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

Original


Source: Matheson A (2017).


Objective

Pizzas are the easiest meals for the UK residents to cook, order takeaways, and order in the restaurants. The pie chart developed by Matheson (2017), helps UK residents to understand what are their favorite toppings when ordering and eating pizzas. It also helps the cooks to understand the eating favor of the UK residents, and prepare the perfect menu. Besides, it helps the business owner in retail and food to target the restaurant market in the UK and understand customers eating habits.

Although this interesting pie chart had attracted three major groups of target audiences, UK citizens, cooks, and business owners in retail and food, the pie chart had many issues in data visualisation and they need to be fixed.

The Pizza Pie Chart had the following three main issues:

  1. Incorrect Proportioning: When describing the number of people who like the toppings, the proportions in the pie chart are incorrectly used. For example, the proportions of 56% of the people liked Pepperoni having the same proportion size as 65% of the people liked Mushrooms. Also, there are three proportions containing more than one element, such as the people who like Pineapple and Ham are in one proportion. The incorrectly used proportions in the pie chart make the reader confused in understanding, and hard to make comparisons between other variables.

  2. Misleading Colouring: The peppers’ colour is hard to see in the pizza, the reader may first recognise the red thing in the pizza is pepper, which is misleading. Also, the Sweetcorn and Pineapple, Tomato and Pepperoni have almost the same colour, which may let the reader hard to understand and they need to spend time comparing with food, it is unprofessional. Besides, the whole pie chart describes the color of the pizza as looking almost red color, and the food with other colours are few.

  3. Incorrect and misleading in adding detailed descriptions: The detail description, located below the pie chart, should only contain the information that the pie chart cannot be described, and the attributes are unrelated to the pie chart. However, there are 8 toppings described in detail descriptions, which is incorrect, and they should be described in the pie chart. Only the information indicates “2% of people say they only like Margherita pizzas” is correctly used.

Reference

Code

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

# Loading required libraries
library(ggplot2)
library(colourpicker)
library(dplyr)

# Creating Data Frame
Pizzas <- data.frame(Name = c("Pappers", "Pepperoni","Olives", "Tomato(as a topping)", "Mushrooms", 
                               "Ham", "Pineapple", "Spinach", "Bacon", "Sweetcorn",
                               "Onions", "Chicken", "Beef", "Chillies", "Jalapenos", 
                               "Pork", "Tuna", "Anchovies", "Other"),
                      Percentage = c(60, 56, 33, 51, 65, 
                                     61, 42, 26, 49, 42,
                                     62, 56, 36, 31, 30,
                                     25, 22, 18, 2))

# Loading Colours
bar_color <- c("#AC3931ff", "#B44D36ff", "#BB603Aff", "#C98642ff", "#D7AD4Aff",
         "#E5D352ff", "#DFDD5Fff", "#D9E76Cff", "#90FCF9ff", "#7AD8E5ff",
         "#63B4D1ff", "#7699D4ff", "#8571C8ff", "#9448BCff", "#6E2689ff",
         "#480355ff", "#6EB29Eff", "#9FD356ff", "#6A8147ff")

# Creating New Bar Chart
p1 <- ggplot(arrange(Pizzas, Percentage), aes(x = Percentage, y = reorder(Name, Percentage)))
p1 <- p1 + geom_col(color = bar_color, fill = bar_color) +   
           geom_text(aes(label=Percentage, x = 0), fill = "gray", hjust = "top", family = "Georgia") + 
           labs(title = "The UK's most liked pizza topping", 
                caption = "Author: Matheson A. (2017)
                Source: The Sun
                * Other means people only like Margherita pizzas",
                x = "Number of People Liked (Percentage %)", y = "Name of the toppings")

# Setting background colour
background <- "#EFF1F0"

# Adjust Colour, Theme and Clean-up
p1 <- p1 +
    theme_gray() +
    theme(plot.background = element_rect(fill = background),
        panel.background = element_rect(fill = background),
        legend.background = element_rect(fill = background),
        title = element_text(face = "bold"),
        legend.title = element_blank())

Data Reference

Reconstruction

The following plot fixes the main issues in the original.

Description: It is better to use the bar chart to describe the UK’s most liked pizza topping, as all the names of the toppings can be found in the bar chart, and they can compare with each other. The detailed information described at the bottom of the chart is easy to understand and the chart had include the author and source as references.