rshinyr-plotlygooglevis
Issue with retaining the info of lasso select and box select in Plotly map with Shiny
I am trying to create an interactive map using Plotly in the Shiny app that allows the user to select the region by box select and lasso select on the map, then it can return a GoogleVis motion chart showing the statistics on the region selected within the Shiny app. Here is the UI function:
library(shiny)
library(shinyWidgets)
library(plotly)
library(leaflet)
shinyUI(fluidPage(
titlePanel("Johns Hopkins COVID-19 Modeling Visualization Map"),
setBackgroundImage(
src = "https://brand.jhu.edu/assets/uploads/sites/5/2014/06/university.logo_.small_.horizontal.blue_.jpg"
),
sidebarLayout(
sidebarPanel(
radioButtons("countyFill", "Choose the County Map Type", c("Map by total confirmed", "Map by total death"), selected = "Map by total confirmed"),
checkboxGroupInput("statesInput", "Choose the State(s)",
c("AL", "MO", "AK", "MT", "AZ", "NE",
"AR", "NV", "CA", "NH", "CO", "NJ",
"CT", "NM", "DE", "NY", "DC", "NC",
"FL", "ND", "GA", "OH", "HI", "OK",
"ID", "OR", "IL", "PA", "IN", "RI",
"IA", "SC", "KS", "SD", "KY", "TN",
"LA", "TX", "ME", "UT", "MD", "VT",
"MA", "VA", "MI", "WA", "MN", "WV",
"MS", "WI", "WY"),
inline = TRUE),
submitButton("Submit (may take 30s to load)")
),
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("County Level", plotlyOutput("countyPolygonMap"), htmlOutput("motionChart"), verbatimTextOutput("brush")),
tabPanel("State Level", leafletOutput("statePolygonMap")),
tags$div(
tags$p(
"JHU.edu Copyright © 2020 by Johns Hopkins University & Medicine. All rights reserved."
),
tags$p(
tags$a(href="https://it.johnshopkins.edu/policies/privacystatement",
"JHU Information Technology Privacy Statement for Websites and Mobile Applications")
)
)
)
)
)))
And here is the server function:
library(shiny)
library(leaflet)
library(magrittr)
library(rgdal)
library(plotly)
library(rjson)
library(dplyr)
library(viridis)
library(googleVis)
library(lubridate)
library(reshape2)
shinyServer(function(input, output, session) {
statepolygonZip <- download.file("https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip",
destfile = "cb_2018_us_state_500k.zip");
unzip("cb_2018_us_state_500k.zip");
statePolygonData <- readOGR("cb_2018_us_state_500k.shp", layer = "cb_2018_us_state_500k",
GDAL1_integer64_policy = TRUE);
## obtaning the state shape file data provided by cencus.gov
## for more categories of region shape file:
## https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
countyGeo <- rjson::fromJSON(file=url)
## Obtaining the geographical file for all U.S. counties
url2<- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv"
covidCases <- read.csv(url2, header = TRUE)
fips <- sprintf("%05d",covidCases$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases$countyNames, covidCases[11,ncol(covidCases)])
gvisCasesData <- melt(data = covidCases, id.vars = "countyNames",measure.vars = c(colnames(covidCases)[c(12:ncol(covidCases))]))
colnames(gvisCasesData)[2:3] <- c("Date", "numCases")
gvisCasesData$Date <- mdy(gvisCasesData$Date)
url3 <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv"
covidDeath <- read.csv(url3, header = TRUE)
totalDeath <- covidDeath[,ncol(covidDeath)]
v <- reactiveValues(data = totalComfirmed)
observeEvent(input$countyFill, {
if (input$countyFill == "Map by total confirmed") {
v$data <- totalComfirmed;
v$zmin = 100;
v$zmax = 12000;
v$hover <- with(covidCases, paste(countyName));
}
if (input$countyFill == "Map by total death") {
v$data <- totalDeath;
v$zmin = 0;
v$zmax = 1600;
v$hover <- with(covidDeath, paste(countyName));
}
})
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "countyMap") %>% add_trace(
countyName <- covidCases$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=v$data,
colorscale="Viridis",
zmin= v$zmin,
zmax= v$zmax,
text = ~v$hover,
marker=list(line=list(width=0),opacity=0.5)
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
);
countyPolygonMap;
## generating the interactive plotly map
})
output$motionChart <- renderGvis({
subset(gvisCasesData, countyNames %in% c(selected))
motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
plot(motionChart)
})
output$statePolygonMap <-renderLeaflet ({
statesAbbr <- subset(statePolygonData, input$statesInput %in% statePolygonData$STUSPS);
## subsetting the shape file with the selected states
leaflet(statesAbbr) %>%
addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5,
opacity = 1.0, fillOpacity = 0.5,
fillColor = ~colorQuantile("YlOrRd", ALAND)(ALAND),
highlightOptions = highlightOptions
(color = "white", weight = 2,bringToFront = TRUE))
})
## producing the map with polygon boundary on the state level
})
However, it always tries to jump to a web browser for the GoogleVis chart, and it gives the error of
Error: $ operator is invalid for atomic vectors
Can you help me with it?
Solution
You had a few issues. In your case, actionButton is better than submitButton. You need to have an observeEvent for this button in the server. When you melt, you need a data table. Lastly, countyNames was misspelled in one case. As I could not install googleVis, you should uncomment that part and run on your pc to get the motionChart. You should be able to fix the remaining part.
The following code gives the output at the bottom.
ui <- fluidPage(
titlePanel("Johns Hopkins COVID-19 Modeling Visualization Map"),
setBackgroundImage(
src = "https://brand.jhu.edu/assets/uploads/sites/5/2014/06/university.logo_.small_.horizontal.blue_.jpg"
),
sidebarLayout(
sidebarPanel(
radioButtons("countyFill", "Choose the County Map Type", c("Map by total confirmed", "Map by total death"), selected = "Map by total confirmed"),
checkboxGroupInput("statesInput", "Choose the State(s)",
c("AL", "MO", "AK", "MT", "AZ", "NE",
"AR", "NV", "CA", "NH", "CO", "NJ",
"CT", "NM", "DE", "NY", "DC", "NC",
"FL", "ND", "GA", "OH", "HI", "OK",
"ID", "OR", "IL", "PA", "IN", "RI",
"IA", "SC", "KS", "SD", "KY", "TN",
"LA", "TX", "ME", "UT", "MD", "VT",
"MA", "VA", "MI", "WA", "MN", "WV",
"MS", "WI", "WY"),
inline = TRUE),
actionButton("submit", "Submit (may take 30s to load)")
),
mainPanel(
tabsetPanel(type = "tabs",
tabPanel("County Level", plotlyOutput("countyPolygonMap"),
#htmlOutput("motionChart"),
verbatimTextOutput("brush")),
tabPanel("State Level", leafletOutput("statePolygonMap")),
tags$div(
tags$p(
"JHU.edu Copyright © 2020 by Johns Hopkins University & Medicine. All rights reserved."
),
tags$p(
tags$a(href="https://it.johnshopkins.edu/policies/privacystatement",
"JHU Information Technology Privacy Statement for Websites and Mobile Applications")
)
)
)
)
)
)
server <- function(input, output, session) {
statepolygonZip <- download.file("https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip",
destfile = "cb_2018_us_state_500k.zip");
unzip("cb_2018_us_state_500k.zip");
statePolygonData <- readOGR("cb_2018_us_state_500k.shp", layer = "cb_2018_us_state_500k",
GDAL1_integer64_policy = TRUE);
## obtaning the state shape file data provided by cencus.gov
## for more categories of region shape file:
## https://www.census.gov/geographies/mapping-files/time-series/geo/carto-boundary-file.html
url <- 'https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json'
countyGeo <- rjson::fromJSON(file=url)
## Obtaining the geographical file for all U.S. counties
url2<- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv"
covidCases <- read.csv(url2, header = TRUE)
fips <- sprintf("%05d",covidCases$FIPS)
colnames(covidCases)[6] <- "countyNames"
totalComfirmed <- covidCases[,ncol(covidCases)]
destroyX = function(es) {
f = es
for (col in c(1:ncol(f))){ #for each column in dataframe
if (startsWith(colnames(f)[col], "X") == TRUE) { #if starts with 'X' ..
colnames(f)[col] <- substr(colnames(f)[col], 2, 100) #get rid of it
}
}
assign(deparse(substitute(es)), f, inherits = TRUE) #assign corrected data to original name
}
destroyX(covidCases)
gvisCasesData <- cbind.data.frame(covidCases$countyNames, covidCases[11,ncol(covidCases)])
gvisCasesData <- melt(data = setDT(covidCases), id.vars = "countyNames",measure.vars = c(colnames(covidCases)[c(12:ncol(covidCases))]))
colnames(gvisCasesData)[2:3] <- c("Date", "numCases")
gvisCasesData$Date <- mdy(gvisCasesData$Date)
url3 <- "https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv"
covidDeath <- read.csv(url3, header = TRUE)
totalDeath <- covidDeath[,ncol(covidDeath)]
v <- reactiveValues(data = totalComfirmed)
observeEvent(input$countyFill, {
if (input$countyFill == "Map by total confirmed") {
v$data <- totalComfirmed;
v$zmin = 100;
v$zmax = 12000;
v$hover <- with(covidCases, paste(countyNames));
}
if (input$countyFill == "Map by total death") {
v$data <- totalDeath;
v$zmin = 0;
v$zmax = 1600;
v$hover <- with(covidDeath, paste(countyNames));
}
})
observeEvent(input$submit, {
req(input$submit)
output$countyPolygonMap <- renderPlotly({
countyPolygonMap <- plot_ly(source = "countyMap") %>% add_trace(
countyName <- covidCases$countyNames,
type="choroplethmapbox",
geojson=countyGeo,
locations=fips,
z=v$data,
colorscale="Viridis",
zmin= v$zmin,
zmax= v$zmax,
text = ~v$hover,
marker=list(line=list(width=0),opacity=0.5)
) %>% layout(
mapbox=list(
style="carto-positron",
zoom =2,
center=list(lon= -95.71, lat=37.09))
);
countyPolygonMap;
## generating the interactive plotly map
})
# output$motionChart <- renderGvis({
# subset(gvisCasesData, countyNames %in% c(selected))
# motionChart <- gvisMotionChart(gvisCasesDataSubset, "countyNames", "Date", options=list(width=800, height=400))
# plot(motionChart)
# })
output$statePolygonMap <-renderLeaflet ({
statesAbbr <- subset(statePolygonData, statePolygonData$STUSPS %in% input$statesInput);
## subsetting the shape file with the selected states
leaflet(statesAbbr) %>%
addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5,
opacity = 1.0, fillOpacity = 0.5,
fillColor = ~colorQuantile("YlOrRd", ALAND)(ALAND),
highlightOptions = highlightOptions
(color = "white", weight = 2,bringToFront = TRUE))
})
## producing the map with polygon boundary on the state level
})
}
shinyApp(ui, server)
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