In purposeanalytics/lemr: Low-end of Market Rental Monitor

devtools::load_all()
library(htmltools)
library(knitr)
library(leaflet)
library(mapview)
library(tmap)
library(ceramic)
library(tmaptools)
library(dplyr)

knitr::opts_chunk$set(
  echo = FALSE, message = FALSE, warning = FALSE,
  dpi = 300, out.width = "95%", fig.align = "center"
)

level <- params$level
neighbourhood <- params$neighbourhood
compare <- level == "neighbourhood"

title <- switch(level,
  "neighbourhood" = neighbourhood,
  "city" = "City of Toronto"
)

dataset <- lemr:::determine_dataset_from_level(level, neighbourhood)

legend <- if (level == "neighbourhood") {
  legend_label <- glue::glue("A legend showing {neighbourhood} (dark blue) versus City of Toronto (grey), used for plots on this page.")
  shiny::HTML(glue::glue("<div role = 'img' aria-label = '{legend_label}'>{lemr::create_neighbourhood_legend(neighbourhood)}</div>"))
}

`r title`

map_alt_text <- glue::glue("A map of {area} showing the locations of apartment buildings, above guideline increase applications, and tenant defense fund grant recipients.", area = ifelse(level == "city", "Toronto", neighbourhood))

wzxhzdk:2 wzxhzdk:3

wzxhzdk:4

## Summary statistics wzxhzdk:5 ### Estimated rental supply (2016) wzxhzdk:6 wzxhzdk:7

### Estimated supply of low-end of market rental wzxhzdk:8

wzxhzdk:9 wzxhzdk:10 wzxhzdk:11 ### Rooming house licenses (2020) wzxhzdk:12 ### AGI Applications (2016 to 2020) and TDF Grants (2018 to 2020) wzxhzdk:13

wzxhzdk:14 wzxhzdk:15 wzxhzdk:16 ### Proximity to services (2020) wzxhzdk:17