Data in R

Working with data in R requires getting data into your R environment. At the end of the Basics tutorial we put together a dataframe of information we made up about abandoned lots. For small datasets, manual entry like that might be worth doing so let’s revisit those functions.

Manual entry

• c() combines items into a list or vector
• rbind() combines vectors into a dataframe as rows
• cbind() combines vectors into a dataframe as columns

Exercise 1: make up some data!

# make up three lists you can combine in different ways
# need some inspiration? how about...
# three lists of the age, favorite color, and birthday of people you know. do these make sense to combine as rows or columns?
# a list of books, a list of their authors, and a list of whether or not you like them
# do these make sense to combine as rows or columns?

Note that my suggestions are within the code block but they don’t run as lines of code. This is because they start with # which makes them ‘comments’. Comments are useful for putting notes in your code.

Reading in data files from your computer

Odds are, recording your data in R is not the best way forward for real research projects. Many people enter their data in Excel. We can read those files into R in a couple ways.

Files types from Excel

You can save different files from Excel. Most newer versions default to xlsx and older versions to xls. Either of these can be read into R without conversion, but it does require a function that is not included in the basic functions of R. That will be covered a little later.

A great option is to save files as comma separated values or a .csv file. This is possible through Excel using “Save as…” but it will only save one sheet of a workbook so if you’re using multiple tabs they’ll need to be saved separately.

Let’s read in…

#data_csv <- read.csv()

Other packages