# We'll treat anyone as under 16 as a child, and then use the apply technique with a function to create a new column
# Revisit Lecture 45 for a refresher on how to do this.
# First let's make a function to sort through the sex
def male_female_child(passenger):
# Take the Age and Sex
age,sex = passenger
# Compare the age, otherwise leave the sex
if age < 16:
return 'child'
else:
return sex
# We'll define a new column called 'person', remember to specify axis=1 for columns and not index
titanic_df['person'] = titanic_df[['Age','Sex']].apply(male_female_child,axis=1)