Syracuse Tax Parcels
About
This dataset represents approximately 42,000 tax parcels for the city of Syracuse, NY. Each row represents a unique parcel of land within city limits.
The dataset is available in the DataCuse OPEN DATA PORTAL.
“Parcel dataset created by the Department of Neighborhood and Business Development. This dataset includes a large amount of information about each parcel (or area of land for properties) in the city.”
Syracuse Parcels
Downtown Syracuse
Data Dictionary
This data set contains the following variables:
| VARIABLE | DESCRIPTION |
|---|---|
| tax_id | unique parcel ID (numeric) |
| neighborhood | city neighborhood for tax parcel (character) |
| stnum | parcel address (numeric) |
| stname | parcel address (character) |
| zip | parcel address (numeric) |
| owner | property owner (character) |
| frontfeet | length of the front of the lot (numeric) |
| depth | depth of the lot (numeric) |
| acres | size of the parcel in acres (numeric) |
| yearbuilt | year of construction for the building on the parcel (numeric) |
| age | age of the building (numeric) |
| age_range | age of the building by decade (factor) |
| land_use | zoning purpose of the parcel (factor) |
| units | number of units in multi-unit buildings (numeric) |
| residential | is the parcel zoned for residential (T/F) |
| rental | is the residential space zoned for rental (T/F) |
| vacantbuil | is the building vacant (T/F) |
| assessedla | assessed value of the parcel land (numeric) |
| assessedva | assessed value of the parcel land plus buildings (numeric) |
| tax.exempt | is the parcel tax exempt (T/F) |
| countytxbl | value of parcel for tax purposes (numeric) |
| schooltxbl | value of parcel for tax purposes (numeric) |
| citytaxabl | value of parcel for tax purposes (numeric) |
| star | does the parcel qualify for a residential tax break (T/F) |
| amtdelinqu | amount of tax bill that is delinquint (numeric) |
| taxyrsdeli | length of time tax bill is delinquint (numeric) |
| totint | total interest owed for delinquint taxes (numeric) |
| overduewater | total owed on overdue water bills (numeric) |
Load Dataset
We are using a number of variables from the 2015 extract of tax parcels saved as a CSV file on GitHub for easy loading:
URL <- "https://raw.githubusercontent.com/DS4PS/Data-Science-Class/master/DATA/syr_parcels.csv"
dat <- read.csv( URL, stringsAsFactors=FALSE )
head( dat ) %>% pander| tax_id | neighborhood | stnum | stname | zip |
|---|---|---|---|---|
| 1.393e+09 | South Valley | 2655 | VALLEY DR | 13215 |
| 1.393e+09 | South Valley | 2635 | VALLEY DR | 13120 |
| 1.437e+09 | South Valley | 203 | HAYES TERR | 13224 |
| 1.425e+09 | South Valley | 100 | EDNA RD & CITY LINE | 13120 |
| 1.425e+09 | South Valley | 104 | EDNA RD | 13205 |
| 1.425e+09 | South Valley | 108 | EDNA RD | 13205 |
| owner | frontfeet | depth | sqft | acres | yearbuilt |
|---|---|---|---|---|---|
| CLARMIN BUILDERS ONON COR | 67.2 | 50 | 2149 | 0.04934 | NA |
| JOHNSTON LEE R | 104.8 | 46.5 | 6370 | 0.1462 | 1925 |
| CHRISTO CRAIG S | 82.87 | 168.3 | 12910 | 0.2964 | 1957 |
| HAWKINS FARMS INC | 65 | 160.9 | 10323 | 0.237 | 1958 |
| PETERS LYNNETTE | 65 | 160.9 | 10458 | 0.2401 | 1965 |
| MITCHELL LOTAN G | 65 | 160.9 | 10458 | 0.2401 | 1954 |
| age | age_range | land_use | units | residential | rental | vacantbuil |
|---|---|---|---|---|---|---|
| NA | NA | Vacant Land | 0 | FALSE | FALSE | FALSE |
| 90 | 81-90 | Single Family | 0 | TRUE | FALSE | FALSE |
| 58 | 51-60 | Single Family | 0 | TRUE | FALSE | FALSE |
| 57 | 51-60 | Single Family | 0 | TRUE | FALSE | FALSE |
| 50 | 41-50 | Single Family | 0 | TRUE | FALSE | FALSE |
| 61 | 61-70 | Single Family | 0 | TRUE | FALSE | FALSE |
| assessedla | assessedva | tax.exempt | countytxbl | schooltxbl | citytaxabl |
|---|---|---|---|---|---|
| 475 | 500 | TRUE | 500 | 500 | 500 |
| 10800 | 69300 | FALSE | 69300 | 69300 | 69300 |
| 20200 | 88300 | FALSE | 88300 | 88300 | 88300 |
| 18000 | 70500 | FALSE | 70500 | 70500 | 70500 |
| 18000 | 74000 | FALSE | 74000 | 74000 | 74000 |
| 18000 | 95000 | FALSE | 95000 | 95000 | 95000 |
| star | amtdelinqu | taxyrsdeli | totint | overduewater |
|---|---|---|---|---|
| NA | 0 | 0 | 0 | 0 |
| TRUE | 0 | 0 | 0 | 177.8 |
| TRUE | 0 | 0 | 0 | 0 |
| NA | 0 | 0 | 0 | 0 |
| TRUE | 0 | 0 | 0 | 0 |
| TRUE | 0 | 0 | 0 | 0 |
Parcel Shapefiles
The shapefile has been converted to a geojson format, and is available on GitHub:
library( geojsonio )
library( sp )
library( rgdal )
syr <- geojson_read( "data/syr_parcels.geojson", what="sp" )
plot( syr, border=NA, col="gray80" )Neighborhoods
Downtown
# sp package doesn't allow subsets when NAs present:
# replace all NAs with blanks fields
syr$Nhood <- as.character(syr$Nhood)
syr$Nhood[ is.na(syr$Nhood) ] <- ""
downtown <- syr[ syr$Nhood == "Downtown" , ]
plot( downtown )
table( downtown$LandUse ) %>% pander()| Apartment | Commercial | Community Services | Industrial | Parking | Parks |
|---|---|---|---|---|---|
| 6 | 209 | 17 | 4 | 78 | 8 |
| Recreation | Religious | Schools | Single Family | Utilities | Vacant Land |
|---|---|---|---|---|---|
| 5 | 6 | 4 | 1 | 6 | 45 |
these <- downtown$Acres > 1 # define your group
group.colors <- ifelse( these, "firebrick", "gray80" ) # don't change this
par( mar=c(0,0,0,0) )
plot( downtown, border=NA, col=group.colors ) # don't change this
names(downtown) <- tolower( names(downtown) )
# geojson_write( input=downtown, geometry = "polygon", file="downtown-syr.geojson" )Land Use
