This is a task for the data science coursera course about developing data products for week 4.

Shiny app: https://courseprojectweek3.shinyapps.io/week4courseproject/ Presentation: https://github.com/JannekeSchipper/Course-9—Developing-Data-products

Top 10 countries who use the most plastic in the world

##   X      Entity Code Plastic GDPPC Literacy InfantMortality Agriculture
## 1 1      Kuwait  KWT   0.686 28985    0.963             7.1       0.004
## 2 2      Guyana  GUY   0.586  4127    0.885            31.5       0.182
## 3 3    Barbados  BRB   0.570 15360    0.997             8.8       0.017
## 4 4 Saint Lucia  LCA   0.522  7764    0.901            11.2       0.029
## 5 5     Germany  DEU   0.485 41219    0.990             3.4       0.007
## 6 6 Netherlands  NLD   0.424 44433    0.990             3.6       0.018
##   Population NetMigration
## 1    3892000         -2.0
## 2     767085         -6.4
## 3     284215          1.6
## 4     184999         -2.7
## 5   81410000          1.5
## 6   16940000          1.9

library(shiny)
# Define UI for application that draws a histogram
shinyUI(fluidPage(
  # Application title
  titlePanel("Top 10 Countries plastic useage"),
  # Sidebar with a slider input for number of bins 
  sidebarLayout(
    sidebarPanel(
      selectInput("variable", "Variable:", 
                  c("Plastic" = "Plastic",
                    "Gross Domestic Product Per Capita" = "GDPPC",
                    "Literacy" = "Literacy",
                    "Infant Mortality" = "InfantMortality",
                    "Population" = "Population"))
    ),
    # Show a plot of the generated distribution
    mainPanel(
       plotOutput("distPlot")
    )
  )
))

library(shiny)
library(plotly)
library(ggplot2)
library(dplyr)
dataset <- read.csv("./top10.csv")
top10 <- dataset%>%
  top_n(10, Plastic)%>%
  arrange(desc(Plastic))
# Define server logic required to draw a histogram
shinyServer(function(input, output) {
  formulaText <- reactive({
    paste("courty vs ", input$variable)
  })
  output$caption <- renderText({
    formulaText()
  })
  output$distPlot <- renderPlot({
    ggplot(top10, aes_string(y=input$variable, x="Entity", fill = "Entity")) + 
      geom_bar(stat = "identity", width = 0.7) +
      coord_flip() +
      theme(legend.position="none") +
      labs(title = "Top 10 Countries plastic usage", x = "Country")
  })
})