In [14]:

    

import pandas as pd
import pylab as pl
import geopandas as gpd
from fiona.crs import from_epsg


    

In [67]:

    

mn = gpd.read_file("/home/dj/Desktop/Manhattan16V2/MNMapPLUTO.shp")
mn.to_crs(epsg=2263, inplace=True)
grid = gpd.read_file("/home/dj/Documents/hp/polygon_grid.shp")
grid.crs = from_epsg(2263)
res = gpd.sjoin(mn, grid, how='inner')


    

In [72]:

    

res.columns


    

    
Out[72]:





Index([     u'APPBBL',     u'APPDate',     u'Address',  u'AreaSource',
        u'AssessLand',   u'AssessTot',         u'BBL',    u'BldgArea',
         u'BldgClass',   u'BldgDepth',   u'BldgFront',       u'Block',
          u'BoroCode',     u'Borough',    u'BsmtCode',    u'BuiltFAR',
            u'CB2010',          u'CD',      u'CT2010',     u'ComArea',
           u'CommFAR',     u'CondoNo',     u'Council',   u'EDesigNum',
         u'Easements',  u'ExemptLand',   u'ExemptTot',         u'Ext',
          u'FacilFAR',  u'FactryArea',    u'FireComp',  u'GarageArea',
        u'HealthArea',    u'HistDist',  u'IrrLotCode',     u'LandUse',
          u'Landmark',         u'Lot',     u'LotArea',    u'LotDepth',
          u'LotFront',     u'LotType',   u'LtdHeight',  u'MAPPLUTO_F',
          u'NumBldgs',   u'NumFloors',  u'OfficeArea',   u'OtherArea',
          u'Overlay1',    u'Overlay2',   u'OwnerName',   u'OwnerType',
        u'PLUTOMapID',  u'PolicePrct',    u'ProxCode',     u'ResArea',
          u'ResidFAR',  u'RetailArea',  u'SHAPE_Area',  u'SHAPE_Leng',
           u'SPDist1',     u'SPDist2',     u'SPDist3',     u'Sanborn',
         u'SanitBoro',  u'SanitDistr',    u'SanitSub',  u'SchoolDist',
         u'SplitZone',   u'StrgeArea',      u'TaxMap',   u'Tract2010',
          u'UnitsRes',  u'UnitsTotal',     u'Version',      u'XCoord',
            u'YCoord',  u'YearAlter1',  u'YearAlter2',   u'YearBuilt',
            u'ZMCode',     u'ZipCode',   u'ZoneDist1',   u'ZoneDist2',
         u'ZoneDist3',   u'ZoneDist4',     u'ZoneMap',    u'geometry',
       u'index_right',          u'ID'],
      dtype='object')

In [68]:

    

res.head()


    

    
Out[68]:







  

    

      

      
APPBBL
      
APPDate
      
Address
      
AreaSource
      
AssessLand
      
AssessTot
      
BBL
      
BldgArea
      
BldgClass
      
BldgDepth
      
...
      
ZMCode
      
ZipCode
      
ZoneDist1
      
ZoneDist2
      
ZoneDist3
      
ZoneDist4
      
ZoneMap
      
geometry
      
index_right
      
ID
    
  
  

    

      
1
      
1.000090e+09
      
12/26/1985
      
17 STATE STREET
      
2
      
14670000.0
      
59250600.0
      
1.000090e+09
      
544015
      
O4
      
118.0
      
...
      

      
10004
      
C5-5
      

      

      

      
12b
      
POLYGON ((980492.3622000068 195423.9452120797,...
      
100496
      
100497
    
    

      
1
      
1.000090e+09
      
12/26/1985
      
17 STATE STREET
      
2
      
14670000.0
      
59250600.0
      
1.000090e+09
      
544015
      
O4
      
118.0
      
...
      

      
10004
      
C5-5
      

      

      

      
12b
      
POLYGON ((980492.3622000068 195423.9452120797,...
      
100210
      
100211
    
    

      
1
      
1.000090e+09
      
12/26/1985
      
17 STATE STREET
      
2
      
14670000.0
      
59250600.0
      
1.000090e+09
      
544015
      
O4
      
118.0
      
...
      

      
10004
      
C5-5
      

      

      

      
12b
      
POLYGON ((980492.3622000068 195423.9452120797,...
      
99924
      
99925
    
    

      
1
      
1.000090e+09
      
12/26/1985
      
17 STATE STREET
      
2
      
14670000.0
      
59250600.0
      
1.000090e+09
      
544015
      
O4
      
118.0
      
...
      

      
10004
      
C5-5
      

      

      

      
12b
      
POLYGON ((980492.3622000068 195423.9452120797,...
      
99638
      
99639
    
    

      
1
      
1.000090e+09
      
12/26/1985
      
17 STATE STREET
      
2
      
14670000.0
      
59250600.0
      
1.000090e+09
      
544015
      
O4
      
118.0
      
...
      

      
10004
      
C5-5
      

      

      

      
12b
      
POLYGON ((980492.3622000068 195423.9452120797,...
      
99352
      
99353
    
  

5 rows × 90 columns

In [20]:

    

# mn.UnitsRes
# mn.UnitsTotal


    

In [69]:

    

df = pd.DataFrame(res.groupby('ID').apply(lambda x: sum(x.UnitsRes)), columns=[['UnitsRes']])
df['ID'] = df.index
df.reset_index(drop=True, inplace=True)
res2 = pd.merge(grid, df, on='ID')
res2.to_file("ResUnit")


    

In [71]:

    

res2.head()


    

    
Out[71]:







  

    

      

      
ID
      
geometry
      
UnitsRes
    
  
  

    

      
0
      
133
      
POLYGON ((981437.7442907944 212819.6018336797,...
      
0
    
    

      
1
      
134
      
POLYGON ((981487.7442907944 212819.6018336797,...
      
0
    
    

      
2
      
135
      
POLYGON ((981537.7442907944 212819.6018336797,...
      
0
    
    

      
3
      
136
      
POLYGON ((981587.7442907944 212819.6018336797,...
      
0
    
    

      
4
      
137
      
POLYGON ((981637.7442907944 212819.6018336797,...
      
0