R Web Scraping - Data is Incomplete (Yahoo Finance)

Expanding on my earlier comment here is a (partial) answer relying on the quantmod package and its handling of the request. Yahoo! actually supports a range of fields, and the Python package yfinance has slightly better documentation.

Here we first select (interactively !) the fields we want:

> library(quantmod) # CRAN package used here
> qf <- yahooQF()   # launches a GUI-based selector
> qf                # this corresponds to the selection I made
[[1]]
 [1] "symbol"                      "shortName"                  
 [3] "ask"                         "bid"                        
 [5] "regularMarketPrice"          "regularMarketChange"        
 [7] "regularMarketOpen"           "regularMarketDayHigh"       
 [9] "regularMarketDayLow"         "regularMarketVolume"        
[11] "regularMarketChangePercent"  "regularMarketPreviousClose" 
[13] "fiftyTwoWeekLow"             "fiftyTwoWeekHigh"           
[15] "ytdReturn"                   "trailingPE"                 
[17] "trailingAnnualDividendYield" "netAssets"                  
[19] "netExpenseRatio"            

[[2]]
 [1] "Symbol"            "Name"              "Ask"              
 [4] "Bid"               "Last"              "Change"           
 [7] "Open"              "High"              "Low"              
[10] "Volume"            "% Change"          "P. Close"         
[13] "52-week Low"       "52-week High"      "YTD Return"       
[16] "P/E Ratio"         "Dividend Yield"    "Net Assets"       
[19] "Net Expense Ratio"

attr(,"class")
[1] "quoteFormat"
>

Next we use this selection to download data for IVV:

> getQuote("IVV", what=qf)
             Trade Time Symbol                     Name    Ask    Bid
IVV 2025-07-30 15:52:42    IVV iShares Core S&P 500 ETF 634.96 635.02
      Last   Change  Open    High    Low  Volume  % Change P. Close
IVV 636.16 -2.24005 639.1 640.735 634.59 2909287 -0.350885    638.4
    52-week Low 52-week High YTD Return P/E Ratio Dividend Yield
IVV         484       641.74    6.18625   27.3658     0.00890977
     Net Assets Net Expense Ratio
IVV 6.22809e+11              0.03
> 

This function is vectorized so given a selection of fields as in qf here you could also retrieve multiple quotes at once.

PS For completeness a re-usable display of the qf variable I used:

> dput(qf)
structure(list(c("symbol", "shortName", "ask", "bid", "regularMarketPrice", 
"regularMarketChange", "regularMarketOpen", "regularMarketDayHigh", 
"regularMarketDayLow", "regularMarketVolume", "regularMarketChangePercent", 
"regularMarketPreviousClose", "fiftyTwoWeekLow", "fiftyTwoWeekHigh", 
"ytdReturn", "trailingPE", "trailingAnnualDividendYield", "netAssets", 
"netExpenseRatio"), c("Symbol", "Name", "Ask", "Bid", "Last", 
"Change", "Open", "High", "Low", "Volume", "% Change", "P. Close", 
"52-week Low", "52-week High", "YTD Return", "P/E Ratio", "Dividend Yield", 
"Net Assets", "Net Expense Ratio")), class = "quoteFormat")
> 

Ada's Qunatmod answer is to be preferred, but you asked

What code change is required to grab all values in the first table under the graph?

A lot. You want all <li> items in the <ul> below the div[@data-testid="quote-statistics"]. For a cleaner approach, you could target the 12 <fin-streamer> elements

<fin-streamer data-symbol="IVV" data-value="4,559,917" data-trend="none" active="" data-dfield="longFmt" data-field="regularMarketVolume" class="yf-1b7pzha">4,559,917</fin-streamer>

and manually adress the 3 remaining fields and pull their attributes. In my Code, I use selenider + chromote and then just pull the raw text out of the 15 <li> elements and apply some string splitting.

library(chromote)
library(selenider)
session <- selenider_session("chromote",options = chromote_options(headless = FALSE))
open_url("https://finance.yahoo.com/quote/IVV/")
try(s("button[name='reject']") |> elem_click(), silent = TRUE)
tab <- do.call(rbind,lapply(ss(xpath = '//div[@data-testid="quote-statistics"]//ul//li'), \(x) elem_text(x)))[,1]
res <- sub("52 Week", "FiftyTwo Week", tab)
res <- sub("5Y Monthly", "Five Y Monthly", res)
name <- sub("^(\\D+).*", "\\1", res) |> trimws()
value <- sapply(regmatches(res, regexpr("^(.+?)\\s+(?=[0-9])", res, perl = TRUE), invert = TRUE), \(x) trimws(paste(x[-1], collapse = "")))
si <- data.frame(name = name, value = value)
close_session()

                     name           value
1          Previous Close          638.40
2                    Open          639.10
3                     Bid    640.02 x 300
4                     Ask    640.65 x 400
5             Day's Range 634.59 - 640.73
6     FiftyTwo Week Range 484.00 - 641.74
7                  Volume       4,559,917
8             Avg. Volume       5,854,059
9              Net Assets         622.81B
10                    NAV          638.12
11         PE Ratio (TTM)           27.42
12                  Yield           1.29%
13 YTD Daily Total Return           9.12%
14  Beta (Five Y Monthly)            1.00
15    Expense Ratio (net)           0.03%

Disclaimer: I very much do not recommend this, your IP could be temporarly banned.

A much better approach would be to use the yahoofinancer package (I used kable because it makes the result more clear)

library(yahoofinancer)
s <- Ticker$new('IVV')
yf <- s$get_history(start = today(), interval = '1d')
fields <- c('regular_market_price', 'fifty_two_week_high', 'fifty_two_week_low',
            'regular_market_volume', 'exchange_name', 'full_exchange_name',
            'previous_close', 'currency', 'exchange_timezone_name', 'symbol')
yf[fields] <- lapply(fields, \(x) s[[x]])

Or using the code base from {yahoofinanceR} you can write your own function that retrieves the Quote data directly from the API:

# using yahoofinancers function get_meta we can write our own version
# that retrieves the full API response as list
library(jsonlite)
library(httr)

# Source: https://github.com/rsquaredacademy/yahoofinancer/blob/dbad4b14f355ee925650f95d380d0eae52f821ab/R/ticker.R#L433
get_yahoo_symbol_info <- function(sym) {
  url <- paste0("https://query2.finance.yahoo.com/v8/finance/chart/", sym)
  jsonlite::fromJSON(httr::content(httr::GET(url), "text", encoding = "UTF-8"), 
                     simplifyVector = FALSE)$chart$result[[1]]
}

ivv_info <- get_yahoo_symbol_info("IVV")