Scraping table from myneta using R - r

Question

I am trying to scrape a table from http://myneta.info/uttarpradesh2017/index.php?action=summary&subAction=candidates_analyzed&sort=candidate#summary to my R studio.
Here's the code
url<-'http://myneta.info/uttarpradesh2017/index.php?action=summary&subAction=candidates_analyzed&sort=candidate#summary'
webpage<-read_html(url)
candidate_info<- html_nodes(webpage,xpath='//*[#id="main"]/div/div[2]/div[2]/table')
candidate_info<- html_table(candidate_info)
head(candidate_info)
But getting no output, suggest what I am doing wrong?

Answer 1

That site has some very broken HTML. But, it's workable.
I find it better to target nodes in a slightly less fragile way. The XPath below finds it by content of the table.
html_table() croaks (or took forever and I didn't want to wait) so I ended up building the table "manually".
library(rvest)
# helper to clean column names
mcga <- function(x) { make.unique(gsub("(^_|_$)", "", gsub("_+", "_", gsub("[[:punct:][:space:]]+", "_", tolower(x)))), sep = "_") }
pg <- read_html("http://myneta.info/uttarpradesh2017/index.php?action=summary&subAction=candidates_analyzed&sort=candidate#summary")
# target the table
tab <- html_node(pg, xpath=".//table[contains(thead, 'Liabilities')]")
# get the rows so we can target columns
rows <- html_nodes(tab, xpath=".//tr[td[not(#colspan)]]")
# make a data frame
do.call(
cbind.data.frame,
c(lapply(1:8, function(i) {
html_text(html_nodes(rows, xpath=sprintf(".//td[%s]", i)), trim=TRUE)
}), list(stringsAsFactors=FALSE))
) -> xdf
# make nicer names
xdf <- setNames(xdf, mcga(html_text(html_nodes(tab, "th")))) # get the header to get column names
str(xdf)
## 'data.frame': 4823 obs. of 8 variables:
## $ sno : chr "1" "2" "3" "4" ...
## $ candidate : chr "A Hasiv" "A Wahid" "Aan Shikhar Shrivastava" "Aaptab Urf Aftab" ...
## $ constituency : chr "ARYA NAGAR" "GAINSARI" "GOSHAINGANJ" "MUBARAKPUR" ...
## $ party : chr "BSP" "IND" "Satya Shikhar Party" "Islam Party Hind" ...
## $ criminal_case: chr "0" "0" "0" "0" ...
## $ education : chr "12th Pass" "10th Pass" "Graduate" "Illiterate" ...
## $ total_assets : chr "Rs 3,94,24,827 ~ 3 Crore+" "Rs 75,106 ~ 75 Thou+" "Rs 41,000 ~ 41 Thou+" "Rs 20,000 ~ 20 Thou+" ...
## $ liabilities : chr "Rs 58,46,335 ~ 58 Lacs+" "Rs 0 ~" "Rs 0 ~" "Rs 0 ~" ...