Adding and removing columns in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

How do you add a new column to a data frame in R?

You can add a new column by assigning a vector to a new column name using the $ operator or bracket notation. For example, df$new_column <- c(1, 2, 3) adds a column named new_column.

beginner

What is the syntax to remove a column from a data frame in R?

You can remove a column by setting it to NULL: df$column_to_remove <- NULL. This deletes the column from the data frame.

intermediate

What happens if you assign a vector of different length than the number of rows when adding a column?

R will recycle the vector to match the number of rows, repeating the values to fill the column. A warning is given if its length does not divide evenly into the number of rows.

intermediate

How can you add multiple columns at once to a data frame?

You can add multiple columns by assigning a data frame or list to new columns. For example, df[c('col1', 'col2')] <- list(c(1,2), c(3,4)) adds two columns.

intermediate

Can you remove multiple columns at once? How?

Yes, by setting multiple columns to NULL using their names in brackets: df[c('col1', 'col2')] <- NULL removes both columns.

Which of the following adds a new column named 'age' with values 25, 30, 35 to data frame df?

A df$age = 25

B df['age'] = 25:35

C df$age <- c('25', '30', '35')

D df$age <- c(25, 30, 35)

Option D correctly assigns a numeric vector of length 3 to the new column 'age'.

How do you remove the column 'salary' from data frame df?

A df$salary <- NULL

B df$salary <- NA

C df <- df[-salary]

D remove(df$salary)

Setting df$salary to NULL deletes the column from the data frame.

What happens if you add a column with a vector shorter than the number of rows?

A The column is filled with NA

B R throws an error always

C R recycles the vector values to fill the column

D The data frame shrinks to match vector length

R recycles shorter vectors to fill the column, issuing a warning if the length does not divide evenly.

Which syntax adds two columns 'x' and 'y' at once to df?

A df[c('x', 'y')] <- list(c(1,2), c(3,4))

B df$x, df$y <- c(1,2), c(3,4)

C df[c('x', 'y')] <- c(1,2,3,4)

D df$xy <- c(1,2,3,4)

Assigning a list of vectors to multiple columns using bracket notation adds them correctly.

How to remove columns 'a' and 'b' from df in one step?

A df$a <- NULL; df$b <- NULL

B df[c('a', 'b')] <- NULL

C df <- df[-c('a', 'b')]

D remove(df$a, df$b)

Setting multiple columns to NULL at once removes them from the data frame.

Explain how to add a new column to a data frame in R and what happens if the vector length differs from the number of rows.

Think about how R handles vectors when adding columns.

Describe the methods to remove one or multiple columns from a data frame in R.

Consider how NULL affects data frame columns.

Practice

1. In R, how do you add a new column named age with values c(25, 30, 35) to an existing dataframe df?

easy

A. df <- c(df, age = c(25, 30, 35))

B. df[age] = c(25, 30, 35)

C. df$age <- c(25, 30, 35)

D. df$age = NULL

Solution

1. Step 1: Understand how to add columns in R

   In R, you add a new column to a dataframe by assigning a vector to df$column_name.

2. Step 2: Apply the assignment for the new column

   Assigning c(25, 30, 35) to df$age adds the new column age with those values.

3. Final Answer:

   df$age <- c(25, 30, 35) -> Option C

4. Quick Check:

   Use $ and assign vector to add column [OK]

Hint: Use df$column <- values to add columns fast [OK]

Common Mistakes:

• Using NULL to add a column instead of removing
• Trying to add column with c() outside assignment
• Using incorrect dataframe syntax like c(df, ...)

2. Which of the following is the correct syntax to remove the column height from dataframe df in R?

easy

A. df$height <- NULL

B. df$height = c()

C. df$height <- NA

D. remove(df$height)

Solution

1. Step 1: Recall how to remove columns in R

   Assigning NULL to a dataframe column removes it completely.

2. Step 2: Apply removal syntax

   Setting df$height <- NULL deletes the height column from df.

3. Final Answer:

   df$height <- NULL -> Option A

4. Quick Check:

   Assign NULL to remove column [OK]

Hint: Remove columns by assigning NULL: df$col <- NULL [OK]

Common Mistakes:

• Assigning empty vector c() instead of NULL
• Assigning NA which keeps column but fills with missing
• Using remove() which is not for dataframe columns

3. What will be the output of the following R code?

df <- data.frame(name = c("Ann", "Bob"), score = c(90, 85))
df$passed <- c(TRUE, FALSE)
df$score <- NULL
df

medium

A. A dataframe with columns: name, passed

B. A dataframe with columns: name, score, passed

C. A dataframe with columns: name, score

D. Error because score column cannot be removed

Solution

1. Step 1: Add new column 'passed'

   The code adds a logical column passed with values TRUE and FALSE.

2. Step 2: Remove the 'score' column

   Assigning NULL to df$score deletes the score column.

3. Final Answer:

   A dataframe with columns: name, passed -> Option A

4. Quick Check:

   Added passed, removed score, left name [OK]

Hint: NULL removes columns; new assignment adds columns [OK]

Common Mistakes:

• Thinking score column remains after NULL assignment
• Expecting error on removing existing column
• Confusing TRUE/FALSE vector with numeric

4. Consider this R code snippet:

df <- data.frame(x = 1:3, y = 4:6)
df$z = c(7, 8)
df$y <- NULL
df

What is the problem and how to fix it?

medium

A. Error because data.frame cannot have NULL columns; fix by using list

B. No error; code runs fine and removes y column

C. Error because NULL cannot remove columns; fix by using NA

D. Warning because length of z vector does not match rows; fix by matching length

Solution

1. Step 1: Check length of new column vector

   The dataframe has 3 rows, but c(7, 8) has length 2, causing a length mismatch warning.

2. Step 2: Fix by providing vector of correct length

   Use c(7, 8, 9) or recycle values properly to match 3 rows.

3. Final Answer:

   Warning due to length mismatch; fix by matching vector length -> Option D

4. Quick Check:

   New column vector length must match dataframe rows [OK]

Hint: New column vector length must equal dataframe rows [OK]

Common Mistakes:

• Ignoring vector length mismatch causing warning
• Thinking NULL cannot remove columns
• Trying to assign NA to remove columns

5. You have a dataframe df with columns id, score1, and score2. You want to create a new column average that is the mean of score1 and score2, then remove score1 and score2. Which code correctly does this?

hard

A. df$average <- mean(df$score1, df$score2)
df$score1 <- NULL
df$score2 <- NULL

B. df$average <- rowMeans(df[c("score1", "score2")])
df$score1 <- NULL
df$score2 <- NULL

C. df$average <- mean((df$score1 + df$score2) / 2)
df$score1 <- NULL
df$score2 <- NULL

D. df$average <- (score1 + score2) / 2
df$score1 <- NULL
df$score2 <- NULL

Solution

1. Step 1: Calculate average of two columns row-wise

   Use rowMeans() on the subset df[c("score1", "score2")] to get the mean for each row.

2. Step 2: Remove the original score columns

   Assign NULL to df$score1 and df$score2 to delete them.

3. Final Answer:

   df$average <- rowMeans(df[c("score1", "score2")]) df$score1 <- NULL df$score2 <- NULL -> Option B

4. Quick Check:

   Use rowMeans() for row-wise average, then remove columns [OK]

Hint: Use rowMeans() for row averages, then assign NULL to remove [OK]

Common Mistakes:

• Using mean() which computes overall mean, not row-wise
• Referencing columns without df$ prefix
• Trying to remove columns by assigning NA