20-pandas polymerization

AS NP numpy Import 
Import PANDAS PD AS 
#. 1 once the polymerization. 
DF = pd.DataFrame ({ "Age": [18,20,22,22,23,23], 
                 "name": [ "A", "B" , "C", "D", "E", "F."], 
                 "price1": [1000,900,800,700,600,600], 
                 "price2": [10,9,8,7,6,6]}) 
Print (DF ) 
RESULT1 = df.groupby ( "age") [ "price1"] # grab according to age. price 
print (result1.groups) 
print (result1.sum ()) # sum 
print (result1.mean ()) # average 
print ( result1.max ()) 
Print (result1.min ()) 

. 2 # polymerization times 
d1 = { 'item': [ ' radish', 'cabbage', 'pepper', 'melon', 'radish', 'cabbage ',' pepper ',' melon '],
    'color':['white','white','red','green','white','white','red','green'],
    'weight':[1,2,3,4,1,2,3,4],
    'price':[1,2,3,4,1,2,3,4]}
df=pd.DataFrame(d1)
result=df.groupby("color")["price"]
print(result.groups)
print(result.sum()["white"])
print(result.sum()["red"])
print(result.max()["white"])
print(result.mean()["white"])

result2=df.groupby("item")["price","weight"]
print(result2.groups)
print(result2.sum()["weight"]["萝卜"])
print(result2.sum()["weight"].萝卜)

sums=df.groupby("color").sum().add_prefix("avg__")
print(sums)
print(pd.merge(pd,sums,left_on="color",right_index=True))