Accessing Columns in Data Frames
Data frames always have named columns, and you can use these names to extract specific columns. There are two main approaches.
Using Square Brackets
You can specify the column name inside square brackets.
Example
1234567name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) # Extracting the name with square brackets test[, "name"]
Using the Dollar Sign
Data frames also support a shorthand operator, $
, which allows you to access a column by name without quotes.
Example
1234567name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) # Extracting the name with dollar sign test$name
Swipe to start coding
You have the mtcars
dataset.
Your tasks are:
- Extract the
cyl
column values using square brackets. - Extract the
disp
column values using the dollar$
sign.
Solution
Thanks for your feedback!
single
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Accessing Columns in Data Frames
Swipe to show menu
Data frames always have named columns, and you can use these names to extract specific columns. There are two main approaches.
Using Square Brackets
You can specify the column name inside square brackets.
Example
1234567name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) # Extracting the name with square brackets test[, "name"]
Using the Dollar Sign
Data frames also support a shorthand operator, $
, which allows you to access a column by name without quotes.
Example
1234567name <- c("Alex", "Julia", "Finn") age <- c(24, 43, 32) gender <- c("M", "F", "M") test <- data.frame(name, age, gender) # Extracting the name with dollar sign test$name
Swipe to start coding
You have the mtcars
dataset.
Your tasks are:
- Extract the
cyl
column values using square brackets. - Extract the
disp
column values using the dollar$
sign.
Solution
Thanks for your feedback!
single