Getting and Cleaning Data

• Subsetting example walkthrough
• Apples to Oranges Data Organisation Challenge
• dplyr introductory tutorial and R Markdown document: A 39-minute video tutorial that covers the five basic dplyr “verbs” and a dozen other dplyr functions. dplyr is an update to the plyr package, useful for subsetting, sorting, summarizing, and merging data using a more intuitive syntax than plyr or base R.
• dplyr “going deeper” tutorial and R Markdown document: A 37-minute video tutorial that covers the new functionality in dplyr versions 0.3 and 0.4.
• Downloading files general advice
• Codebook sample
• Second Codebook sample
• Query string (and other fields-within-fields) unrolling
• Pre-processing Excel files before loading them into R
• Codebook template that can be used in the Getting and Cleaning Data project
• “Real world” example - reading American Community Survey 2000 PUMS Data: Demonstrates how to extract records of a given type from a data file containing multiple record types, and how to use an Excel-based code book to specify arguments for reading a fixed-width file.
• 18 Months of CTA advice
• Common Problems: Quiz 1 - Missing Java Runtime Explains how to solve the problem of a missing Java Runtime for the question that requires students to process a Microsoft Excel spreadsheet.
• Strategy for Reading Files & APIs / Quiz 2
• Common Problems: Quiz 2 - sqldf() driver fails to connect
• Tutorial: Downloading Files Illustrates various ways of downloading files, including binary and text files.
• Creating dataframes from xml data

Comprehensive Notes

• Complete notes for Getting and Cleaning Data