R Tutorials: Basics
By Simon Ejdemyr
Introduction. In this first in
a number of tutorials, we'll cover the very basics of R: how to
execute code; how to install and load packages; style; and
Vectors. This tutorial introduces a
key object in R: vectors. It explains how to create
different types of vectors, how to subset them, how to
modify them, and how to summarize them.
Dataset Basics. This tutorial
introduces datasets — “data frames” in R. Datasets can
be thought of as a collection of vectors stored as columns.
We’ll talk about how to create datasets and how to read them
from file. We’ll also talk more conceptually about how
datasets should be structured.
Modifying Data. Being able to
quickly modify datasets — using tasks like subsetting,
sorting, extracting unique observations, renaming variables,
dropping variables, and creating new variables — is
critical. This tutorial explains how to easily do this in R
with functions from the dplyr package.
Collapsing Data. This
tutorial explains how to find summary statistics for
different categories in a dataset — what is often
referred to as collapsing data. Like the tutorial on
modifying data, the tutorial draws on a set of intuitive and
elegant functions from the dplyr package.
Merging & Appending.
This tutorial explains how to combine datasets by merging or
appending them. Merging means transferring columns from one
dataset to another, while appending means transferring rows
from one dataset to another.
Wide & Long Data.
This tutorial explains the difference between long and wide
form datasets, shows why it's generally preferable to use
long form datasets, and goes over how to convert datasets
from wide to long form.
This tutorial explains how to write for loops — which
can be useful when you want to iterate a process in R
— and shows how to use for loops to carry out Monte
This tutorial explains how you can write your own functions
in R. After explaining the basics, the tutorial dives into
two data science applications for writing functions.
Tables in R.
This tutorial explains how to create and export tables
in R. It was originally designed for undergraduate
students at Stanford who tend to use Word rather than