New Zealand coronavirus/COVID-19 case chart as Shiny app. Published at https://bartj.shinyapps.io/covid19/.

app.R

library(shiny)
library(tidyverse)
library(lubridate)
library(plotly)
library(scales)

ui <- shiny::fillPage(
  
  titlePanel("Coronavirus in NZ"),
  
  mainPanel(
    plotlyOutput(outputId = "casesOverTime")
  )
)

server <- function(input, output) {
  output$casesOverTime <- renderPlotly({
    url <- 'https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv'
    raw <- readr::read_csv(url, col_types = cols(
      .default = col_integer(),
      `Province/State` = col_character(),
      `Country/Region` = col_character(),
      Lat = col_double(),
      Long = col_double()
    ))
    
    nz <- raw %>% 
      filter(`Country/Region` == "New Zealand") %>% 
      select(-`Province/State`, -Lat, -Long) %>% 
      pivot_longer(-`Country/Region`) %>% 
      mutate(DateNzLocal = lubridate::parse_date_time(name, orders="mdy") %>% as.Date) %>% 
      rename(NumberOfCases = value) %>% 
      select(DateNzLocal, NumberOfCases)
    
    plot <- ggplot(nz) +
      geom_line(aes(x = DateNzLocal, y = NumberOfCases)) +
      labs (
        x = "Date, NZ",
        y = "Cumulative number of cases",
        title = "Number of positive COVID-19 cases in New Zealand",
        subtitle = "Data source: https://github.com/CSSEGISandData"
      ) +
      scale_y_continuous(breaks = pretty_breaks())
    
    ggplotly(plot)
  })
}

shinyApp(ui, server)