Chapter 3 Creating Objects
Within R objects are stored within memory, allowing the object to be quickly accessed for analysis, modelling, and visualization. A common use of objects is to store data, however objects can be used to store many things, such as results from an equation, output from an analysis, functions, and even plots. In order to commit something to an object the <- assignment operator must be used. The following basic math equation will create a data object called x x <- 1 + 1, where the same basic math equation without the assignment operator will not create a data object 1 + 1
This section will focus on creating data objects with later sections showing how the assignment operator can be used to make different objects.
3.1 Variables
A variable is the storage of a single object. Variables can be created from providing specific values, or as a result of combining multiple variables together through adding, subtracting, multiplying, dividing, or a function.
3.1.1 Create a character variable
| Description | |
|---|---|
| Create a variable object in memory for a specific character value |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
object_name <- "text"Actual Instructions
character_variable <- "Halifax"3.1.2 Create a numeric variable
| Description | |
|---|---|
| Create a variable object in memory for a specific number value |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
object_name <- numberActual Instructions
number_variable <- 103.1.3 Create a variable from an equation
| Description | |
|---|---|
| Create a variable object in memory for a specific mathematical equation |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
object_name <- number + numberActual Instructions
total_variable <- 10 + 103.1.4 Create a variable from combining variables
| Description | |
|---|---|
| Create a variable object in memory by combining two variable objects together |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Preparation
first_number_variable <- 5
second_number_variable <- 10Sample Instructions
object_name <- variable1 + variable2Actual Instructions
combined_variable <- first_number_variable + second_number_variable3.1.5 Create a variable from a function
| Description | |
|---|---|
| Create a variable object in memory from the output from the system date function |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
object_name <- function()Actual Instructions
current_date_variable <- Sys.Date()3.2 Vectors
A vector is a simple data structure that stores a sequence of values. A requirement of a vector object is that all objects be of the same data type (i.e. character, integer, numeric, or logical). While basic vectors are a very useful data structure that are helpful in various data analytics situations.
3.2.1 Create a character vector
| Description | |
|---|---|
| Create a vector object in memory that has multiple character values |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
object_name <- c("text", "text", "text")Actual Instructions
character_vector <- c("one", "two", "three")3.2.2 Create a numeric vector
| Description | |
|---|---|
| Create a vector object in memory that has multiple numeric values |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
object_name <- c(number, number, number)Actual Instructions
number_vector <- c(1, 2, 3)3.3 Dataframe
A vector is a simple data structure that stores a sequence of values. A requirement of a vector object is that all objects be of the same data type (i.e. character, integer, numeric, or logical). While basic vectors are a very useful data structure that are helpful in various data analytics situations.
3.3.1 Create dataframe with multiple character columns
| Description | |
|---|---|
| Create a dataframe object in memory that has multiple character columns |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
dataframe_name <- data.frame(first_column_name = c("text", "text", "text", "text"), second_column_name = c("text", "text", "text", "text"))Actual Instructions
atlantic_provinces <- data.frame(province = c("NL", "NS", "PE", "NB"), capital = c("St John's", "Halifax", "Charlottetown", "Saint John"))3.3.2 Create dataframe with multiple numeric columns
| Description | |
|---|---|
| Create a dataframe object in memory that has multiple numeric columns |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
dataframe_name <- data.frame(first_column_name = c(number, number, number, number), second_column_name = c(number, number, number, number))Actual Instructions
weather_station_temperatures <- data.frame(station_id = c(100, 101, 102, 103), temperature = c(10, 15.1, 6.3, -4.3))3.3.3 Create dataframe with multiple character and numeric columns
| Description | |
|---|---|
| Create a dataframe object in memory that has multiple character and numeric columns |
| Ingredients | |
|---|---|
| Package | Data |
| NA | NA |
Sample Instructions
dataframe_name <- data.frame(first_column_name = c(number, number, number, number), second_column_name = c("text", "text", "text", "text"), third_column_name = c(number, number, number, number), forth_column_name = c(number, number, number, number))Actual Instructions
atlantic_capital_temperatures <- data.frame(station_id = c(100, 101, 102, 103), province = c("NL", "NS", "PE", "NB"), city = c("St John's", "Halifax", "Charlottetown", "Saint John"), temperature = c(10, 15.1, 6.3, -4.3))