Accessing columns ($, []) in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of accessing columns with $ vs []

What is the output of the following R code?

R Programming

df <- data.frame(a = 1:3, b = 4:6)
print(df$a)
print(df["a"])
print(class(df$a))
print(class(df["a"]))

A

[1] 1 2 3
[1] 1 2 3
[1] "integer"
[1] "integer"

B

[1] 1 2 3
  a
1 1
2 2
3 3
[1] "data.frame"
[1] "integer"

C

[1] 1 2 3
  a
1 1
2 2
3 3
[1] "integer"
[1] "data.frame"

D Error in print(df$a) : object 'a' not found

💡 Hint

Remember that $ returns a vector, while [] returns a data frame.

Using $ to access a column returns a vector of that column's values. Using [] with a column name returns a data frame with that column. Hence, the classes differ.

❓ Predict Output

intermediate

Accessing multiple columns with []

What is the output of this R code snippet?

R Programming

df <- data.frame(x = 10:12, y = 20:22, z = 30:32)
print(df[c("x", "z")])

A

   x  y  z
1 10 20 30
2 11 21 31
3 12 22 32

B [1] 10 11 12 30 31 32

C Error in df[c("x", "z")] : invalid subscript type 'character'

D

   x  z
1 10 30
2 11 31
3 12 32

💡 Hint

Using [] with a vector of column names returns those columns as a data frame.

Using df[c("x", "z")] selects columns x and z and returns a data frame with those columns.

❓ Predict Output

advanced

Difference between df$col and df[, "col"]

What is the output of this R code?

R Programming

df <- data.frame(a = 1:2, b = c("x", "y"))
print(class(df$a))
print(class(df[, "a"]))
print(class(df[, "a", drop = FALSE]))

A

[1] "integer"
[1] "integer"
[1] "data.frame"

B

[1] "integer"
[1] "integer"
[1] "integer"

C

[1] "integer"
[1] "data.frame"
[1] "data.frame"

D

[1] "data.frame"
[1] "integer"
[1] "data.frame"

💡 Hint

The drop argument controls whether the result is simplified to a vector.

Accessing a column with $ or [ , "col"] returns a vector by default. Using drop = FALSE keeps the result as a data frame.

❓ Predict Output

advanced

Accessing columns with numeric indices

What is the output of this R code?

R Programming

df <- data.frame(m = 5:7, n = 8:10)
print(df$`1`)
print(df[1])
print(df[[1]])

A

NULL
  m
1 5
2 6
3 7
[1] 5 6 7

B

Error: unexpected numeric constant
  m
1 5
2 6
3 7
[1] 5 6 7

C

Error: object '1' not found
  m
1 5
2 6
3 7
[1] 5 6 7

D

NULL
Error in df[1] : subscript out of bounds
[1] 5 6 7

💡 Hint

The $ operator expects a name, not a number.

Using df$1 returns NULL because 1 is not a valid name. df[1] returns the first column as a data frame. df[[1]] returns the first column as a vector.

🧠 Conceptual

expert

Why does df$col fail but df[["col"]] works?

Given a data frame df with a column named "123", which of the following statements is true?

A Both df$123 and df[["123"]] fail because column names cannot start with numbers.

B df$123 fails because $ expects a valid variable name, but df[["123"]] works because it accepts any string as column name.

C df$123 works because $ accepts numeric column names.

D df$123 works only if the column is numeric, df[["123"]] works for any type.

💡 Hint

Think about how $ operator interprets names versus [[ operator.

The $ operator requires a syntactically valid name (like a variable name). Column names starting with numbers are not valid names, so df$123 fails. However, df[["123"]] accesses the column by string name and works regardless of name format.