Featured in this medium article: "A Beginner’s Guide to Creating a Corona “Dashboard” (Part 1)" https://medium.com/@jonas.schroeder1991/a-beginners-guide-to-creating-a-corona-dashboard-3553b01d8d44

Corona Dashboard Part 1.R

# Data gathered from European Center for Disease Prevention and Control
# https://www.ecdc.europa.eu/en/publications-data/download-todays-data-geographic-distribution-covid-19-cases-worldwide
# Note: Number of cases per day may differ from other sources; cases might be moved from one day to another
# Author: Jonas Schröder https://medium.com/@jonas.schroeder1991

library(readxl)
library(httr)
library(tidyverse)
library(dplyr)
library(ggpubr)

# Define date of data pull
url <- paste("https://www.ecdc.europa.eu/sites/default/files/documents/COVID-19-geographic-disbtribution-worldwide-", "2020-03-22", ".xlsx", sep = "")

# DL and read data set
GET(url, authenticate(":", ":", type="ntlm"), write_disk(tf <- tempfile(fileext = ".xlsx")))
data <- read_excel(tf)

#------------------------------------------------------------------------------------------------------------------------------
# VISUALIZE GROWTH PER DAY AND COUNTRY
#------------------------------------------------------------------------------------------------------------------------------

# China
data_china <- filter(data, data$GeoId=="CN")

ggplot(data_china, aes(x=DateRep, y=Cases)) +
  geom_point(color = "darkred") +
  geom_smooth(method="auto", se=T, color = "darkred") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("China: New Cases per Day")


ggplot(data_china) +
  geom_line(aes(rev(DateRep), cumsum(Cases[order(Cases)])), color = "darkred") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("China: Cummulative Cases")


# Spain
data_spain <- filter(data, data$GeoId=="ES")
data_spain <- filter(data_spain, data_spain$DateRep > "2020-02-20")

cpd_spain <- ggplot(data_spain, aes(x=DateRep, y=Cases)) +
  geom_point(color = "darkorange") +
  geom_smooth(method="auto", se=T, color = "darkorange") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Spain: New Cases per Day")


ggplot(data_spain) +
  geom_line(aes(rev(DateRep), cumsum(Cases[order(Cases)])), color = "darkorange") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Spain: Cummulative Cases")


# France
data_france <- filter(data, data$GeoId=="FR")
data_france <- filter(data_france, data_france$DateRep > "2020-02-20")

cpd_france <- ggplot(data_france, aes(x=DateRep, y=Cases)) +
  geom_point(color = "blue") +
  geom_smooth(method="auto", se=T, color = "blue") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("France: New Cases per Day")


ggplot(data_france) +
  geom_line(aes(rev(DateRep), cumsum(Cases[order(Cases)])), color = "blue") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("France: Cummulative Cases")


# Germany
data_germany <- filter(data, data$GeoId=="DE")
data_germany <- filter(data_germany, data_germany$DateRep > "2020-02-20")

cpd_germany <- ggplot(data_germany, aes(x=DateRep, y=Cases)) +
  geom_point(color = "black") +
  geom_smooth(method="auto", se=T, color = "black") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Germany: New Cases per Day")


ggplot(data_germany) +
  geom_line(aes(rev(DateRep), cumsum(Cases[order(Cases)])), color = "black") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Germany: Cummulative Cases")


# Italy
data_italy <- filter(data, data$GeoId=="IT")
data_italy <- filter(data_italy, data_italy$DateRep > "2020-02-20")

cpd_italy <- ggplot(data_italy, aes(x=DateRep, y=Cases)) +
  geom_point(color = "darkgreen") +
  geom_smooth(method="auto", se=T ,color = "darkgreen") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Italy: New Cases per Day")


ggplot(data_italy) +
  geom_line(aes(rev(DateRep), cumsum(Cases[order(Cases)])), color = "darkgreen") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Italy: Cummulative Cases")


# Country comparison
cpd_comparison_1 <- ggplot() +
  geom_line(data=data_italy, aes(x=DateRep, y=Cases, color="Italy")) +
  geom_line(data=data_spain, aes(x=DateRep, y=Cases, color="Spain")) +
  geom_line(data=data_germany, aes(x=DateRep, y=Cases, color="Germany")) +
  geom_line(data=data_france, aes(x=DateRep, y=Cases, color="France")) +
  scale_color_manual(values = c(
    'Italy' = 'darkgreen',
    'Spain' = 'darkorange',
    'Germany' = 'black',
    'France' = 'blue')) +
  labs(color = 'Country') +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("Country Comparison: New Cases per Day") +
  theme(
    legend.position="right",
    axis.title = element_text(size=12),
    axis.text = element_text(size=12),
    plot.title = element_text(size=14),
    legend.title = element_text(size=12),
    legend.text = element_text(size=10)
    )

cpd_comparison_2 <- ggplot() +
  geom_smooth(data=data_italy, aes(x=DateRep, y=Cases), color="darkgreen", method = "loess") +
  geom_smooth(data=data_spain, aes(x=DateRep, y=Cases), color="darkorange", method = "loess") +
  geom_smooth(data=data_germany, aes(x=DateRep, y=Cases), color="black", method = "loess") +
  geom_smooth(data=data_france, aes(x=DateRep, y=Cases), color="blue", method = "loess") +
  xlab("Date") +
  ylab("Cases") +
  ggtitle("New Cases per Day (Interpolated)") +
  theme(
    legend.position="right",
    axis.title = element_text(size=12),
    axis.text = element_text(size=12),
    plot.title = element_text(size=14),
    legend.title = element_text(size=12),
    legend.text = element_text(size=10)
  )

ggplot() +
  geom_line(data=data_italy, aes(x=rev(DateRep), y=cumsum(Cases[order(Cases)]), color = "Italy")) +
  geom_line(data=data_germany, aes(x=rev(DateRep), y=cumsum(Cases[order(Cases)]), color = "Germany")) +
  geom_line(data=data_spain, aes(x=rev(DateRep), y=cumsum(Cases[order(Cases)]), color = "Spain")) +
  geom_line(data=data_france, aes(x=rev(DateRep), y=cumsum(Cases[order(Cases)]), color = "France")) +
  xlab("Date") +
  ylab("Cases") +
  scale_color_manual(values = c(
    'Italy' = 'darkgreen',
    'Spain' = 'darkorange',
    'Germany' = 'black',
    'France' = 'blue')) +
  theme(
    legend.position="right",
    axis.title = element_text(size=12),
    axis.text = element_text(size=12),
    plot.title = element_text(size=14),
    legend.title = element_text(size=12),
    legend.text = element_text(size=10)
  ) +
  ggtitle("Country Comparison: Total Number of Cases (Cumulative)")


# Merge plots to dashboard
part1 <- ggarrange(cpd_italy, cpd_spain, cpd_germany, cpd_france, align="hv")
part2 <- ggarrange(cpd_comparison_2, cpd_comparison_1, ncol=2, align="h")
ggarrange(part1, part2, nrow=2, heights=c(2,3), align="hv")