I am trying to scrape the reviews for a product using the below url in R. When I run the below code, I am able to get a single review scraped.
comment<- read_html("https://www.influenster.com/reviews/chobani-greek-yogurt")
comment %>% html_node(".content-item-text") %>% html_text()
comment %>% html_node(".date") %>% html_text()
However, when I use the below code for scraping multiple comments on multiple pages, it returns NULL.
reviews <- lapply(paste0('https://www.influenster.com/reviews/chobani-greek-yogurt?review_page=2', 2:50),
function(url){
url %>% read_html() %>%
html_nodes(".content-item-text review-text") %>%
html_nodes(".date") %>%
html_text()
})
Does the following code achieve what you are looking for?
comment<- read_html("https://www.influenster.com/reviews/chobani-greek-yogurt")
reviews <- c()
dates <- c()
for(i in 1:10){
reviews <- c(reviews,
comment %>%
html_node(paste0(".review-item:nth-child(", i, ") .review-text")) %>%
html_text())
dates <- c(dates,
comment %>%
html_node(paste0(".review-item:nth-child(", i, ") .date")) %>%
html_text())
}
for(j in 2:50){
comment <- read_html(paste0("https://www.influenster.com/reviews/chobani-greek-yogurt?review_page=", j))
for(i in 1:10){
reviews <- c(reviews,
comment %>%
html_node(paste0(".review-item:nth-child(", i, ") .review-text")) %>%
html_text())
dates <- c(dates,
comment %>%
html_node(paste0(".review-item:nth-child(", i, ") .date")) %>%
html_text())
}
}
Just note that I am in the UK and the extracted dates seem to be corrected (- 6 hours what is stated on the site)
Furthermore, apologies for the multiple looping I am not yet very quick at translating loops to the apply functions :)
Related
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)
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......
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;
}
}
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 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)