Hometask: VizQuiz

COVID-19 is a challenge of the year even in statistical visualization. One of the artlicles published on Wikipedia is dedicated to Statistics of the COVID-19 pandemic in the United States. At the above side of the web-page the following graph with the reference to Statista is presented:

This picture can be more informative, while there is a lack of representation that affect information perception.

• We have to focus more if we want to compare numbers of excess deaths;
• There is a combination of absolute and relative values that cause a misleading;
• Misunderstanding of categories - United Stated is depicted together with its cities.

Not changing a message of the graph, the following way to represent the same data is suggested:

library(tidyverse)
library(tibble)

# creating data frame
data <- data.frame(city = c("Michigan", "New York State",
                            "New Your City", "New Jersey", "Maryland",
                            "United States", 
                            "Michigan", "New York State",
                            "New Your City", "New Jersey", "Maryland",
                            "United States"), 
                   Case = c("excess deaths", "excess deaths", "excess deaths", 
                            "excess deaths", "excess deaths", "excess deaths",
                            "reported","reported", "reported", 
                            "reported", "reported", "reported"),
                   number = c(700, 1700, 6300, 2200, 300, 15400, 
                              539, 1020, 2520, 836, 54, 8162))

# changing data types
data$city <- factor(data$city, levels = c("Michigan", "New York State",
                            "New Your City", "New Jersey", "Maryland",
                            "United States"))
data$Case <- factor(data$Case, levels = c("reported", "excess deaths"))
data$number <- as.numeric(data$number)

# plotting
ggplot() + geom_col(data = data, aes(x = city, y = number, 
                                     fill = Case), 
                    width = 0.8,
                    color = "dimgray", 
                    position = "dodge", 
                    alpha = 0.9) + 
  scale_x_discrete(labels = c("Michigan", "New York State",
                              "New Your City", "New Jersey", "Maryland",
                              expression(bold("United States")))) +
  geom_text(
    aes(x = data$city, 
        y = data$number, 
        label = data$number, 
        group = data$Case),
    position = position_dodge(width = 1),
    hjust = -0.3, 
    vjust = -0.05,
    size = 3, 
    color = "dimgray",
    fontface = 3) + 
  coord_flip() + 
  ylim(0, 18000) + 
  xlab(" ") + ylab("Absolute values") +
  ggtitle("U.S. COVID-19 Deaths Could Be Far Higher Than Reported") +
  theme(legend.position = "bottom", legend.title = element_blank(),
        plot.background = element_rect(fill = "#F4F8FB"),
        legend.background = element_rect(fill = "#F4F8FB"),
        strip.background = element_rect(fill = "#F4F8FB"),
        panel.border = element_rect(color = NA, fill = NA),
        panel.background = element_rect(fill = "#F4F8FB"),
        plot.title = element_text(hjust = 0.5)) +
  scale_fill_manual(values = c("#80080A", "#E97790"))

Maybe this plot is not so eye-catching as its previous version, the stated above issues are solved.