Data Viz Analysis
The above image is a data visualization from The Guardian in an article about Australia's progress on the climate crisis.
Strengths of the above data visualization:
The data displays a large amount of information covering a period of 23 years. It is easy to compare the Co2 emissions in 2010 because the bubbles are accompanied with values. Since there are multiple values in the dataset, the bubbles made it easier to take in all the information at once. I also like the chart because it explains the complexity of carbon emissions from different countries in a simple way.
The data displays a large amount of information covering a period of 23 years. It is easy to compare the Co2 emissions in 2010 because the bubbles are accompanied with values. Since there are multiple values in the dataset, the bubbles made it easier to take in all the information at once. I also like the chart because it explains the complexity of carbon emissions from different countries in a simple way.
Weaknesses of the data visualization:
It’s impossible to tell whether emissions increased or decreased in the first two circles (2001 and 2002). While the first circle is 1.76 per cent, the other is 2.22 per cent. If the same data was in a bar chart it would have been easier to see a marked increase or decrease instead of comparing the area of two circles. The data records the largest increase and decrease in Co2 emissions and sorts them according to colour which is confusing. A line chart depicting the same increase and decrease would be easier to read. Especially in the year 2020, it’s hard to make out the difference in the decrease since all the blue bubbles look approximately the same size due to the COVID-19 pandemic. The circles depict both negative and positive values on the same axis which creates further confusion about a marked increase or decrease. It is hard to compare the data between any two countries when looking at the bubbles alone. While there was an increase and decrease in Co2 emissions over the years, the chart creates an illusion that the emissions were fairly constant or same throughout since it is flat. In a line chart or bar graph, it is easy to tell whether something increased or decreased since the downfall or increase is indicated by clear points. There are three variables in the above chart: emissions, year and countries. If the values of emissions were placed on one axis and the year on the other, it would have been relatively easier to mark the countries on the graph.
I like this chart as well Nyamat. I think its a good idea showing increasing emissions in red and blue as decreasing emissions. Theyre universal colours for this positive and negative change. but i do agree, its major fault is not being able to tell the differences in sizes of some of the bubbles.
ReplyDeleteHi Nyamat, I agree with you that if this chart were a line graph, it would be better. One thing I'm still confused with is the two colours used in the chart. Do they play any role in the visualization? Other than that, good job
ReplyDeleteI like Nyamat chart. I think it's a good idea to show increasing emissions in red and blue as decreasing emissions. These are universal colors for this positive and negative change. I agree with you that it would be better if this graph was a line chart. One thing that still confuses me is the two colors used in the chart.
ReplyDeleteHello Nyamat, I also agree that this would be better shown as a line graph instead of bubbles. However, I believe that the colours are a poor way to convey whether it is increasing or decreasing, as two large bubbles of different colours would indicate a sharp change in the trend, but this isn't very intuitive from two similar looking bubbles where as a line would show a steep segment.
ReplyDeleteThe idea of comparing carbon emissions by red and blue dots is interesting. But too much data makes this visual data view a bit messy, and readers can't find the data they want to know quickly. If you put the numbers into a graph or bar chart, it will be better to express the content of the news.
ReplyDeleteI think you chose a great data visualization to critique, and I liked that you highlighted lots of specific examples to explain why bubble charts are often difficult to understand. I think if you had split up the information into smaller paragraphs it would be a bit easier to read. Overall, great work!
ReplyDelete