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

Original


Source: Publisher Distribution by Yearly Number of Game and Sales.


Objective

The following information refers to the overall sale of virtual games in previous years, segmented by game publishers. The graphs show the increase in total retail sales since 1983. Essentially, it reveals that in 2006, consumers paid over $200 million on virtual gaming, a staggering increase from 1983. The figure represents the highest level in at least two decades. The visualization was created to attract various game publishers in order to enhance their sales and customer demand for virtual games.

The visualization chosen had the following three main issues:

  • Given the aforementioned image, the legend suggests that understanding and reading the data will be complicated. On the y axis, the circles-shaped graphics appear to be overlapping, which makes it difficult for readers to interpret the analysis report.
  • Deception: There is insufficient data for visualization from 1983 to 1989. A list of other game publishers is included in the data set. This indicates that there is a problem with data integrity.
  • The size of the circle defines the number of games, but the audience may not understand the exact count by looking at the size of the circle.

Reference

Code

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

# Packages Used for the report:

library(readr)
library(gdata)
library(magrittr)
library(dplyr)
library(tidyr)
library(ggplot2)
library(ggthemes)

## Setting Directory

setwd("C:/Users/CLOUD/Downloads/Compressed")

## Importing Dataset from the Directory

Vgames <- read.csv("vgsales.csv")

## Data Manipulation

Vgames1 <- Vgames %>% select(Year,Publisher,Global_Sales) %>% filter(Publisher %in% c("EA Games","Konami DE","Namco","Nintendo","Sony CE"))

Vgames1$Publisher <- factor(Vgames1$Publisher, levels = c("EA Games","Konami DE","Namco","Nintendo","Sony CE"),labels = c("EA_Games"," Konami_DE","Namco","Nintendo","Sony_CE"))

p1 <- ggplot(Vgames1,aes(x=Year,y=Global_Sales,fill= Publisher))+
  geom_bar(stat="identity") +
  coord_flip() +
  facet_grid(.~Publisher,scales="free") +
  ggtitle("Publisher Distribution by Yearly Number of Game and Sales") +
  xlab("Sales made Globally") +
  ylab("Years") +
  theme_excel_new()

Data Reference

Reconstruction

The following plot fixes the main issues in the original.