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 is to track the progress of the vaccination drive in the United Kingdom. It aims to provide information such as the number of doses administered, number of people vaccinated within groups , and the percentage of people vaccinated within groups.
The primary target audience for the visualisation is the adult public (over 18) residing within UK. This visualisation can help them track the progress of vaccination drive within their country while giving them a sense of how long it would take for their turn (depending on the priority group). The secondary target audience would the public that is interested in knowing the status of vaccination drive within UK through news/visualisation.
The visualisation chosen had the following three main issues:
Poor choice of visualisation: The visualisation for different groups is difficult to compare since the charts are stacked. The amount of precision is lost due to the stacked chart and users have to manually calculate values if they want to compare between groups. Also the data presented in the visualisation is not correct, for example, in week 6 the visual shows that all of priority 1-4 has been vaccinated while a small percentage of priority group 5-9 is also vaccinated. This is not correct. As per the data, ~13 million have been vaccinated by week 6 however ~8 million in priority group 1-4 and ~5 million people in priority group 5-9 have been vaccinated. These discrepancies mislead the audience
Incomplete/Missing data source: The source of the data visualisation mentioned is not correct. The source refers to the main home page of UK government covid dashboard, however, the vaccination details presented in the visualisation is not available on that link
Incomplete data: In the visualisation, there is a segment which is completely empty (vaccinations for “Rest of adult population”) and does not add much value to the visualisation.
Reference
UK Politics. Reddit.com. (2021). Retrieved 3 May 2021, from https://www.reddit.com/r/ukpolitics/comments/mdmp6k/weekly_coronavirus_vaccination_levels_up_to_and/.
COVID-19 Vaccinations Archive. England.nhs.uk. (2021). Retrieved 3 May 2021, from https://www.england.nhs.uk/statistics/statistical-work-areas/covid-19-vaccinations/covid-19-vaccinations-archive/.
The following code was used to fix the issues identified in the original.
library(ggplot2)
library("readxl")
library(RColorBrewer)
weekly_vaccinations <- read_excel("/Applications/Documents/Study/RMIT Learning/Third Semester/02 Data Visualization/02 Task 2/02 Transformed Data set/Weekly_Vaccinations_data_UK_revised.xlsx",sheet = "Sheet4")
weekly_vaccinations$Number <- as.factor(weekly_vaccinations$Number)
plot <- ggplot(weekly_vaccinations, aes(Number, percentage, fill=dose_type))
plot <- plot + geom_bar(stat = "identity", position = 'dodge')
p <-plot + facet_wrap(~Group) + scale_y_continuous(labels = scales::percent) + theme(legend.position="top") +
theme(panel.background = element_blank(), axis.line = element_line(colour = "grey")) + xlab("Week numbers (2021)") + ylab("Percentage of population") + scale_fill_brewer(palette = "Set2", name = "# of vaccines administered", labels=c("One dose","Two dose")) + labs(title = "Vaccine distribution in UK by priority group (2021)") + theme(plot.title = element_text(hjust = 0.5))
Data Reference
The following plot fixes the main issues in the original.