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@Yankim Yankim/server.R

Last active Sep 19, 2016
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# server.R
library(shiny); library(maps); library(mapproj); library(shinydashboard); library(plotly); library(DT); source("helpers.R")
shinyServer(
function(input, output) {
output$map <- renderPlot({
args <- switch(input$var,
"Percent Adult Obese 2009" = list(health2$PCT_OBESE_ADULTS09, "darkgreen", "% Obese"),
"Percent Adult Obese 2010" = list(health2$PCT_OBESE_ADULTS10, "darkgreen", "% Obese"),
"Percent Adult Diabetic 2009" = list(health2$PCT_DIABETES_ADULTS09, "darkred", "% Diabetic"),
"Percent Adult Diabetic 2010" = list(health2$PCT_DIABETES_ADULTS10, "darkred", "% Diabetic"),
"Percent Poverty 2010" = list(socioeconomic2$POVRATE10, "blue", "% Poverty"))
args$min <- input$range[1]
args$max <- input$range[2]
args$name <- input$var
do.call(percent_map, args)
}, height = 510, width = 900 )
output$trendPlot <- renderPlotly({
args1 <- switch(input$var1,
"Percent Adult Obese 2010" = "PCT_OBESE_ADULTS10",
"Percent Adult Diabetic 2010" = "PCT_DIABETES_ADULTS10",
"Percent Poverty 2010" = "POVRATE10",
"Median household income, 2010" = "MEDHHINC10",
"Population, low access to store (%), 2010" ="PCT_LACCESS_POP10",
"Grocery stores/1,000 pop, 2012" = "GROCPTH12",
"Convenience stores/1,000 pop, 2012" = "CONVSPTH12",
"Fast-food restaurants/1,000 pop, 2012" = "FFRPTH12",
"Full-service restaurants/1,000 pop, 2012" = "FSRPTH12",
"Household food insecurity (%), 2010-12" = "FOODINSEC_10_12",
"Farms with direct sales, 2007" = "DIRSALES_FARMS07",
"Farmers' markets/1,000 pop, 2013" = "FMRKTPTH13",
"Vegetable farms, 2007" = "VEG_FARMS07",
"High schoolers physically active (%), 2009" = "PCT_HSPA09",
"Recreation & fitness facilities/1,000 pop, 2012" = "RECFACPTH12",
"% Population 65 years or older, 2010" = "PCT_65OLDER10",
"% Population under age 18, 2010" = "PCT_18YOUNGER10"
)
#arg2 identical to arg1, code not included to save space
# Create a convenience data.frame which can be used for charting
plot.df <- data.frame(fulldb[,args1],
fulldb[,args2],
fulldb$County,
fulldb$State,
fulldb$PCT_OBESE_ADULTS10)
# Add column names
colnames(plot.df) <- c("x", "y", "County", "State", "Obese")
p <- plot_ly(plot.df, x = x, y = y,
text = paste(County, ",", State, "Adult % Obese:",Obese),
mode = "markers", color = Obese)
layout(p,title = paste(input$var2, "vs ", input$var1),
xaxis = list(title = input$var1),
yaxis = list(title = input$var2))
})
output$predtable <- renderUI({
g <- predfunc(GROC = input$GROC, Conv = input$Conv, Full = input$Full, FF = input$FF, LACCESS =
input$LACCESS, MEDHHIN = input$MEDHHIN, RECFAC = input$RECFAC,
PCT18 = input$PCT18, FOODINS = input$FOODINS, FARMRT = input$FARMRT,
VEGFARM = input$VEGFARM, DIABETE = input$DIABETE, HSACT = input$HSACT,
POVRT = input$POVRT, PCT65 = input$PCT65)
str1 = paste("Predicted obesity rate", round(g[1], 1), "%")
str2 = paste("95% confident that prediction is within", round(g[2], 1), "%", "to", round(g[3], 1), "%")
HTML(paste(str1, str2, sep = '<br/>'))
})
}
)
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