Difference between revisions of "RPR-Data-Import"
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Importing data in R | Importing data in R | ||
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(Data import from unstructured text, structured text, spreadsheets, online repositories, and Web pages) | (Data import from unstructured text, structured text, spreadsheets, online repositories, and Web pages) | ||
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Revision as of 02:39, 3 February 2018
Importing data in R
(Data import from unstructured text, structured text, spreadsheets, online repositories, and Web pages)
Abstract:
Practical for data import from text files, spreadsheets and Web pages.
Objectives: |
Outcomes: |
Deliverables:
- Time management: Before you begin, estimate how long it will take you to complete this unit. Then, record in your course journal: the number of hours you estimated, the number of hours you worked on the unit, and the amount of time that passed between start and completion of this unit.
- Journal: Document your progress in your Course Journal. Some tasks may ask you to include specific items in your journal. Don't overlook these.
- Insights: If you find something particularly noteworthy about this unit, make a note in your insights! page.
Prerequisites:
Contents
Contents
- Line endings
- Unstructured text files, headers, skip, omit, and rownames
- Caution with stringsAsFactors
- Caution with coerced data
- Text files with keywords
- Text-files: changing state
- Text-files: csv and tsv (and Excel sheets)
- Text-files: slurping, chunking and streaming
- curl
- httr GET and POST
- XML - libraries and cpath
- Binary Data
- R objects: save() and load()
Regex for screenscraping example:
Screenscraping
Write a PHP program that screenscrapes resolution data for a protein structure file from the PDB.
Here is a link to a PDB record to illustrate the URL format.
Solution
Fetch the contents of the URL into a string. Use a regex that captures the data you want to retrieve as part of some unique pattern in the HTML source. Print.