Adding age with timegap
The basetable of previous exercise is given. The timeline is given below, there is a timegap of one month. In this exercise, you will learn how to add the age of the donors to the basetable, compliant with the timeline.
Questo esercizio fa parte del corso
Intermediate Predictive Analytics in Python
Istruzioni dell'esercizio
- Fill out the reference date on which the age should be calculated, this is the start date of the timegap.
- Add a column "age" to the
basetablethat is the age of the donor on the reference date. The functioncalculate_agehas been implemented for you. It takesdate_of_birthandreference_dateas arguments. - Print the mean age of all donors.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Reference date
reference_date = datetime.date(____, ____, ____)
# Add age to the basetable
basetable["age"] = (pd.Series([calculate_age(____, ____)
for date_of_birth in basetable["date_of_birth"]]))
# Calculate mean age
print(round(basetable["____"].____()))