https://www.stat.berkeley.edu/classes/s133/Readexample.html Examples of Reading Web Pages with R Examples of Reading Web Pages with R

Examples of Reading Web Pages with R

As an example of how to extract information from a web page, consider the task of extracting the spring baseball schedule for the Cal Bears from http://calbears.cstv.com/sports/m-basebl/sched/cal-m-basebl-sched.html .

1  Reading a web page into R

Read the contents of the page into a vector of character strings with the readLines function: 
> thepage = readLines('http://calbears.cstv.com/sports/m-basebl/sched/cal-m-basebl-sched.html')
Note:  When you're reading a web page, make a local copy for testing; as a courtesy to the owner of the web site whose pages you're using, don't overload their server by constantly rereading the page. To make a copy from inside of R, look at the download.file function. You could also save a copy of the result of using readLines, and practice on that until you've got everything working correctly.
Now we have to focus in on what we're trying to extract. The first step is finding where it is. If you look at the web page, you'll see that the title "Opponent / Event" is right above the data we want. We can locate this line using the grep function: 
> grep('Opponent / Event',thepage)
[1] 357 
If we look at the lines following this marker, we'll notice that the first date on the schedule can be found in line 400, with the other information following after: 
> thepage[400:407]
[1] "      <tr id=\"990963\" title=\"2009,1,21,16,00,00\" valign=\"TOP\" bgcolor=\"#d1d1d1\" class=\"event-listing\">"
[2] "      "
[3] "      <td class=\"row-text\">02/21/09</td>"
[4] "      "                                   
[5] "      <td class=\"row-text\">vs. UC Riverside</td>"
[6] "      "
[7] "      <td class=\"row-text\">Berkeley, Calif.</td>"
[8] "      "                                                             
Based on the previous step, the data that we want is always preceded by the HTML tag "<td class="row-text»", and followed by "</td>". Let's grab all the lines that have that pattern: 
> mypattern = '<td class="row-text">([^<]*)</td>'
> datalines = grep(mypattern,thepage[400:length(thepage)],value=TRUE)
I used value=TRUE, so I wouldn't have to worry about the indexing when I restricted myself to the lines from 400 on. Also notice that I've already tagged the part that I want, in preparation to the final call to gsub.
Now that I've got the lines where my data is, I can use grexpr, then getexpr (from the previous lecture), and gsub to extract the information without the HTML tags: 
> getexpr = function(s,g)substring(s,g,g+attr(g,'match.length')-1)
> gg = gregexpr(mypattern,datalines)
> matches = mapply(getexpr,datalines,gg)
> result = gsub(mypattern,'\\1',matches)
> names(result) = NULL
> result[1:10]
 [1] "02/21/09"         "vs. UC Riverside" "Berkeley, Calif." "1:00 p.m. PT"    
 [5] "02/22/09"         "vs. Vanderbilt"   "Berkeley, Calif." "1:00 p.m. PT"    
 [9] "02/23/09"         "vs. Vanderbilt"  
It seems pretty clear that we've extracted just what we wanted - to make it more usable, we'll convert it to a data frame and provide some titles. Since it's hard to describe how to convert a vector to a data frame, we'll use a matrix as an intermediate step. Since there are four pieces of information (columns) for each game (row), a matrix is a natural choice: 
> schedule = as.data.frame(matrix(result,ncol=4,byrow=TRUE)) 
> names(schedule) = c('Date','Opponent','Location','Result') 
> head(schedule)
      Date            Opponent            Location       Result
1 02/21/09    vs. UC Riverside    Berkeley, Calif. 1:00 p.m. PT
2 02/22/09      vs. Vanderbilt    Berkeley, Calif. 1:00 p.m. PT
3 02/23/09      vs. Vanderbilt    Berkeley, Calif. 1:00 p.m. PT
4 02/25/09      at Santa Clara Santa Clara, Calif. 6:00 p.m. PT
5 02/27/09 at Long Beach State  Long Beach, Calif. 6:30 p.m. PT
6 02/28/09 at Long Beach State  Long Beach, Calif. 2:00 p.m. PT

2  Another Example

At http://www.imdb.com/chart is a box-office summary of the ten top movies, along with their gross profits for the current weekend, and their total gross profits. We would like to make a data frame with that information. As always, the first part of the solution is to read the page into R, and use an anchor to find the part of the data that we want. In this case, the table has column headings, including one for "Rank". 
> x = readLines('http://www.imdb.com/chart/')
> grep('Rank',x)
[1] 1141 1393 1651
Starting with line 1141 we can look at the data to see where the information is. A little experimentation shows that the useful data starts on line 1157: 
> x[1157:1165]
[1] "      <td class=\"chart_even_row\">"                                                 
[2] "          <a href=\"/title/tt0989757/\">Dear John</a> (2010/I)"                      
[3] "      </td>"                                                                         
[4] "      <td class=\"chart_even_row\" style=\"text-align: right; padding-right: 20px\">"
[5] "          $30.5M"                                                                    
[6] "      </td>"                                                                         
[7] "      <td class=\"chart_even_row\" style=\"text-align: right\">"                     
[8] "          $30.5M"                                                                    
[9] "      </td>"                                   
There are two types of lines that contain useful data: the ones with the title, and the ones that begin with some blanks followed by a dollar sign. Here's a regular expression that will pull out both those lines: 
> goodlines = '<a href="/title[^>]*>(.*)</a>.*$|^ *\\$'
> try = grep(goodlines,x,value=TRUE)
Looking at the beginning of try, it seems like we got what we want: 
> try[1:10]
 [1] "          <a href=\"/title/tt1001508/\">He's Just Not That Into You</a> (2009)"
 [2] "          $27.8M"                                                              
 [3] "          $27.8M"                                                              
 [4] "          <a href=\"/title/tt0936501/\">Taken</a> (2008/I)"                    
 [5] "          $20.5M"                                                              
 [6] "          $53.6M"                                                              
 [7] "          <a href=\"/title/tt0327597/\">Coraline</a> (2009)"                   
 [8] "          $16.8M"                                                              
 [9] "          $16.8M"                                                              
[10] "          <a href=\"/title/tt0838232/\">The Pink Panther 2</a> (2009)"         
Sometimes the trickiest part of getting the data off a webpage is figuring out exactly the part you need. In this case, there is a lot of extraneous information after the table we want. By examining the output, we can see that we only want the first 30 entries. We also need to remove the extra information from the title line. We can use the sub function with a modified version of our regular expression: 
> try = try[1:30]
> try = sub('<a href="/title[^>]*>(.*)</a>.*$','\\1',try)
> head(try)
[1] "          He's Just Not That Into You"
[2] "          $27.8M"                     
[3] "          $27.8M"                     
[4] "          Taken"                      
[5] "          $20.5M"                     
[6] "          $53.6M"          
Once the spaces at the beginning of each line are removed, we can rearrange the data into a 3-column data frame: 
> try = sub('^ *','',try)
> movies = data.frame(matrix(try,ncol=3,byrow=TRUE))
> names(movies) = c('Name','Wkend Gross','Total Gross')
> head(movies)
                  Name Wkend Gross Total Gross
1            Dear John      $30.5M      $30.5M
2               Avatar      $22.9M       $629M
3 From Paris with Love      $8.16M      $8.16M
4     Edge of Darkness      $6.86M      $28.9M
5          Tooth Fairy      $6.63M      $34.5M
6         When in Rome      $5.55M      $20.9M

3  Dynamic Web Pages

While reading data from static web pages as in the previous examples can be very useful (especially if you're extracting data from many pages), the real power of techniques like this has to do with dynamic pages, which accept queries from users and return results based on those queries. For example, an enormous amount of information about genes and proteins can be found at the National Center of Biotechnology Information website (http://www.ncbi.nlm.nih.gov/), much of it available through query forms. If you're only performing a few queries, it's no problem using the web page, but for many queries, it's beneficial to automate the process.
Here is a simple example that illustrate the concept of accessing dynamic information from web pages. The page http://finance.yahoo.com provides information about stocks; if you enter a stock symbol on the page, (for example aapl for Apple Computer), you will be directed to a page whose URL (as it appears in the browser address bar) is 
http://finance.yahoo.com/q?s=aapl&x=0&y=0
The way that stock symbols are mapped to this URL is pretty obvious. We'll write an R function that will extract the current price of whatever stock we're interested in.
The first step in working with a page like this is to download a local copy to play with, and to read the page into a vector of character strings: 
> download.file('http://finance.yahoo.com/q?s=aapl&x=0&y=0','quote.html')
trying URL 'http://finance.yahoo.com/q?s=aapl&x=0&y=0'
Content type 'text/html; charset=utf-8' length unknown
opened URL
.......... .......... .......... .........
downloaded 39Kb
> x = readLines('quote.html')
To get a feel for what we're looking for, notice that the words "Last Trade:" appear before the current quote. Let's look at the line containing this string: 
> grep('Last Trade:',x)
25
> nchar(x[25])
[1] 873
Since there are over 800 characters in the line, we don't want to view it directly. Let's use gregexpr to narrow down the search: 
> gregexpr('Last Trade:',x[25])
[[1]]
[1] 411
attr(,"match.length")
[1] 11
This shows that the string "Last Trade:" starts at character 411. We can use substr to see the relevant part of the line: 
substring(x[25],411,500)
[1] "Last Trade:</th><td class=\"yfnc_tabledata1\"><big><b><span id=\"yfs_l10_aapl\">196.19</span><"
There's plenty of context - we want the part surrounded by <big><b><span ... and </span>. One easy way to grab that part is to use a tagged regular expression with gsub: 
> gsub('^.*<big><b><span [^>]*>([^<]*)</span>.*$','\\1',x[25])
[1] "196.19"
This suggests the following function: 
> getquote = function(sym){
+    baseurl = 'http://finance.yahoo.com/q?s='
+    myurl = paste(baseurl,sym,'&x=0&y=0',sep='')
+    x = readLines(myurl)
+    q = gsub('^.*<big><b><span [^>]*>([^<]*)</span>.*$','\\1',grep('Last Trade:',x,value=TRUE))
+    as.numeric(q)
+} 
As always, functions like this should be tested: 
> getquote('aapl')
[1] 196.19
> getquote('ibm')
[1] 123.21
> getquote('nok')
[1] 13.35
These functions provide only a single quote; a little exploration of the yahoo finance website shows that we can get CSV files with historical data by using a URL of the form: 
http://ichart.finance.yahoo.com/table.csv?s=xxx
where xxx is the symbol of interest. Since it's a comma-separated file, We can use read.csv to read the chart. 
gethistory = function(symbol)
   read.csv(paste('http://ichart.finance.yahoo.com/table.csv?s=',symbol,sep=''))
Here's a simple test: 
> aapl = gethistory('aapl')
> head(aapl)
        Date  Open  High   Low Close   Volume Adj.Close
1 2009-02-20 89.40 92.40 89.00 91.20 26780200     91.20
2 2009-02-19 93.37 94.25 90.11 90.64 32945600     90.64
3 2009-02-18 95.05 95.85 92.72 94.37 24417500     94.37
4 2009-02-17 96.87 97.04 94.28 94.53 24209300     94.53
5 2009-02-13 98.99 99.94 98.12 99.16 21749200     99.16
6 2009-02-12 95.83 99.75 95.83 99.27 29185300     99.27
Unfortunately, if we try to use the Date column in plots, it will not work properly, since R has stored it as a factor. The format of the date is the default for the as.Date function, so we can modify our function as follows: 
gethistory = function(symbol){
   data = read.csv(paste('http://ichart.finance.yahoo.com/table.csv?s=',symbol,sep=''))
   data$Date = as.Date(data$Date)
   data
}
Now, we can produce plots with no problems: 
> aapl = gethistory('aapl')
> plot(aapl$Date,aapl$Close,main='Closing price for AAPL',type='l')
The plot is shown below:
This suggest a function for plotting any of the variables in the CSV file: 
plothistory = function(symbol,what){
   match.arg(what,c('Open','High','Low','Close','Volume','Adj.Close'))
   data = gethistory(symbol)
   plot(data$Date,data[,what],main=paste(what,'price for ',symbol),type='l')
   invisible(data)
}
This function introduces several features of functions that we haven't seen yet.

4  Another Example

When using google, it's sometimes inconvenient to have to click through all the pages. Let's write a function that will return the web links from a google search. If you type a search time into google, for example a search for 'introduction to r", you'll notice that the address bar of your browser looks something like this: 
http://www.google.com/search?q=introduction+to+r&ie=utf-8&oe=utf-8&aq=t&rls=com.ubuntu:en-US:unofficial&client=firefox-a
For our purposes, we only need the "q=" part of the search. For our current example, that would be the URL 
http://www.google.com/search?q=introduction+to+r
Note that, since blanks aren't allowed in URLs, plus signs are used in place of spaces. If we were to click on the "Next" link at the bottom of the page, the URL changes to something like 
http://www.google.com/search?hl=en&safe=active&client=firefox-a&rls=com.ubuntu:en-US:unofficial&hs=xHq&q=introduction+to+r&start=10&sa=N
For our purposes, we only need to add the &start= argument to the web page. Since google displays 10 results per page, the second page will have start=10, the next page will have start=20, and so on. Let's read in the first page of this search into R: 
z = readLines('http://www.google.com/search?q=introduction+to+r')
Warning message:
In readLines("http://www.google.com/search?q=introduction+to+r") :
  incomplete final line found on 'http://www.google.com/search?q=introduction+to+r'
As always, you can safely ignore the message about the incomplete final line.
Since we're interested in the web links, we only want lines with "href=" in them. Let's check how many lines we've got, how long they are, and which ones contain the href string: 
> length(z)
[1] 9
> nchar(z)
Error in nchar(z) : invalid multibyte string 3
The error message looks pretty bad - fortunately it's very easy to fix. Basically, the error means that, for the computer's current setup, there's a character that isn't recognized. We can force R to recognize every character by issuing the following command: 
> Sys.setlocale('LC_ALL','C')
[1] "LC_CTYPE=C;LC_NUMERIC=C;LC_TIME=C;LC_COLLATE=C;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTIFICATION=C"
The "UTF-8" means that all characters will now be recognized. 
> nchar(z)
[1]   561   125 25086   351   131   520   449     5    17
> grep('href *=',z)
[1] 3
It's pretty clear that all of the links are on the third line.
Now we can construct a tagged regular expression to grab all the links. 
> hrefpat = 'href *= *"([^"]*)"'
> getexpr = function(s,g)substring(s,g,g+attr(g,'match.length')-1)
> gg = gregexpr(hrefpat,z[[3]])
> res = mapply(getexpr,z[[3]],gg)
> res = sub(hrefpat,'\\1',res)
> res[1:10]
 [1] "http://images.google.com/images?q=introduction+to+r&um=1&ie=UTF-8&sa=N&hl=en&tab=wi"                          
 [2] "http://video.google.com/videosearch?q=introduction+to+r&um=1&ie=UTF-8&sa=N&hl=en&tab=wv"                      
 [3] "http://maps.google.com/maps?q=introduction+to+r&um=1&ie=UTF-8&sa=N&hl=en&tab=wl"                              
 [4] "http://news.google.com/news?q=introduction+to+r&um=1&ie=UTF-8&sa=N&hl=en&tab=wn"                              
 [5] "http://www.google.com/products?q=introduction+to+r&um=1&ie=UTF-8&sa=N&hl=en&tab=wf"                           
 [6] "http://mail.google.com/mail/?hl=en&tab=wm"                                                                    
 [7] "http://www.google.com/intl/en/options/"                                                                       
 [8] "/preferences?hl=en"                                                                                           
 [9] "https://www.google.com/accounts/Login?hl=en&continue=http://www.google.com/search%3Fq%3Dintroduction%2Bto%2Br"
[10] "http://www.google.com/webhp?hl=en"                    
We don't want the internal (google) links - we want external links which will begin with "http://". Let's extract all the external links, and then eliminate the ones that just go back to google: 
> refs = res[grep('^https?:',res)]
> refs = refs[-grep('google.com/',refs)]
> refs[1:3]
 [1] "http://cran.r-project.org/doc/manuals/R-intro.pdf"                                                                                                                   
 [2] "http://74.125.155.132/search?q=cache:d4-KmcWVA-oJ:cran.r-project.org/doc/manuals/R-intro.pdf+introduction+to+r&cd=1&hl=en&ct=clnk&gl=us&ie=UTF-8"                    
 [3] "http://74.125.155.132/search?q=cache:d4-KmcWVA-oJ:cran.r-project.org/doc/manuals/R-intro.pdf+introduction+to+r&amp;cd=1&amp;hl=en&amp;ct=clnk&amp;gl=us&amp;ie=UTF-8"
If you're familiar with google, you may recognize these as the links to google's cached results. We can easily eliminate them: 
> refs = refs[-grep('cache:',refs)]
> length(refs)
[1] 10
We can test these same steps with some of the other pages from this query: 
> z = readLines('http://www.google.com/search?q=introduction+to+r&start=10')
Warning message:
In readLines("http://www.google.com/search?q=introduction+to+r&start=10") :
  incomplete final line found on 'http://www.google.com/search?q=introduction+to+r&start=10'
> hrefpat = 'href *= *"([^"]*)"'
> getexpr = function(s,g)substring(s,g,g+attr(g,'match.length')-1)
> gg = gregexpr(hrefpat,z[[3]])
> res = mapply(getexpr,z[[3]],gg)
> res = sub(hrefpat,'\\1',res)
> refs = res[grep('^https?:',res)]
> refs = refs[-grep('google.com/',refs)]
> refs = refs[-grep('cache:',refs)]
> length(refs)
[1] 10
Once again, it found all ten links. This obviously suggests a function: 
googlerefs = function(term,pg=0){
  getexpr = function(s,g)substring(s,g,g+attr(g,'match.length')-1)
  qurl = paste('http://www.google.com/search?q=',term,sep='')
  if(pg > 0)qurl = paste(qurl,'&start=',pg * 10,sep='')
  qurl = gsub(' ','+',qurl)
  z = readLines(qurl)
  hrefpat = 'href *= *"([^"]*)"'
  wh = grep(hrefpat,z)
  gg = gregexpr(hrefpat,z[[wh]])
  res = mapply(getexpr,z[[wh]],gg)
  res = sub(hrefpat,'\\1',res)
  refs = res[grep('^https?:',res)]
  refs = refs[-grep('google.com/|cache:',refs)]
  names(refs) = NULL
  refs[!is.na(refs)]
}
Now suppose that we want to retreive the links for the first ten pages of query results: 
> links = sapply(0:9,function(pg)googlerefs('introduction to r',pg))
> links = unlist(links)
> head(links)
[1] "http://cran.r-project.org/doc/manuals/R-intro.pdf"             
[2] "http://cran.r-project.org/manuals.html"                        
[3] "http://www.biostat.wisc.edu/~kbroman/Rintro/"                  
[4] "http://faculty.washington.edu/tlumley/Rcourse/"                
[5] "http://www.stat.cmu.edu/~larry/all-of-statistics/=R/Rintro.pdf"
[6] "http://www.stat.berkeley.edu/~spector/R.pdf"