Complete the code to create a data frame with columns 'Name' and 'Age'.
df <- data.frame(Name = c("Alice", "Bob"), Age = c(25, [1]))
The Age column should contain numeric values. Using 30 (without quotes) correctly assigns the age as a number.
Complete the code to create a data frame with three columns: 'ID', 'Score', and 'Passed'.
df <- data.frame(ID = 1:3, Score = c(88, 92, 79), Passed = c(TRUE, [1], FALSE))
The 'Passed' column should contain logical values TRUE or FALSE without quotes.
Fix the error in the code to create a data frame with columns 'Product' and 'Price'.
df <- data.frame(Product = c("Pen", "Notebook"), Price = c(1.5, [1]))
The Price column should contain numeric values without quotes or extra c().
Fill both blanks to create a data frame with columns 'City' and 'Population' where population is numeric.
df <- data.frame(City = c("NY", "LA", "SF"), Population = c([1], [2], 3000000))
Population values should be numeric without quotes or extra c().
Fill all three blanks to create a data frame with columns 'Name', 'Age', and 'Member' where 'Member' is logical.
df <- data.frame(Name = c("Anna", [1], "John"), Age = c(28, 34, [2]), Member = c(TRUE, [3], FALSE))
Name values are strings, Age values are numeric, and Member values are logical TRUE or FALSE without quotes.