RMIT Data Visulisation Reconstruction Task

Deconstruct, Reconstruct Web Report

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

Original

Data: http://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/data/

Objective

Objective of Andy Lee Robinson is to highlight the decline of the arctic sea volumn

The visualisation chosen had the following main issues:

• While pretty, the visulisation does not make it obvious to compare the timelines

• Axis are not on the same line making it hard for comparison

Reference

• PIOMAS Ice Volume Data, 1979-present.
  Retrieved September 9, 2019, from The Polar Science Center website: http://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/data/

Code

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

library(readr)
library(ggplot2)
library(tidyverse)
library(lubridate)

pio <- read_csv("PIOMAS.csv")

pio$y <- paste(as.character(pio$year),"01","01", sep = "-")
pio$date <- as.Date(pio$day, origin = pio$y)

pio$month <- pio$date %>% month(label = T)

piosum <- pio %>% group_by(year, month) %>% summarise(monthmean = mean(vol))

p <- ggplot(data = piosum, aes(x=year, y = monthmean, colour = month))

p1 <- p + geom_line() + 
  labs(title = "PIOMAS Arctic Sea Ice Volume", 
       subtitle = "Data: http://psc.apl.uw.edu/research/projects/arctic-sea-ice-volume-anomaly/data/") + 
  ylab("Montly Average Arctic Sea Ice Volume") + 
  scale_fill_brewer(palette = "Spectral")+
  theme_minimal()

Data Reference

• PIOMAS Ice Volume Data, 1979-present.
  Retrieved September 9, 2019, from The Polar Science Center website: http://psc.apl.uw.edu/wordpress/wp-content/uploads/schweiger/ice_volume/PIOMAS.vol.daily.1979.2019.Current.v2.1.dat.gz

Reconstruction

The following plot fixes the main issues in the original.