index.Rmd

---
title: "COVID-19 Tracker"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
---

```{r setup, include=FALSE}
# Dependencies
library(flexdashboard)
# Functions
`%>%` <- magrittr::`%>%`
source("./dev/functions.R")
# Setting the data requirements 
df <- coronavirus::refresh_coronavirus_jhu()
load("./data/gis_codes.RData")
load("./data/gis_mapping.RData")

df2 <- df %>%
  dplyr::filter(location_type == "country",
                !is.na(location_code),
                data_type != "recovered_new") %>%
  dplyr::left_join(gis_codes %>% 
                     dplyr::select(-lat, - long) %>%
                     dplyr::filter(combined_key == country_region, 
                                               is.na(province_state)), by = c("location" = "combined_key")) %>%
  dplyr::left_join(continent_mapping %>% dplyr::select(continent_name, continent_code, iso2), by = "iso2")


d <- df2 %>% 
  dplyr::filter(location_type == "country",
                data_type == "cases_new") %>%
  dplyr::group_by(location, continent_name) %>%
  dplyr::summarise(total_cases = sum(value), .groups = "drop") %>%
  dplyr::mutate(perc = 100 * total_cases / sum(total_cases)) %>%
  dplyr::arrange(-total_cases) 

# Fix missing values
d$continent_name[which(d$location == "South Korea")] <- "Asia"
d$continent_name[which(d$location == "Kosovo")] <- "Europe"


df3 <- df %>% 
  dplyr::filter(location_type == "country",
                data_type != "recovered_new") %>%
  dplyr::group_by(date, data_type) %>%
  dplyr::summarise(total = sum(value), .groups = "drop") %>%
  tidyr::pivot_wider(names_from = data_type, values_from = total) 

df3$trend_new_cases <- (df3$cases_new + 
                        dplyr::lag(df3$cases_new,1) +
                        dplyr::lag(df3$cases_new,2) + 
                        dplyr::lag(df3$cases_new,3) +
                        dplyr::lag(df3$cases_new,4) + 
                        dplyr::lag(df3$cases_new,5) + 
                        dplyr::lag(df3$cases_new,6)) /7
df3$trend_deaths_cases <- (df3$deaths_new + 
                        dplyr::lag(df3$deaths_new,1) +
                        dplyr::lag(df3$deaths_new,2) + 
                        dplyr::lag(df3$deaths_new,3) +
                        dplyr::lag(df3$deaths_new,4) + 
                        dplyr::lag(df3$deaths_new,5) + 
                        dplyr::lag(df3$deaths_new,6)) /7

last_update <- paste("Last update: ", max(df$date), sep = "")
```

<script>
document.querySelector(".navbar-header > span.navbar-brand > span.navbar-author").innerHTML = "`r last_update`";
</script>

<style>
.navbar-author {
  position: absolute;
  right: 1rem;
}
</style>


# Summary

## Column {data-width="600"}

### Daily New Confirmed Cases - Worldwide

```{r}
highcharter::hchart(df3, "scatter", highcharter::hcaes(x = date, 
                                                       y = cases_new),
                    name = "Daily New Cases",
                    color = "rgba(69, 123, 157, 0.5)",
  showInLegend = TRUE) %>%
   highcharter::hc_tooltip(crosshairs = TRUE, pointFormat = "Total Cases: {point.cases_new}") %>%
   highcharter::hc_add_series(
    df3, type = "line",  highcharter::hcaes(x = date, 
                              y = trend_new_cases),
    color = "rgba(29, 53, 87, 1)",
    name = "Trend Line", 
    id = "trend",
    showInLegend = TRUE)   %>%
  highcharter::hc_plotOptions(
    line = list(
      color = "blue",
      marker = list(
        fillColor = "white",
        lineWidth = 2,
        radius=1,
        lineColor = NULL
      )
    )
  ) %>%
   highcharter::hc_legend( #Not in use, showInLegend = FALSE
    layout = "vertical",
    verticalAlign = "top",
    align = "right",
     floating = TRUE
  ) %>%
   highcharter::hc_xAxis(
    title = list(text = ""),
    gridLineWidth = 0,
    dateTimeLabelFormats = list(day = '%d/%m/%Y'),
    type = "datetime",
    reversed = FALSE
    ) %>%
   highcharter::hc_yAxis(
    title = list(text = "Cases"),
    gridLineWidth = 0,
    reversed = FALSE
    ) %>%
    # highcharter::hc_title(
    # style = list(color = highcharter::hex_to_rgba("black", 0.5)),
    # text = "Daily New Confirmed Cases - Worldwide"
    # ) %>%
  # highcharter::hc_subtitle(
  #   style = list(color = hex_to_rgba("black", 0.5)),
  #   text = "Source: John Hopkins University"
  #   ) %>%
  highcharter::hc_caption(text = "Trend line calculated by using 7-days moving average <br>Source: Center for Systems Science and Engineering (CSSE) at Johns Hopkins University") %>%
    highcharter::hc_tooltip(
    crosshairs = TRUE,
    backgroundColor = "#F0F0F0",
    shared = TRUE, 
    borderWidth = 5
    ) 
```

### Daily Death Cases - Worldwide

```{r}
highcharter::hchart(df3, "scatter", highcharter::hcaes(x = date, 
                                                       y = deaths_new),
                    name = "Daily Death Cases",
                    color = "rgba(214, 40, 40, 0.5)",
  showInLegend = TRUE) %>%
   highcharter::hc_tooltip(crosshairs = TRUE, pointFormat = "Total Cases: {point.deaths_new}") %>%
   highcharter::hc_add_series(
    df3, type = "line",  highcharter::hcaes(x = date, 
                              y = trend_deaths_cases),
    color = "rgba(29, 53, 87, 1)",
    name = "Trend Line", 
    id = "trend",
    showInLegend = TRUE)   %>%
  highcharter::hc_plotOptions(
    line = list(
      color = "blue",
      marker = list(
        fillColor = "white",
        lineWidth = 2,
        radius=1,
        lineColor = NULL
      )
    )
  ) %>%
  highcharter::hc_legend( #Not in use, showInLegend = FALSE
    layout = "vertical",
    verticalAlign = "top",
    align = "right",
     floating = TRUE
  ) %>%
   highcharter::hc_xAxis(
    title = list(text = ""),
    gridLineWidth = 0,
    dateTimeLabelFormats = list(day = '%d/%m/%Y'),
    type = "datetime",
    reversed = FALSE
    ) %>%
   highcharter::hc_yAxis(
    title = list(text = "Cases"),
    gridLineWidth = 0,
    reversed = FALSE
    ) %>%
    # highcharter::hc_title(
    # style = list(color = highcharter::hex_to_rgba("black", 0.5)),
    # text = "Daily Death Cases - Worldwide"
    # ) %>%
  # highcharter::hc_subtitle(
  #   style = list(color = hex_to_rgba("black", 0.5)),
  #   text = "Source: John Hopkins University"
  #   ) %>%
  # highcharter::hc_caption(text = "Trend line calculated by using 7-days moving average <br>Source: Center for Systems Science and Engineering (CSSE) at Johns Hopkins University") %>%
  #   highcharter::hc_tooltip(
  #   crosshairs = TRUE,
  #   backgroundColor = "#F0F0F0",
  #   shared = TRUE, 
  #   borderWidth = 5
  #   ) %>%
  highcharter::hc_caption(
    text = "Trend line calculated by using 7-days moving average <br>Source: Center for Systems Science and Engineering (CSSE) at Johns Hopkins University", 
    useHTML = TRUE
    ) 
```

## Column {data-width="400"}

### Distribution of Total Cases by Country/Continent

```{r}
pb <- highcharter::hchart(d %>% dplyr::filter(continent_name != "Antarctica"), "packedbubble", highcharter::hcaes(name = location, value = total_cases, group = continent_name)) %>% 
  highcharter::hc_tooltip(
    useHTML = TRUE,
    pointFormat = "<b>{point.name}:</b> {point.value}"
  )

q95 <- as.numeric(quantile(d$total_cases, .95))

pb %>%
  highcharter::hc_plotOptions(
    packedbubble = list(
      maxSize = "150%",
      zMin = 0,
      layoutAlgorithm = list(
        gravitationalConstant =  0.05,
        splitSeries =  TRUE, # TRUE to group points
        seriesInteraction = TRUE,
        dragBetweenSeries = TRUE,
        parentNodeLimit = TRUE
      ),
      dataLabels = list(
        enabled = TRUE,
        format = "{point.name}",
        filter = list(
          property = "y",
          operator = ">",
          value = q95
        ),
        style = list(
          color = "black",
          textOutline = "none",
          fontWeight = "normal"
        )
      )
    )
  ) 
pb
```

# About

**The COVID-19 Tracker Dashboard**

This dashboard is part of the [Deploy Flexdashboard on Github Pages with Github Actions and Docker](https://github.com/RamiKrispin/deploy-flex-actions) tutorial. This tutorial provides a step-by-step guide and a template for deploying and refreshing a [flexdashboard](https://pkgs.rstudio.com/flexdashboard/) dashboard on [Github Pages](https://pages.github.com/) with [Docker](https://www.docker.com/) and [Github Actions](https://github.com/features/actions).

**Data**

The input data for this dashboard is the [coronavirus](https://github.com/RamiKrispin/coronavirus) R package. The data and dashboard is refreshed on a daily bases. The raw data was pulled from the Johns Hopkins University Center for Systems Science and Engineering (JHU CCSE) Coronavirus [repository](https://github.com/CSSEGISandData/COVID-19).

**Packages**

The dashboard uses the following packages:

-   Dashboard - [flexdashboard](https://pkgs.rstudio.com/flexdashboard/index.html)
-   Data - [coronavirus](https://github.com/RamiKrispin/coronavirus)
-   Data visualization - [highcharter](https://jkunst.com/highcharter/index.html)
-   Utility - [dplyr](https://dplyr.tidyverse.org/), [tidyr](https://tidyr.tidyverse.org/), [lubridate](https://lubridate.tidyverse.org/)

**License**

This tutorial is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-nc-sa/4.0/) License.

**Connect**

For any question or feedback, you can either open an [issue](https://github.com/RamiKrispin/deploy-flex-actions/issues) or contact me on [Twitter](https://twitter.com/Rami_Krispin).