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

Table continues below
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

Table continues below
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

Table continues below
age	age_range	land_use	residential	rental	vacantbuil
NA	NA	Vacant Land	FALSE	FALSE	FALSE
90	81-90	Single Family	TRUE	FALSE	FALSE
58	51-60	Single Family	TRUE	FALSE	FALSE
57	51-60	Single Family	TRUE	FALSE	FALSE
50	41-50	Single Family	TRUE	FALSE	FALSE
61	61-70	Single Family	TRUE	FALSE	FALSE

Table continues below
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( "syr_parcels.geojson", method="local", 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()

Table continues below
Apartment	Cemetery	Commercial	Community Services	Industrial
6	0	209	17	4

Table continues below
Multiple Residence	Parking	Parks	Recreation	Religious	Schools
0	78	8	5	6	4

Single Family	Three Family	Two Family	Utilities	Vacant Land
1	0	0	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" )