I'm struggling to webscrape this search and was wondering if anyone has an idea on how I should be organizing the nested loop? At one point I was running into the problem that read_html() can't read multiple rows in a data frame. I tried to get around this with how I set up the loop, but have been unsuccessful. (I also could use some pointers on the outputs of loops:/). Thanks in advance.
library(purrr)
library(rvest)
library(data.table)
library(tidyverse)
library(quanteda)
library(quanteda.textstats)
#seach first page
url_1 <- "https://www.congress.gov/quick-search/legislation?wordsPhrases=healthcare&wordVariants=on&congressGroups%5B%5D=0&congresses%5B%5D=all&legislationNumbers=&legislativeAction=&sponsor=on&representative=&senator=&houseCommittee%5B%5D=hsif00&q={%22chamber%22:%22House%22,%22type%22:%22bills%22,%22subject%22:%22Health%22,%22house-committee%22:%22Energy+and+Commerce%22}&pageSize=250"
#seach second page
url_2 <- "https://www.congress.gov/quick-search/legislation?wordsPhrases=healthcare&wordVariants=on&congressGroups%5B0%5D=0&congresses%5B0%5D=all&legislationNumbers=&legislativeAction=&sponsor=on&representative=&senator=&houseCommittee%5B0%5D=hsif00&q=%7B%22chamber%22%3A%22House%22%2C%22type%22%3A%22bills%22%2C%22subject%22%3A%22Health%22%2C%22house-committee%22%3A%22Energy+and+Commerce%22%7D&pageSize=250&page=2"
read_html(url_1)
#css_selector <- ".result-heading a"
#scrape all 250 bill hyperlinks on first page
urlLinks <- url_1 %>%
read_html() %>%
html_nodes(".result-heading a") %>%
html_attr("href")
urlLinks<- unique(urlLinks)
as.data.frame(urlLinks)
#pull text from the first bill hyperlink
first_link <- urlLinks[1]
first_link <- gsub("\\?.*", "", first_link) #Remove everything from ?q
first_link <- paste0("https://www.congress.gov", first_link, "/text") #Add /text to the link and prepare the hyperlink url
#Get text from the first bill hyperlink
get_text <- read_html(first_link) %>%
html_nodes(".generated-html-container") %>%
html_text(trim = T)
get_text
Sys.sleep(5)
#loop above for all 250 bill hyperlinks on one page
billTexts <- c()
for (i in 1:length(urlLinks)){
rest_of_links <- urlLinks[i]
rest_of_links <- gsub("\\?.*", "", rest_of_links)
rest_of_links <- paste0("https://www.congress.gov", rest_of_links, "/text")
billText <- read_html(rest_of_links) %>%
html_nodes(".generated-html-container") %>%
html_text(trim = T)
billTexts <- c(billTexts, billText)
}
#Loop for each page (34)
final <- c() #final table for the loop output
output <- c() #inner loop output
pageNumber <- c(2:34)
#urls for search pages
urls <- url_1
for(i in 1:length(pageNumber)){
urls <- c(urls, paste0("https://www.congress.gov/quick-search/legislation?wordsPhrases=healthcare&wordVariants=on&congressGroups%5B0%5D=0&congresses%5B0%5D=all&legislationNumbers=&legislativeAction=&sponsor=on&representative=&senator=&houseCommittee%5B0%5D=hsif00&q=%7B%22chamber%22%3A%22House%22%2C%22type%22%3A%22bills%22%2C%22subject%22%3A%22Health%22%2C%22house-committee%22%3A%22Energy+and+Commerce%22%7D&pageSize=250&page=",pageNumber[i], sep=""))
#read the 250 hyperlinks on each of the 34 pages
urlLinks <- urls[i] %>%
read_html() %>%
html_nodes(".result-heading a") %>%
html_attr("href")
urlLinks<- unique(urlLinks)
billTexts <- c()
#loop for pulling bill text for each of the 250 hyperlinks
for (j in 1:length(urlLinks)){
rest_of_links <- urlLinks[j]
rest_of_links <- gsub("\\?.*", "", rest_of_links)
rest_of_links <- paste0("https://www.congress.gov", rest_of_links, "/text")
billText <- read_html(rest_of_links) %>%
html_nodes(".generated-html-container") %>%
html_text(trim = T)
billTexts <- c(billTexts, billText)
#taking bill output and putting in table
output <- c(output,billTexts)
}
#taking inner loop output and combining with outer loop output and putting it in table
final <- c(output, urlLinks)
#return the final dataset here
}
I was expecting to get a data frame with the bill texts (1 per link) in each hyperlink (250 links) on each page of the search (34 pages).
We can split the nested loop into simple loops using lapply,
First generate links for all the 34 pages,
urls <- c(urls, paste0("https://www.congress.gov/quick-search/legislation?wordsPhrases=healthcare&wordVariants=on&congressGroups%5B0%5D=0&congresses%5B0%5D=all&legislationNumbers=&legislativeAction=&sponsor=on&representative=&senator=&houseCommittee%5B0%5D=hsif00&q=%7B%22chamber%22%3A%22House%22%2C%22type%22%3A%22bills%22%2C%22subject%22%3A%22Health%22%2C%22house-committee%22%3A%22Energy+and+Commerce%22%7D&pageSize=250&page=",2:34))
Second get links from each of the 34 page,
df = lapply(urls, function(x){
urlLinks = x %>%
read_html() %>%
html_nodes(".result-heading a") %>%
html_attr("href")
urlLinks<- unique(urlLinks)
first_link <- gsub("\\?.*", "", urlLinks)
first_link <- paste0("https://www.congress.gov", first_link, "/text")
})
Third get text from each of the links,
text = lapply(df, function(x) lapply(x, function(x){
text1 = read_html(x) %>%
html_nodes(".generated-html-container") %>%
html_text(trim = T)
})
)
We now have text from all the 34 pages stored in a list.
Related
I have a code to scrape a senate website and extract all the information about representatives in a data frame. It runs fine up until I try to scrape the part about their term information. The function I'm using just returns "NA" instead of the term assignments. Would really appreciate some help in figuring out what I'm doing wrong in the last block of code (baselink3 onwards).
install.packages("tidyverse")
install.packages("rvest")
library(rvest)
library(dplyr)
library(stringr)
#Create blank lists
member_list <- list()
photo_list <- list()
memberlink_list <- list()
cycle_list <- list()
#Scrape data
cycles <- c("2007","2009","2011","2013","2015","2017","2019","2021")
base_link <- "https://www.legis.state.pa.us/cfdocs/legis/home/member_information/mbrList.cfm?Body=S&SessYear="
for(cycle in cycles) {
member_list[[cycle]] <- read_html(paste(base_link, cycle, sep="")) %>%
html_nodes(".MemberInfoList-MemberBio a") %>%
html_text()
memberlink_list[[cycle]] <- read_html(paste(base_link, cycle, sep="")) %>%
html_nodes(".MemberInfoList-MemberBio a") %>%
html_attr("href")
photo_list[[cycle]] <- read_html(paste(base_link, cycle, sep="")) %>%
html_nodes(".MemberInfoList-PhotoThumb img") %>%
html_attr("src")
cycle_list[[cycle]] <- rep(cycle, times = length(member_list[[cycle]]))
}
#Assemble data frame
member_list2 <- unlist(member_list)
cycle_list2 <- unlist(cycle_list)
photo_list2 <- unlist(photo_list)
memberlink_list2 <- unlist(memberlink_list)
senate_directory <- data.frame(cycle_list2, member_list2, photo_list2, memberlink_list2) %>%
rename(Cycle = cycle_list2,
Member = member_list2,
Photo = photo_list2,
Link = memberlink_list2)
#New Section from March 12
##Trying to use each senator's individual page
#Convert memberlink_list into dataframe
df <- data.frame(matrix(unlist(memberlink_list), nrow=394, byrow=TRUE),stringsAsFactors=FALSE)
colnames(df) <- "Link" #rename column to link
base_link3 <- paste0("https://www.legis.state.pa.us/cfdocs/legis/home/member_information/", df$Link) #creating each senator's link
terminfo <- sapply(base_link2, function(x) {
val <- x %>%
read_html %>%
html_nodes('div.MemberBio-TermInfo') %>%
html_text() %>%
str_extract('(?<=Senate Term )\\d+')
if(length(val)) val else NA
}, USE.NAMES = FALSE)
terminfo <- data.frame(terminfo, df$Link)
I am not sure what exactly you are looking for, but something like this might help you. Note that the page has a crawl delay of 5 seconds. Something you did not implement or respect in your code above. See here
library(httr)
library(purrr)
extract_terminfo <- function(link) {
html <- httr::GET(link)
Sys.sleep(runif(1,5,6))
val <- html %>%
content(as = "parsed") %>%
html_nodes('div.MemberBio-TermInfo') %>%
html_text() %>%
str_extract('(?<=Term Expires: )\\d+')
if(length(val)>0){
return(data.frame(terminfo = val, link = link))
} else {
return(data.frame(terminfo = "historic", link = link))
}
}
link <- base_link3[1]
link
extract_terminfo(link)
term_info <- map_dfr(base_link3[1:3],extract_terminfo)
I'm trying to build a web scraper to scrape articles published on www.20min.ch, a news website, with R. Their api is openly accessible so I could create a dataframe containing titles, urls, descriptions, and timestamps with rvest. The next step would be to access every single link and create a list of article texts and combine it with my dataframe. However I don't know how to automatize the access to those articles. Ideally, I would like to read_html link 1, then copy the text with html node and then proceed to link 2...
This is what I wrote so far:
site20min <- read_xml("https://api.20min.ch/rss/view/1")
site20min
url_list <- site20min %>% html_nodes('link') %>% html_text()
df20min <- data.frame(Title = character(),
Zeit = character(),
Lead = character(),
Text = character()
)
for(i in 1:length(url_list)){
myLink <- url_list[i]
site20min <- read_html(myLink)
titel20min <- site20min %>% html_nodes('h1 span') %>% html_text()
zeit20min <- site20min %>% html_nodes('#story_content .clearfix span') %>% html_text()
lead20min <- site20min %>% html_nodes('#story_content h3') %>% html_text()
text20min <- site20min %>% html_nodes('.story_text') %>% html_text()
df20min_a <- data.frame(Title = titel20min)
df20min_b <- data.frame(Zeit = zeit20min)
df20min_c <- data.frame(Lead = lead20min)
df20min_d <- data.frame(Text = text20min)
}
What I need is R to open every single link and extract some information:
site20min_1 <- read_html("https://www.20min.ch/schweiz/news/story/-Es-liegen-auch-Junge-auf-der-Intensivstation--14630453")
titel20min_1 <- site20min_1 %>% html_nodes('h1 span') %>% html_text()
zeit20min_1 <- site20min_1 %>% html_nodes('#story_content .clearfix span') %>% html_text()
lead20min_1 <- site20min_1 %>% html_nodes('#story_content h3') %>% html_text()
text20min_1 <- site20min_1 %>% html_nodes('.story_text') %>% html_text()
It should not be too much of a problem to rbind this to a dataframe. but at the moment some of my results turn out empty.
thx for your help!
You're on the right track with setting up a dataframe. You can loop through each link and rbind it to your existing dataframe structure.
First, you can set a vector of urls to be looped through. Based on the edit, here is such a vector:
url_list <- c("http://www.20min.ch/ausland/news/story/14618481",
"http://www.20min.ch/schweiz/news/story/18901454",
"http://www.20min.ch/finance/news/story/21796077",
"http://www.20min.ch/schweiz/news/story/25363072",
"http://www.20min.ch/schweiz/news/story/19113494",
"http://www.20min.ch/community/social_promo/story/20407354",
"https://cp.20min.ch/de/stories/635-stressfrei-durch-den-verkehr-so-sieht-der-alltag-von-busfahrer-claudio-aus")
Next, you can set a dataframe structure that includes everything you're looking to gether.
# Set up the dataframe first
df20min <- data.frame(Title = character(),
Link = character(),
Lead = character(),
Zeit = character())
Finally, you can loop through each url in your list and add the relevant info to your dataframe.
# Go through a loop
for(i in 1:length(url_list)){
myLink <- url_list[i]
site20min <- read_xml(myLink)
# Extract the info
titel20min <- site20min %>% html_nodes('title') %>% html_text()
link20min <- site20min %>% html_nodes('link') %>% html_text()
zeit20min <- site20min %>% html_nodes('pubDate') %>% html_text()
lead20min <- site20min %>% html_nodes('description') %>% html_text()
# Structure into dataframe
df20min_a <- data.frame(Title = titel20min, Link =link20min, Lead = lead20min)
df20min_b <- df20min_a [-(1:2),]
df20min_c <- data.frame(Zeit = zeit20min)
# Insert into final dataframe
df20min <- rbind(df20min, cbind(df20min_b,df20min_c))
}
My doubt is how to include a column in "my_data" (my_data$sector), showing what url_list[[j]] or url_info was used for that line.
Each url will bring me a table (35 x 100) and I need to show what element was the source when putting all together.
url_list <- vector()
url_info <- vector()
# then, i feed it.
total_pages <- 1:5 #for my use, i need almost 100 pages
for (i in total_pages) {
url_list [i] <- paste('http://www.mylink/result.php?sector=',i,sep = "")
url_info [i] <- paste('sector_',i,sep = "")
}
url_list
>> [1] "http://www.mylink/result.php?sector=1" "http://www.mylink/result.php?sector=2"
[3] "http://www.mylink/result.php?sector=3" "http://www.mylink/result.php?sector=4"
[5] "http://www.mylink/result.php?sector=5"
url_info
>> [1] "sector_1" "sector_2" "sector_3" "sector_4" "sector_5"
#scraping
my_data <- list()
for (j in seq_along(url_list)) {
my_data[[j]] <- url_list[[j]] %>%
read_html() %>%
html_node("table") %>%
html_table()
}
final_data <- cbind(do.call(rbind, my_data))
I don't have a list of url with tables you can rbind, but try something below, it will append the url to the last column.
You have to try it on your actual data for rbind:
my_data <- list()
url_list=c(
"http://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_population",
"https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_historical_population",
"https://en.wikipedia.org/wiki/List_of_countries_and_dependencies_by_population")
for (j in seq_along(url_list)) {
my_data[[j]] <- url_list[[j]] %>%
read_html() %>%
html_node("table") %>%
html_table() %>%
mutate(url=url_list[j])
}
Something like this should work
library(tidyverse)
library(xml2)
pipe_function <- . %>%
read_html() %>%
html_node("table") %>%
html_table()
tibble(url_info,url_list) %>%
mutate(table = url_list %>% map_dfr(pipe_function))
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$Title[lowers[j]:uppers[j]]){
tmpSession <- html_session(url_base)
nextpage1 <- tmpSession %>% follow_link(i) %>% read_html()
list1[[i]]<- nextpage1 %>%
html_nodes(".grid-row") %>% html_text()
}
}
)
Not sure if this is what you want or not, I might have misunderstood the things that are supposed to be changing.
I want to scrape the ranking on the left of this page, which is spread over 34 views and which I believe (total newbie to scraping) to be Java-genereated. All views have the same url, so I cannot loop over these.
As far as I gather, each view seems to have node #elferspielerhistorie_subcont_j td, starting with j=0.
I can scrape the first entries with
library(rvest)
library(tidyverse)
elfer_url <- "http://www.kicker.de/news/fussball/bundesliga/spieltag/1-bundesliga/elfmeter-schuetzen-geschichte.html"
# first page
elfmeter <- read_html(elfer_url)
Schuetzen <- elfmeter %>% html_nodes("#elferspielerhistorie_subcont_0 td") %>% html_text()
My "strategy" is then to click, with RSelenium, on the link for the next page, paste the next node and do over. The loop however returns empty entries for the next 33 views (entire code for completeness):
library(rvest)
library(tidyverse)
library(RSelenium)
elfer_url <- "http://www.kicker.de/news/fussball/bundesliga/spieltag/1-bundesliga/elfmeter-schuetzen-geschichte.html"
rD <- rsDriver(port = 4444L, browser = "firefox")
remDr <- rD$client
remDr$navigate(elfer_url)
# first page
elfmeter <- read_html(elfer_url)
Schuetzen <- elfmeter %>% html_nodes("#elferspielerhistorie_subcont_0 td") %>% html_text() %>% matrix(ncol=10, byrow=T) %>% data.frame()
clicknext <- remDr$findElements("xpath","//*[#id='ctl00_PlaceHolderContent_elfer_blaettern_elferhistorie_PagerForward']")
j <- 1
while (j<=34){
clicknext[[1]]$clickElement() # sends me to the right view
#elfmeter <- read_html(elfer_url) # switching this on or off does not change things
current.node <- paste0("#elferspielerhistorie_subcont_",j," td") # should be the node
weitere_Schuetzen <- elfmeter %>% html_node(current.node) %>% html_text() %>% matrix(ncol=10, byrow=T) %>% data.frame() # returns empty result
Schuetzen <- rbind(Schuetzen,weitere_Schuetzen)
j <- j+1
}
Since the views are generated dynamically you have to get the page source on every turn. It might be, that the ID of the next button changes so it is save to also find that button on every iteration.
The following code should work. Notice that I also read out those empty rows which are dropped when the loop has finished:
library(rvest)
library(tidyverse)
library(RSelenium)
elfer_url <- "http://www.kicker.de/news/fussball/bundesliga/spieltag/1-bundesliga/elfmeter-schuetzen-geschichte.html"
rD <- rsDriver(port = 4447L, browser = "firefox")
remDr <- rD$client
remDr$navigate(elfer_url)
getTable <- function(x) {
remDr$getPageSource()[[1]] %>%
read_html %>%
html_nodes(paste0("#elferspielerhistorie_subcont_", x, " table")) %>%
html_table(fill = T) %>%
.[[1]] %>%
data.frame
}
# first page
data <- getTable(0)
for(j in 1:33) {
next_button <- remDr$findElements("css","a[id=\"ctl00_PlaceHolderContent_elfer_blaettern_elferhistorie_PagerForward\"]") %>% .[[1]]
remDr$executeScript(script = "arguments[0].scrollIntoView(true);", args = list(next_button))
next_button$clickElement()
# sometimes the loop is too fast and it cannot fetch the table. so pause here
Sys.sleep(1)
data <- rbind(data, getTable(j))
j <- j+1
}
rD$server$stop()
data <- data[-which(data$Spieler == ""),]
dim(data)
> [1] 935 10