %>% html_nodes('p.name a') %>% html_attr('href')
data.frame(name, address, links)
j <- j+1
}
#convert list to data frame
tbl <- do.call(rbind, tbl)
Create urls using paste0 directly, no need for a loop.
library(rvest)
pages <- 1:2
urls <- paste0("https://concreteplayground.com/sydney/bars?page=", pages)
If you put the code on that page in a function, you can use it with map_df to get combined dataframe directly. map_df does the job of for loop and do.call(rbind, tbl) together.
get_web_data <- function(url) {
webpage <- url %>% read_html()
name <- webpage %>% html_nodes('p.name a') %>%html_text() %>% trimws()
address <- webpage %>% html_nodes('p.address') %>% html_text() %>% trimws()
links <- webpage %>% html_nodes('p.name a') %>% html_attr('href')
data.frame(name, address, links)
}
purrr::map_df(urls, get_web_data)

R scraping reviews from multiple pages on TripAdvisor

I'm trying to pull out a few pages of reviews from TripAdvisor for a academic project.
Here's my attempt using R
#Load libraries
library(rvest)
library(RSelenium)
# main url for stadium
urlmainlist=c(
hampdenpark="http://www.tripadvisor.com.ph/Attraction_Review-g186534-d214132-Reviews-Hampden_Park-Glasgow_Scotland.html"
)
# Specify how many search pages and counter
morepglist=list(
hampdenpark=seq(10,360,10)
)
#----------------------------------------------------------------------------------------------------------
# create pickstadium variable
pickstadium="hampdenpark"
# get list of urllinks corresponding to different pages
# url link for first search page
urllinkmain=urlmainlist[pickstadium]
# counter for additional pages
morepg=as.numeric(morepglist[[pickstadium]])
urllinkpre=paste(strsplit(urllinkmain,"Reviews-")[[1]][1],"Reviews",sep="")
urllinkpost=strsplit(urllinkmain,"Reviews-")[[1]][2]
urllink=rep(NA,length(morepg)+1)
urllink[1]=urllinkmain
for(i in 1:length(morepg)){
urllink[i+1]=paste(urllinkpre,"-or",morepg[i],"-",urllinkpost,sep="")
}
head(urllink)
write.csv(urllink,'urllink.csv')
##########
#SCRAPING#
##########
library(rvest)
library(RSelenium)
#install.packages('RSelenium')
testurl <- read.csv("urllink.csv", header=FALSE, quote="'", stringsAsFactors = F)
testurl=testurl[-1,]
testurl=testurl[,-1]
testurl=as.data.frame(testurl)
testurl=gsub('"',"",testurl$testurl)
list<-unlist(testurl)
tripadvisor <- NULL
#Scrape
for(i in 1:length(list)){
reviews <- list[i] %>%
read_html() %>%
html_nodes("#REVIEWS .innerBubble")
id <- reviews %>%
html_node(".quote a") %>%
html_attr("id")
rating <- reviews %>%
html_node(".rating .rating_s_fill") %>%
html_attr("alt") %>%
gsub(" of 5 stars", "", .) %>%
as.integer()
date <- reviews %>%
html_node(".rating .ratingDate") %>%
html_attr("title") %>%
strptime("%b %d, %Y") %>%
as.POSIXct()
review <- reviews %>%
html_node(".entry .partial_entry") %>%
html_text()%>%
as.character()
rowthing <- data.frame(id, review,rating, date, stringsAsFactors = FALSE)
tripadvisor<-rbind(rowthing, tripadvisor)
}
However this results in an empty tripadvisor dataframe. Any help on fixing this would be appreciated.
Additional Question
I'd like to capture the full reviews, as my code currently intends to capture partial entries only. For each review, I'd like to automatically click on the 'More' link and then extract the full review.
Here too, any help would be grately appreciated.

Looping through a list of webpages with rvest follow_link

I'm trying to webscrape the government release calendar: https://www.gov.uk/government/statistics and use the rvest follow_link functionality to go to each publication link and scrape text from the next page. I have this working for each single page of results (40 publications are displayed per page), but can't get a loop to work so that I can run the code over all publications listed.
This is the code I run first to get the list of publications (just from the first 10 pages of results):
#Loading the rvest package
library('rvest')
library('dplyr')
library('tm')
#######PUBLISHED RELEASES################
###function to add number after 'page=' in url to loop over all pages of published releases results (only 40 publications per page)
###check the site and see how many pages you want to scrape, to cover months of interest
##titles of publications - creates a list
publishedtitles <- lapply(paste0('https://www.gov.uk/government/statistics?page=', 1:10),
function(url_base){
url_base %>% read_html() %>%
html_nodes('h3 a') %>%
html_text()
})
##Dates of publications
publisheddates <- lapply(paste0('https://www.gov.uk/government/statistics?page=', 1:10),
function(url_base){
url_base %>% read_html() %>%
html_nodes('.public_timestamp') %>%
html_text()
})
##Organisations
publishedorgs <- lapply(paste0('https://www.gov.uk/government/statistics?page=', 1:10),
function(url_base){
url_base %>% read_html() %>%
html_nodes('.organisations') %>%
html_text()
})
##Links to publications
publishedpartial_links <- lapply(paste0('https://www.gov.uk/government/statistics?page=', 1:10),
function(url_base){
url_base %>% read_html() %>%
html_nodes('h3 a') %>%
html_attr('href')
})
#Check all lists are the same length - if not, have to deal with missings before next step
# length(publishedtitles)
# length(publisheddates)
# length(publishedorgs)
# length(publishedpartial_links)
#str(publishedorgs)
#Combining all the lists to form a data frame
published <-data.frame(Title = unlist(publishedtitles), Date = unlist(publisheddates), Organisation = unlist(publishedorgs), PartLinks = unlist(publishedpartial_links))
#adding prefix to partial links, to turn into full URLs
published$Links = paste("https://www.gov.uk", published$PartLinks, sep="")
#Drop partial links column
keeps <- c("Title", "Date", "Organisation", "Links")
published <- published[keeps]
Then I want to run something like the below, but over all pages of results. I've ran this code manually changing the parameters for each page, so know it works.
session1 <- html_session("https://www.gov.uk/government/statistics?page=1")
list1 <- list()
for(i in published$Title[1:40]){
nextpage1 <- session1 %>% follow_link(i) %>% read_html()
list1[[i]]<- nextpage1 %>%
html_nodes(".grid-row") %>% html_text()
df1 <- data.frame(text=list1)
df1 <-as.data.frame(t(df1))
}
So the above would need to change page=1 in the html_session, and also the publication$Title[1:40] - I'm struggling with creating a function or loop that includes both variables.
I think I should be able to do this using lapply:
df <- lapply(paste0('https://www.gov.uk/government/statistics?page=', 1:10),
function(url_base){
for(i in published$Title[1:40]){
nextpage1 <- url_base %>% follow_link(i) %>% read_html()
list1[[i]]<- nextpage1 %>%
html_nodes(".grid-row") %>% html_text()
}
}
)
But I get the error
Error in follow_link(., i) : is.session(x) is not TRUE
I've also tried other methods of looping and turning it into a function but didn't want to make this post too long!
Thanks in advance for any suggestions and guidance :)
It looks like you may have just need to start a session inside the lapply function. In the last chunk of code, url_base is simply a text string that gives the base URL. Would something like this work:
df <- lapply(paste0('https://www.gov.uk/government/statistics?page=', 1:10),
function(url_base){
for(i in published$Title[1:40]){
tmpSession <- html_session(url_base)
nextpage1 <- tmpSession %>% follow_link(i) %>% read_html()
list1[[i]]<- nextpage1 %>%
html_nodes(".grid-row") %>% html_text()
}
}
)
To change the published$Title[1:40] for each iteraction of the lapply function, you could make an object that holds the lower and upper bounds of the indices:
lowers <- cumsum(c(1, rep(40, 9)))
uppers <- cumsum(rep(40, 10))
Then, you could include those in the call to lapply
df <- lapply(1:10, function(j){
url_base <- paste0('https://www.gov.uk/government/statistics?page=', j)
for(i in published$Title[lowers[j]:uppers[j]]){
tmpSession <- html_session(url_base)
nextpage1 <- tmpSession %>% follow_link(i) %>% read_html()
list1[[i]]<- nextpage1 %>%
html_nodes(".grid-row") %>% html_text()
}
}
)
Not sure if this is what you want or not, I might have misunderstood the things that are supposed to be changing.

Scraping information from multiple webpages using rvest

I am trying to scrape the results from the 2012-2016 Stockholm Marathon races. I am able to do so using the code outlined below, but every time that I've scraped the results from one year I have to go through the process of manually changing the URL to capture the next year.
This bothers me as the only thing that needs to change is the bold part of http://results.marathon.se/2012/?content=list&event=STHM&num_results=250&page=1&pid=list&search[sex]=M&lang=SE.
How can I modify the code below so that it scrapes the results from each year, outputting the results into a single dataframe that also includes a column to indicate the year to which the observation belongs?
library(dplyr)
library(rvest)
library(tidyverse)
# Find the total number of pages to scrape
tot_pages <- read_html('http://results.marathon.se/2012/?content=list&event=STHM&num_results=250&page=1&pid=list&search[sex]=M&lang=EN') %>%
html_nodes('a:nth-child(6)') %>% html_text() %>% as.numeric()
#Store the URLs in a vector
URLs <- sprintf('http://results.marathon.se/2012/?content=list&event=STHM&num_results=250&page=%s&pid=list&search[sex]=M&lang=EN', 1:tot_pages)
#Create a progress bar
pb <- progress_estimated(tot_pages, min = 0)
# Create a function to scrape the name and finishing time from each page
getdata <- function(URL) {
pb$tick()$print()
pg <- read_html(URL)
html_nodes(pg, 'tbody td:nth-child(3)') %>% html_text() %>% as_tibble() %>% set_names(c('Name')) %>%
mutate(finish_time = html_nodes(pg, 'tbody .right') %>% html_text())
}
#Map everything into a dataframe
map_df(URLs, getdata) -> results
You can use lapply to do this:
library(dplyr)
library(rvest)
library(tidyverse)
# make a vector of the years you want
years <- seq(2012,2016)
# now use lapply to iterate your code over those years
Results.list <- lapply(years, function(x) {
# make a target url with the relevant year
link <- sprintf('http://results.marathon.se/%s/?content=list&event=STHM&num_results=250&page=1&pid=list&search[sex]=M&lang=EN', x)
# Find the total number of pages to scrape
tot_pages <- read_html(link) %>%
html_nodes('a:nth-child(6)') %>% html_text() %>% as.numeric()
# Store the URLs in a vector
URLs <- sprintf('http://results.marathon.se/%s/?content=list&event=STHM&num_results=250&page=%s&pid=list&search[sex]=M&lang=EN', x, 1:tot_pages)
#Create a progress bar
pb <- progress_estimated(tot_pages, min = 0)
# Create a function to scrape the name and finishing time from each page
getdata <- function(URL) {
pb$tick()$print()
pg <- read_html(URL)
html_nodes(pg, 'tbody td:nth-child(3)') %>% html_text() %>% as_tibble() %>% set_names(c('Name')) %>%
mutate(finish_time = html_nodes(pg, 'tbody .right') %>% html_text())
}
#Map everything into a dataframe
map_df(URLs, getdata) -> results
# add an id column indicating which year
results$year <- x
return(results)
})
# now collapse the resulting list into one tidy df
Results <- bind_rows(Results.list)

R return multiple nodes in 1 search using rvest (massive list of urls)

I am using rvest to scrape a website. It works, buy highly inefficient, and I can't figure out how to get it to work better.
in url is a list of over 10.000 url's.
number <- sapply(url, function(x)
read_html(x) %>%
html_nodes(".js-product-artnr") %>%
html_text())
price_new <- sapply(url, function(x)
read_html(x) %>%
html_nodes(".product-page__price__new") %>%
html_text())
price_old <- sapply(url, function(x)
read_html(x) %>%
html_nodes(".product-page__price__old") %>%
html_text())
The problem above is, rvest visits the 10.000 urls to get the first node in ".js-product-artnr", then visits the same 10.000 urls again for the second node and so on. In the end I expect to need about 10 different nodes from these 10.000 pages. getting them 1 by 1 and combining into a data frame later on takes way to long, there must be a better way.
I am looking for something like below, to get all information in 1 search
info <- sapply(url, function(x)
read_html(x) %>%
html_nodes(".js-product-artnr") %>%
html_nodes(".product-page__price__new") %>%
html_nodes(".product-page__price__old") %>%
html_text())
This works for me.
func <- function(url){
sample <- read_html(url) %>%
scrape1 <- html_nodes(sample, ".js-product-artnr")%>%
html_text()
scrape2 <- html_nodes(sample, ".product-page__price__new") %>%
html_text()
scrape3 <- html_nodes(sample,".product-page__price__old") %>%
html_text()
df <- cbind(scrape1, scrape2, scrape3)
final_df <- as.data.frame(df)
return(final_df)
}
data <- lapply(urls_all, func)

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