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R Introduction: Part I
course content

Course Content

R Introduction: Part I

R Introduction: Part I

1. Basic Syntax and Operations
Why R?Basic ArithmeticUsing the print() Function Comments in RInteger Division and RemaindersExponentiationcat() FunctionVariablesRevenue CalculationAssignment Operators
2. Basic Data Types and Vectors
Data TypesNumbersType ConversionLogical TypesVectorsLabeling VectorsIndexing in VectorsModifying VectorsDeleting Elements from VectorsArithmetic Operations with Vectors
3. Factors
What is a Factor?Indexing in FactorsLevelsCounting ValuesGrouping Numeric DataGrades Summary

bookWhat is a Factor?

Factor variables are a fundamental concept in statistics and data analysis, often referred to as categorical variables. These variables differ from numerical variables in that they have a limited and fixed set of possible values. Examples of factor variables include blood type, currency, and nationality.

Conversely, variables such as monthly income, height, and price are typically not considered categorical due to their unlimited range of potential values. However, even these can be converted into categorical variables, a process we will explore in later chapters.

Before creating a factor variable, let's first create a vector of currencies:


              
1234

            
# Vector of currencies
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
typeof(curr)
copy

In fact, a factor is a type of vector. To indicate to R that we are working with factor values, we use the factor() function and pass the relevant vector of values as an argument:


              
12345

            
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
# Convert into factor
curr_f <- factor(curr)
curr_f
copy

Upon execution, not only is the vector of values output, but we also see a line titled Levels:, which indicates all the distinct (unique) values the factor can take.

Task

Imagine we conducted a survey on blood groups and received 26 responses, which are now stored in the blood vector. Here's what you need to do:

  1. Display the values of the original vector blood.
  2. Convert blood into a factor and assign it to the variable blood_gr.
  3. Display the values of blood_gr.

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Everything was clear?

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Section 3. Chapter 1
toggle bottom row

bookWhat is a Factor?

Factor variables are a fundamental concept in statistics and data analysis, often referred to as categorical variables. These variables differ from numerical variables in that they have a limited and fixed set of possible values. Examples of factor variables include blood type, currency, and nationality.

Conversely, variables such as monthly income, height, and price are typically not considered categorical due to their unlimited range of potential values. However, even these can be converted into categorical variables, a process we will explore in later chapters.

Before creating a factor variable, let's first create a vector of currencies:


              
1234

            
# Vector of currencies
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
typeof(curr)
copy

In fact, a factor is a type of vector. To indicate to R that we are working with factor values, we use the factor() function and pass the relevant vector of values as an argument:


              
12345

            
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
# Convert into factor
curr_f <- factor(curr)
curr_f
copy

Upon execution, not only is the vector of values output, but we also see a line titled Levels:, which indicates all the distinct (unique) values the factor can take.

Task

Imagine we conducted a survey on blood groups and received 26 responses, which are now stored in the blood vector. Here's what you need to do:

  1. Display the values of the original vector blood.
  2. Convert blood into a factor and assign it to the variable blood_gr.
  3. Display the values of blood_gr.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 3. Chapter 1
toggle bottom row

bookWhat is a Factor?

Factor variables are a fundamental concept in statistics and data analysis, often referred to as categorical variables. These variables differ from numerical variables in that they have a limited and fixed set of possible values. Examples of factor variables include blood type, currency, and nationality.

Conversely, variables such as monthly income, height, and price are typically not considered categorical due to their unlimited range of potential values. However, even these can be converted into categorical variables, a process we will explore in later chapters.

Before creating a factor variable, let's first create a vector of currencies:


              
1234

            
# Vector of currencies
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
typeof(curr)
copy

In fact, a factor is a type of vector. To indicate to R that we are working with factor values, we use the factor() function and pass the relevant vector of values as an argument:


              
12345

            
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
# Convert into factor
curr_f <- factor(curr)
curr_f
copy

Upon execution, not only is the vector of values output, but we also see a line titled Levels:, which indicates all the distinct (unique) values the factor can take.

Task

Imagine we conducted a survey on blood groups and received 26 responses, which are now stored in the blood vector. Here's what you need to do:

  1. Display the values of the original vector blood.
  2. Convert blood into a factor and assign it to the variable blood_gr.
  3. Display the values of blood_gr.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Factor variables are a fundamental concept in statistics and data analysis, often referred to as categorical variables. These variables differ from numerical variables in that they have a limited and fixed set of possible values. Examples of factor variables include blood type, currency, and nationality.

Conversely, variables such as monthly income, height, and price are typically not considered categorical due to their unlimited range of potential values. However, even these can be converted into categorical variables, a process we will explore in later chapters.

Before creating a factor variable, let's first create a vector of currencies:


              
1234

            
# Vector of currencies
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
typeof(curr)
copy

In fact, a factor is a type of vector. To indicate to R that we are working with factor values, we use the factor() function and pass the relevant vector of values as an argument:


              
12345

            
curr <- c('USD', 'EUR', 'AUD', 'NOK', 
          'CHF', 'EUR', 'AUD', 'EUR')
# Convert into factor
curr_f <- factor(curr)
curr_f
copy

Upon execution, not only is the vector of values output, but we also see a line titled Levels:, which indicates all the distinct (unique) values the factor can take.

Task

Imagine we conducted a survey on blood groups and received 26 responses, which are now stored in the blood vector. Here's what you need to do:

  1. Display the values of the original vector blood.
  2. Convert blood into a factor and assign it to the variable blood_gr.
  3. Display the values of blood_gr.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 3. Chapter 1
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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