Factor in analysis and plotting in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this factor level count?

Consider the following R code that creates a factor and counts its levels.
What will be the output of table(f)?

R Programming

f <- factor(c("apple", "banana", "apple", "cherry", "banana", "banana"))
table(f)

A

apple 2
banana 3
cherry 1

B

apple 3
banana 2
cherry 1

C

apple 2
banana 2
cherry 2

D

apple 1
banana 3
cherry 2

💡 Hint

Remember that table() counts how many times each factor level appears.

The factor f has levels apple, banana, and cherry. The vector has apple twice, banana three times, and cherry once. So table(f) counts these occurrences.

❓ Predict Output

intermediate

What does this plot show about factor levels?

Given this R code, what will the barplot display?

R Programming

f <- factor(c("red", "blue", "red", "green", "blue", "blue"))
barplot(table(f), col = c("red", "blue", "green"))

A A barplot with 3 bars: red=3, blue=2, green=1, colored incorrectly

B A barplot with 3 bars: red=2, blue=3, green=1, colored accordingly

C A barplot with 2 bars: red=2, blue=3, green missing

D An error because colors do not match factor levels

💡 Hint

Check the counts from table(f) and the colors vector length.

The factor has levels red, blue, green with counts 2, 3, and 1. The colors vector matches these levels in order, so the barplot shows 3 bars with correct colors.

🔧 Debug

advanced

Why does this factor releveling code fail?

This code tries to reorder factor levels but causes an error. What is the error?

R Programming

f <- factor(c("small", "medium", "large"))
levels(f) <- c("large", "medium", "small")
print(f)

A It changes the levels but does not reorder the factor values, so output is incorrect

B It causes a warning but prints factor with new levels

C It causes an error: 'replacement has length zero' because levels assignment is invalid

D It silently fails and keeps original levels

💡 Hint

Changing levels directly does not reorder factor values; use factor(..., levels=...) instead.

Assigning new levels directly changes the labels but does not reorder the underlying factor codes, so the factor values become mismatched with levels. This does not cause an error but leads to incorrect factor values.

📝 Syntax

advanced

Which option correctly creates an ordered factor?

You want to create an ordered factor with levels: low < medium < high. Which code does this correctly?

A f <- factor(c("low", "high", "medium"), levels = c("low", "medium", "high"), ordered = TRUE)

B f <- factor(c("low", "high", "medium"), levels = c("high", "medium", "low"), ordered = TRUE)

C f <- factor(c("low", "high", "medium"), ordered = TRUE)

D f <- ordered(c("low", "high", "medium"), levels = c("low", "medium", "high"))

💡 Hint

Use ordered() or factor(..., ordered=TRUE) with correct levels order.

Option D uses ordered() with levels in correct ascending order, creating an ordered factor. Option D is valid but less idiomatic. Option D misses levels so order is default. Option D reverses levels order.

🚀 Application

expert

How many bars will this ggplot show?

Given this R code using ggplot2, how many bars will appear in the plot?

R Programming

library(ggplot2)
data <- data.frame(
  category = factor(c("A", "B", "A", "C", "B", "B"), levels = c("A", "B", "C", "D")),
  value = c(5, 3, 6, 2, 4, 1)
)
ggplot(data, aes(x = category, y = value)) + geom_bar(stat = "identity")

A 4 bars: one for each level A, B, C, D (D with height zero)

B 3 bars: only for levels A, B, C present in data

C 6 bars: one for each row in data

D Error because level D has no data

💡 Hint

Remember that geom_bar with stat="identity" plots one bar per row, not per factor level.

With stat="identity", ggplot plots one bar per row in the data frame, so 6 bars appear. The factor levels control x-axis order but do not reduce bars. Level D has no data, so no bar for D.