Why factors represent categorical data in R Programming - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a factor from a character vector.

R Programming

colors <- c("red", "blue", "green", "red")
factor_colors <- factor([1])
print(factor_colors)

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Ac("red", "blue")

Bas.factor

Ccolors

Dlevels

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the function name as.factor instead of the vector.

Passing only part of the vector like c("red", "blue").

Using levels which is not a vector.

The factor() function converts a vector into a factor, which represents categorical data. Here, we pass the vector colors to create the factor.

2fill in blank

medium

Complete the code to get the levels of a factor.

R Programming

colors <- factor(c("red", "blue", "green", "red"))
levels_list <- [1](colors)
print(levels_list)

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Alevels

Bunique

Cas.character

Dclass

Attempts:

3 left

💡 Hint

Common Mistakes

Using unique() which works on vectors but not specifically for factor levels.

Using as.character() which converts factor to string but does not list levels.

Using class() which returns the type, not levels.

The levels() function returns the categories (levels) of a factor, showing the distinct groups it represents.

3fill in blank

hard

Fix the error in the code to correctly create a factor with specified levels.

R Programming

colors <- c("red", "blue", "green", "red")
factor_colors <- factor(colors, levels = [1])
print(factor_colors)

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Ac("yellow", "blue", "green")

Bc("red", "blue", "green")

Cc("red", "green")

Dc("red", "blue")

Attempts:

3 left

💡 Hint

Common Mistakes

Omitting some colors from the levels causes NA values.

Including colors not present in the vector is allowed but not necessary here.

Using incomplete levels causes unexpected factor behavior.

The levels argument must include all categories present in the vector to avoid missing or unexpected values. Here, all colors are included.

4fill in blank

hard

Fill both blanks to create a factor and check if it is a factor.

R Programming

data <- c("small", "medium", "large", "medium")
f <- [1](data)
is_fact <- [2](f)
print(is_fact)

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Afactor

Bis.factor

Cas.factor

Dis.character

Attempts:

3 left

💡 Hint

Common Mistakes

Using as.factor is also valid to create a factor but here factor is expected.

Using is.character returns FALSE because the object is a factor, not a character vector.

factor() creates a factor from a vector. is.factor() checks if an object is a factor, returning TRUE or FALSE.

5fill in blank

hard

Fill all three blanks to create a factor with ordered levels and check if it is ordered.

R Programming

sizes <- c("small", "medium", "large", "medium")
ordered_sizes <- factor(sizes, levels = [1], ordered = [2])
is_ordered <- [3](ordered_sizes)
print(is_ordered)

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Ac("small", "medium", "large")

BTRUE

Cis.ordered

DFALSE

Attempts:

3 left

💡 Hint

Common Mistakes

Using unordered levels or ordered = FALSE will make the factor unordered.

Using is.factor() instead of is.ordered() will not check ordering.

To create an ordered factor, specify the levels in order and set ordered = TRUE. Then is.ordered() checks if the factor is ordered.