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.