notebook.community

Edit and run 





In [1]:



    


from pathlib import Path
import json
from functools import reduce
import math
import datetime as dt
import pytz 
from itertools import product
from collections import OrderedDict
import time
import sys

import requests
import numpy as np
import pandas as pd
import geopandas as gpd
import shapely.ops as so

import helpers as hp

%load_ext autoreload
%autoreload 2

Download rent data





In [11]:



    


url_by_name = {
    'detailed-lodged-bonds.csv': 'https://www.mbie.govt.nz/assets/Data-Files/Tenancy-and-housing/Rental-bond-data/Quarterly/9da3db7a4d/detailed-lodged-bonds.csv',
    'detailed-mean-rents.csv': 'https://www.mbie.govt.nz/assets/Data-Files/Tenancy-and-housing/Rental-bond-data/Quarterly/427a0a5095/detailed-mean-rents.csv',
    'detailed-geo-mean-rents.csv': 'https://www.mbie.govt.nz/assets/Data-Files/Tenancy-and-housing/Rental-bond-data/Quarterly/fcb5839378/detailed-geo-mean-rents.csv',
}

for name, url in url_by_name.items():
    r = requests.get(url)
    if not r.ok:
        print("Failed to get", name)
    else:
        print("Getting and saving", name)
        path = hp.DATA_DIR/'collected'/name
        with path.open('w') as tgt:
            tgt.write(r.text)



    


















    






Getting and saving detailed-lodged-bonds.csv
Getting and saving detailed-mean-rents.csv
Getting and saving detailed-geo-mean-rents.csv

Prepare rent data





In [12]:



    


# Reshape and merge all rent data sets

def clean(f, name):
    f = f.copy()
    f = f.rename(columns={
        'SAU': 'au2001',
        'Property_Type': 'property_type',
        'Bedrooms': '#bedrooms'
    })

    # Drop subtotals
    cond = False
    for col in ['au2001', 'property_type', '#bedrooms']:
        cond |= f[col].str.contains('total', case=False)

    f = f[~cond].copy()
    
    # Reshape
    id_vars = ['au2001', 'property_type', '#bedrooms']
    value_vars = [c for c in f.columns if '-' in c]
    f = pd.melt(f, id_vars=id_vars, value_vars=value_vars,
      var_name='quarter', value_name=name)
    
    return f

paths = [
    hp.DATA_DIR/'collected'/'detailed-lodged-bonds.csv',
    hp.DATA_DIR/'collected'/'detailed-mean-rents.csv',
    hp.DATA_DIR/'collected'/'detailed-geo-mean-rents.csv',
]
names = [
    'rent_count', 
    'rent_mean', 
    'rent_geo_mean',
]
frames = []
for path, name in zip(paths, names):
    print(path)
    f = pd.read_csv(path, dtype={'SAU': str})
    frames.append(clean(f, name))
    
f = reduce(lambda x, y: pd.merge(x, y), frames)

# Merge in region data
path = hp.get_path('au2001_csv')
g = pd.read_csv(path, dtype={'au2001': str})
f = f.merge(g)

# Write to file
path = hp.get_path('rents')
f.to_csv(path, index=False)
f[f['rent_count'].notnull()].head()



    


















    






/home/araichev/affordability_nz/data/collected/detailed-lodged-bonds.csv
/home/araichev/affordability_nz/data/collected/detailed-mean-rents.csv
/home/araichev/affordability_nz/data/collected/detailed-geo-mean-rents.csv










    
Out[12]:











  
    

      
      au2001
      property_type
      #bedrooms
      quarter
      rent_count
      rent_mean
      rent_geo_mean
      au_name
      territory
      region
      rental_area
    

  
  
    

      256
      500202
      Flat or Apartment
      1
      1995-03-01
      8.0
      82.0
      82.0
      Mangonui East
      Far North District
      Northland
      Mangonui/Kaeo
    

    

      280
      500202
      Flat or Apartment
      1
      1996-03-01
      5.0
      79.0
      79.0
      Mangonui East
      Far North District
      Northland
      Mangonui/Kaeo
    

    

      284
      500202
      House
      3
      1996-03-01
      5.0
      123.0
      118.0
      Mangonui East
      Far North District
      Northland
      Mangonui/Kaeo
    

    

      314
      500202
      House
      3
      1997-06-01
      5.0
      154.0
      152.0
      Mangonui East
      Far North District
      Northland
      Mangonui/Kaeo
    

    

      344
      500202
      House
      3
      1998-09-01
      7.0
      139.0
      137.0
      Mangonui East
      Far North District
      Northland
      Mangonui/Kaeo
    

  




















In [13]:



    


# Print latest 2 quarters
hp.get_latest_quarters(2)



    


















    
Out[13]:








['2018-09-01', '2018-12-01']

Explore rents





In [14]:



    


rents = hp.get_data('rents')
print(rents['quarter'].unique())
rents.head()



    


















    






['1993-03-01' '1993-06-01' '1993-09-01' '1993-12-01' '1994-03-01'
 '1994-06-01' '1994-09-01' '1994-12-01' '1995-03-01' '1995-06-01'
 '1995-09-01' '1995-12-01' '1996-03-01' '1996-06-01' '1996-09-01'
 '1996-12-01' '1997-03-01' '1997-06-01' '1997-09-01' '1997-12-01'
 '1998-03-01' '1998-06-01' '1998-09-01' '1998-12-01' '1999-03-01'
 '1999-06-01' '1999-09-01' '1999-12-01' '2000-03-01' '2000-06-01'
 '2000-09-01' '2000-12-01' '2001-03-01' '2001-06-01' '2001-09-01'
 '2001-12-01' '2002-03-01' '2002-06-01' '2002-09-01' '2002-12-01'
 '2003-03-01' '2003-06-01' '2003-09-01' '2003-12-01' '2004-03-01'
 '2004-06-01' '2004-09-01' '2004-12-01' '2005-03-01' '2005-06-01'
 '2005-09-01' '2005-12-01' '2006-03-01' '2006-06-01' '2006-09-01'
 '2006-12-01' '2007-03-01' '2007-06-01' '2007-09-01' '2007-12-01'
 '2008-03-01' '2008-06-01' '2008-09-01' '2008-12-01' '2009-03-01'
 '2009-06-01' '2009-09-01' '2009-12-01' '2010-03-01' '2010-06-01'
 '2010-09-01' '2010-12-01' '2011-03-01' '2011-06-01' '2011-09-01'
 '2011-12-01' '2012-03-01' '2012-06-01' '2012-09-01' '2012-12-01'
 '2013-03-01' '2013-06-01' '2013-09-01' '2013-12-01' '2014-03-01'
 '2014-06-01' '2014-09-01' '2014-12-01' '2015-03-01' '2015-06-01'
 '2015-09-01' '2015-12-01' '2016-03-01' '2016-06-01' '2016-09-01'
 '2016-12-01' '2017-03-01' '2017-06-01' '2017-09-01' '2017-12-01'
 '2018-03-01' '2018-06-01' '2018-09-01' '2018-12-01']










    
Out[14]:











  
    

      
      au2001
      property_type
      #bedrooms
      quarter
      rent_count
      rent_mean
      rent_geo_mean
      au_name
      territory
      region
      rental_area
    

  
  
    

      0
      500100
      House
      2
      1993-03-01
      NaN
      NaN
      NaN
      Awanui
      Far North District
      Northland
      Rural Far North
    

    

      1
      500100
      House
      3
      1993-03-01
      NaN
      NaN
      NaN
      Awanui
      Far North District
      Northland
      Rural Far North
    

    

      2
      500100
      House
      2
      1993-06-01
      NaN
      NaN
      NaN
      Awanui
      Far North District
      Northland
      Rural Far North
    

    

      3
      500100
      House
      3
      1993-06-01
      NaN
      NaN
      NaN
      Awanui
      Far North District
      Northland
      Rural Far North
    

    

      4
      500100
      House
      2
      1993-09-01
      NaN
      NaN
      NaN
      Awanui
      Far North District
      Northland
      Rural Far North
    

  




















In [15]:



    


# Slice in time and aggregate 
agg_rents = hp.aggregate_rents(rents, '2018-06-01')
agg_rents.head()



    


















    






/home/araichev/affordability_nz/py/helpers.py:200: FutureWarning: Interpreting tuple 'by' as a list of keys, rather than a single key. Use 'by=[...]' instead of 'by=(...)'. In the future, a tuple will always mean a single key.
  g = f.groupby(groupby_cols).apply(my_agg).reset_index()
/home/araichev/affordability_nz/py/helpers.py:190: RuntimeWarning: invalid value encountered in double_scalars
  d['rent_count']










    
Out[15]:











  
    

      
      rental_area
      #bedrooms
      territory
      region
      rent_count
      rent_mean
      rent_geo_mean
    

  
  
    

      0
      Addington
      1
      Christchurch City
      Canterbury
      176.0
      215.215909
      210.847596
    

    

      1
      Addington
      2
      Christchurch City
      Canterbury
      88.0
      323.079545
      314.383257
    

    

      2
      Addington
      3
      Christchurch City
      Canterbury
      64.0
      421.828125
      415.562506
    

    

      3
      Addington
      4
      Christchurch City
      Canterbury
      6.0
      472.000000
      466.000000
    

    

      4
      Addington
      5+
      Christchurch City
      Canterbury
      0.0
      NaN
      NaN
    

  




















In [16]:



    


f = hp.aggregate_rents(rents, '2018-06-01', groupby_cols=('au2001', '#bedrooms'))
cond = f['region'] == 'Auckland'
f[cond]



    


















    
Out[16]:











  
    

      
      au2001
      #bedrooms
      territory
      region
      rent_count
      rent_mean
      rent_geo_mean
    

  
  
    

      286
      505300
      1
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      287
      505300
      2
      Rodney District
      Auckland
      5.0
      430.000000
      429.000000
    

    

      288
      505300
      3
      Rodney District
      Auckland
      22.0
      439.863636
      436.726565
    

    

      289
      505300
      4
      Rodney District
      Auckland
      12.0
      457.250000
      456.459393
    

    

      290
      505300
      5+
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      291
      505400
      1
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      292
      505400
      2
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      293
      505400
      3
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      294
      505400
      4
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      295
      505500
      1
      Rodney District
      Auckland
      7.0
      293.000000
      289.000000
    

    

      296
      505500
      2
      Rodney District
      Auckland
      28.0
      428.785714
      425.648316
    

    

      297
      505500
      3
      Rodney District
      Auckland
      58.0
      527.206897
      524.557070
    

    

      298
      505500
      4
      Rodney District
      Auckland
      30.0
      570.000000
      565.235589
    

    

      299
      505500
      5+
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      300
      505600
      1
      Rodney District
      Auckland
      6.0
      340.000000
      331.000000
    

    

      301
      505600
      2
      Rodney District
      Auckland
      49.0
      475.285714
      470.140848
    

    

      302
      505600
      3
      Rodney District
      Auckland
      52.0
      637.807692
      623.467525
    

    

      303
      505600
      4
      Rodney District
      Auckland
      53.0
      753.773585
      724.939614
    

    

      304
      505600
      5+
      Rodney District
      Auckland
      12.0
      939.500000
      900.564823
    

    

      305
      505802
      1
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      306
      505802
      2
      Rodney District
      Auckland
      26.0
      467.192308
      462.925573
    

    

      307
      505802
      3
      Rodney District
      Auckland
      73.0
      595.082192
      590.647379
    

    

      308
      505802
      4
      Rodney District
      Auckland
      40.0
      694.350000
      684.733922
    

    

      309
      505802
      5+
      Rodney District
      Auckland
      7.0
      886.000000
      879.000000
    

    

      310
      505803
      1
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      311
      505803
      2
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      312
      505803
      3
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      313
      505804
      1
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      314
      505804
      2
      Rodney District
      Auckland
      0.0
      NaN
      NaN
    

    

      315
      505804
      3
      Rodney District
      Auckland
      5.0
      538.000000
      533.000000
    

    

      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
    

    

      1936
      525910
      4
      Franklin District
      Auckland
      56.0
      595.589286
      560.896041
    

    

      1937
      525910
      5+
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1938
      525921
      1
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1939
      525921
      2
      Franklin District
      Auckland
      28.0
      402.642857
      400.929660
    

    

      1940
      525921
      3
      Franklin District
      Auckland
      90.0
      486.455556
      484.082136
    

    

      1941
      525921
      4
      Franklin District
      Auckland
      60.0
      557.666667
      555.299084
    

    

      1942
      525921
      5+
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1943
      525922
      1
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1944
      525922
      2
      Franklin District
      Auckland
      22.0
      367.227273
      364.761858
    

    

      1945
      525922
      3
      Franklin District
      Auckland
      27.0
      476.888889
      474.778584
    

    

      1946
      525922
      4
      Franklin District
      Auckland
      12.0
      552.916667
      550.852692
    

    

      1947
      525922
      5+
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1948
      526101
      1
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1949
      526101
      2
      Franklin District
      Auckland
      24.0
      373.833333
      371.435741
    

    

      1950
      526101
      3
      Franklin District
      Auckland
      63.0
      463.761905
      460.703722
    

    

      1951
      526101
      4
      Franklin District
      Auckland
      28.0
      511.500000
      507.470196
    

    

      1952
      526101
      5+
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1953
      526102
      2
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1954
      526102
      3
      Franklin District
      Auckland
      12.0
      466.000000
      464.206850
    

    

      1955
      526102
      4
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1956
      526200
      1
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1957
      526200
      2
      Franklin District
      Auckland
      10.0
      382.500000
      377.559267
    

    

      1958
      526200
      3
      Franklin District
      Auckland
      75.0
      443.600000
      441.620082
    

    

      1959
      526200
      4
      Franklin District
      Auckland
      35.0
      489.628571
      488.064100
    

    

      1960
      526200
      5+
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1976
      526701
      1
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1977
      526701
      2
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1978
      526701
      3
      Franklin District
      Auckland
      10.0
      508.000000
      500.497752
    

    

      1979
      526701
      4
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

    

      1980
      526701
      5+
      Franklin District
      Auckland
      0.0
      NaN
      NaN
    

  



1680 rows × 7 columns



















In [17]:



    


# What fraction of rental data do we have by #bedrooms?

def hits(group):
    d = {}
    d['hit_frac'] = group['rent_mean'].count()/group['rent_mean'].shape[0]
    return pd.Series(d)

date = '2018-06-01'
f = hp.aggregate_rents(rents, date, groupby_cols=('au2001', '#bedrooms'))
cond = f['region'] == 'Auckland'
print('census area units')
print(f[cond].copy().groupby('#bedrooms').apply(hits).reset_index())

f = hp.aggregate_rents(rents, date, groupby_cols=('rental_area', '#bedrooms'))
cond = f['region'] == 'Auckland'
print('rental area units')
print(f[cond].copy().groupby('#bedrooms').apply(hits).reset_index())



    


















    






census area units
  #bedrooms  hit_frac
0         1  0.340557
1         2  0.650289
2         3  0.863248
3         4  0.536023
4        5+  0.127796
rental area units
  #bedrooms  hit_frac
0         1  0.696970
1         2  0.959596
2         3  1.000000
3         4  0.838384
4        5+  0.282828

Select latest two quarters and slice into regional chunks





In [18]:



    


# Get latest two quarters of rents
start_date = hp.get_latest_quarters(2)[0]
rents = hp.get_data('rents')
rents = rents[rents['quarter'] >= start_date].copy()

# Create regional slices
for region in hp.REGIONS:
    # Build rents
    region_c = region.capitalize()
    region_rents = rents[rents['region'] == region_c].copy()
    print(region, region_rents['quarter'].unique(), '#rows =', region_rents.shape[0])
    path = hp.get_path('rents', region)
    print('  Saving to', path)
    
    # Create region directory if it does not exist
    if not path.parent.exists():
        path.parent.mkdir()
        
    region_rents.to_csv(path, index=False)



    


















    






auckland ['2018-09-01' '2018-12-01'] #rows = 5600
  Saving to /home/araichev/affordability_nz/data/processed/auckland/rents.csv
canterbury ['2018-09-01' '2018-12-01'] #rows = 2542
  Saving to /home/araichev/affordability_nz/data/processed/canterbury/rents.csv
wellington ['2018-09-01' '2018-12-01'] #rows = 2420
  Saving to /home/araichev/affordability_nz/data/processed/wellington/rents.csv

JSONize regional rents for the web, grouping by rental area and number of bedrooms





In [19]:



    


for region in hp.REGIONS:
    region_rents = hp.get_data('rents', region)
    d = hp.build_json_rents(region_rents)
    path = hp.get_path('rents_json', region)
    print('**', region, '\n', d)
    with path.open('w') as tgt:
        json.dump(d, tgt)



    


















    






** auckland 
 {'Albany': {'1': 304.0, '2': 505.0, '3': 587.0, '4': 710.0}, 'Avondale': {'1': 247.0, '2': 436.0, '3': 545.0, '4': 552.0}, 'Balmoral': {'1': 338.0, '2': 498.0, '3': 712.0, '4': 771.0}, 'Beachhaven/Birkdale': {'1': None, '2': 464.0, '3': 564.0, '4': 593.0}, 'Blockhouse Bay/New Windsor': {'1': 238.0, '2': 501.0, '3': 555.0, '4': 672.0}, 'Botony Downs': {'1': None, '2': 465.0, '3': 597.0, '4': 689.0}, 'Browns Bay': {'1': 408.0, '2': 493.0, '3': 607.0, '4': 693.0}, 'Bucklands Beach': {'1': None, '2': 564.0, '3': 630.0, '4': 777.0}, 'Central East': {'1': 396.0, '2': 544.0, '3': 785.0, '4': None}, 'Central West': {'1': 397.0, '2': 514.0, '3': 687.0, '4': None}, 'Chatswood/Birkenhead/Northcote Point': {'1': 359.0, '2': 490.0, '3': 645.0, '4': 685.0}, 'Dannemora': {'1': None, '2': 509.0, '3': 627.0, '4': 696.0}, 'Devonport': {'1': 449.0, '2': 513.0, '3': 747.0, '4': 916.0}, 'East Coast Bays': {'1': None, '2': 532.0, '3': 685.0, '4': 785.0}, 'Eden Terrace': {'1': 441.0, '2': 585.0, '3': 646.0, '4': None}, 'Ellerslie': {'1': 423.0, '2': 487.0, '3': 629.0, '4': 701.0}, 'Epsom': {'1': 275.0, '2': 533.0, '3': 777.0, '4': 880.0}, 'Glen Eden': {'1': None, '2': 432.0, '3': 501.0, '4': 591.0}, 'Glen Innes/Pt England/Wai O Taiki': {'1': None, '2': None, '3': 577.0, '4': None}, 'Glendene': {'1': None, '2': 409.0, '3': 497.0, '4': None}, 'Glendhu/Glenfield': {'1': None, '2': 483.0, '3': 572.0, '4': 652.0}, 'Greenhithe/Unsworth Heights': {'1': 450.0, '2': 503.0, '3': 617.0, '4': 772.0}, 'Grey Lynn/Arch Hill': {'1': 376.0, '2': 639.0, '3': 814.0, '4': 934.0}, 'Gulf Harbour': {'1': None, '2': 436.0, '3': 526.0, '4': 586.0}, 'Half Moon Bay/Farm Cove': {'1': None, '2': 460.0, '3': 556.0, '4': 665.0}, 'Harbourside': {'1': 352.0, '2': 687.0, '3': 828.0, '4': None}, 'Henderson': {'1': None, '2': 437.0, '3': 505.0, '4': 624.0}, 'Herne Bay/St Marys': {'1': 436.0, '2': 639.0, '3': 1015.0, '4': None}, 'Highland Park': {'1': None, '2': 471.0, '3': 582.0, '4': 630.0}, 'Hillcrest/Northcote': {'1': 377.0, '2': 480.0, '3': 594.0, '4': 674.0}, 'Hillsborough': {'1': 386.0, '2': 463.0, '3': 597.0, '4': 669.0}, 'Howick': {'1': None, '2': 467.0, '3': 573.0, '4': 675.0}, 'Kelston': {'1': 327.0, '2': 387.0, '3': 500.0, '4': 610.0}, 'Kingsland': {'1': 428.0, '2': 557.0, '3': 726.0, '4': None}, 'Kohimarama': {'1': None, '2': 545.0, '3': 706.0, '4': 1073.0}, 'Lynfield': {'1': None, '2': 466.0, '3': 578.0, '4': 684.0}, 'Mangere': {'1': None, '2': 420.0, '3': 510.0, '4': 647.0}, 'Mangere Bridge/Airport': {'1': 344.0, '2': None, '3': 575.0, '4': None}, 'Mangere East': {'1': 292.0, '2': 423.0, '3': 491.0, '4': None}, 'Manukau Central': {'1': 354.0, '2': 474.0, '3': 543.0, '4': None}, 'Manukau Heights and Manurewa Heights': {'1': None, '2': 463.0, '3': 561.0, '4': 660.0}, 'Manurewa North': {'1': 348.0, '2': 430.0, '3': 507.0, '4': 574.0}, 'Maraetai/Clevedon': {'1': 390.0, '2': 466.0, '3': 605.0, '4': 718.0}, 'Massey/Royal Heights': {'1': None, '2': 193.0, '3': 501.0, '4': 572.0}, 'Meadowbank': {'1': 404.0, '2': 527.0, '3': 706.0, '4': 863.0}, 'Mission Bay/Orakei': {'1': 377.0, '2': 584.0, '3': 784.0, '4': 996.0}, 'Mt Albert/Owairaka': {'1': 289.0, '2': 471.0, '3': 625.0, '4': 753.0}, 'Mt Eden': {'1': 397.0, '2': 516.0, '3': 735.0, '4': 895.0}, 'Mt Roskill/Wesley': {'1': None, '2': 493.0, '3': 573.0, '4': None}, 'Mt Wellington': {'1': None, '2': 465.0, '3': 574.0, '4': 667.0}, 'Mt Wellington North': {'1': 318.0, '2': 461.0, '3': 591.0, '4': None}, 'New Lynn': {'1': 325.0, '2': 437.0, '3': 529.0, '4': 617.0}, 'Newmarket': {'1': 434.0, '2': 560.0, '3': 759.0, '4': None}, 'Newton/Grafton': {'1': 364.0, '2': 586.0, '3': 574.0, '4': None}, 'North Harbour/Pine Hill': {'1': 276.0, '2': 495.0, '3': 623.0, '4': 747.0}, 'Onehunga/Oranga/Te Papapa': {'1': 302.0, '2': 485.0, '3': 605.0, '4': 797.0}, 'Orewa/Whangaparaoa': {'1': 373.0, '2': 462.0, '3': 560.0, '4': 721.0}, 'Otahuhu': {'1': 260.0, '2': 430.0, '3': 493.0, '4': 600.0}, 'Otara': {'1': 253.0, '2': 436.0, '3': 502.0, '4': None}, 'Pakuranga': {'1': None, '2': 447.0, '3': 560.0, '4': 627.0}, 'Panmure': {'1': 338.0, '2': 467.0, '3': 555.0, '4': None}, 'Papakura/Drury/Karaka': {'1': 251.0, '2': 418.0, '3': 489.0, '4': 628.0}, 'Papatoetoe North': {'1': 332.0, '2': 458.0, '3': 555.0, '4': None}, 'Papatoetoe South': {'1': 300.0, '2': 445.0, '3': 546.0, '4': 623.0}, 'Papatoetoe West': {'1': None, '2': 444.0, '3': 541.0, '4': None}, 'Parnell': {'1': 470.0, '2': 685.0, '3': 880.0, '4': None}, 'Penrose/Mt Wellington South': {'1': 264.0, '2': 447.0, '3': 560.0, '4': 622.0}, 'Ponsonby/Freemans Bay': {'1': 496.0, '2': 667.0, '3': 893.0, '4': 1125.0}, 'Pt Chevalier': {'1': 284.0, '2': 566.0, '3': 702.0, '4': None}, 'Pukekohe/Tuakau': {'1': 328.0, '2': 394.0, '3': 467.0, '4': 549.0}, 'Ranui': {'1': None, '2': 417.0, '3': 468.0, '4': 590.0}, 'Remuera': {'1': 374.0, '2': 611.0, '3': 810.0, '4': 1001.0}, 'Remuera South/Meadowbank South': {'1': 373.0, '2': 496.0, '3': 697.0, '4': 845.0}, 'Rewiti/Kumeu/Riverhead': {'1': 331.0, '2': 491.0, '3': 628.0, '4': 709.0}, 'Rothesay/Murrays/Mairangi Bays': {'1': None, '2': 513.0, '3': 664.0, '4': 755.0}, 'Royal Oak/One Tree Hill': {'1': 325.0, '2': 532.0, '3': 648.0, '4': 812.0}, 'Rural Franklin': {'1': None, '2': None, '3': 475.0, '4': 598.0}, 'St Helliers/Glendowie': {'1': None, '2': 570.0, '3': 773.0, '4': 1053.0}, 'St Johns': {'1': 335.0, '2': 519.0, '3': 688.0, '4': 876.0}, 'St Lukes/Sandringham': {'1': 425.0, '2': 485.0, '3': 623.0, '4': 810.0}, 'Sunnynook/Westlake': {'1': None, '2': 517.0, '3': 623.0, '4': 740.0}, 'Takanini/Ardmore': {'1': 355.0, '2': None, '3': 521.0, '4': 621.0}, 'Takapuna': {'1': 492.0, '2': 578.0, '3': 707.0, '4': 965.0}, 'Te Atatu': {'1': None, '2': 423.0, '3': 514.0, '4': 564.0}, 'Te Atatu Peninsula': {'1': None, '2': 463.0, '3': 558.0, '4': 646.0}, 'Three Kings': {'1': 423.0, '2': None, '3': 629.0, '4': 714.0}, 'Titirangi': {'1': None, '2': 445.0, '3': 530.0, '4': None}, 'Torbay': {'1': 371.0, '2': 483.0, '3': 596.0, '4': 738.0}, 'Waiheke Island': {'1': 382.0, '2': 489.0, '3': 602.0, '4': 758.0}, 'Wairau Park/Glenfield North': {'1': None, '2': 447.0, '3': 579.0, '4': 664.0}, 'Waiuku': {'1': None, '2': 384.0, '3': 454.0, '4': 513.0}, 'Waterview/Avondale Heights': {'1': 268.0, '2': 472.0, '3': 586.0, '4': 713.0}, 'Wattle Downs/Conifer Grove': {'1': None, '2': 432.0, '3': 537.0, '4': 607.0}, 'Wellsford/Warkworth/Helensville': {'1': None, '2': 431.0, '3': 475.0, '4': 517.0}, 'West Harbour': {'1': None, '2': 554.0, '3': 601.0, '4': 734.0}, 'Western Beaches/Rural': {'1': None, '2': 434.0, '3': 521.0, '4': 619.0}, 'Western Springs/Morningside': {'1': 397.0, '2': 454.0, '3': 627.0, '4': 785.0}, 'Westmere/Surrey Crescent': {'1': 303.0, '2': 605.0, '3': 775.0, '4': 1150.0}, 'Weymouth': {'1': None, '2': None, '3': 516.0, '4': 580.0}}
** canterbury 
 {'Addington': {'1': 210.0, '2': 314.0, '3': 403.0, '4': 466.0}, 'Aranui/Bromley/Bexley': {'1': None, '2': None, '3': 357.0, '4': None}, 'Ashburton': {'1': 226.0, '2': 297.0, '3': 344.0, '4': 425.0}, 'Avon Loop/Christchurch East': {'1': 258.0, '2': 375.0, '3': 417.0, '4': None}, 'Avonhead/Yaldhurst': {'1': 158.0, '2': 364.0, '3': 425.0, '4': 473.0}, 'Banks Peninsula/Selwyn': {'1': None, '2': 385.0, '3': 424.0, '4': 504.0}, 'Bishopdale/Papanui': {'1': 213.0, '2': 350.0, '3': 427.0, '4': 452.0}, 'Burnside/Harewood': {'1': None, '2': None, '3': 435.0, '4': 497.0}, 'Burwood/Dallington/Avondale': {'1': None, '2': 355.0, '3': 401.0, '4': 449.0}, 'Christchurch Central/Hagley': {'1': 317.0, '2': 431.0, '3': 502.0, '4': None}, 'Fendalton/Strowan/Bryndwr': {'1': 190.0, '2': 420.0, '3': 473.0, '4': 588.0}, 'Halswell/Wigram': {'1': 191.0, '2': 382.0, '3': 462.0, '4': 569.0}, 'Hillmorton/Hoon Hay': {'1': None, '2': None, '3': 404.0, '4': 452.0}, 'Horby/Islington/Hei Hei': {'1': None, '2': 328.0, '3': 415.0, '4': None}, 'Ilam/Westburn': {'1': 150.0, '2': 358.0, '3': 441.0, '4': 536.0}, 'Kaikoura/Hurunui': {'1': None, '2': None, '3': 353.0, '4': None}, 'Linwood/Phillipstown': {'1': 216.0, '2': 297.0, '3': 391.0, '4': 415.0}, 'MacKenzie/Waimate': {'1': 188.0, '2': 224.0, '3': 283.0, '4': None}, 'Marshland/Redwood': {'1': None, '2': None, '3': 421.0, '4': 497.0}, 'Merivale/St Albans West': {'1': 218.0, '2': 360.0, '3': 487.0, '4': 567.0}, 'North Beach/New Brighton/Southshore': {'1': 150.0, '2': 336.0, '3': 390.0, '4': 444.0}, 'Rangiora/Kaiapoi': {'1': None, '2': 322.0, '3': 391.0, '4': 478.0}, 'Redcliffs/Sumner': {'1': 366.0, '2': 386.0, '3': 454.0, '4': 457.0}, 'Riccarton': {'1': 207.0, '2': 358.0, '3': 423.0, '4': 493.0}, 'Richmond/Avonside': {'1': 176.0, '2': 316.0, '3': 390.0, '4': None}, 'Richmond/Shirley': {'1': None, '2': 329.0, '3': 412.0, '4': None}, 'Rural Timaru/Temuka/Geraldine': {'1': None, '2': None, '3': 331.0, '4': None}, 'Rural Waimakariri': {'1': None, '2': None, '3': 439.0, '4': 437.0}, 'Sawyers Arms/Northcote/Belfast': {'1': None, '2': 349.0, '3': 417.0, '4': 580.0}, 'Sockburn/Upper Riccarton': {'1': 187.0, '2': 363.0, '3': 396.0, '4': 419.0}, 'Spreydon/Somerfield': {'1': 167.0, '2': 345.0, '3': 413.0, '4': 459.0}, 'St Albans East/Edgeware': {'1': 204.0, '2': 328.0, '3': 448.0, '4': 471.0}, 'St Albans North/ Mairehau': {'1': None, '2': 332.0, '3': 459.0, '4': 523.0}, 'St Martins/Beckenham/Huntsbury': {'1': None, '2': 287.0, '3': 444.0, '4': None}, 'Styx/Parklands': {'1': None, '2': None, '3': 415.0, '4': 508.0}, 'Sydenham/Waltham': {'1': 193.0, '2': 318.0, '3': 394.0, '4': None}, 'Timaru Township': {'1': 210.0, '2': 255.0, '3': 353.0, '4': 390.0}, 'Waitaki': {'1': 149.0, '2': 270.0, '3': 308.0, '4': None}, 'Westmorland/Cashmere/Barrington': {'1': None, '2': 391.0, '3': 427.0, '4': 539.0}, 'Woolston/Opawa': {'1': 155.0, '2': 315.0, '3': 392.0, '4': 478.0}}
** wellington 
 {'Brooklyn': {'1': 275.0, '2': 467.0, '3': 626.0, '4': 795.0}, 'Carterton/South Wairarapa': {'1': None, '2': 318.0, '3': 374.0, '4': None}, 'Eastern Bays': {'1': None, '2': None, '3': 587.0, '4': 698.0}, 'Epuni/Avalon': {'1': 196.0, '2': 444.0, '3': 530.0, '4': None}, 'Hataitai': {'1': 346.0, '2': 455.0, '3': 672.0, '4': 728.0}, 'Heretaunga/Silverstream': {'1': None, '2': 328.0, '3': 480.0, '4': None}, 'Hutt Central/Waterloo': {'1': 294.0, '2': 433.0, '3': 568.0, '4': 724.0}, 'Island Bay/Melrose': {'1': 202.0, '2': 476.0, '3': 660.0, '4': None}, 'Johnsonville/Newlands': {'1': 207.0, '2': 431.0, '3': 530.0, '4': 678.0}, 'Karori': {'1': None, '2': 521.0, '3': 585.0, '4': 750.0}, 'Karori South/Makara': {'1': None, '2': 476.0, '3': 534.0, '4': None}, 'Kelburn/Aro Valley': {'1': 334.0, '2': 493.0, '3': 682.0, '4': 929.0}, 'Khandallah': {'1': 341.0, '2': None, '3': 726.0, '4': 805.0}, 'Kilbirnie/Lyall Bay': {'1': 301.0, '2': 466.0, '3': 621.0, '4': None}, 'Kingston/Happy Valley': {'1': None, '2': 363.0, '3': 501.0, '4': None}, 'Lambton': {'1': 306.0, '2': 568.0, '3': 682.0, '4': None}, 'Masterton': {'1': None, '2': 253.0, '3': 345.0, '4': 370.0}, 'Miramar/Strathmore': {'1': 400.0, '2': 480.0, '3': 621.0, '4': None}, 'Moera/Waiwhetu': {'1': 247.0, '2': None, '3': 419.0, '4': None}, 'Mt Cook': {'1': 272.0, '2': 526.0, '3': 633.0, '4': 699.0}, 'Mt Victoria/Roseneath': {'1': 321.0, '2': 558.0, '3': 583.0, '4': 585.0}, 'Ngaio/Kaiwharawhara/Wilton': {'1': 353.0, '2': 422.0, '3': 590.0, '4': None}, 'Northland': {'1': 326.0, '2': 469.0, '3': 588.0, '4': 801.0}, 'Oriental Bay/Seatoun': {'1': None, '2': 614.0, '3': 706.0, '4': 903.0}, 'Papakowhai/Whitby/Pauatahanui': {'1': None, '2': None, '3': 559.0, '4': 658.0}, 'Paramata/Mana/Pukerua Bay': {'1': None, '2': None, '3': 500.0, '4': None}, 'Paraparaumu/Raumati': {'1': 198.0, '2': 393.0, '3': 450.0, '4': 517.0}, 'Petone West/Alicetown': {'1': None, '2': 367.0, '3': 562.0, '4': None}, 'Petone/Esplanade': {'1': 271.0, '2': 477.0, '3': 551.0, '4': 692.0}, 'Porirua East/Waitangirua': {'1': None, '2': None, '3': 390.0, '4': None}, 'Stokes Valley': {'1': None, '2': 345.0, '3': 458.0, '4': None}, 'Taita/Naenae': {'1': 223.0, '2': 399.0, '3': 451.0, '4': None}, 'Tawa/Grenada North': {'1': 211.0, '2': 414.0, '3': 486.0, '4': 583.0}, 'Te Aro': {'1': 384.0, '2': 548.0, '3': 682.0, '4': 890.0}, 'Titahi Bay/Onepoto/Elsdon': {'1': 238.0, '2': 434.0, '3': 413.0, '4': None}, 'Totara Park/Maoribank/Te Marua': {'1': None, '2': 352.0, '3': 468.0, '4': None}, 'Trentham North/Wallaceville': {'1': None, '2': 330.0, '3': None, '4': None}, 'Trentham West/Eldersley/Clouston Park': {'1': 183.0, '2': 342.0, '3': 499.0, '4': None}, 'Vogeltown/Berhampore/Newtown': {'1': 301.0, '2': 458.0, '3': 610.0, '4': 760.0}, 'Wadestown/Thordon': {'1': 388.0, '2': 564.0, '3': 666.0, '4': None}, 'Waikanae/Otaki': {'1': 218.0, '2': 359.0, '3': 406.0, '4': 478.0}, 'Wainuiomata': {'1': None, '2': None, '3': 422.0, '4': None}, 'Western Hills/Haywards': {'1': 247.0, '2': 371.0, '3': 507.0, '4': None}}

















In [ ]:

Content source: araichev/affordability_nz

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