Introduction

This file covers the absolute basics of R programming, such as syntax, functions, and types of data.

download and install then comment out so it doesn’t run again

#install.packages("tidyverse") 
#install.packages("redlistr") 
#install.packages("terra")

load packages

library("ggplot2")
library("tidyr")
# top 2 are included in tidyverse library
library("tidyverse")

Help options

?round # go to help
args(round) # use args in the Console

## function (x, digits = 0, ...) 
## NULL

Basics

2+1

## [1] 3

1:30

##  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
## [26] 26 27 28 29 30

6 * 2

## [1] 12

#6 % 2
Age <- 25 
first_name <- 'Bill'
Age + 1

## [1] 26

Age + Age

## [1] 50

x = 15 + 25.1 + 20.25
y = 5
x + y

## [1] 65.35

Naming Errors:

01_age <- 25 # starts with a number !_age <- 25 # no special symbols age bob <- 25 # no spaces age bob <- 25 # no spaces, but with back ticks

Functions

years_old <- 25.7
round(years_old) # rounds up

## [1] 26

floor(years_old) # rounds down

## [1] 25

years_old <- 25.765
round (years_old, 2) # comma after the object to specify argument to 2 decimal places

## [1] 25.76

Paste Function

years_old <- 24
Ryan <- paste("Ryan is", years_old)

Misconceptions (variables in programs do not work the same way as they do in spreadsheets)

grade <- 55
total <- grade + 10
print (total)

## [1] 65

grade <- 90
print (total) # value of total in a spreadsheet will be 100, but in programming a variable holds the value it was assigned (65)

## [1] 65

total <- grade + 10
print (total) # executed in the way it was defined

## [1] 100

Debugging errors

p <- 2
z <- 5
out <- p * z  # What should the value of out be?
print (out) # What is the value of out? Is it the same as expected?

## [1] 10

#out <- p * a # undefined variable.
## > Error: object 'a' not found
out <- p * z

Example: Lacks commas between objects

my_quiz <- c(“uno”, “dos”, “tres”, “cuatro” “cinco”) print (my_quis) #Quiz misspelled str(my_quiz) len(my_quiz) #Len should be length

Fixed Code

my_quiz <- c("uno",
             "dos",
             "tres",
             "cuatro",
             "cinco")
print (my_quiz)

## [1] "uno"    "dos"    "tres"   "cuatro" "cinco"

str(my_quiz)

##  chr [1:5] "uno" "dos" "tres" "cuatro" "cinco"

length(my_quiz)

## [1] 5

Testing if data is numeric or a character

x <- 1
is.character(x)

## [1] FALSE

is.numeric (x)

## [1] TRUE

Types of Data

#Vector
y <- c(1, 2, 3)
z <- c("Sarah", "Tracy", "Jon")

class(y)

## [1] "numeric"

class(z)

## [1] "character"

#Lists (values inside can be of different types)
x <- list(1, "a", TRUE)
x

## [[1]]
## [1] 1
## 
## [[2]]
## [1] "a"
## 
## [[3]]
## [1] TRUE

x[[2]] #Retrieve 2nd value

## [1] "a"

#Insted of importing .csv files you can make your own data frames by adding vectors and giving them column names
my_dataframe <-  data.frame (no = c(1,2,3), name = c("Tracey", "John", "Pete"), pass = c(TRUE, FALSE, TRUE))
my_dataframe

##   no   name  pass
## 1  1 Tracey  TRUE
## 2  2   John FALSE
## 3  3   Pete  TRUE

str(my_dataframe)

## 'data.frame':    3 obs. of  3 variables:
##  $ no  : num  1 2 3
##  $ name: chr  "Tracey" "John" "Pete"
##  $ pass: logi  TRUE FALSE TRUE

#Set 1st column as categorical rather than numeric 
my_dataframe$no = as.factor(my_dataframe$no)
str (my_dataframe)

## 'data.frame':    3 obs. of  3 variables:
##  $ no  : Factor w/ 3 levels "1","2","3": 1 2 3
##  $ name: chr  "Tracey" "John" "Pete"
##  $ pass: logi  TRUE FALSE TRUE

Class : We want to take a .csv dataset representing counts from a BRUVs survey and turn it into a plot of the abundance of a single species. What major steps - the main tasks you would need to do using programming, might be required to get from a structured .csv table to a plot of a single species? Record your answers in your script using numbered comments.

Workshop 1 Module 1

Ryan Waln

2026-05-20