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

Original


Source: ACMA Research and Analysis Section (2015).


Objective

Explain the objective of the original data visualisation and the targetted audience.

The visualisation chosen had the following three main issues:

  • Briefly explain issue 1
  • Briefly explain issue 2
  • Briefly explain issue 3

Reference

Code

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

library(ggplot2)
smartphone <- data.frame(Year = c("Dec-10", "Dec-11", 
                                  "Dec-12", "Dec-13", "Dec-14"),
                      Count = c(2247, 2818, 3379, 4476,5218),
                      Perc = c(13, 16, 19, 25,29))

p1 <- ggplot(data = smartphone, aes(group = 1, x = Year,y = Perc))
p1 <- p1 + geom_line(stat = "identity", colour = "turquoise3") + geom_point(colour = "turquoise3") + 
  geom_text(aes(label = paste(Perc,"%",sep="")),nudge_y = -2, nudge_x = .05) +
  labs(
    title = "Australian Mobile-only Phone Users % of Population",
    y = "Population %") + theme_minimal() + scale_y_continuous(limits = c(0,30))

Data Reference

Reconstruction

The following plot fixes the main issues in the original.