Assignment 2: Data Visualisation Critique

MATH2404: Data Visualisation and Communication

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

Source: Ampere Analysis (2021).

Objective

The side by side visualisation of the two pie charts was designed to demonstrate the breakdown of market share certain Subscription Video-on-Demand (SVOD) services had during 2019 and 2020.

The side by side visualisation for the market share of streaming services had the following issues:

• Titles - There is no overarching title for the visualisation.
• Data description/Title - It is not clear what market the data represents.
• Data - Neither pie chart has 100% of the market displayed. The segments of the pie charts equal 85% not 100%.
• Data - On review of the source data the 2% market share of Paramount+ is not displayed on the 2019 pie chart.
• Visualisation - The use of two side by side pie charts does not allow for easy comparison of the 2019 and 2020 data.
• Visualisation - The colours used in the pie charts do not have any correlation to the to the data being displayed and do not vaule add to the visualisation.

Reference

• Ampere Analysis (2021). Why Netflix May Be the Future of Gaming. Retrieved 27 March 2023, from No Ordinary Strategy website: https://www.bcrschroeder.com/p/netflix-video-games

Code

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

library(ggplot2) # Package for creating visualisations
library(readr) # Package for importing data

# Import dataset

SVOD_data <- read_csv("SVOD_2019_2020.csv")

SVOD_data$year_2019 <- c('2019')
SVOD_data$year_2020 <- c('2020')

data_19 <- data.frame(SVOD_data$SVOD_type, SVOD_data$`2019_data`, SVOD_data$year_2019) 
data_20 <- data.frame(SVOD_data$SVOD_type, SVOD_data$`2020_data`, SVOD_data$year_2020) 

colnames(data_19) <- c("SVOD_type","Percentage","Year")
colnames(data_20) <- c("SVOD_type","Percentage","Year")

SVOD_data <- rbind(data_19,data_20)

SVOD_data$Percentage <- SVOD_data$Percentage * 100

p1 <- ggplot(SVOD_data, aes(x=SVOD_type, y=Percentage, fill=Year)) +  
        geom_col(width=0.5, position=position_dodge2()) +
        ggtitle("Market Share of Subscription Video-on-Demand (SVOD) \n services in the United States (2019-2020)") +
        xlab("SVOD") + 
        ylab("Percentage Market Share") + 
        theme(plot.title = element_text(hjust = 0.5, size=20), legend.position=c(0.9,0.8), axis.title.x = element_text(size=15), axis.title.y=element_text(size=15), axis.text.x =element_text(size=10), axis.text.y=element_text(size=10)) +
        geom_text(aes(label=paste0(Percentage,"%")), position=position_dodge(width=0.5), vjust=-.2) 
p1

Data Reference

• Ampere Analysis (2021). Why Netflix May Be the Future of Gaming. Retrieved 27 March 2023, from No Ordinary Strategy website: https://www.bcrschroeder.com/p/netflix-video-games

Reconstruction

The following plot fixes the main issues in the original.