In NewYorkCityCouncil/council_snapshots: Council Snapshots
library(ggplot2)
# library(councildown)
knitr::knit_hooks$set(embed = councildown::hook_pdfembed)
knitr::opts_chunk$set(echo = FALSE, embed = TRUE, warning = FALSE, message = FALSE)
knitr::opts_knit$set(root.dir = here::here())
week <- params$week
coun_dist <- params$coun_dist
library(shiny)
library(shinydashboard)
library(tibble)
library(ggplot2)
library(dplyr)
library(lubridate)
library(stringr)
library(leaflet)
library(stringr)
library(purrr)
library(sf)
utils <- list.files(path = "util", pattern = "\\.(R|r)$", full.names = TRUE)
lapply(utils, source)
current_week <- tbl(snapshots_db, "sr_top_10_week_district_closed") %>%
group_by(coun_dist) %>%
summarize(week = max(week)) %>%
ungroup() %>%
summarize(week = min(week)) %>%
pull()
dists <- tbl(snapshots_db, "council_districts") %>%
collect_geo()
Fmt <- function(x) UseMethod("Fmt")
Fmt.difftime <- function(x) {
units(x) <- "secs"
x <- unclass(x)
NextMethod()
}
Fmt.default <- function(x) {
y <- abs(x)
# if(is.na(y)){ return("Ongoing as of last update")}
sprintf("%02d hours %02d minutes",
y %/% 3600, # hours
y %% 3600 %/% 60) # minutes
}
311 Service Requests ^[Note: 311 Service Requests data is representative of the population that makes a service request. Generalizations can't be made for the entire city or district population.]
Submitted Service Requests
dist_week <- tbl(snapshots_db, "sr_ind_top_10_week_district") %>%
filter(coun_dist == local(coun_dist),
week == local(week)) %>%
collect_geo()
dist_week %>%
count(complaint_type) %>%
# wrap labels for prettiness
mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>%
str_wrap(15) %>%
reorder(n)) %>%
ggplot(aes(complaint_type, n, fill = complaint_type,
text = paste(complaint_type, n, sep = "<br>"))) +
geom_col(show.legend = FALSE) +
coord_flip() +
labs(x = "Complaint type",
y = "Number of service requests") +
councildown::scale_fill_nycc() +
scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) +
theme_bw()
dat <- dist_week %>%
as.data.frame()
pal <- colorFactor(councildown::nycc_pal()(length(unique(dat$complaint_type))),
reorder(count(dat, complaint_type)$complaint_type, count(dat, complaint_type)$n))
map_data <- dist_week %>%
mutate(lon = st_coordinates(.)[,1], lat = st_coordinates(.)[,2]) %>%
as.data.frame() %>%
group_by(lon, lat, complaint_type) %>%
summarize(n = n(), created_date = paste0(created_date, collapse = "<br>"),
incident_address = paste0(unique(incident_address), collapse = "<br>")) %>%
st_as_sf(coords = c("lon", "lat"), crs = st_crs(dist_week))
bbox <- as.numeric(st_bbox(map_data))
leaflet(map_data) %>%
councildown::addCouncilStyle() %>%
clearGroup("complaints") %>%
addCircleMarkers(radius = 4, weight = 15, fillOpacity = .8, opacity = 0,
fillColor = ~pal(complaint_type)) %>%
fitBounds(bbox[1], bbox[2], bbox[3], bbox[4])
dist_ytd <- tbl(snapshots_db, "sr_top_10_ytd_district") %>%
filter(coun_dist == local(coun_dist)) %>%
select(-locations) %>%
collect()
dist_ytd %>%
mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>%
str_wrap(15) %>%
reorder(n_tot)) %>%
ggplot(aes(complaint_type, n_tot, fill = as.numeric(complaint_type),
text = paste(complaint_type, n_tot, sep = "<br>"))) +
geom_col(show.legend = FALSE) +
coord_flip() +
scale_fill_gradient(low = "#2F56A6", high = "#23417D") +
scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) +
labs(x = "Complaint type",
y = "Number of service requests") +
theme_bw()
dist_all <- tbl(snapshots_db, "sr_week_district") %>%
filter(coun_dist == local(coun_dist)) %>%
select(-locations)
dist_all %>%
filter(week <= local(current_week)) %>%
group_by(week) %>%
summarize(n = sum(n)) %>%
collect() %>%
mutate(date = floor_date(ymd("2019-01-01")+(7*(week-1)), unit = "week") + 1) %>%
ggplot(aes(date, n,
text = paste0("Week of ", format(date, format = "%b %e"), ": ", n, " service requests"), group = 1, group = 1)) +
geom_point(color = "#23417D") +
geom_line(color = "#23417D") +
labs(x = "Week",
y = "Number of service requests") +
theme_bw()
setProgress(.2)
Closed Service Requests
dist_week <- tbl(snapshots_db, "sr_ind_top_10_week_district_closed") %>%
filter(coun_dist == local(coun_dist),
week == local(week)) %>%
collect_geo()
dist_week %>%
count(complaint_type) %>%
# wrap labels for prettiness
mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>%
str_wrap(15) %>%
reorder(n)) %>%
ggplot(aes(complaint_type, n, fill = complaint_type,
text = paste(complaint_type, n, sep = "<br>"))) +
geom_col(show.legend = FALSE) +
coord_flip() +
labs(x = "Complaint type",
y = "Number of service requests") +
councildown::scale_fill_nycc() +
scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) +
theme_bw()
dat <- dist_week %>%
as.data.frame()
pal <- colorFactor(councildown::nycc_pal()(length(unique(dat$complaint_type))),
reorder(count(dat, complaint_type)$complaint_type, count(dat, complaint_type)$n))
map_data <- dist_week %>%
mutate(lon = st_coordinates(.)[,1], lat = st_coordinates(.)[,2]) %>%
as.data.frame() %>%
group_by(lon, lat, complaint_type) %>%
summarize(n = n(), created_date = paste0(created_date, collapse = "<br>"),
incident_address = paste0(unique(incident_address), collapse = "<br>")) %>%
st_as_sf(coords = c("lon", "lat"), crs = st_crs(dist_week))
bbox <- as.numeric(st_bbox(map_data))
leaflet(map_data) %>%
councildown::addCouncilStyle() %>%
clearGroup("complaints") %>%
addCircleMarkers(radius = 4, weight = 15, fillOpacity = .8, opacity = 0,
fillColor = ~pal(complaint_type)) %>%
fitBounds(bbox[1], bbox[2], bbox[3], bbox[4])
dist_ytd <- tbl(snapshots_db, "sr_top_10_ytd_district_closed") %>%
filter(coun_dist == local(coun_dist)) %>%
select(-locations) %>%
collect()
dist_ytd %>%
mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>%
str_wrap(15) %>%
reorder(n_tot)) %>%
ggplot(aes(complaint_type, n_tot, fill = as.numeric(complaint_type),
text = paste(complaint_type, n_tot, sep = "<br>"))) +
geom_col(show.legend = FALSE) +
coord_flip() +
scale_fill_gradient(low = "#2F56A6", high = "#23417D") +
scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) +
labs(x = "Complaint type",
y = "Number of service requests") +
theme_bw()
dist_all <- tbl(snapshots_db, "sr_week_district_closed") %>%
filter(coun_dist == local(coun_dist)) %>%
select(-locations)
dist_all %>%
filter(week <= local(current_week)) %>%
group_by(week) %>%
summarize(n = sum(n)) %>%
collect() %>%
mutate(date = floor_date(ymd("2019-01-01")+(7*(week-1)), unit = "week") + 1) %>%
ggplot(aes(date, n,
text = paste0("Week of ", format(date, format = "%b %e"), ": ", n, " service requests"), group = 1, group = 1)) +
geom_point(color = "#23417D") +
geom_line(color = "#23417D") +
labs(x = "Week",
y = "Number of service requests") +
theme_bw()
setProgress(.4)
OEM Incidents^[Note: Emergency Response Incidents are emergencies that NYCEM responded to. There are 13 emergency categories to date: Administration, Aviation, Fire, HazMat, Law Enforcement, Marine, Medical, Rescue, Structural, Transportation, Utility, Weather and Other.]
oem_week_dist <- tbl(snapshots_db, "emergency_response") %>%
filter(date_part("week", creation_date) == local(week)) %>%
collect_geo() %>%
st_join(dists) %>%
rename(coun_dist_dat = coun_dist) %>%
filter(coun_dist_dat == coun_dist) %>%
mutate(duration = closed_date - creation_date,
duration_pretty = ifelse(is.na(duration), "Ongoing as of last update", Fmt(duration)))
if (nrow(oem_week_dist) > 0){
bbox <- as.numeric(st_bbox(oem_week_dist))
oem_week_dist %>%
leaflet() %>%
councildown::addCouncilStyle() %>%
addCircleMarkers(radius = ~ifelse(is.na(duration), 5, 25*sqrt(as.double(duration)/max(as.double(duration)))),
popup = ~paste(incident_type, location, paste(creation_date, closed_date, sep = " - "), duration_pretty, sep = "<br>"),
fillOpacity = .8, fillColor = ~ifelse(is.na(closed_date), "#D05D4E","#2F56A6"), opacity = 0, weight = 15,
group = "oem_incidents") %>%
clearControls() %>%
flyToBounds(bbox[1], bbox[2], bbox[3], bbox[4], options = list(duration = .25))
}
if (nrow(oem_week_dist) > 0){
oem_week_dist %>%
as.data.frame() %>%
select(incident_type, location, creation_date, closed_date) %>%
knitr::kable(col.names = c('Incident','Location', 'Start Time', 'Closed'))
}
r if (nrow(oem_week_dist) == 0) {"No emergency incidents."}
setProgress(.6)
HPD Vacate Orders
Issued Vacate Orders
issued_week_dist <- tbl(snapshots_db, "vacate_orders") %>%
filter(council_district == local(coun_dist),
date_part("week", vacate_effective_date) == local(week)) %>%
mutate(address = paste(number, street)) %>%
collect_geo()
if (nrow(issued_week_dist) > 0) {
bbox <- as.numeric(st_bbox(issued_week_dist))
issued_week_dist %>%
leaflet() %>%
councildown::addCouncilStyle() %>%
addCircleMarkers(radius = 5,
fillOpacity = .8, fillColor = "#2F56A6", opacity = 0, weight = 15,
popup = ~paste(address, primary_vacate_reason, vacate_effective_date, sep = "<br>"),
group = "issued") %>%
clearControls() %>%
flyToBounds(bbox[1], bbox[2], bbox[3], bbox[4], options = list(duration = .25))
}
if (nrow(issued_week_dist) > 0) {
issued_week_dist %>%
as.data.frame() %>%
select(address, primary_vacate_reason, vacate_type, vacate_effective_date, number_of_vacated_units) %>%
knitr::kable(col.names = c('Address','Vacate Reason','Type', 'Effective Date', 'Units Vacated'))
}
r if (nrow(issued_week_dist) == 0) {"No issued vacate orders."}
setProgress(.8)
Rescinded Vacate Orders
rescinded_week_dist <- tbl(snapshots_db, "vacate_orders") %>%
filter(council_district == local(coun_dist),
date_part("week", rescind_date) == local(week)) %>%
mutate(address = paste(number, street)) %>%
collect_geo()
if (nrow(rescinded_week_dist) > 0) {
bbox <- as.numeric(st_bbox(rescinded_week_dist))
rescinded_week_dist %>%
leaflet() %>%
councildown::addCouncilStyle() %>%
addCircleMarkers(radius = 5,
fillOpacity = .8, fillColor = "#2F56A6", opacity = 0, weight = 15,
popup = ~paste(address, primary_vacate_reason, vacate_effective_date, sep = "<br>"),
group = "rescinded") %>%
clearControls() %>%
flyToBounds(bbox[1], bbox[2], bbox[3], bbox[4], options = list(duration = .25))
}
if (nrow(rescinded_week_dist) > 0) {
rescinded_week_dist %>%
as.data.frame() %>%
select(address, primary_vacate_reason, vacate_type, vacate_effective_date, number_of_vacated_units) %>%
knitr::kable(col.names = c('Address','Vacate Reason','Type', 'Effective Date', 'Units Vacated'))
}
r if (nrow(rescinded_week_dist) == 0) {"No rescinded vacate orders."}
Sources
311 Service Requests, NYC OpenData: 311, DoITT, https://data.cityofnewyork.us/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9
Emergency Response Incidents, NYC OpenData: NYCEM, https://data.cityofnewyork.us/Public-Safety/Emergency-Response-Incidents/pasr-j7fb
Order to Repair/Vacate Orders, NYC OpenData: HPD, https://data.cityofnewyork.us/Housing-Development/Order-to-Repair-Vacate-Orders/tb8q-a3ar
setProgress(.9)
NewYorkCityCouncil/council_snapshots documentation built on Oct. 30, 2019, 10:11 p.m.
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library(ggplot2) # library(councildown) knitr::knit_hooks$set(embed = councildown::hook_pdfembed) knitr::opts_chunk$set(echo = FALSE, embed = TRUE, warning = FALSE, message = FALSE) knitr::opts_knit$set(root.dir = here::here())
week <- params$week coun_dist <- params$coun_dist
library(shiny) library(shinydashboard) library(tibble) library(ggplot2) library(dplyr) library(lubridate) library(stringr) library(leaflet) library(stringr) library(purrr) library(sf) utils <- list.files(path = "util", pattern = "\\.(R|r)$", full.names = TRUE) lapply(utils, source) current_week <- tbl(snapshots_db, "sr_top_10_week_district_closed") %>% group_by(coun_dist) %>% summarize(week = max(week)) %>% ungroup() %>% summarize(week = min(week)) %>% pull() dists <- tbl(snapshots_db, "council_districts") %>% collect_geo() Fmt <- function(x) UseMethod("Fmt") Fmt.difftime <- function(x) { units(x) <- "secs" x <- unclass(x) NextMethod() } Fmt.default <- function(x) { y <- abs(x) # if(is.na(y)){ return("Ongoing as of last update")} sprintf("%02d hours %02d minutes", y %/% 3600, # hours y %% 3600 %/% 60) # minutes }
311 Service Requests ^[Note: 311 Service Requests data is representative of the population that makes a service request. Generalizations can't be made for the entire city or district population.]
Submitted Service Requests
dist_week <- tbl(snapshots_db, "sr_ind_top_10_week_district") %>% filter(coun_dist == local(coun_dist), week == local(week)) %>% collect_geo()
dist_week %>% count(complaint_type) %>% # wrap labels for prettiness mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>% str_wrap(15) %>% reorder(n)) %>% ggplot(aes(complaint_type, n, fill = complaint_type, text = paste(complaint_type, n, sep = "<br>"))) + geom_col(show.legend = FALSE) + coord_flip() + labs(x = "Complaint type", y = "Number of service requests") + councildown::scale_fill_nycc() + scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) + theme_bw()
dat <- dist_week %>% as.data.frame() pal <- colorFactor(councildown::nycc_pal()(length(unique(dat$complaint_type))), reorder(count(dat, complaint_type)$complaint_type, count(dat, complaint_type)$n))
map_data <- dist_week %>% mutate(lon = st_coordinates(.)[,1], lat = st_coordinates(.)[,2]) %>% as.data.frame() %>% group_by(lon, lat, complaint_type) %>% summarize(n = n(), created_date = paste0(created_date, collapse = "<br>"), incident_address = paste0(unique(incident_address), collapse = "<br>")) %>% st_as_sf(coords = c("lon", "lat"), crs = st_crs(dist_week))
bbox <- as.numeric(st_bbox(map_data)) leaflet(map_data) %>% councildown::addCouncilStyle() %>% clearGroup("complaints") %>% addCircleMarkers(radius = 4, weight = 15, fillOpacity = .8, opacity = 0, fillColor = ~pal(complaint_type)) %>% fitBounds(bbox[1], bbox[2], bbox[3], bbox[4])
dist_ytd <- tbl(snapshots_db, "sr_top_10_ytd_district") %>% filter(coun_dist == local(coun_dist)) %>% select(-locations) %>% collect()
dist_ytd %>% mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>% str_wrap(15) %>% reorder(n_tot)) %>% ggplot(aes(complaint_type, n_tot, fill = as.numeric(complaint_type), text = paste(complaint_type, n_tot, sep = "<br>"))) + geom_col(show.legend = FALSE) + coord_flip() + scale_fill_gradient(low = "#2F56A6", high = "#23417D") + scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) + labs(x = "Complaint type", y = "Number of service requests") + theme_bw()
dist_all <- tbl(snapshots_db, "sr_week_district") %>% filter(coun_dist == local(coun_dist)) %>% select(-locations)
dist_all %>% filter(week <= local(current_week)) %>% group_by(week) %>% summarize(n = sum(n)) %>% collect() %>% mutate(date = floor_date(ymd("2019-01-01")+(7*(week-1)), unit = "week") + 1) %>% ggplot(aes(date, n, text = paste0("Week of ", format(date, format = "%b %e"), ": ", n, " service requests"), group = 1, group = 1)) + geom_point(color = "#23417D") + geom_line(color = "#23417D") + labs(x = "Week", y = "Number of service requests") + theme_bw()
setProgress(.2)
Closed Service Requests
dist_week <- tbl(snapshots_db, "sr_ind_top_10_week_district_closed") %>% filter(coun_dist == local(coun_dist), week == local(week)) %>% collect_geo()
dist_week %>% count(complaint_type) %>% # wrap labels for prettiness mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>% str_wrap(15) %>% reorder(n)) %>% ggplot(aes(complaint_type, n, fill = complaint_type, text = paste(complaint_type, n, sep = "<br>"))) + geom_col(show.legend = FALSE) + coord_flip() + labs(x = "Complaint type", y = "Number of service requests") + councildown::scale_fill_nycc() + scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) + theme_bw()
dat <- dist_week %>% as.data.frame() pal <- colorFactor(councildown::nycc_pal()(length(unique(dat$complaint_type))), reorder(count(dat, complaint_type)$complaint_type, count(dat, complaint_type)$n))
map_data <- dist_week %>% mutate(lon = st_coordinates(.)[,1], lat = st_coordinates(.)[,2]) %>% as.data.frame() %>% group_by(lon, lat, complaint_type) %>% summarize(n = n(), created_date = paste0(created_date, collapse = "<br>"), incident_address = paste0(unique(incident_address), collapse = "<br>")) %>% st_as_sf(coords = c("lon", "lat"), crs = st_crs(dist_week))
bbox <- as.numeric(st_bbox(map_data)) leaflet(map_data) %>% councildown::addCouncilStyle() %>% clearGroup("complaints") %>% addCircleMarkers(radius = 4, weight = 15, fillOpacity = .8, opacity = 0, fillColor = ~pal(complaint_type)) %>% fitBounds(bbox[1], bbox[2], bbox[3], bbox[4])
dist_ytd <- tbl(snapshots_db, "sr_top_10_ytd_district_closed") %>% filter(coun_dist == local(coun_dist)) %>% select(-locations) %>% collect()
dist_ytd %>% mutate(complaint_type = tools::toTitleCase(tolower(complaint_type)) %>% str_wrap(15) %>% reorder(n_tot)) %>% ggplot(aes(complaint_type, n_tot, fill = as.numeric(complaint_type), text = paste(complaint_type, n_tot, sep = "<br>"))) + geom_col(show.legend = FALSE) + coord_flip() + scale_fill_gradient(low = "#2F56A6", high = "#23417D") + scale_x_discrete(labels = function(x) str_replace(x, "(^.*?\\n)(.*?)(\\n.*?)+$", "\\1\\2...")) + labs(x = "Complaint type", y = "Number of service requests") + theme_bw()
dist_all <- tbl(snapshots_db, "sr_week_district_closed") %>% filter(coun_dist == local(coun_dist)) %>% select(-locations)
dist_all %>% filter(week <= local(current_week)) %>% group_by(week) %>% summarize(n = sum(n)) %>% collect() %>% mutate(date = floor_date(ymd("2019-01-01")+(7*(week-1)), unit = "week") + 1) %>% ggplot(aes(date, n, text = paste0("Week of ", format(date, format = "%b %e"), ": ", n, " service requests"), group = 1, group = 1)) + geom_point(color = "#23417D") + geom_line(color = "#23417D") + labs(x = "Week", y = "Number of service requests") + theme_bw()
setProgress(.4)
OEM Incidents^[Note: Emergency Response Incidents are emergencies that NYCEM responded to. There are 13 emergency categories to date: Administration, Aviation, Fire, HazMat, Law Enforcement, Marine, Medical, Rescue, Structural, Transportation, Utility, Weather and Other.]
oem_week_dist <- tbl(snapshots_db, "emergency_response") %>% filter(date_part("week", creation_date) == local(week)) %>% collect_geo() %>% st_join(dists) %>% rename(coun_dist_dat = coun_dist) %>% filter(coun_dist_dat == coun_dist) %>% mutate(duration = closed_date - creation_date, duration_pretty = ifelse(is.na(duration), "Ongoing as of last update", Fmt(duration)))
if (nrow(oem_week_dist) > 0){ bbox <- as.numeric(st_bbox(oem_week_dist)) oem_week_dist %>% leaflet() %>% councildown::addCouncilStyle() %>% addCircleMarkers(radius = ~ifelse(is.na(duration), 5, 25*sqrt(as.double(duration)/max(as.double(duration)))), popup = ~paste(incident_type, location, paste(creation_date, closed_date, sep = " - "), duration_pretty, sep = "<br>"), fillOpacity = .8, fillColor = ~ifelse(is.na(closed_date), "#D05D4E","#2F56A6"), opacity = 0, weight = 15, group = "oem_incidents") %>% clearControls() %>% flyToBounds(bbox[1], bbox[2], bbox[3], bbox[4], options = list(duration = .25)) }
if (nrow(oem_week_dist) > 0){ oem_week_dist %>% as.data.frame() %>% select(incident_type, location, creation_date, closed_date) %>% knitr::kable(col.names = c('Incident','Location', 'Start Time', 'Closed')) }
r if (nrow(oem_week_dist) == 0) {"No emergency incidents."}
setProgress(.6)
HPD Vacate Orders
Issued Vacate Orders
issued_week_dist <- tbl(snapshots_db, "vacate_orders") %>% filter(council_district == local(coun_dist), date_part("week", vacate_effective_date) == local(week)) %>% mutate(address = paste(number, street)) %>% collect_geo()
if (nrow(issued_week_dist) > 0) { bbox <- as.numeric(st_bbox(issued_week_dist)) issued_week_dist %>% leaflet() %>% councildown::addCouncilStyle() %>% addCircleMarkers(radius = 5, fillOpacity = .8, fillColor = "#2F56A6", opacity = 0, weight = 15, popup = ~paste(address, primary_vacate_reason, vacate_effective_date, sep = "<br>"), group = "issued") %>% clearControls() %>% flyToBounds(bbox[1], bbox[2], bbox[3], bbox[4], options = list(duration = .25)) }
if (nrow(issued_week_dist) > 0) { issued_week_dist %>% as.data.frame() %>% select(address, primary_vacate_reason, vacate_type, vacate_effective_date, number_of_vacated_units) %>% knitr::kable(col.names = c('Address','Vacate Reason','Type', 'Effective Date', 'Units Vacated')) }
r if (nrow(issued_week_dist) == 0) {"No issued vacate orders."}
setProgress(.8)
Rescinded Vacate Orders
rescinded_week_dist <- tbl(snapshots_db, "vacate_orders") %>% filter(council_district == local(coun_dist), date_part("week", rescind_date) == local(week)) %>% mutate(address = paste(number, street)) %>% collect_geo()
if (nrow(rescinded_week_dist) > 0) { bbox <- as.numeric(st_bbox(rescinded_week_dist)) rescinded_week_dist %>% leaflet() %>% councildown::addCouncilStyle() %>% addCircleMarkers(radius = 5, fillOpacity = .8, fillColor = "#2F56A6", opacity = 0, weight = 15, popup = ~paste(address, primary_vacate_reason, vacate_effective_date, sep = "<br>"), group = "rescinded") %>% clearControls() %>% flyToBounds(bbox[1], bbox[2], bbox[3], bbox[4], options = list(duration = .25)) }
if (nrow(rescinded_week_dist) > 0) { rescinded_week_dist %>% as.data.frame() %>% select(address, primary_vacate_reason, vacate_type, vacate_effective_date, number_of_vacated_units) %>% knitr::kable(col.names = c('Address','Vacate Reason','Type', 'Effective Date', 'Units Vacated')) }
r if (nrow(rescinded_week_dist) == 0) {"No rescinded vacate orders."}
Sources
311 Service Requests, NYC OpenData: 311, DoITT, https://data.cityofnewyork.us/Social-Services/311-Service-Requests-from-2010-to-Present/erm2-nwe9
Emergency Response Incidents, NYC OpenData: NYCEM, https://data.cityofnewyork.us/Public-Safety/Emergency-Response-Incidents/pasr-j7fb
Order to Repair/Vacate Orders, NYC OpenData: HPD, https://data.cityofnewyork.us/Housing-Development/Order-to-Repair-Vacate-Orders/tb8q-a3ar
setProgress(.9)
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