Scraping information from multiple webpages using rvest - r

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)

Related

R Webscraping: How to feed URLS into a function

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......

Why does rvest pull empty data when inclosed in loop?

I'm trying to scrape hotel reviews from a certain hotel on from tripadvisor. I'm using Rvest to accomplish my goal. This script has to scrape multiple pages.
When executing my script rvest sometimes returns vectors with empty values when executing in a loop. This is completely random. Does anyone have a fix for this?
I tried manually walking trough the script. When i slowly go trough it it works most of the time, but sometimes still manages to pull empty data.
# Webscrapen
df <- data.frame()
x = 0
for(i in 1:250){
url <- paste("https://www.tripadvisor.com/Hotel_Review-g295424-d7760386-Reviews-or",x,"-Hyatt_Regency_Dubai_Creek_Heights-Dubai_Emirate_of_Dubai.html", sep = "")
x = x + 5
reviews <- url %>%
read_html() %>%
html_nodes('.common-text-ReadMore__content--2X4LR') %>%
html_node('.hotels-hotel-review-community-content-review-list-parts-ExpandableReview__reviewText--2OVqJ span') %>%
html_text()
rating <- url %>%
read_html() %>%
html_nodes(".hotels-hotel-review-community-content-review-list-parts-RatingLine__bubbles--3d2Be span") %>%
html_attr("class")
rating <- sapply(strsplit(rating, "_"), `[`, 4) %>%
as.numeric()
if(nrow(df) == 0){
df <- data.frame(reviews[!is.na(reviews)], rating, stringsAsFactors = F)
} else {
temp <- df
df <- rbind(temp, data.frame(reviews[!is.na(reviews)], rating, stringsAsFactors = F))
}
}
I expect to scrape all the reviews till my for loop stops. I should have a dataframe of at least 100 reviews.
I've found a workaround by placing the review in a repeat loop and keep repeating as long as the vector hasn't been filled.
The code takes a bit longer to execute but it gets the job done.
repeat{
Review <- url %>%
read_html() %>%
html_nodes('.common-text-ReadMore__content--2X4LR') %>%
html_node('.hotels-hotel-review-community-content-review-list-parts-ExpandableReview__reviewText--2OVqJ span') %>%
html_text()
if(length(Review) >= 1 ){
break;
}
}

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.

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)

Loop URL and store info in R

I'm trying to write a for loop that will loop through many websites and extract a few elements, and store the results in a table in R. Here's my go so far, just not sure how to start the for loop, or copy all results into one variable to be exported later.
library("dplyr")
library("rvest")
library("leaflet")
library("ggmap")
url <- c(html("http://www.webiste_name.com/")
agent <- html_nodes(url,"h1 span")
fnames<-html_nodes(url, "#offNumber_mainLocContent span")
address <- html_nodes(url,"#locStreetContent_mainLocContent")
scrape<-t(c(html_text(agent),html_text(fnames),html_text(address)))
View(scrape)
Given that your question isn't fully reproducible, here's a toy example that loops through three URLs (Red Socks, Jays and Yankees):
library(rvest)
# teams
teams <- c("BOS", "TOR", "NYY")
# init
df <- NULL
# loop
for(i in teams){
# find url
url <- paste0("http://www.baseball-reference.com/teams/", i, "/")
page <- read_html(url)
# grab table
table <- page %>%
html_nodes(css = "#franchise_years") %>%
html_table() %>%
as.data.frame()
# bind to dataframe
df <- rbind(df, table)
}
# view captured data
View(df)
The loop works because it replaces i in paste0 with each team in sequence.
I would go with lapply.
The code would look something like this:
library("rvest")
library("dplyr")
#a vector of urls you want to scrape
URLs <- c("http://...1", "http://...2", ....)
df <- lapply(URLs, function(u){
html.obj <- read_html(u)
agent <- html_nodes(html.obj,"h1 span") %>% html_text
fnames<-html_nodes(html.obj, "#offNumber_mainLocContent span") %>% html_text
address <- html_nodes(html.obj,"#locStreetContent_mainLocContent") %>% html_text
data.frame(Agent=agent, Fnames=fnames, Address=address)
})
df <- do.all(rbind, df)
View(df)

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