Crash when Scraping Nasdaq website with RVEST-CodePudding

I´m trying to scrap this website https://www.nasdaq.com/market-activity/ipos to get the UNCOMING and PRICED IPO tables but Rstudio crash always I use rvest.

This is my code:

library(rvest)

url="https://www.nasdaq.com/market-activity/ipos"

web <- read_html(url)

datos_web <- web %>%
  html_nodes(xpath = '//*[@]') %>%
  html_table()

How can I do to get this tables into a dataframe?

CodePudding user response：

I don't know if something has changed on the site but you can get the required data from this link which I found from the Networks tab on the webpage.

library(jsonlite)
data <- fromJSON('https://api.nasdaq.com/api/ipo/calendar?date=2021-11')

data$data$upcoming$upcomingTable$rows

#          dealID proposedTickerSymbol                                  companyName     proposedExchange
#1  816750-100864                   SG                             Sweetgreen, Inc.                 NYSE
#2 1182126-100788                  KLC                               KC Holdco, LLC                 NYSE
#3  1171463-98726                HORIU               Emerging Markets Horizon Corp.        NASDAQ Global
#4  888571-100721                 USER                            UserTesting, Inc.                 NYSE
#5 1183593-100874                 IREN                              Iris Energy Ltd NASDAQ Global Select
#6 1028510-100829                 BRZE                                  Braze, Inc. NASDAQ Global Select
#7  1160405-97685                IRRXU INTEGRATED RAIL & RESOURCES ACQUISITION CORP                 NYSE


#  proposedSharePrice sharesOffered expectedPriceDate dollarValueOfSharesOffered
#1        23.00-25.00    12,500,000        11/18/2021               $359,375,000
#2        18.00-21.00    25,775,434        11/18/2021            $622,476,729.00
#3              10.00    25,000,000        11/18/2021               $287,500,000
#4        15.00-17.00    14,169,407        11/17/2021            $277,011,906.00
#5        25.00-27.00     8,269,231        11/17/2021            $256,759,605.00
#6        55.00-60.00     8,000,000        11/17/2021            $528,000,000.00
#7              10.00    20,000,000        11/12/2021               $200,000,000

Similarly, priced data can be found at data$data$priced$rows.