Ratio of last month's and last year's average

An interesting variable to add to the basetable is the average gift a donor donated last month compared to the average gift a donor donated last year. In this exercise, you will learn how to add this variable to the basetable. The gifts made last month by donors are already selected in gifts_last_month and the gifts made last year are selected in gifts_last_year.

This exercise is part of the course

Intermediate Predictive Analytics in Python

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Exercise instructions

Calculate for each donor in gifts_last_month the average donation in the last month.
Calculate for each donor in gifts_last_year the average donation in the last year.
Add the average donation last month and average donation last year to the basetable.
Calculate the ratio of last month's and last year's average donation in the basetable.

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Average gift last month for each donor
average_gift_last_month = gifts_last_month.____("____")["____"].____().reset_index()
average_gift_last_month.columns = ["donor_ID", "mean_gift_last_month"]

# Average gift last year for each donor
average_gift_last_year = ____
average_gift_last_year.columns = ["donor_ID", "mean_gift_last_year"]

# Add average gift last month and year to basetable
basetable = pd.merge(____, ____, on="____", how="____")
basetable = pd.merge(____, ____, on="____", how="____")

# Calculate ratio of last month's and last year's average
basetable["ratio_month_year"] = basetable["____"] / basetable["____"]
print(basetable.head())

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