Been playing around a bit with PANDAS and ArcGIS Feature Servers for Tax Data
Been playing around a bit with PANDAS and ArcGIS Feature Servers for Tax Data … π
For example, to find the most valuable parcels in Albany County.
from arcgis.features import FeatureLayer
lyr_url = 'https://gisservices.its.ny.gov/arcgis/rest/services/NYS_Tax_Parcel_Centroid_Points/MapServer/0'
layer = FeatureLayer(lyr_url)
query_result1 = layer.query(where="COUNTY_NAME='Albany' AND FULL_MARKET_VAL > 100000000",
out_fields='PARCEL_ADDR,CITYTOWN_NAME,FULL_MARKET_VAL,OWNER_TYPE', out_sr='4326')
df=query_result1.sdf.sort_values(by='FULL_MARKET_VAL', ascending=False)
df['Full Market Value'] = df['FULL_MARKET_VAL'].map('${:,.0f}'.format)
df
OBJECTID | PARCEL_ADDR | CITYTOWN_NAME | FULL_MARKET_VAL | OWNER_TYPE | SHAPE | Full Market Value | |
---|---|---|---|---|---|---|---|
11 | 26652 | 64 Eagle St | Albany | 1204254925 | 2 | {“x”: -73.75980312511581, “y”: 42.650469918250… | $1,204,254,925 |
3 | 9150 | 1200 Washington Ave | Albany | 886298715 | 2 | {“x”: -73.81092293494828, “y”: 42.679257168282… | $886,298,715 |
4 | 10208 | 1400 Washington Ave | Albany | 642398287 | 2 | {“x”: -73.82369286130952, “y”: 42.685845700657… | $642,398,287 |
0 | 885 | 251 Fuller Rd | Albany | 440042827 | 2 | {“x”: -73.83559002316825, “y”: 42.690208093507… | $440,042,827 |
5 | 18164 | 632 New Scotland Ave | Albany | 377568201 | 8 | {“x”: -73.80381341626146, “y”: 42.655758957669… | $377,568,201 |
1 | 906 | 141 Fuller Rd | Albany | 321199143 | 2 | {“x”: -73.83323986150171, “y”: 42.693189748928… | $321,199,143 |
19 | 108087 | See Card 1067 | Watervliet | 280898876 | 1 | {“x”: -73.70670724174552, “y”: 42.719628647232… | $280,898,876 |
15 | 65380 | 737 Alb Shaker Rd | Colonie | 263916100 | 3 | {“x”: -73.80365248218001, “y”: 42.747956678125… | $263,916,100 |
9 | 21923 | 304 Madison Ave | Albany | 234265418 | 2 | {“x”: -73.76227373289564, “y”: 42.648000674457… | $234,265,418 |
2 | 907 | 201 Fuller Rd | Albany | 203426124 | 2 | {“x”: -73.83362605353057, “y”: 42.692609131686… | $203,426,124 |
16 | 69999 | 515 Loudon Rd | Colonie | 166065600 | 8 | {“x”: -73.74958475282632, “y”: 42.719321807666… | $166,065,600 |
7 | 20592 | 47 New Scotland Ave | Albany | 162276338 | 8 | {“x”: -73.77597163421673, “y”: 42.653565689693… | $162,276,338 |
6 | 20574 | 132 S Lake Ave | Albany | 146296360 | 2 | {“x”: -73.77970918544908, “y”: 42.654390366929… | $146,296,360 |
8 | 20597 | 113 Holland Ave | Albany | 143498501 | 2 | {“x”: -73.77306688593143, “y”: 42.650762742870… | $143,498,501 |
17 | 78203 | Mannsville | Colonie | 142570400 | 1 | {“x”: -73.71245452369443, “y”: 42.718124477080… | $142,570,400 |
18 | 95509 | 1 Crossgates Mall Rd | Guilderland | 130554700 | 8 | {“x”: -73.84702700595471, “y”: 42.687699053797… | $130,554,700 |
10 | 24521 | 86 S Swan St | Albany | 128436403 | 2 | {“x”: -73.75980563770365, “y”: 42.653931892804… | $128,436,403 |
13 | 46883 | 1916 US 9W | Coeymans | 110000000 | 8 | {“x”: -73.83388475575597, “y”: 42.488730743021… | $110,000,000 |
12 | 35152 | 380 River Rd | Bethlehem | 105263158 | 8 | {“x”: -73.76445503554325, “y”: 42.595925419330… | $105,263,158 |
14 | 65097 | 15 Wolf Rd | Colonie | 101967213 | 8 | {“x”: -73.81423716588279, “y”: 42.709939498581… | $101,967,213 |