Click the Original, Code and Reconstruction tabs to read about the issues and how they were fixed.
Objective
The objective of the original data visualisation was to show global game market in all time. The target audience of this visualisation include consumers, shop owners and platform owners. Consumers who are new to gaming are able to follow the statistic to search more most popular gaming consoles, which often means contain more choices of games or more versatile. Shop owners too can refer to this kind of data visualisation to decide their stocking options.Platform owners, no doubt are able to use the statistics for advertiisng their products.
The visualisation chosen had the following three main issues:
Using the Trifecta check, we are examining the question, data and visualisation brought by the graph. The question is not very clear and subjective, the author addressed the most popular gaming console of all times indicating the author’s intention to present the popularity of each gaming console worldwide. This question is, however, less relevant to the market in overall as a cumulative sales over a long period of time overestimate the popularity of certain product. and underestimate the popularity of new product included in the data.
The data covers cumulative sales of all gaming consoles at all times, including retro gaming consoles from more than 20 years ago which is not being manufacture anymore and lack of new games. This is therefore less relevant to buyers and shop owners as they will have to actively research into each console seperately to find out if the consoles are still appealing.
Visualisation wise is lay out and plotted properly but lack of focus point and requies a scan through each bar to search for the data of interest. The data could be aggregated by platform or year release so the key message is highlighted and draw attention to the audience quickly.
Reference
Vailshery, L.S. (2021). Global unit sales of video game consoles as of June 2021. [online] Statista. Available at: https://www.statista.com/statistics/1101872/unit-sales-video-game-consoles/ [Accessed 31 Jul. 2021].
The following code was used to fix the issues identified in the original.
library(ggplot2)
library(readxl)
library(tidyverse)
df <- read_excel("Game_console_sales.xlsx")
names(df) <- c ("Platform" , "Firm" , "Released" , "Units_sold")
summary(df)
## Platform Firm Released Units_sold
## Length:28 Length:28 Min. :1977 Length:28
## Class :character Class :character 1st Qu.:1987 Class :character
## Mode :character Mode :character Median :1995 Mode :character
## Mean :1997
## 3rd Qu.:2006
## Max. :2020
unique(df$Units_sold)
## [1] ">155 million" "115.9 million" "102.49 million" "101.63 million"
## [5] ">87.4 million" "84.59 million" ">84 million" "61.91 million"
## [9] "51 million" "49.10 million" "35 million" "32.93 million"
## [13] "30 million" "24 million" "21.74 million" "13.56 million"
## [17] "10–13 million" "10 million" "9.26 million" "9.13 million"
## [21] "6.5 million" ">3.4 million" "3 million" ">2 million"
## [25] "2 million" ">1 million" "1 million"
unique(df$Platform)
## [1] "PlayStation 2"
## [2] "PlayStation 4"
## [3] "PlayStation"
## [4] "Wii"
## [5] "PlayStation 3"
## [6] "Nintendo Switch #hybrid video game console"
## [7] "Xbox 360"
## [8] "Nintendo Entertainment System"
## [9] "Xbox One"
## [10] "Super Nintendo Entertainment System"
## [11] "Sega Genesis"
## [12] "Nintendo 64"
## [13] "Atari 2600"
## [14] "Xbox"
## [15] "GameCube"
## [16] "Wii U"
## [17] "Master System"
## [18] "PlayStation 5"
## [19] "TurboGrafx-16"
## [20] "Sega Saturn"
## [21] "Dreamcast"
## [22] "Xbox Series X/S"
## [23] "Sega Pico"
## [24] "Intellivision"
## [25] "ColecoVision"
## [26] "Magnavox Odyssey"
## [27] "Philips CD-i"
## [28] "Atari 5200"
df$Platform <- gsub("Nintendo Switch #hybrid video game console", "Nintendo Switch", df$Platform)
df$Units_sold <- gsub("[a-zA-Z,>]", "", df$Units_sold)
df$Units_sold <- gsub("10–13", "11.5", df$Units_sold)
df$Units_sold<- str_trim(df$`Units_sold`)
options(digits = 5)
df$Released <- as.character(df$Released)
df$Units_sold <- as.numeric(as.character(df$Units_sold))
df <- df %>% filter(df$Released>=2011)
df$Platform <- factor(df$Platform, levels = rev(df$Platform))
safe_colorblind_palette <- c("#88CCEE", "#CC6677", "#DDCC77", "#117733", "#332288", "#AA4499",
"#44AA99", "#999933", "#882255", "#661100", "#6699CC", "#888888")
scales::show_col(safe_colorblind_palette)
group.colors <- c(Microsoft = "#117733", Nintendo = "#CC6677", Sony ="#332288")
p1 <- ggplot(data = df, aes( x = Units_sold ,y = Platform, fill=Firm))
p1 <- p1 + geom_bar(stat = "identity") +
geom_text(aes(label = paste(Units_sold,"m",sep="")), hjust = 0) +
labs(title = "Cumulative sales of Video Game Console from 2011 to 2021", x = "Unit Sales (Millions)", y="Game Console") +
theme_minimal() +xlim(0,130) + scale_fill_manual(values=group.colors)
p1
Data Reference
Wikipedia Contributors (2019). List of best-selling game consoles. [online] Wikipedia. Available at: https://en.wikipedia.org/wiki/List_of_best-selling_game_consoles.
Stack Overflow. (n.d.). R Plot Color Combinations that Are Colorblind Accessible. [online] Available at: https://stackoverflow.com/questions/57153428/r-plot-color-combinations-that-are-colorblind-accessible [Accessed 31 Jul. 2021].
The following plot fixes the main issues in the original. The question now is to showcase consoles that are most popular in the past 10 years, only consoles published in the last 10 years are presented here so that it is more relevant to the recent market. Visualisation wise, a combination of colour blindness safe was chosen and each colour chosen is highly associative with each Firm’s representative colour.