Python Question
pandas groupby - mean and count on different columns
I have the following data frame (df):
Items Category Quantity Weight(each)
Spoon Kitchen 2 0.7
Tent Shelter 1 80.0
Sleeping Bag Shelter 1 20.0
Sunscreen Health 2 5.0
Water Bottles Kitchen 2 35.0
I want to count the quantity of each category, and the mean of the weight by category.
The desired output:
count(Quantity) mean(Weight)
Category
Kitchen 4 17.5
Shelter 2 50.0
Health 2 5.0
I know how to do it separately. But I'm not sure how to merge them together.
Separately:
df.groupby('Category')['Quantity'].agg(['count'])
df.groupby('Category')['Weight(each)'].agg(['mean'])
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Answer Source
I think you're looking for groupby + agg passed as a dict.
df.groupby('Category').agg({'Quantity' : 'sum', 'Weight(each)' : 'mean'})
Weight(each) Quantity
Category
Health 5.00 2
Kitchen 17.85 4
Shelter 50.00 2
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