R: Webscraping: XML content does not seem to be XML: Using HTMLParse - html

Question

I am trying to webscrape data over numerous years (represented by different webpages). My 2019 data works exactly like I want it to, but I am getting an error when I try to prep my 2016 data like my 2019 data.
url19 <- 'https://www.pro-football-reference.com/draft/2019-combine.htm'
get_pfr_HTML_file19 <- GET(url19)
combine.parsed19 <- htmlParse(get_pfr_HTML_file19)
page.tables19 <- readHTMLTable(combine.parsed19, stringsAsFactors = FALSE)
data19 <- data.frame(page.tables19[1])
cleanData19 <- data19[!rowSums(data19 == "")> 0,]
cleanData19 <- filter(cleanData19, cleanData19$combine.Pos == 'CB' | cleanData19$combine.Pos == 'S')
cleanData19 is exactly what I want, but when I try to run it with 2016 data, I get the error: XML content does not seem to be XML: ''
url16 <- 'https://www.pro-football-reference.com/draft/2016-combine.htm'
get_pfr_HTML_file16 <- GET(url16)
combine.parsed16 <- htmlParse(get_pfr_HTML_file16)
page.tables16 <- readHTMLTable(combine.parsed16, stringsAsFactors = FALSE)
data16 <- data.frame(page.tables16[1])
cleanData16 <- data16[!rowSums(data16 == "")> 0,]
cleanData16 <- filter(cleanData16, cleanData16$combine.Pos == 'CB' | cleanData16$combine.Pos == 'S')
I get the error when I try to run combine.parsed16 <- htmlParse(get_pfr_HTML_file16)

Answer 1

I am not 100% sure of your desired output, you did not include your library calls in your example. Any way, using this code you can get the table
library(rvest)
library(dplyr)
url <- 'https://www.pro-football-reference.com/draft/2016-combine.htm'
read_html(url) %>%
html_nodes(".stats_table") %>%
html_table() %>%
as.data.frame() %>%
filter(Pos == 'CB' | Pos == "S")
Several years at once:
library(rvest)
library(magrittr)
library(dplyr)
library(purrr)
years <- 2013:2019
urls <- paste0(
'https://www.pro-football-reference.com/draft/',
years,
'-combine.htm')
map(
urls,
~read_html(.x) %>%
html_nodes(".stats_table") %>%
html_table() %>%
as.data.frame()
) %>%
set_names(years) %>%
bind_rows(.id = "year") %>%
filter(Pos == 'CB' | Pos == "S")