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- library(shiny)
- library(tidyverse)
- # Load precomputed data
- sct_data <- readRDS(file = "data/rds/proj.rds")
- sct_data_b <- readRDS(file = "data/rds/categories.rds")
- choropleth_data <- readRDS(file = "data/rds/choropleth_data.rds")
- bar_data <- readRDS(file = "data/rds/bar_data.rds")
- radar_data <- readRDS(file = "data/rds/radar_data.rds")
- tree_data <- readRDS(file = "data/rds/tree_data.rds")
- parset_data <- read_csv2("data/parset_data.csv")
- treemap_data <- readRDS(file = "data/rds/treemap_data.rds")
- heatmap_2012_data <- readRDS(file = "data/rds/heatmap_2012_data.rds")
- heatmap_2013_data <- readRDS(file = "data/rds/heatmap_2013_data.rds")
- heatmap_2014_data <- readRDS(file = "data/rds/heatmap_2014_data.rds")
- heatmap_2015_data <- readRDS(file = "data/rds/heatmap_2015_data.rds")
- heatmap_2016_data <- readRDS(file = "data/rds/heatmap_2016_data.rds")
- heatmap_2017_data <- readRDS(file = "data/rds/heatmap_2017_data.rds")
- choropleth_UF2012_data <- readRDS(file = "data/rds/percentage_UF2012.rds")
- choropleth_UF2013_data <- readRDS(file = "data/rds/percentage_UF2013.rds")
- choropleth_UF2014_data <- readRDS(file = "data/rds/percentage_UF2014.rds")
- choropleth_UF2015_data <- readRDS(file = "data/rds/percentage_UF2015.rds")
- choropleth_UF2016_data <- readRDS(file = "data/rds/percentage_UF2016.rds")
- choropleth_UF2017_data <- readRDS(file = "data/rds/percentage_UF2017.rds")
- choropleth_meso2012_data <- readRDS(file = "data/rds/percentage_meso2012.rds")
- choropleth_meso2013_data <- readRDS(file = "data/rds/percentage_meso2013.rds")
- choropleth_meso2014_data <- readRDS(file = "data/rds/percentage_meso2014.rds")
- choropleth_meso2015_data <- readRDS(file = "data/rds/percentage_meso2015.rds")
- choropleth_meso2016_data <- readRDS(file = "data/rds/percentage_meso2016.rds")
- choropleth_meso2017_data <- readRDS(file = "data/rds/percentage_meso2017.rds")
- server <- function(input, output, session) {
- observe({
- session$sendCustomMessage(type="scatterplot_values",
- message = list(sct_data, sct_data_b))
- })
- observe({
- session$sendCustomMessage(type="parset_values",
- message = c(treemap_data,
- list(parset_data[-c(1,3,4,5,6)])))
- })
- observe({
- session$sendCustomMessage(type="dendrogram_values",
- message = list(tree_data,
- bar_data,
- radar_data))
- })
- observe({
- session$sendCustomMessage(type="choropleth_values",
- message = list(
- list(choropleth_UF2012_data,
- choropleth_UF2013_data,
- choropleth_UF2014_data,
- choropleth_UF2015_data,
- choropleth_UF2016_data,
- choropleth_UF2017_data),
- list(heatmap_2012_data,
- heatmap_2013_data,
- heatmap_2014_data,
- heatmap_2015_data,
- heatmap_2016_data,
- heatmap_2017_data),
- list(choropleth_meso2012_data,
- choropleth_meso2013_data,
- choropleth_meso2014_data,
- choropleth_meso2015_data,
- choropleth_meso2016_data,
- choropleth_meso2017_data))
- )
- })
- # Comunication with parallel sets
- observe({
- req(input$scope)
- req(input$name)
- s <- input$scope
- v <- input$name
- switch(
- s,
- "pais"= {
- filtered <- filter(parset_data, pais == v)[-c(1,3,4,5,6)]
- },
- "regiao"= {
- filtered <- filter(parset_data, regiao == v)[-c(1,2,4,5,6)]
- },
- "uf"= {
- filtered <- filter(parset_data, uf == v)[-c(1,2,3,5,6)]
- },
- "mesorregiao"= {
- filtered <- filter(parset_data, mesorregiao == v)[-c(1,2,3,4,6)]
- },
- "microrregiao"= {
- filtered <- filter(parset_data, microrregiao == v)[-c(1,2,3,4,5)]
- },
- #there is no way to reach this level for now
- "municipio"= {
- filtered <- filter(parset_data, municipio == v)[-c(1,2,3,4,5)]
- }
- )
- session$sendCustomMessage(type="treemap_values_change", message = filtered)
- })
- }
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