zhuge

# -*- coding: utf-8 -*-
"""
Created on Fri Dec  1 18:08:06 2017

@author: Administrator
"""


def popo(dmi,columns):

    most_area=Counter(dmi[columns]).most_common(1)

    if most_area[0][1]>=2:

        dmi2=dmi[dmi[columns]==most_area[0][0]]
        print('dmi=',dmi)
        #dmi2=dmi1

        dmiy=lower_dimention(dmi2)
        ratio2=(dmiy.max()-dmiy.min())/dmiy.mean()
        ww1=round(k_means(    dmiy   ),2)
        ww2=round(k_means(dmi2[columns]),2)

        print('dmi2=',dmi2)



        if ratio2<0.1 and len(dmiy)>1:


            return [ww1,ww2,10]
            print('area_filter',dd)
        else:
            return [ww1,ww2,len(dmiy)]


dd=numpy.array([[None,None,None],[None,None,None],[None,None,None]])



dd[0]=popo(dmi2,'room')








def filter_data(dmi):

    dd=numpy.array([[None,None,None],[None,None,None],[None,None,None]])

    #dmi_values=dmi['total_price']

    #ratio1=(dmi_values.max()-dmi_values.min())/dmi_values.mean()

    #cred1=set(dmi['url'])

    #avg1=dmi['total_price']/dmi['area']


    dmix=lower_dimention(dmi)
    ratio1=(dmix.max()-dmix.min())/dmix.mean()
    vv1=round(k_means(    dmix   ),2)
    vv2=round(k_means(dmi['area']),2)

    print('x'*100)
    print(dmi)

    if ratio1<0.1 and len(dmix)>1: 


        dd[0]=[vv1,vv2,10]
        print('room_filter',dd)



    else:
        dd[0]=[vv1,vv2,len(dmix)]

        most_area=Counter(dmi['area']).most_common(1)

        if most_area[0][1]>=2:

            dmi2=dmi[dmi['area']==most_area[0][0]]
            print('dmi=',dmi)
            #dmi2=dmi1

            dmiy=lower_dimention(dmi2)
            ratio2=(dmiy.max()-dmiy.min())/dmiy.mean()
            ww1=round(k_means(    dmiy   ),2)
            ww2=round(k_means(dmi2['area']),2)

            print('dmi2=',dmi2)

            #dmi2_values=dmi2['total_price']

            #ratio2=(dmi2_values.max()-dmi2_values.min())/dmi2_values.mean()

            #cred2=set(dmi2['url'])

            if ratio2<0.1 and len(dmiy)>1:

                #avg1=dmi['total_price']/dmi['area']

                #avg2=dmi2['total_price']/dmi2['area']

                #ww1=round(k_means(    avg2   ),2)
                #ww2=round(k_means(dmi['area']),2)

                dd[1]=[ww1,ww2,10]
                print('area_filter',dd)
            else:
                dd[1]=[ww1,ww2,len(dmiy)]
                print('****************************************'*10)
                #print(dmi2)
                #print(dmi2['floor'])
                most_floor=Counter(dmi2['floor']).most_common(1)
                #dmi2['floor']=dmi2['floor'].fillna(most_floor[0][0])

                if most_floor[0][1]>=2:

                    dmi3=dmi2[dmi2['floor']==most_floor[0][0]]  
                    #dmi2=dmi1

                    print('dmi3=',dmi3)

                    dmiz=lower_dimention(dmi3)
                    ratio3=(dmiz.max()-dmiz.min())/dmiz.mean()
                    xx1=round(k_means(    dmiz    ),2)
                    xx2=round(k_means(dmi3['area']),2)
                    #dmi3=dmi2[dmi2['floor']==most_floor[0][0]] 
                    #dmi3_values=dmi3['total_price']
                    #ratio3=(dmi3_values.max()-dmi3_values.min())/dmi3_values.mean()
                    #cred3=set(dmi2['url'])


                    if ratio3<0.1 and len(dmiz)>1:
                        #avg3=dmi3['total_price']/dmi3['area']
                        #xx1=round(k_means(    dimz  ),2)
                        #xx2=round(k_means(dmi['area']),2)
                        dd[2]=[xx1,xx2,10]
                        print(dd)
                    else:
                        dd[2]=[xx1,xx2,len(dmiz)]




    return dd 






ddr=filter_data(dmi2)