Why data frames are central to R in R Programming - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a data frame with columns 'Name' and 'Age'.

R Programming

df <- data.frame(Name = c("Alice", "Bob"), Age = c(25, [1]))

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

Ac(30)

B"30"

C30

DAge

Attempts:

3 left

💡 Hint

Common Mistakes

Putting numbers in quotes makes them strings, which is not correct here.

The Age column should contain numeric values, so 30 without quotes is correct.

2fill in blank

medium

Complete the code to access the 'Age' column from the data frame 'df'.

R Programming

ages <- df$[1]

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

AAge

B"Age"

Cage

DAGE

Attempts:

3 left

💡 Hint

Common Mistakes

Using quotes inside the $ operator causes an error.

Using wrong case for the column name.

To access a column using the $ operator, use the column name without quotes and with exact case.

3fill in blank

hard

Fix the error in the code to add a new column 'Salary' with values 50000 and 60000.

R Programming

df$Salary <- c(50000, [1])

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

A60000L

B60000

C"60000"

Dc(60000)

Attempts:

3 left

💡 Hint

Common Mistakes

Using quotes makes the value a string.

Using c(60000) inside c() creates a nested vector.

The Salary column should be numeric, so 60000 without quotes or extra c() is correct.

4fill in blank

hard

Fill both blanks to filter rows where Age is greater than 25 and select the 'Name' column.

R Programming

subset_df <- df[df$[1] [2] 25, "Name"]

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

AAge

B>

C<

DSalary

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name for filtering.

Using the wrong comparison operator.

We filter rows where Age > 25 and select the 'Name' column.

5fill in blank

hard

Fill all three blanks to create a summary data frame with mean Age and mean Salary.

R Programming

summary_df <- data.frame(MeanAge = mean(df$[1]), MeanSalary = mean(df$[2]), Count = nrow(df[3]))

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

AAge

BSalary

C[, ]

D()

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong column names.

Forgetting parentheses after nrow.

Use Age and Salary columns for mean, and nrow(df) with parentheses to count rows.