Assignment 2

Deconstruct, Reconstruct Web Report

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

Original

Source: Business Insider (2013).

Objective

The objective of the visualisation is to display the significant size of large fast food chains and the comparison with the GDP of countries. Its target audience is people who buy fast food on a regular basis, and is to show how much we are reliant on fast food.

The visualisation chosen had the following three main issues:

Colour issues - The colours in the diagram are distracting given that every logo has different colours.

Perception issues - Furthermore, the country overlaps with the two of the other fast food chain logos and the comparison is not apparent.

Perception issues - Burger King has three times the sales as Starbucks however the width and size of the Burger King logo is misleading.

Reference

• Business Insider. (2013). 27 Worst Charts of all time. Retrieved September 23, 2019, from Business Insider website: https://www.businessinsider.com.au/the-27-worst-charts-of-all-time-2013-6?r=US&IR=T#burger-king-has-3-times-as-much-in-sales-than-starbucks-it-makes-sense-that-its-three-times-taller-but-the-fact-that-its-area-is-nine-times-that-of-starbucks-shows-why-this-chart-exemplifies-everything-that-is-wrong-with-charts-that-try-to-incorporate-cutesy-graphics-2

Code

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

library(ggplot2)
fast_food <- data.frame(fast_food_chains = c("McDonalds", "Burger King", "Wendys", "KFC", "Pizza Hut", "Taco Bell", "Starbucks"),
                        Value = c(41000000000, 11300000000, 9400000000,8200000000,8000000000,4300000000,4100000000))

#divide by billion to remove zeros
fast_food$Value <- (fast_food$Value)/1000000000

p1 <- ggplot(fast_food, aes(x = reorder(fast_food_chains,-Value), y = Value)) 

p2 <- p1 + geom_bar(stat = "identity", fill = "blue") + theme_minimal() + theme(axis.text.x=element_text(angle=45,hjust=1)) +
  labs(title = "Comparison of Fast Food sales with GDP of small countries",
       y = "Value ($ billions)",
       x = "Fast food chains") + geom_text(aes(label=round(Value,2)), 
                                           vjust = -0.5,size = 3)+ geom_hline(yintercept = 12.73,
                                                                              colour = "red") + annotate("text",
                                                                                                         x=6, 
                                                                                                         y=12.73, #Average GDP of bottom 100 countries 
                                                                                                         vjust = -1,
                                                                                                         label =
                                                                                                           "Average GDP of bottom 100 countries")

Data Reference

• Worldometers. (2018). GDP by Country. Retrieved September 23, 2019, from Worldometer website: https://www.worldometers.info/gdp/gdp-by-country/

Reconstruction

The following plot fixes the main issues in the original.