loading_data_in_r

Getting your data into R is

  • Comma separated value (.csv) files

    • read.csv is the standard function included in R. However, it can be slow for very large datasets.
    • The readr package is very new, but provides much faster reading of csv files.

  • Stata (.dta):

    • foreign package function read.dta is the standard way to do this. But this does not work with datasets created by Stata 13.
    • The package haven reads Stata .dta files from all versions (in addition to SAS and SPSS files).
  • SPSS (.por, .sav). The function read.spss in the foreign library.
  • Excel (.xls, .xlsx files). There are several packages that can read these. However, the newest and best is the readxl package. It is very new (not on CRAN), but provides fast reading and writing of xls fils. However, try to avoid dealing with Excel files if at all possible; while you may need to read data from one, you should not save your own data in them.
  • PDF … abandon all hope, nothing can save you.

  • Increasingly data is available on the web through APIs. See the CRAN task view Web Technologies for a list of packages that provide interfaces to web data. For example,

    • WDI World Bank’s World Development Indicators.
    • The rOpenGov project maintains many government data related R packages.

  • R has functions and packages to handle many more types of data and documents (json, HTML, XML, databases, …) but you will probably not encounter them in this course. If you do, try finding it up yourself, and if you cannot, ask one of us and we’ll point you to the right means to load it.

References

A few other articles on this. They may suggest other functions (there are often many ways to do the same thing in R) or cover other types of files:

  • Quick-R Importing Data
  • http://www.r-tutor.com/r-introduction/data-frame/data-import