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

Original


Source: Statistica (2020)


Objective

The original data visualisation was created to showcase the top ten richest people on the planet on the basis of their net worth. The focus of this visualization was to consider another prespective of analysing the top richest people other than their net worth.

The visualisation chosen had the following three main issues:

  • Since the purchasing power of different countries are not the same, the metric of net worth based on US dollars is not a universal indicator
  • Since the dataset contains the countries of origin of the billionaires it is crucial to include a world map based graph.
  • Sorting without PP and wealth parity is crucial

Reference

Code

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

library(tidyverse)
library(plotly)
data <- read_csv("C:/Users/sande/OneDrive/Desktop/rmit/billionaires.csv")

#data ＜- Richest %＞% mutate( net_worth = factor(net_worth),
             #             Model = rownames(Richest))

# Basic bubble plot in ggplot2

plot1 ＜- data %＞% ggplot(aes(x = name, y = age, size = net_worth)) +
         geom_point(alpha = 0.5) 

plot1

# Bubble plot with color and custom size

plot2 ＜- data %＞% ggplot(aes(x = name, y = age, size = net_worth, 
                              label = Model)) +
         geom_point(alpha = 0.5) +
         scale_size(range = c(.1, 15))

#plot2

Data Reference

Reconstruction

The following plot fixes the main issues in the original.

  1. The plot shows the wealth disparity based on the net worth they possess.
  2. The age is shown which is also an indicator for future progress