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

Original


Source: https://en.wikipedia.org/wiki/File:Operatingsystem_market_share.svg


Objective

The usage share of operating systems is the percentage of the operating systems used in computing devices.There are 3 big personal computing platforms, two of which claim over 1.4 billion users, Android and Windows. Another one, Apple’s iOS and macOS, combined have over 1 billion users.
So considering the depicted visualization of Market Share usage of few years ago, The visualisation chosen had the following three main issues:

-PLOT Selection * The spaghetti line plots made it difficult to address the major factor in the visualization as it cramped up and looked very unorganised.

-Perceptional Point of view * The splitting up of plots in order to address the percentage of the other OS market share made it messy and degraded the visual perspective. Had it been for a client meet, it would be a mess to explain and catch up with each of the plotted OS line.

  • Perspective
  • The practical point of view could have been improved in terms of visualising the data as the date bandwith is of 6 months in the visualization. This could be increased to a year and the colour combination used has made it difficult to point out each category.

Reference

Code

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

library(dplyr)
library(readr)
library(reshape2)
library(ggplot2)
library(RColorBrewer)
library(scales)
os <- read_csv("C:/Users/amand/Downloads/DataViz Assignments/DataViz Assign2/os.csv")



## Adding date to the columns section


os$date<-as.Date(paste(os$month,os$year, 1),"%B %Y %e")



## Assigning OS into columnar chart and creating a column for family. Later assigning family to each variable


os<-melt(os, id=c("month","year","date"))
os$family<-NA


os[os$variable=="Win10",]$family<-"Windows PC"
os[os$variable=="Win8",]$family<-"Windows PC"
os[os$variable=="Win7",]$family<-"Windows PC"
os[os$variable=="Vista",]$family<-"Windows PC"
os[os$variable=="WinXP",]$family<-"Windows PC"
os[os$variable=="NT",]$family<-"Windows Server"
os[os$variable=="Linux",]$family<-"Linux"
os[os$variable=="Mac",]$family<-"Apple"
os[os$variable=="Chrome OS",]$family<-"Linux"
os[os$variable=="Mobile",]$family<-"Other";
os[os$variable=="W2000",]$family<-"Windows PC"
os[os$variable=="W2003",]$family<-"Windows Server"
os[os$variable=="Win98",]$family<-"Windows PC"
os[os$variable=="Win95",]$family<-"Windows PC"

# Order factors
os$variable<-factor(os$variable, levels =
                      c("Win10", "Win8", "Win7", "Vista",
                        "WinXP", "W2000", "Win98", "Win95",
                        "W2003", "NT",
                        "Mac", "Linux", "Chrome OS", "Mobile"))





## Plotting the final data that is the reconstructed visualization of the Operating System Market Share from the year of 2003 until 2016:


plot1 <- ggplot(os,aes(date,value))+
  geom_area(position="fill",aes(fill=variable),color="black",alpha=.75)+
  scale_fill_manual("Operating\nSystem",values=c(
        # Windows PCs
        rev(brewer.pal(8,"Blues")),
        # Windows Servers
        rev(brewer.pal(3,"Greens")[2:3]),
        # Apple
        brewer.pal(3,"Purples")[3],
        # Linux family
        rev(brewer.pal(3,"Oranges")[2:3]),
        # Other
        brewer.pal(3,"Greys")[2]),
    labels=c("Windows 10", "Windows 8", "Windows 7", "Windows Vista",
             "Windows XP", "Windows 2000", "Windows 98", "Windows 95",
             "Windows 2003", "Windows NT*",
             "Macintosh", "Linux", "Chrome OS", "Mobile"))+
  scale_y_continuous(labels=scales::percent)+
  labs(title="Operating System Market Share Reconstructed Visualization",
       subtitle="----------------------",
       x="",
       y="Market Share",
       caption="* after the year of 2012, \"Windows NT\" is clubbed as the following Windows Server operating systems (NT, 2000, 2003, and 2008)")+
  theme_bw()
ggsave("OS Share.png",height=9,width=16,dpi=120,type="cairo-png")

Data Reference

The exact image that is being reconstructed is : https://en.wikipedia.org/wiki/File:Operatingsystem_market_share.svg

The data that has been used is from : https://www.w3schools.com/browsers/browsers_os.asp

Reconstruction

The following plot fixes the main issues in the original.

Conclusion

As there were a lot of updates and developments in each of the personal computing platform, I believed it will be right to display the Market Share that was consumed during the years mentioned in the dataset.

I wanted to make the following improvements:

Group OS families by color. Force an area plot. Expanding the data set to most recent available.

This helped in understanding how Windows XP was the game changer during the era of 2000’s to 2012. Every decade we tend to see such game changers as technology breaks through numerous barriers.