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<pre><code class="r">#
# scraping a simple html page
# Page has 4 people with contact information. We want to get them into a dataframe
#
library(rvest)
# Read the page
pg = read_html("simplePage.html")
# Get list of names
# attribute id can be extracted with prefixing #
name = pg %>% html_nodes("#name") %>% html_text()
name
</code></pre>
<pre><code>## [1] "Alexander, Jones" "Liz, Phillips" "Joe, Whoisit"
## [4] "Hello, Howareyou"
</code></pre>
<pre><code class="r"># extracting names with xpath
names2 = pg %>% html_nodes(xpath = "//li//div[@id = 'name']") %>% html_text()
names2
</code></pre>
<pre><code>## [1] "Alexander, Jones" "Liz, Phillips" "Joe, Whoisit"
## [4] "Hello, Howareyou"
</code></pre>
<pre><code class="r"># get links from href attribute
link = pg %>% html_nodes("a") %>% html_attr("href")
link
</code></pre>
<pre><code>## [1] "http:/www.meetup.com" "http:/www.google.com" "http:/www.google.com"
## [4] "http:/www.google.com"
</code></pre>
<pre><code class="r"># Get list of addresses and cities
# attribute class can be extracted with prefixing period (.)
addr = pg %>% html_nodes(".add") %>% html_text()
addr
</code></pre>
<pre><code>## [1] "123, Maple Drive" "123, Walnut Drive" "999, Icecream Blvd"
## [4] "843, Crazy Drive"
</code></pre>
<pre><code class="r">city = pg %>% html_nodes("li .city span") %>% html_text()
city
</code></pre>
<pre><code>## [1] "Indianapolis" "Chicago" "New York" "San Francisco"
</code></pre>
<pre><code class="r"># Get state and zip code info
state = pg %>% html_nodes("p[geo = 'state']") %>% html_text()
state
</code></pre>
<pre><code>## [1] "IN" "IL" "NY" "CA"
</code></pre>
<pre><code class="r">zipcode = pg %>% html_nodes("p[geocode = 'zip']") %>% html_text()
zipcode
</code></pre>
<pre><code>## [1] "12345" "67809" "54321" "11111"
</code></pre>
<pre><code class="r"># What if geo and geocode attributes are not there in html
state2 = pg %>% html_nodes("div p") %>% html_text() # won't work since it gets both state and zip code
state2
</code></pre>
<pre><code>## [1] "IN" "12345" "IL" "67809" "NY" "54321" "CA" "11111"
</code></pre>
<pre><code class="r"># directly using xpath handy since it is able to just extract the first element for state and second element for zip
state2 = pg %>% html_nodes(xpath = "//div[@class = 'city']/p[1]") %>% html_text()
state2
</code></pre>
<pre><code>## [1] "IN" "IL" "NY" "CA"
</code></pre>
<pre><code class="r">zip2 = pg %>% html_nodes(xpath = "//div[@class = 'city']/p[2]") %>% html_text()
zip2
</code></pre>
<pre><code>## [1] "12345" "67809" "54321" "11111"
</code></pre>
<pre><code class="r"># Get phone numbers
phone = pg %>% html_nodes(".comm p[type = 'phone']") %>% html_text()
phone # problem since only 2 addresses have phone numbers and it will be hard to align with other fields
</code></pre>
<pre><code>## [1] "317-123-4567" "123-999-4567"
</code></pre>
<pre><code class="r"># workaround is to force using all nodes
addrnodes = pg %>% html_nodes("li")
addrnodes
</code></pre>
<pre><code>## {xml_nodeset (4)}
## [1] <li>\n <div id="name"><a href="http:/www.meetup.com">Alexa ...
## [2] <li>\n <div id="name"><a href="http:/www.google.com">Liz, ...
## [3] <li>\n <div id="name"><a href="http:/www.google.com">Joe, ...
## [4] <li>\n <div id="name"><a href="http:/www.google.com">Hello ...
</code></pre>
<pre><code class="r">phone = sapply(addrnodes, function(x) x %>% html_nodes(".comm p[type = 'phone']") %>% html_text())
phone # has length 0 fields when phone doesn't exist
</code></pre>
<pre><code>## [[1]]
## [1] "317-123-4567"
##
## [[2]]
## character(0)
##
## [[3]]
## [1] "123-999-4567"
##
## [[4]]
## character(0)
</code></pre>
<pre><code class="r">phone = sapply(phone, function(x) if(length(x) == 0) NA else x) # set NA to missing phone numbers
phone
</code></pre>
<pre><code>## [1] "317-123-4567" NA "123-999-4567" NA
</code></pre>
<pre><code class="r"># Get email addresses
email = sapply(addrnodes, function(x) x %>% html_nodes(".comm p[type = 'email']") %>% html_text())
email = sapply(email, function(x) if(length(x) == 0) NA else x)
email
</code></pre>
<pre><code>## [1] "jabc@gmail.com" NA "jwhst@yahoo.com" "hhru@yahoo.com"
</code></pre>
<pre><code class="r"># create a dataframe with address data
addrdf = data.frame(name = name, addr = addr, city = city, state = state, zipcode = zipcode,
phone = phone, email = email, link = link)
addrdf
</code></pre>
<pre><code>## name addr city state zipcode
## 1 Alexander, Jones 123, Maple Drive Indianapolis IN 12345
## 2 Liz, Phillips 123, Walnut Drive Chicago IL 67809
## 3 Joe, Whoisit 999, Icecream Blvd New York NY 54321
## 4 Hello, Howareyou 843, Crazy Drive San Francisco CA 11111
## phone email link
## 1 317-123-4567 jabc@gmail.com http:/www.meetup.com
## 2 <NA> <NA> http:/www.google.com
## 3 123-999-4567 jwhst@yahoo.com http:/www.google.com
## 4 <NA> hhru@yahoo.com http:/www.google.com
</code></pre>
<pre><code class="r">#
# Scraping a html table
# scraping list of packages from CRAN site
#
url = "http://cran.us.r-project.org/web/packages/available_packages_by_date.html"
cranpg = read_html(url)
cranlist = cranpg %>% html_nodes("table") %>% html_table()
head(cranlist[[1]])
</code></pre>
<pre><code>## Date Package
## 1 2016-01-17 DJL
## 2 2016-01-17 freqparcoord
## 3 2016-01-17 nlme
## 4 2016-01-17 OECD
## 5 2016-01-17 proportion
## 6 2016-01-17 RcmdrPlugin.NMBU
## Title
## 1 Distance Measure Based Judgment and Learning
## 2 Novel Methods for Parallel Coordinates
## 3 Linear and Nonlinear Mixed Effects Models
## 4 Search and Extract Data from the OECD
## 5 Inference on Single Binomial Proportion and Bayesian\nComputations
## 6 R Commander Plug-in for University Level Applied Statistics
</code></pre>
<pre><code class="r"># Used RStudio 0.99.489
sessionInfo()
</code></pre>
<pre><code>## R version 3.2.3 (2015-12-10)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: OS X 10.11.1 (El Capitan)
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] rmarkdown_0.8.1 rvest_0.3.1 xml2_0.1.2
##
## loaded via a namespace (and not attached):
## [1] Rcpp_0.12.2 XML_3.98-1.3 digest_0.6.8 R6_2.1.1
## [5] magrittr_1.5 evaluate_0.8 httr_1.0.0 stringi_1.0-1
## [9] curl_0.9.4 tools_3.2.3 stringr_1.0.0 selectr_0.2-3
## [13] markdown_0.7.7 htmltools_0.2.6 knitr_1.11
</code></pre>
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