Factor in analysis and plotting in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to convert the variable 'group' into a factor.

R Programming

group <- c('A', 'B', 'A', 'C')
group_factor <- [1](group)

Drag options to blanks, or click blank then click option'

Aas.character

Bas.numeric

Cfactor

Dlist

Attempts:

3 left

💡 Hint

Common Mistakes

Using as.numeric() which converts to numbers, not categories.

Using as.character() which keeps it as text.

The factor() function converts a vector into a factor, which is useful for categorical data analysis.

2fill in blank

medium

Complete the code to create a bar plot of the factor variable 'group_factor'.

R Programming

library(ggplot2)
data <- data.frame(group = group_factor)
ggplot(data, aes(x = [1])) + geom_bar()

Drag options to blanks, or click blank then click option'

Agroup

Baes

Cdata

Dgroup_factor

Attempts:

3 left

💡 Hint

Common Mistakes

Using the factor variable name directly instead of the data frame column name.

Passing the whole data frame instead of a column.

The aes() function expects the name of the variable in the data frame, which is 'group'.

3fill in blank

hard

Fix the error in the code to reorder the factor levels by frequency.

R Programming

data$group <- factor(data$group, levels = names(sort(table(data$group), [1] = TRUE)))

Drag options to blanks, or click blank then click option'

Adecreasing

Bincreasing

Cdesc

Dorder

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'increasing' which is not a valid argument.

Using 'desc' or 'order' which are not arguments of sort().

The sort() function uses the argument decreasing = TRUE to sort in descending order.

4fill in blank

hard

Fill both blanks to create a summary table of counts and proportions for the factor 'group'.

R Programming

summary_table <- data.frame(
  count = table(data$group),
  proportion = prop.table(table(data$[1]))
)
rownames(summary_table) <- levels(data$[2])

Drag options to blanks, or click blank then click option'

Agroup

Bgroup_factor

Attempts:

3 left

💡 Hint

Common Mistakes

Mixing 'group' and 'group_factor' which causes errors.

Using incorrect variable names.

Both blanks refer to the column name 'group' in the data frame.

5fill in blank

hard

Fill all three blanks to create a ggplot showing counts with reordered factor levels and custom colors.

R Programming

ggplot(data, aes(x = factor(data$[1], levels = names(sort(table(data$[2]), [3] = TRUE))))) +
  geom_bar(fill = 'skyblue') +
  xlab('Group') + ylab('Count') +
  ggtitle('Bar Plot with Reordered Factor Levels')

Drag options to blanks, or click blank then click option'

Agroup

Cdecreasing

Dincreasing

Attempts:

3 left

💡 Hint

Common Mistakes

Using different variable names for blanks 1 and 2.

Setting 'decreasing' to FALSE or using 'increasing'.

The factor is reordered by sorting the table of 'group' counts in decreasing order.

Practice

1. What is the main purpose of using a factor in R when analyzing data?

easy

A. To convert text data into categories for easier analysis and plotting

B. To perform mathematical calculations on numeric data

C. To store large datasets efficiently

D. To create complex machine learning models

Solution

1. Step 1: Understand what factors represent

   Factors in R are used to represent categorical data, turning text into categories.

2. Step 2: Recognize the benefit of factors

   Using factors helps in organizing data for analysis and plotting by grouping similar values.

3. Final Answer:

   To convert text data into categories for easier analysis and plotting -> Option A

4. Quick Check:

   Factors = Categories [OK]

Hint: Factors group text into categories for analysis and plots [OK]

Common Mistakes:

• Thinking factors perform calculations
• Confusing factors with numeric vectors
• Assuming factors store data efficiently

2. Which of the following is the correct way to create a factor with levels ordered as "Low", "Medium", "High" in R?

easy

A. factor(x, order = c("Low", "Medium", "High"))

B. factor(x, levels = c("Low", "Medium", "High"))

C. factor(x, labels = c("Low", "Medium", "High"))

D. factor(x, sort = c("Low", "Medium", "High"))

Solution

1. Step 1: Recall factor syntax for setting levels

   The correct argument to set the order of categories is levels.

2. Step 2: Check the options

   Only factor(x, levels = c("Low", "Medium", "High")) uses levels correctly to order the factor levels.

3. Final Answer:

   factor(x, levels = c("Low", "Medium", "High")) -> Option B

4. Quick Check:

   Use levels= to order categories [OK]

Hint: Use levels= to set factor order, not order= or sort= [OK]

Common Mistakes:

• Using order= instead of levels=
• Confusing labels= with levels=
• Trying to sort levels with sort= argument

3. Consider the following R code:

x <- c("apple", "banana", "apple", "cherry")
f <- factor(x, levels = c("banana", "apple", "cherry"))
summary(f)

What will be the output of summary(f)?

medium

A. banana: 1apple: 2cherry: 1

B. apple: 2banana: 1cherry: 1

C. apple: 2cherry: 1banana: 1

D. cherry: 1banana: 1apple: 2

Solution

1. Step 1: Understand factor levels order

   The factor levels are set as "banana", "apple", "cherry" which determines the order in summary output.

2. Step 2: Count occurrences of each level

   In x, "banana" appears once, "apple" twice, and "cherry" once.

3. Final Answer:

   banana: 1
   apple: 2
   cherry: 1 -> Option A

4. Quick Check:

   Summary shows counts in levels order [OK]

Hint: Summary counts follow factor levels order [OK]

Common Mistakes:

• Assuming summary sorts alphabetically
• Ignoring levels order in summary
• Counting values incorrectly

4. The following R code is intended to create a factor with levels "Small", "Medium", "Large" and plot a bar chart. However, the plot shows the levels in alphabetical order instead of the specified order.

sizes <- c("Medium", "Large", "Small", "Medium")
f <- factor(sizes, levels = c("Small", "Medium", "Large"))
barplot(table(f))

What is the likely cause of this issue?

medium

A. The factor levels are correct, but barplot plots in alphabetical order by default

B. The barplot function ignores factor levels and sorts alphabetically

C. The factor was not created with the correct levels argument

D. The table function converts factor to character and loses order

Solution

1. Step 1: Check factor creation syntax

   The factor is created with levels specified correctly, so this is not the issue.

2. Step 2: Understand barplot and table behavior

   The table() function converts the factor to a named vector which may lose the factor level order, causing barplot to plot in alphabetical order.

3. Step 3: Identify common mistake

   Using table() directly on factor can lose order; using barplot with factor levels preserved requires careful handling.

4. Final Answer:

   The table function converts factor to character and loses order -> Option D

5. Quick Check:

   Use methods preserving factor order for plotting [OK]

Hint: Always set levels when creating factor to control plot order [OK]

Common Mistakes:

• Assuming barplot ignores factor levels
• Not setting levels argument in factor()
• Using character vector instead of factor in table()

5. You have a dataset with a column rating containing values "Poor", "Average", "Good", and "Excellent". You want to create a factor that orders these levels from worst to best and then plot a bar chart showing the counts in this order. Which R code correctly achieves this?

hard

A. rating_factor <- factor(rating, levels = sort(unique(rating)))
barplot(table(rating_factor))

B. rating_factor <- factor(rating)
barplot(table(rating_factor))

C. rating_factor <- factor(rating, levels = c("Poor", "Average", "Good", "Excellent"))
barplot(table(rating_factor))

D. rating_factor <- factor(rating, labels = c("Poor", "Average", "Good", "Excellent"))
barplot(table(rating_factor))

Solution

1. Step 1: Set factor levels in desired order

   To order from worst to best, levels must be explicitly set as "Poor", "Average", "Good", "Excellent".

2. Step 2: Plot counts respecting factor order

   Using table() on the factor and plotting with barplot() will show bars in factor level order.

3. Final Answer:

   rating_factor <- factor(rating, levels = c("Poor", "Average", "Good", "Excellent")) barplot(table(rating_factor)) -> Option C

4. Quick Check:

   Explicit levels order controls plot order [OK]

Hint: Set levels explicitly to control order in plots [OK]

Common Mistakes:

• Not setting levels, so order is alphabetical
• Using labels= instead of levels= to order
• Sorting unique values instead of custom order