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

Original


Source : https://howmuch.net/articles/world-most-admired-companies-2018


Objective

Objective : The World’s Most Valued Companies in 2018 (by Market Cap)

The data is a survey published as Fortune’s list of world’s most valued companies in the year 2018. It follows industry-wise classification for the top 50 companies, in terms of their market capitalisation. The market capitalisation is measured in terms of billions and forms the basis of comparison.The data is collected from surveys of executives and analysts in terms of largest companies by market capitalisation.

Target Audience

The data caters to the business enthusiasts/economists, jobseekers as well as investors who are interested in knowing industry-wise dominating companies.

Issues

The three major issues identified in the visualisation are as follows:

  • Plot Anatomy (Area & Size) : The basic aim of the visualisation is to compare the top 50 companies in terms of market capitalisation. The original visualisation serves the aim with the help of bubble chart. It represents the increment of market capitalisation through increasing size of bubbles/circles. The area is inferior to the position. It is hard to compare the figurative increase by looking at the bubbles.

  • Title : The title of the visualisation - World’s Most Admired Companies - is misleading. The title can mislead the audience into believing that market capitalisation is the measure for admiration/reputation of company and not its value.

  • Cluttering/Visual bombarment : The visual makes it harder for the audience to read the comapnies with relatively low market capitalisation as the bubble representing those companies are very small. The spread of insutries across graph makes it difficult for the reader to compare compare within industry.

Reference

*Data Reference : https://howmuch.net/articles/world-most-admired-companies-2018

Code

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

library(readxl)
library(ggplot2)

dataset <- read_excel("~/Desktop/Book3.xlsx")

p <- ggplot(data = dataset, aes(x= reorder(Company,Market_Cap), y= Market_Cap))+
  theme_classic()+
  geom_bar(stat= "identity", aes(fill = `Industry `), position= position_dodge()) +
    coord_flip() + facet_grid(rows = vars(`Industry `), scales = "free_y", space = "free_y", switch = "y") +
  theme(strip.placement = "outside", strip.background  = element_blank(),
        panel.border = element_blank(), strip.text.y = element_blank()) + labs(title = "World's Most Valued Companies in 2018 (by Market Cap, in $B)", x = "Company", y ="Market Capitalisation(in $B)")

p

Data Reference

*Code Reference : https://rstudio.com/wp-content/uploads/2015/03/ggplot2-cheatsheet.pdf

Reconstruction

The following plot fixes the main issues in the original.

  • We have tackled the major of comparison by plotting a bar graph which clearly shows difference between market capitalisation of different companies through its length.

  • We have made the title more informative - World’s Most Valued Companies in 2018 (by Market Cap).

  • With clear industry-wise classification in bar chart, it is easier to distinguish between companies.