web scraping data table with r rvest

Question

I\'m trying to scrape a table from the following website:

http://www.basketball-reference.com/leagues/NBA_2016.html?lid=header_seasons#all_misc_stats

The table

Answer 1

Here is and another messy solution. Read the page, save it, reread it, remove the comment markers and then process the page:

gameUrl <- "http://www.basketball-reference.com/leagues/NBA_2016.html?lid=header_seasons#all_misc_stats"
gameHtml <- gameUrl %>% read_html()
#gameHtml %>% html_nodes("tbody")

#Only save and work with the body
body<-html_node(gameHtml,"body")
write_xml(body, "nba.xml")

#Find and remove comments
lines<-readLines("nba.xml")
lines<-lines[-grep("<!--", lines)]
lines<-lines[-grep("-->", lines)]
writeLines(lines, "nba2.xml")

#Read the file back in and process normally
body<-read_html("nba2.xml")

#Table 10 was found by looking at all of tables and picking the one of interest
tableofinterest<-(html_nodes(body, "tbody")[10])

rows<-html_nodes(tableofinterest, "tr")
tableOfResults<-t(sapply(rows, function(x) {html_text(html_nodes(x, "td"))}))
#find titles from the frist record's attributes
titles<-html_attrs(html_nodes(rows[1], "td"))
dfnames<-unlist(titles)[seq(2, 2*length(titles), by=2)]

#Final results are stored in data frame "df"
df<-as.data.frame(tableOfResults)
names(df)<-dfnames

This code works but should be simplified! This was based on a similar solution which I posted here: How to get table using rvest()

Answer 2

Since the table you want is hidden in a comment until revealed by JavaScript, you either need to use RSelenium to run the JavaScript (which is kind of a pain), or parse the comments (which is still a pain, but slightly less so).

library(rvest)
library(readr)    # for type_convert

adv <- "http://www.basketball-reference.com/leagues/NBA_2016.html?lid=header_seasons#all_misc_stats"

h <- adv %>% read_html()    # be kind; don't rescrape unless necessary

df <- h %>% html_nodes(xpath = '//comment()') %>%    # select comments
    html_text() %>%    # extract comment text
    paste(collapse = '') %>%    # collapse to single string
    read_html() %>%    # reread as HTML
    html_node('table#misc_stats') %>%    # select desired node
    html_table() %>%    # parse node to table
    { setNames(.[-1, ], paste0(names(.), .[1, ])) } %>%    # extract names from first row
    type_convert()    # fix column types

df[1:6, 1:14]
##   Rk                   Team  Age PW PL   MOV   SOS   SRS  ORtg  DRtg Pace   FTr  3PAr   TS%
## 2  1 Golden State Warriors* 27.4 65 17 10.76 -0.38 10.38 114.5 103.8 99.3 0.250 0.362 0.593
## 3  2     San Antonio Spurs* 30.3 67 15 10.63 -0.36 10.28 110.3  99.0 93.8 0.246 0.223 0.564
## 4  3 Oklahoma City Thunder* 25.8 59 23  7.28 -0.19  7.09 113.1 105.6 96.7 0.292 0.275 0.565
## 5  4   Cleveland Cavaliers* 28.1 57 25  6.00 -0.55  5.45 110.9 104.5 93.3 0.259 0.352 0.558
## 6  5  Los Angeles Clippers* 29.7 53 29  4.28 -0.15  4.13 108.3 103.8 95.8 0.318 0.324 0.556
## 7  6       Toronto Raptors* 26.3 53 29  4.50 -0.42  4.08 110.0 105.2 92.9 0.328 0.287 0.552