Demo

Jens von Bergmann

2019-11-04

library(VancouvR)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
library(tidyr)
library(ggplot2)

Get metadata for tax report

get_cov_metadata("property-tax-report") %>%
  tail(10)
#> # A tibble: 10 × 4
#>    name                       type   label                      description     
#>    <chr>                      <chr>  <chr>                      <chr>           
#>  1 current_land_value         int    CURRENT_LAND_VALUE         The market valu…
#>  2 current_improvement_value  int    CURRENT_IMPROVEMENT_VALUE  The market valu…
#>  3 tax_assessment_year        text   TAX_ASSESSMENT_YEAR        Year in effect …
#>  4 previous_land_value        int    PREVIOUS_LAND_VALUE        This value is f…
#>  5 previous_improvement_value int    PREVIOUS_IMPROVEMENT_VALUE This value is f…
#>  6 year_built                 text   YEAR_BUILT                 Year that the p…
#>  7 big_improvement_year       text   BIG_IMPROVEMENT_YEAR       Year of major i…
#>  8 tax_levy                   double TAX_LEVY                   This is the tot…
#>  9 neighbourhood_code         text   NEIGHBOURHOOD_CODE         This is a 3-dig…
#> 10 report_year                text   REPORT_YEAR                Report year

Get an overview of land values in RS zones

search_cov_datasets("property-tax") %>%
  pull(dataset_id) %>%
  lapply(function(ds)
    aggregate_cov_data(ds,
                       group_by="tax_assessment_year as Year",
                       where="zoning_district like 'RS-'",
                       select="sum(current_land_value) as Land, sum(current_improvement_value) as Building")) %>% 
  bind_rows() %>%
  mutate(Date=as.Date(paste0(as.integer(Year)-1,"-07-01"))) %>%
  pivot_longer(c("Land","Building")) %>%
  ggplot(aes(x=Year,y=value,color=name,group=name)) +
  geom_line() +
  scale_y_continuous(labels=function(x)paste0("$",x/1000000000,"Bn")) +
  labs(title="City of Vancouver RS zoned land values",color="",y="Aggregate value (nominal)")
#> Downloading data from CoV Open Data portal
#> Downloading data from CoV Open Data portal
#> Downloading data from CoV Open Data portal
#> Downloading data from CoV Open Data portal

Get data for property tax report and property polygons

tax_data <- get_cov_data(dataset_id = "property-tax-report",
                         where="tax_assessment_year='2021'",
                         select = "current_land_value, land_coordinate as tax_coord")
#> Downloading data from CoV Open Data portal
#> Warning in mask$eval_all_mutate(quo): NAs introduced by coercion to integer
#> range
property_polygons <- get_cov_data(dataset_id="property-parcel-polygons",format = "geojson") %>%
  sf::st_transform(26910)
#> Downloading data from CoV Open Data portal

Compute and plot relative land values

plot_data <- property_polygons %>% 
  left_join(tax_data %>% group_by(tax_coord) %>% summarize(current_land_value=sum(current_land_value)),by="tax_coord") %>%
  mutate(rlv=current_land_value/as.numeric(sf::st_area(geometry))) %>%
  mutate(rlvd=cut(rlv,breaks=c(-Inf,1000,2000,3000,4000,5000,7500,10000,25000,50000,Inf),
                  labels=c("<$1k","$1k-$2k","$2k-$3k","$3k-$4k","$4k-$5k","$5k-$7.5k","$7.5k-$10k","$10k-$25k","$25k-$50k",">$50k"),
                  ordered_result = TRUE))
ggplot(plot_data) +
  geom_sf(aes(fill=rlvd),color=NA) +
  scale_fill_viridis_d(option="magma",na.value="darkgrey") +
  labs(title="July 2020 relative land values",fill="Value per m^2",caption="CoV Open Data") +
  coord_sf(datum=NA)