Click the Original, Code and Reconstruction tabs to read about the issues and how they were fixed.

Original


Source: ESPNcricinfo Ltd (2019).


Objective Objective of the original data visualization is to present what percentage of a teams score was scored by their top scorer in the ICC Wordl Cup 2019. The targeted audiance in this case is the cricket fanatics.

The visualisation chosen had the following three main issues:

  • Failure to answer a practical question: The visualization goes by the title “THE WORLD CUP’S BIG GUNS % OF TEAMS’ RUNS SCORED BY TOP SCORERS” but fails to give any information on what teams these players play for.

  • Deceptive methods: Doughnut charts can be used when the data adds up to 100%. But the data in the given visualization does not add up to a meaningful whole.

  • Perceptual/color issue: Similar shades of same color have been used which don’t help in differentiation. Also, because the given stats represent same aspect of an idea, a bar chart with uniform colors will be helpful.

Reference

Code

The following code was used to fix the issues identified in the original.

library(ggplot2)

player <- c("Williamson", "Rohit", "Shakib", "Warner", "Babar", "Du Plessis",
            "Pooran", "Root", "Kushal Perera", "Rahmat Shah")
team <- c("New Zealand", "India", "Bangladesh", "Australia","Pakistan", 
          "South Africa", "West Indies", "England", "Sri Lanka", "Afghanistan")
percentage <- c(30.23,29.05,28.25,25.02,24.51,21.06,20.01,19.07,18.16,14.8)
p_labels <- c("30.23%","29.05%","28.25%","25.02%","24.51%","21.06%","20.01%",
              "19.07%","18.16%","14.8%")

df <- data.frame(player,team,percentage,p_labels)

# Barplot
p1 <- ggplot(df, aes(x=reorder(player, percentage), y=percentage)) + 
      geom_bar(stat = "identity") +
      geom_text(aes(label = p_labels),hjust = 1.1, color = "white") +
      geom_text(aes(label = team),position = position_stack(vjust = 0.5), color = "white") +
      labs(title = "The World Cup's big guns % of teams’ runs scored by top scorers", 
        x = "Players", y = "Players' contribution in Percentages % ") + 
      coord_flip()

Data Reference

Reconstruction

The following plot fixes the main issues in the original.