I have two datasets which are subset using a sliderInput that selects for a range of dates. The filtered data then shows the latitude and longitude (based ont the zipcode) of certain events (weed and shops) within the range of dates selected. When I render the leaflet map however, only one set of datapoints ever shows up. If I comment out the first set observe function I can see the second set of datapoints and visa versa but I can never get both observers to show both sts of datapoints at the same time.
Date Zip MainSource
2014-01-03 17:35:00 98103 Marijuana Plant
2014-01-04 22:53:00 98112 Other Food
2014-01-13 22:50:00 98272 Marijuana Plant
2014-01-14 17:50:00 99210 Marijuana Plant
2014-01-29 19:27:00 99302 thc
2014-02-03 11:55:00 99336 Misc
... ... ...
name zip opening
The Stash Box 98002 2014-11-21
Greenside 98198 2015-01-01
Bud Nation 98106 2015-06-29
West Seattle Cannabis Co. 98168 2015-02-28
Nimbin Farm 98168 2015-04-25
Have a Heart 98178 2015-04-24
... ... ...
Here is the code for the leaflet map.
library(htmltools)
library(dplyr)
library(zipcode)
library(leaflet)
data(zipcode)
ui <- bootstrapPage(
tags$style(type = "text/css", "html, body {width:100%;height:100%}"),
leafletOutput("map", width = "100%", height = "100%"),
# Get user input for selected date range
absolutePanel(top = 10, right = 12,
sliderInput("range",
"Choose your dates:",
min(weed$Date),
max(weed$Date),
value = range(weed$Date),
step = 0.1,
timeFormat = "%b-%d-%Y"
)
)
)
server <- function(input, output, session) {
# Reactive expression for the data subsetted to what the user selected
filteredData <- reactive({
df <- weed[weed$Date >= input$range[1] & weed$Date <= input$range[2],] %>%
group_by(Zip) %>%
summarize(count = n())
names(df) <- c("zip", "count")
df <- join(df, zipcode[,c(1,4,5)], by = "zip")
return(df)
})
filteredShopData <- reactive({
df <- shops[shops$opening >= input$range[1] & shops$opening <= input$range[2],] %>%
group_by(zip) %>%
summarize(count = n())
names(df) <- c("zip", "count")
df <- join(df, zipcode[,c(1,4,5)], by = "zip")
return(df)
})
# Plot static map
output$map <- renderLeaflet({
leaflet() %>% addProviderTiles("CartoDB.Positron") %>%
setView(lng = -122.213380, lat = 47.595225, zoom = 10)
})
# Plot pot shops
observe({
if (nrow(filteredShopData()) == 0) {leafletProxy("map") %>% clearShapes()}
else {
leafletProxy("map", data = filteredShopData()) %>%
clearShapes() %>%
addCircles(~longitude,
~latitude,
radius = ~500*sqrt(count),
color = "black")
}
})
# Plot cases in WA state
observe({
if (nrow(filteredData()) == 0) {leafletProxy("map") %>% clearShapes()}
else {
leafletProxy("map", data = filteredData()) %>%
clearShapes() %>%
addCircles(~longitude,
~latitude,
weight = 1,
radius = ~700*sqrt(count),
color = "red") }
})
}
shinyApp(ui, server)
I think this has to do with the fact that you are passing two data arguments.
instead I would directly call your data
observe({
if (nrow(filteredShopData()) == 0) {leafletProxy("map") %>% clearShapes()}
else {
leafletProxy("map") %>%
clearShapes() %>%
addCircles(filteredShopData()$longitude,
filteredShopData()$latitude,
radius = ~500*sqrt(count),
color = "black")
}
})
# Plot cases in WA state
observe({
if (nrow(filteredData()) == 0) {leafletProxy("map") %>% clearShapes()}
else {
leafletProxy("map") %>%
clearShapes() %>%
addCircles( filteredData()$longitude,
filteredData()$latitude,
weight = 1,
radius = ~700*sqrt(count),
color = "red") }
})