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Thursday, April 5, 2018

Simplified Web Scraping in R using 'rvest' Package For Beginners

laptop image of surfing the web

Data scraping in R is relatively easy and can be done in a few steps. It is the first step to performing a text analytics of website data. Follow this tutorial below to perform your first web scraping project.

Checkout: Learn more about web scraping

First you need to have R and R studio already installed in your device. A tutorial on installing R and R studio is available on this blog. For simplicity purposes, we shall base our first project on google chrome browser. Ensure you have google chrome installed and running on your device. After installing, follow the following steps;

1. Open R studio
2. Install these two packages "rvest" and "dplyr". These packages can easily be installed by
>install.packages("rvest") 
 That installs the rvest package
>install.packages("dplyr") 
 That installs the dplyr package

3. After installing the packages, we are going to deploy them. this can be done by entering library() with the package name in the brackets e.g.
>library("rvest")
>library("dplyr')
4. Next, open google chrome browser and visit selectorgadget.com
At the bottom click install chrome extension and have this extension added to your browser.

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5. Next in a new tab open google news website or any website you wish to scrap data from.
click the selector gadget icon on your browser (it is usually displayed somewhere at the top)
Right click on the text you wish to scrap from the website. In our example, we right clicked on the top most keyword on your right under the "In the news" tab. The selector gadget highlights related keywords and towards the bottom of the browser, a selector gadget tab that is open will display a line of code.

Before you do anything, go back to r studio and in the r console, create an item called trending and assign it the google news URL for the site we are scraping.
>trending <- html("https://news.google.com/news/?ned=us&gl=US&hl=en")
This will load the website data and the next step will be to display our data of interest. we can do this by specifying the html nodes for only the data we selected. Enter the small line of code displayed by the selector gadget in the html_nodes("here") like below.

selectorgadget tab showing a line of code

> trending %>%
+ html_nodes(".kzAuJ") %>%
+ html_text() 
This will now display the scraped data.
sample codes for scraping data in r-studio

image showing scraped data in r-studio

If you need any help with the above tutorial, lets us know. If you enjoyed this tutorial, like us on Facebook to keep seeing more of these. Any comments and compliments are welcome.

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