在 Pandas 中分组查找中位数

Question

I have a properties dataset. I would like to know the median price according to several attributes as follows: suburb , rooms , bathrooms , type , car , age . Then I want to add a new boolean column to state if the property is overpriced or not.

sample of my dataframe(the original dataframe has 180 suburbs):

house=pd.DataFrame({'subrub':['BALWYN NORTH','ARMADALE','ARMADALE','PASCOE VALE'],
                 'price':[1350000.0,800000.0,1250000.0,680000.0],
                'rooms':[3,4,7,2],
                'bathroom':[1.0,2.0,4.0,1.0],
                'type':['h','t','t','u'],
                'car':['2.0','1.0','4.0','1.0'],
                'age':[59.0,69.0,12.0,14.0]})

So far I have grouped by suburbs. I know I can use median to find the median, but I am not sure how to approach the other attributes. Any tip would be helpful. Thank you,

Answer 1

Like this

def over_price(elements):
    median = np.median(elements)
    return elements > median 

house["OverPrice"] = house.groupby(["subrub","rooms","bathroom","type","car","age"])["price"].transform(over_price)