Does age play a role?
Another variable that could influence survival is age: it's probable children were saved first. You can test this by creating a new column with a categorical variable child.
To add this new variable you need to do two things:
Create a new column, which is done through the
$operator. To create a new column,lucky, for example:train$lucky <- NAProvide the values for each observation (i.e., row) based on the age of the passenger. You can use a boolean test inside square brackets for this. For example, to set the
luckycolumn toTRUEfor passengers that survived the disaster, and the others toFALSE, you could use:train$lucky[train$Survived == 1] <- TRUE train$lucky[train$Survived == 0] <- FALSE
This exercise is part of the course
Kaggle R Tutorial on Machine Learning
Exercise instructions
- Finish the code on the right to create a new column
Child - whose default value is
NA, - whose value is
1if the passenger'sAgeis < 18 years and - whose value is
0when the passenger'sAgeis >= 18 years. - Do a two-way comparison on the number of children vs adults that survived, in row-wise proportions.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Your train and test set are still loaded in
str(train)
str(test)
# Create the column child, and indicate whether child or no child
train$Child <- NA
train$Child[train$___ < ___] <- ___
train$Child[train$___ >= ___] <- ___
# Two-way comparison