library(leafdown)
# Run before uploading
#devtools::install_github("hoga-it/leafdown")
# Comment this when uploading
states <- readRDS("../extdata/usa1.RDS")
counties <- readRDS("../extdata/usa2.RDS")
percent <- function(x, digits = 2, format = "f", ...) { # Create user-defined function
paste0(formatC(x * 100, format = format, digits = digits, ...), "%")
}
create_labels <- function(data, map_level) {
labels <- sprintf(
"<strong>%s</strong><br/>
Democrats: %s<br/>
Republicans: %s<br/>
Libertarians: %s<br/>
Green: %s<br/>
</sup>",
data[, paste0("NAME_", map_level)],
percent(data$Democrats2016),
percent(data$Republicans2016),
percent(data$Libertarians2016),
percent(data$Green2016)
)
labels %>% lapply(htmltools::HTML)
}
# Define server for leafdown app
server <- function(input, output) {
# load the shapes for the two levels
spdfs_list <- list(states, counties)
# create leafdown object
my_leafdown <- Leafdown$new(spdfs_list, "leafdown", input)
rv <- reactiveValues()
rv$update_leafdown <- 0
# observers for the drilling buttons
observeEvent(input$drill_down, {
my_leafdown$drill_down()
rv$update_leafdown <- rv$update_leafdown + 1
})
observeEvent(input$drill_up, {
my_leafdown$drill_up()
rv$update_leafdown <- rv$update_leafdown + 1
})
data <- reactive({
req(rv$update_leafdown)
# fetch the current metadata from the leafdown object
data <- my_leafdown$curr_data
# join the metadata with the election-data.
# depending on the map_level we have different election-data so the 'by' columns for the join are different
if(my_leafdown$curr_map_level == 2) {
data$ST <- substr(data$HASC_2, 4, 5)
# there are counties with the same name in different states so we have to join on both
data <- left_join(data, us_election_counties, by = c("NAME_2", "ST"))
} else {
data$ST <- substr(data$HASC_1, 4, 5)
data <- left_join(data, us_election_states, by = "ST")
}
# add the data back to the leafdown object
my_leafdown$add_data(data)
data
})
# this is where the leafdown magic happens
output$leafdown <- renderLeaflet({
req(spdfs_list)
req(data)
data <- data()
# depending on the selected KPI in the dropdown we show different data
if(input$map_sel == "unemployment") {
data$y <- data$Unemployment * 100
fillcolor <- leaflet::colorNumeric("Greens", data$y)
legend_title <- "Unemployment in Percent"
} else {
data$y <- ifelse(data$Republicans2016 > data$Democrats2016, "Republicans", "Democrats")
fillcolor <- leaflet::colorFactor(c("#232066", "#E91D0E"), data$y)
legend_title <- "Winning Party"
}
labels <- create_labels(data, my_leafdown$curr_map_level)
# draw the leafdown object
my_leafdown$draw_leafdown(
fillColor = ~fillcolor(data$y),
weight = 3, fillOpacity = 1, color = "white", label = labels) %>%
# set the view to be center on the USA
setView(-95, 39, 4) %>%
# add a nice legend
addLegend(pal = fillcolor,
values = ~data$y,
title = legend_title,
opacity = 1)
})
# plots
output$socio <- renderEcharts4r({
df <- my_leafdown$curr_sel_data()
# check whether any shape is selected, show basic info for the whole usa if nothing is selected
if(dim(df)[1] > 0){
if(my_leafdown$curr_map_level == 1) {
df <- df[, c("State", "Hispanic", "White", "Black", "Asian", "Amerindian", "Other")]
df <- df %>% pivot_longer(2:7, "race") %>% group_by(State)
df$value <- round(df$value, 2)
} else {
df <- df[, c("County", "Hispanic", "White", "Black", "Asian", "Amerindian", "Other")]
df <- df %>% pivot_longer(2:7, "race") %>% group_by(County)
df$value <- round(df$value/100, 2)
}
} else {
# show basic info for the whole usa as no state is selected
df <- data.frame(
ST = "USA",
race = c("Hispanic", "White", "Black", "Asian", "Amerindian", "Other"),
value = c(0.15, 0.634, 0.134, 0.059, 0.015, 0.027)) %>% group_by(ST)
}
# create the graph
df %>%
e_charts(race) %>%
e_bar(value) %>%
e_tooltip(trigger = "axis",axisPointer = list(type = "shadow")) %>%
e_y_axis(splitArea = list(show = FALSE),
splitLine = list(show = FALSE),
formatter = e_axis_formatter("percent", digits = 2)) %>%
e_legend(orient = 'vertical',right = 10,top = 10) %>%
e_color(brewer.pal(nrow(df), "Set3")) %>%
e_tooltip(formatter = e_tooltip_item_formatter("percent"))
})
output$party <- renderEcharts4r({
df <- my_leafdown$curr_sel_data()
# check whether any shape is selected, show general election-result if nothing is selected
if(dim(df)[1] > 0){
if(my_leafdown$curr_map_level == 1) {
df <- df[, c("ST", "Democrats2016", "Republicans2016", "Libertarians2016", "Green2016")]
df <- df %>% pivot_longer(2:5, "party") %>% group_by(party)
} else {
df <- df[, c("County", "Democrats2016", "Republicans2016", "Libertarians2016", "Green2016")]
df <- df %>% pivot_longer(2:5, "party") %>% group_by(party)
df$value <- df$value
names(df)[1] <- "ST"
}
} else {
# show general election-result as no state is selected
df <- data.frame(
party = c("Democrats2016", "Republicans2016", "Libertarians2016", "Green2016"),
ST = "USA",
value = c(0.153, 0.634, 0.134, 0.059)) %>% group_by(party)
}
# create the graph
df %>%
e_charts(ST, stack="grp") %>%
e_bar(value) %>%
e_y_axis(formatter = e_axis_formatter("percent", digits = 2)) %>%
e_tooltip(trigger = "axis",axisPointer = list(type = "shadow")) %>%
e_legend(right = 10,top = 10) %>%
e_color(c("#232066", "#E91D0E", "#f3b300", "#006900"))%>%
e_tooltip(formatter = e_tooltip_item_formatter("percent", digits = 2))
})
}
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