Row and column indexing in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select the first row of the data frame df.

R Programming

df[[1], ]

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

A0

Bdf

C1

Drow

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 as the row index (R indexing starts at 1).

Using the data frame name instead of a row number.

In R, to select the first row of a data frame, you use df[1, ]. The number 1 specifies the first row.

2fill in blank

medium

Complete the code to select the column named age from the data frame df.

R Programming

df$[1]

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

Aage

B1

Cdf

Dcolumn

Attempts:

3 left

💡 Hint

Common Mistakes

Using a number instead of the column name after the dollar sign.

Putting quotes around the column name after the dollar sign.

To select a column by name in R, use the dollar sign $ followed by the column name, like df$age.

3fill in blank

hard

Fix the error in the code to select the element in the second row and third column of df.

R Programming

df[[1], 3]

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

A0

B2

C1

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 3 as the row index instead of 2.

Using 0 as an index (R indexing starts at 1).

To select the element in the second row and third column, the row index should be 2. So the correct code is df[2, 3].

4fill in blank

hard

Fill both blanks to select rows where the score column is greater than 50.

R Programming

df[df$[1] [2] 50, ]

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

Ascore

B<

C>

Dage

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name.

Using the less than operator instead of greater than.

To select rows where the score column is greater than 50, use df[df$score > 50, ].

5fill in blank

hard

Fill all three blanks to create a new data frame new_df with only the name and age columns for rows where age is less than 30.

R Programming

new_df <- df[df$[1] [2] 30, c([3])]

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

Aage

B<

C"name", "age"

D"score", "age"

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong operator for comparison.

Selecting columns that are not name and age.

Not using quotes around column names inside c().

This code filters rows where age is less than 30 and selects only the name and age columns. The correct code is new_df <- df[df$age < 30, c("name", "age")].

Practice

1. In R, what does data[2, 3] select from a data frame named data?

easy

A. All rows and columns

B. The entire 2nd row

C. The entire 3rd column

D. The value in the 2nd row and 3rd column

Solution

1. Step 1: Understand the indexing format

   In R, data[row, column] selects the element at the specified row and column.

2. Step 2: Apply the given indices

   Here, row = 2 and column = 3, so it selects the value at 2nd row and 3rd column.

3. Final Answer:

   The value in the 2nd row and 3rd column -> Option D

4. Quick Check:

   data[2, 3] = value at row 2, column 3 [OK]

Hint: Use data[row, column] to pick exact cell [OK]

Common Mistakes:

• Confusing row and column order
• Thinking it selects entire row or column
• Using parentheses instead of brackets

2. Which of the following is the correct syntax to select all rows and the 4th column from a data frame df in R?

easy

A. df[, 4]

B. df[4, ]

C. df[4]

D. df[4, 4]

Solution

1. Step 1: Recall indexing rules for rows and columns

   Leaving the row index blank selects all rows; specifying a column index selects that column.

2. Step 2: Match syntax to select all rows and 4th column

   df[, 4] means all rows, 4th column, which is correct.

3. Final Answer:

   df[, 4] -> Option A

4. Quick Check:

   Blank row index means all rows [OK]

Hint: Blank row means all rows; specify column number [OK]

Common Mistakes:

• Using df[4, ] selects 4th row, not column
• Using df[4] selects 4th column but drops dimensions
• Using df[4, 4] selects single cell, not all rows

3. Given the data frame df <- data.frame(A=1:3, B=4:6, C=7:9), what is the output of df[1:2, 2]?

medium

A. [1] 7 8

B. [1] 4 5

C. [1] 1 2

D. [1] 4 5 6

Solution

1. Step 1: Understand the data frame structure

   df has columns A=1,2,3; B=4,5,6; C=7,8,9.

2. Step 2: Select rows 1 and 2, column 2

   Rows 1 and 2 of column B (2nd column) are 4 and 5.

3. Final Answer:

   [1] 4 5 -> Option B

4. Quick Check:

   df[1:2, 2] = c(4, 5) [OK]

Hint: Rows 1:2, column 2 picks values 4 and 5 [OK]

Common Mistakes:

• Confusing column numbers with letters
• Selecting wrong rows or columns
• Expecting output as a data frame instead of vector

4. What is wrong with this R code snippet to select the 3rd row and all columns from data frame df?

df[3]

medium

A. It selects the 3rd column, not the 3rd row

B. It causes a syntax error

C. It selects the 3rd row but drops columns

D. It returns all rows and columns

Solution

1. Step 1: Understand single bracket indexing with one index

   Using one index like df[3] selects the 3rd column, not row.

2. Step 2: Identify correct way to select 3rd row

   To select 3rd row and all columns, use df[3, ].

3. Final Answer:

   It selects the 3rd column, not the 3rd row -> Option A

4. Quick Check:

   df[3] = 3rd column, not row [OK]

Hint: Use df[row, ] to select rows, not df[row] [OK]

Common Mistakes:

• Using single index to select rows
• Expecting df[3] to select 3rd row
• Confusing data frame and vector indexing

5. You have a data frame df with 5 rows and 4 columns named A, B, C, D. How do you select rows 2 to 4 and columns B and D using row and column indexing?

hard

A. df[2:4, c(2, 4)]

B. df[c(2,3,4), 2:4]

C. df[2:4, c("B", "D")]

D. df[2:4, c("2", "4")]

Solution

1. Step 1: Identify rows and columns to select

   Rows 2 to 4 means indices 2, 3, 4; columns B and D are selected by names "B" and "D".

2. Step 2: Use correct syntax for row and column indexing

   Use df[2:4, c("B", "D") ] to select rows 2-4 and columns named B and D.

3. Final Answer:

   df[2:4, c("B", "D") ] -> Option C

4. Quick Check:

   Row indices and column names combined correctly [OK]

Hint: Use row range and column names vector inside brackets [OK]

Common Mistakes:

• Using numeric column indices instead of names
• Passing column names as numbers in quotes
• Selecting wrong rows or columns