Code Handout  Starting with Data
Last updated on 20230710  Edit this page
This document contains all of the functions that were covered in the Introduction to R workshop. Each function is presented alongside an example of how it can be used.
All of the examples below are in the context of the Palmer Penguins, found here (link).
Packages

library()
– loads packages into yourR
session
R
library(tidyverse)
library(lubridate)
Importing Data

read_csv()
– function to import a csv file. First argument is the path to the data, passed as a character (inside quotations).
 You can specify what values should be considered missing, using the
na
argument.
R
penguins < read_csv("data/penguins.csv")
Inspecting Data

dim()
 returns a vector with the number of rows as the first element, and the number of columns as the second element (the dimensions of the object)
R
dim(penguins)

nrow()
 returns the number of rows 
ncol()
 returns the number of columns
R
nrow(penguins)
ncol(penguins)

head()
 displays the first 6 rows of the dataframe 
tail()
 displays the last 6 rows of the dataframe
R
head(penguins)
tail(penguins)

names()
 returns the all of the names of an object (both row and column) 
colnames()
 returns column names for dataframes (without row names)
R
names(penguins)
colnames(penguins)

glimpse()
 provides a preview of the data, where column names are presented with their associated data types, and the entries from each column are printed in each row
R
glimpse(penguins)

str()
 returns the structure of the object and information about the class, the names and data types of each column, and a preview of the first entries of each column
R
str(penguins)

summary()
 provides summary statistics for each column Note: summary statistics for character variables are not meaningful, as they simply state the number of observations (length) of the variable
R
summary(penguins)
Subsetting Data

[]
– selects rows and columns from a dataframe The first entry is the row number, the second entry is the column number(s), and they are separated with a comma.
R
## Selects the element in the first row, second column
penguins[1, 2]
## Selects every element in the fourth row
penguins[4, ]
## Selects every element in the third column
penguins[, 3]

[[]]
– selects a column from a dataframe Inside the brackets you can pass either the number of the column or the name of the column (in quotations)
R
penguins[[1]]
penguins[["island"]]

$
– selects a column from a dataframe, where the name of the dataframe is on the left and the name of the column is on the right
R
penguins$body_mass_g
Working with Different Data Types

factor()
– creates a categorical variable from a character or numeric variable, variable has a factor datatype the values (level) of the factor levels is specified in the
levels
argument, where the levels must be specified in a vector (usingc()
)  Note: the order you wish for the levels to appear is how you should
list them in the
levels
argument, you can also specifyordered = TRUE
to ensure the levels remain in this order
 the values (level) of the factor levels is specified in the
R
penguins$year_fct < factor(penguins$year,
levels = c("2007", "2008", "2009"),
ordered = TRUE)

as.factor()
– creates a categorical variable from a character or numeric variable, variable has a factor datatype does not allow for you to specify the order of the levels
 defaults to alphabetical ordering for factor levels
R
penguins$year_fct < as.factor(penguins$year)

levels()
– returns the levels of a variable with a factor datatype, in the order they were stored Note: this function will not work for character datatypes
R
levels(penguins$year_fct)

nlevels()
– returns the number of levels of a variable with a factor datatype Note: this function will not work for character datatypes
R
nlevels(penguins$year_fct)

as.character()
– creates a character variable from a numeric or factor variable
R
penguins$species_chr < as.character(penguins$species)

ymd()
– transforms dates stored as character or numeric variables to dates Note: to use this function, dates must be stored in yearmonthday format
 The function does well with heterogeneous formats (as seen below), but formats where some of the entries are not in double digits may not be parsed correctly.
R
x < c("20090101", "20090102", "20090103")
ymd(x)

day()
– extracts the day (number) of a date variable
R
day(x)

month()
– extracts the month (number) of a date variable
R
month(x)

year()
– extracts the year of a date variable
R
year(x)
Visualizing Data

plot()
– a generic function for plotting R objects In this lesson
plot()
was used to create bargraphs of categorical variables.
 In this lesson
R
plot(penguins$species)