Numeric type in R Programming - Mini Project: Build & Apply

Working with Numeric Types in R

📖 Scenario: You are helping a small business owner track daily sales amounts. The sales amounts are numbers that include decimals.

🎯 Goal: You will create a numeric vector of sales amounts, set a threshold value, filter sales above the threshold, and print the filtered sales.

📋 What You'll Learn

Create a numeric vector with exact sales amounts

Create a numeric threshold variable

Use a logical condition to filter sales above the threshold

Print the filtered sales vector

💡 Why This Matters

🌍 Real World

Tracking and analyzing sales amounts helps businesses understand their performance and make decisions.

💼 Career

Data analysts and business managers often work with numeric data to filter and summarize important information.

1

Create the sales data vector

Create a numeric vector called sales with these exact values: 23.5, 45.0, 12.75, 67.25, and 34.0.

R Programming

# Create the numeric vector sales with the given values
# Your code here

Hint

Use the c() function to create a numeric vector with the exact numbers.

2

Set the sales threshold

Create a numeric variable called threshold and set it to 30.

R Programming

sales <- c(23.5, 45.0, 12.75, 67.25, 34.0)
# Create the numeric variable threshold and set it to 30
# Your code here

Hint

Assign the number 30 to the variable threshold using the assignment operator <-.

3

Filter sales above the threshold

Create a new vector called high_sales that contains only the values from sales that are greater than threshold.

R Programming

sales <- c(23.5, 45.0, 12.75, 67.25, 34.0)
threshold <- 30
# Create high_sales with sales values greater than threshold
# Your code here

Hint

Use logical indexing with sales > threshold inside square brackets to filter the vector.

4

Print the filtered sales

Print the high_sales vector to display the sales amounts greater than the threshold.

R Programming

sales  threshold]
# Print the high_sales vector
# Your code here

Hint

Use the print() function to display the vector.

Practice

1. Which of the following is TRUE about numeric types in R?

easy

A. Numeric and integer types are the same in R.

B. Integer type stores decimal numbers by default.

C. Numeric type stores decimal numbers by default.

D. You must always use quotes to create numeric values.

Solution

1. Step 1: Understand numeric and integer types in R

   In R, numeric type stores decimal numbers by default, while integer type stores whole numbers with an L suffix.

2. Step 2: Evaluate each option

   Numeric type stores decimal numbers by default correctly states that numeric stores decimals by default. Options A, B, and C are incorrect based on R's type system.

3. Final Answer:

   Numeric type stores decimal numbers by default. -> Option C

4. Quick Check:

   Numeric = decimals [OK]

Hint: Remember: numeric = decimals, integer = whole numbers [OK]

Common Mistakes:

• Confusing integer and numeric types
• Thinking quotes are needed for numbers
• Assuming numeric and integer are identical

2. Which of the following is the correct way to create an integer value 5 in R?

easy

A. x <- 5L

B. x <- "5"

C. x <- 5

D. x <- as.integer("5L")

Solution

1. Step 1: Recall integer creation syntax in R

   In R, to create an integer literal, you add L after the number, e.g., 5L.

2. Step 2: Check each option

   x <- 5L uses 5L which is correct. x <- 5 creates a numeric (decimal) 5, not integer. x <- "5" creates a string. x <- as.integer("5L") fails to convert the string "5L" to integer due to the L suffix, resulting in NA.

3. Final Answer:

   x <- 5L -> Option A

4. Quick Check:

   Integer literal = number + L [OK]

Hint: Use L suffix to make integers, else numeric by default [OK]

Common Mistakes:

• Using plain numbers for integers
• Confusing strings with numbers
• Using as.integer on decimals expecting exact integer

3. What is the output of the following R code?

x <- as.numeric("3.14")
typeof(x)

medium

A. "double"

B. "numeric"

C. "integer"

D. "character"

Solution

1. Step 1: Understand as.numeric() conversion

   as.numeric() converts a string to a numeric type, which in R is stored as double precision floating point.

2. Step 2: Check typeof() result for numeric

   typeof() returns "double" for numeric values with decimals in R.

3. Final Answer:

   "double" -> Option A

4. Quick Check:

   as.numeric() returns double type [OK]

Hint: as.numeric() returns double type, not integer [OK]

Common Mistakes:

• Expecting integer type from as.numeric()
• Confusing character and numeric types
• Thinking numeric means integer

4. Identify the error in this R code:

y <- 10L
z <- "abc"
sum <- y + z

medium

A. Error because sum is a reserved word

B. No error, sum is 10

C. Error because 10L is not numeric

D. Error because "abc" cannot convert to numeric

Solution

1. Step 1: Check addition of integer and character

   z <- "abc" creates a character value. Adding integer y (10L) and character z causes an error because character cannot be converted to numeric for arithmetic operations.

2. Step 2: Confirm the error

   The error is 'non-numeric argument to binary operator' since "abc" cannot convert to numeric.

3. Final Answer:

   Error because "abc" cannot convert to numeric -> Option D

4. Quick Check:

   String in arithmetic causes error [OK]

Hint: Non-numeric strings to as.numeric() produce NA [OK]

Common Mistakes:

• Trying to perform arithmetic on strings
• Thinking 10L is not numeric
• Assuming sum is reserved and causes error

5. You have a character vector c("1", "2.5", "3L", "four"). Which R code correctly converts only the valid numeric values to numeric type, ignoring invalid ones?

hard

A. as.numeric(c("1", "2.5", "3L", "four"))

B. as.numeric(gsub("L", "", c("1", "2.5", "3L", "four")))

C. suppressWarnings(as.numeric(c("1", "2.5", "3L", "four")))

D. as.integer(c("1", "2.5", "3L", "four"))

Solution

1. Step 1: Understand the problem with "3L" and "four"

   "3L" is not directly numeric because of the L suffix as a string; "four" is invalid.

2. Step 2: Use gsub to remove "L" and convert

   Removing "L" from strings allows as.numeric() to convert "3" correctly; "four" becomes NA.

3. Step 3: Check options

   as.numeric(gsub("L", "", c("1", "2.5", "3L", "four"))) removes "L" before conversion, correctly converting valid numbers and producing NA for "four". Others either do not handle "3L" or convert incorrectly.

4. Final Answer:

   as.numeric(gsub("L", "", c("1", "2.5", "3L", "four"))) -> Option B

5. Quick Check:

   Remove non-numeric chars before conversion [OK]

Hint: Remove non-numeric chars before as.numeric() [OK]

Common Mistakes:

• Trying to convert strings with letters directly
• Using as.integer on decimals
• Ignoring warnings from invalid conversions