In [2]:

    

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

%pylab inline


    

    




Populating the interactive namespace from numpy and matplotlib

In [10]:

    

hp_target = gpd.read_file("./hp_target/hp_target.shp")
hp_target.to_crs(epsg=2263, inplace=True)


    

In [5]:

    

ct = gpd.read_file("./nyct2010_17b/nyct2010.shp")
cb = gpd.read_file("./nycb2010_17b/nycb2010.shp")


    

In [9]:

    

ct.to_crs(epsg=2263, inplace=True)
cb.to_crs(epsg=2263, inplace=True)


    

In [18]:

    

ct.BoroCT2010.unique().shape
cb.BCTCB2010.unique().shape


    

    
Out[18]:





(38794,)

In [39]:

    

hp_intersect_ct = gpd.sjoin(hp_target, ct, how='left', op='intersects')
hp_within_ct = gpd.sjoin(hp_target, ct, how='left', op='within')
ct_within_hp = gpd.sjoin(ct, hp_target, how='inner', op='within')


    

In [28]:

    

hp_intersect_ct.groupby('developmen').apply(lambda x: x.BoroCT2010)


    

    
Out[28]:





developmen         
CHELSEA           0    1009300
CHELSEA ADDITION  1    1009700
ELLIOTT           2    1009700
                  2    1009300
FULTON            3    1008900
                  3    1008300
Name: BoroCT2010, dtype: object

In [35]:

    

hp_within_ct.groupby('developmen').apply(lambda x: x.BoroCT2010)


    

    
Out[35]:





developmen         
CHELSEA           0    1009300
CHELSEA ADDITION  1    1009700
ELLIOTT           2        NaN
FULTON            3        NaN
Name: BoroCT2010, dtype: object

In [41]:

    

ct_within_hp.shape


    

    
Out[41]:





(0, 15)

In [44]:

    

hp_intersect_cb = gpd.sjoin(hp_target, cb, how='left', op='intersects')
hp_within_cb = gpd.sjoin(hp_target, cb, how='left', op='within')
cb_within_hp = gpd.sjoin(cb, hp_target, how='inner', op='within')


    

In [37]:

    

hp_intersect_cb.groupby('developmen').apply(lambda x: x.BCTCB2010)


    

    
Out[37]:





developmen         
CHELSEA           0    10093006000
                  0    10093006001
                  0    10093006002
CHELSEA ADDITION  1    10097002002
ELLIOTT           2    10093006001
                  2    10097002002
                  2    10093006002
FULTON            3    10083003000
                  3    10089003001
                  3    10089003000
                  3    10083003001
Name: BCTCB2010, dtype: object

In [38]:

    

hp_within_cb.groupby('developmen').apply(lambda x: x.BCTCB2010)


    

    
Out[38]:





developmen         
CHELSEA           0            NaN
CHELSEA ADDITION  1    10097002002
ELLIOTT           2            NaN
FULTON            3            NaN
Name: BCTCB2010, dtype: object

In [45]:

    

cb_within_hp.shape


    

    
Out[45]:





(0, 11)

In [49]:

    

hp_ct = hp_intersect_ct.groupby('developmen').apply(lambda x: x.BoroCT2010.values)
hp_cb = hp_intersect_cb.groupby('developmen').apply(lambda x: x.BCTCB2010.values)


    

In [55]:

    

hp_target['CT'] = hp_ct.values
hp_target['CB'] = hp_cb.values


    

In [56]:

    

hp_target


    

    
Out[56]:







  

    

      

      
borough
      
developmen
      
geometry
      
CT
      
CB
    
  
  

    

      
0
      
MANHATTAN
      
CHELSEA
      
POLYGON ((983771.073124409 212170.9467828723, ...
      
[1009300]
      
[10093006000, 10093006001, 10093006002]
    
    

      
1
      
MANHATTAN
      
CHELSEA ADDITION
      
POLYGON ((983739.0203669845 212272.0843758562,...
      
[1009700]
      
[10097002002]
    
    

      
2
      
MANHATTAN
      
ELLIOTT
      
(POLYGON ((983769.5173532362 212064.8298691196...
      
[1009700, 1009300]
      
[10093006001, 10097002002, 10093006002]
    
    

      
3
      
MANHATTAN
      
FULTON
      
(POLYGON ((982789.5691819044 210258.9745569509...
      
[1008900, 1008300]
      
[10083003000, 10089003001, 10089003000, 100830...