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Mastering Data analysis with R

You're reading from   Mastering Data analysis with R Gain sharp insights into your data and solve real-world data science problems with R—from data munging to modeling and visualization

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Product type Paperback
Published in Sep 2015
Publisher Packt
ISBN-13 9781783982028
Length 396 pages
Edition 1st Edition
Languages
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Author (1):
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Gergely Daróczi Gergely Daróczi
Author Profile Icon Gergely Daróczi
Gergely Daróczi
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Toc

Table of Contents (17) Chapters Close

Preface 1. Hello, Data! 2. Getting Data from the Web FREE CHAPTER 3. Filtering and Summarizing Data 4. Restructuring Data 5. Building Models (authored by Renata Nemeth and Gergely Toth) 6. Beyond the Linear Trend Line (authored by Renata Nemeth and Gergely Toth) 7. Unstructured Data 8. Polishing Data 9. From Big to Small Data 10. Classification and Clustering 11. Social Network Analysis of the R Ecosystem 12. Analyzing Time-series 13. Data Around Us 14. Analyzing the R Community A. References Index

Scraping data from other online sources

Although the readHTMLTable function is very useful, sometimes the data is not structured in tables, but rather it's available only as HTML lists. Let's demonstrate such a data format by checking all the R packages listed in the relevant CRAN Task View at http://cran.r-project.org/web/views/WebTechnologies.html, as you can see in the following screenshot:

Scraping data from other online sources

So we see a HTML list of the package names along with a URL pointing to the CRAN, or in some cases to the GitHub repositories. To proceed, first we have to get acquainted a bit with the HTML sources to see how we can parse them. You can do that easily either in Chrome or Firefox: just right-click on the CRAN packages heading at the top of the list, and choose Inspect Element, as you can see in the following screenshot:

Scraping data from other online sources

So we have the list of related R packages in an ul (unordered list) HTML tag, just after the h3 (level 3 heading) tag holding the CRAN packages string.

In short:

  • We have to parse...
You have been reading a chapter from
Mastering Data analysis with R
Published in: Sep 2015
Publisher: Packt
ISBN-13: 9781783982028
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