Calculate WMAPE for groupby object with Pandas in Python
I have a dataframe called "revenue" that looks like this:
I want to calculate WMAPE for each month.
https://en.wikipedia.org/wiki/WMAPE
Wikipedia suggests that WMAPE is one scalar number, and I'm struggling to figure out how to calculate that for a groupby object. I know that I have to start by doing this:
revenue.groupby('month')
To calculate WMAPE without group by month, here is my code:
sum(abs(revenue['actual'] - revenue['forecast'])) / sum(abs(revenue['actual']))
Out[1]: 0.12206572769953052
How do I do this for the groupby object?
Solution
You can pass your calculation code to groupby.apply:
revenue.groupby('month').apply(lambda x:sum(abs(x['actual'] - x['forecast'])) / sum(abs(x['actual'])))
# month
# July 0.109890
# June 0.131148
# dtype: float64
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