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| library(shiny); library(shinydashboard); library(plotly); source("helpers.R"); library(DT) | |
| shinyUI(dashboardPage( | |
| dashboardHeader(title = "Food and health demographics in the USA", titleWidth = 400), | |
| dashboardSidebar( | |
| sidebarUserPanel("Yannick Kimmel", image = "Yannick.jpg"), | |
| sidebarMenu( | |
| menuItem("Map", tabName = "mappanel", icon = icon("map")), | |
| menuItem("Trends", tabName = "trends", icon = icon("line-chart")), | |
| menuItem("Predictions", tabName = "predict", icon = icon("chevron-right")), | |
| menuItem("Data", tabName = "data", icon = icon("database")) | |
| ), | |
| helpText(" Information from the USDA's Food Environment Atlas on counties in the USA.") | |
| ), | |
| dashboardBody( | |
| tabItems( | |
| tabItem(tabName = "mappanel", | |
| fluidRow( | |
| column(width = 12, | |
| box( | |
| selectInput("var", # choose the residents | |
| label = "Choose a variable to display", | |
| choices = c("Percent Adult Obese 2009", | |
| "Percent Adult Obese 2010", | |
| "Percent Adult Diabetic 2009", | |
| "Percent Adult Diabetic 2010", | |
| "Percent Poverty 2010"), | |
| selected = "Percent Obese 2009") | |
| ), | |
| box(sliderInput("range", # choose the range | |
| label = "Range of interest %:", | |
| min = 0, max = 50, value = c(0, 50))) | |
| ), | |
| plotOutput("map", width = "100%") | |
| )), | |
| tabItem(tabName = "trends", | |
| fluidRow( | |
| column(width = 12, | |
| box( | |
| # helpText("Create demographic maps with | |
| # information from the USDA's Food Environment Atlas."), | |
| selectInput("var1", # choose the residents | |
| label = "Choose the X variable to display", | |
| choices = c("Percent Adult Obese 2010", | |
| "Percent Adult Diabetic 2010", | |
| "Percent Poverty 2010", | |
| "Median household income, 2010", | |
| "Population, low access to store (%), 2010", | |
| "Grocery stores/1,000 pop, 2012", | |
| "Convenience stores/1,000 pop, 2012", | |
| "Fast-food restaurants/1,000 pop, 2012", | |
| "Full-service restaurants/1,000 pop, 2012", | |
| "Household food insecurity (%), 2010-12", | |
| "Farms with direct sales, 2007", | |
| "Farmers' markets/1,000 pop, 2013", | |
| "Vegetable farms, 2007", | |
| "High schoolers physically active (%), 2009", | |
| "Recreation & fitness facilities/1,000 pop, 2012", | |
| "% Population 65 years or older, 2010", | |
| "% Population under age 18, 2010"), | |
| selected = "Median household income, 2010") | |
| ), | |
| box(selectInput("var2", # choose the residents | |
| label = "Choose the Y variable to display", | |
| choices = c("Percent Adult Obese 2010", | |
| "Percent Adult Diabetic 2010", | |
| "Percent Poverty 2010", | |
| "Median household income, 2010", | |
| "Population, low access to store (%), 2010", | |
| "Grocery stores/1,000 pop, 2012", | |
| "Convenience stores/1,000 pop, 2012", | |
| "Fast-food restaurants/1,000 pop, 2012", | |
| "Full-service restaurants/1,000 pop, 2012", | |
| "Household food insecurity (%), 2010-12", | |
| "Farms with direct sales, 2007", | |
| "Farmers' markets/1,000 pop, 2013", | |
| "Vegetable farms, 2007", | |
| "High schoolers physically active (%), 2009", | |
| "Recreation & fitness facilities/1,000 pop, 2012", | |
| "% Population 65 years or older, 2010", | |
| "% Population under age 18, 2010"), | |
| selected = "Percent Obese 2009") | |
| ) | |
| ), | |
| box(width =12, plotlyOutput("trendPlot", height = 550)) | |
| ) | |
| ), | |
| tabItem(tabName = "predict", | |
| fluidRow( | |
| h2("Let's predict using multiple linear regression*:"), | |
| h3(htmlOutput("predtable")), | |
| column(width = 12, | |
| box( | |
| sliderInput("GROC", label = p("Grocery stores/1000 people, 2012"), | |
| min = rlow(data$GROCPTH12), | |
| max = rhi(data$GROCPTH12), value = | |
| valme(data$GROCPTH12)), | |
| sliderInput("Conv", label = p("Conveniences stores/1000 people, 2012"), | |
| min = rlow(data$CONVSPTH12), | |
| max = rhi(data$CONVSPTH12), value = | |
| valme(data$CONVSPTH12)), | |
| sliderInput("FF", label = p("Fast-food stores/1000 people, 2012"), | |
| min = rlow(data$FFRPTH12), | |
| max = rhi(data$FFRPTH12), value = | |
| valme(data$FFRPTH12)), | |
| sliderInput("Full", label = p("Full-service restaurants/1,000 pop, 2012"), | |
| min = rlow(data$FSRPTH12), | |
| max = rhi(data$FSRPTH12), value = | |
| valme(data$FSRPTH12)), | |
| sliderInput("LACCESS", label = p("Population, low access to store | |
| (%), 2010"), | |
| min = rlow(data$PCT_LACCESS_POP10), | |
| max = rhi(data$PCT_LACCESS_POP10), value = | |
| valme(data$PCT_LACCESS_POP10)), | |
| sliderInput("MEDHHIN", label = p("Median household income, 2010"), | |
| min = rlow(data$MEDHHINC10), | |
| max = rhi(data$MEDHHINC10), value = | |
| valme(data$MEDHHINC10)), | |
| sliderInput("PCT18", label = p("% Population under age 18, 2010"), | |
| min = rlow(data$PCT_18YOUNGER10), | |
| max = rhi(data$PCT_18YOUNGER10), value = | |
| valme(data$PCT_18YOUNGER10)), | |
| sliderInput("RECFAC", label = p("Recreation & fitness facilities/ | |
| 1,000 pop, 2012"), | |
| min = rlow(data$RECFACPTH12), | |
| max = rhi(data$RECFACPTH12), value = | |
| valme(data$RECFACPTH12)) | |
| ), | |
| box( | |
| sliderInput("FOODINS", label = p("Household food insecurity (%, | |
| three-year average), 2010-12*"), | |
| min = rlow(data$FOODINSEC_10_12), | |
| max = rhi(data$FOODINSEC_10_12), value = | |
| valme(data$FOODINSEC_10_12)), | |
| sliderInput("FARMRT",label = p("Farmers' markets/1,000 pop, 2013"), | |
| min = rlow(data$FMRKTPTH13), | |
| max = rhi(data$FMRKTPTH13), value = | |
| valme(data$FMRKTPTH13)), | |
| sliderInput("VEGFARM", label = p("Vegetable farms, 2007"), | |
| min = rlow(data$VEG_FARMS07), | |
| max = rhi(data$VEG_FARMS07), value = | |
| valme(data$VEG_FARMS07)), | |
| sliderInput("DIABETE", label = p("Adult diabetes rate, 2010"), | |
| min = rlow(data$PCT_DIABETES_ADULTS10), | |
| max = rhi(data$PCT_DIABETES_ADULTS10), value = | |
| valme(data$PCT_DIABETES_ADULTS10)), | |
| sliderInput("HSACT", label = p("High schoolers physically active (%), 2009"), | |
| min = rlow(data$PCT_HSPA09), | |
| max = rhi(data$PCT_HSPA09), value = | |
| valme(data$PCT_HSPA09), | |
| step = 0.1), | |
| sliderInput("POVRT", label = p("Poverty rate, 2010"), | |
| min = rlow(data$POVRATE10), | |
| max = rhi(data$POVRATE10), value = | |
| valme(data$POVRATE10)), | |
| sliderInput("PCT65", label = p("% Population 65 years or older, 2010"), | |
| min = rlow(data$PCT_65OLDER10), | |
| max = rhi(data$PCT_65OLDER10), value = | |
| valme(data$PCT_65OLDER10)) | |
| ) | |
| ), | |
| h2("Model fitting:"), | |
| p("Summary: As a preliminary prediction analysis, multiple linear regression was used | |
| on 17 variables of interest to predict obesity rates. Stepwise regression | |
| showed that at least 10 variables are significant. Basic diagnostics indicate | |
| model assumptions were not violated. 76% of the data was complete cases, while | |
| the rest had at least one NA. Only the complete cases were used in prediction."), | |
| h3("Coefficient table"), | |
| DT::dataTableOutput("coefs"), | |
| p(sigcodes), | |
| p(sumreg), | |
| h2("Appendix: Diagnostics"), | |
| dataTableOutput("rendvifs"), | |
| img(src = "Resvsfitted.jpeg"), | |
| img(src = "qqpot.jpeg"), | |
| img(src = "scaleloc.jpeg"), | |
| img(src = "leverage.jpeg"), | |
| img(src = "avplot1.jpeg"), | |
| img(src = "avplot2.jpeg") | |
| ) | |
| ), | |
| tabItem(tabName = "data", | |
| DT::dataTableOutput("tabdb")) | |
| ) | |
| ) | |
| )) |
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