USSR: After 20 years

Delighted to be back after three weeks of treatment, care and medication. I rarely fall ill, so this afforded a nice break from my regular activities and also the chance to browse several websites which deal with data analysis and presentation.

My data-set for this week is from the Guardian Datablog, dated Aug 17th, titled "End of the USSR". The piece is accompanied by an image that uses a map to rate the former soviet provinces on their performance since the collapse.

The data includes yearly figures of GDP, GDP per Capita, Population, Life expectancy and Mortality among other interesting indicators like Intentional homicides, Prison population rate, Prevalence of HIV by gender, Unemployment, Happiness index score, Global peace index and Number of McDonald's!

Given the large difference in figures between Russia and other republics, I was curious to see how the presenter would design the population and the GDP charts for comparison.

I was massively disappointed. The population chart is simply a column chart representing the percentage change of population in 2009 from 1991, and a label to display the current population - very much an easy way out. The GDP chart can be found nowhere, although there is a clustered column chart that displays the GDP per Capita for 3 years out of 20. 1991, 2000 and 2009.

I spent an idle afternoon working on the Population and Life expectancy data and came up with the following after 2 hours.

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The Dorling Cartogram

My last project involved using a multitude of regions for drawing analysis, parallels and comparison. Not wanting to use yet another Choropleth graph, I decided to look up alternatives that were easier to create and preferably required no VBA. Soon I stumbled upon "The Dorling Cartogram", defined in the UCSB site as, "This type of cartogram was named after its inventor, Danny Dorling of the University of Leeds. A Dorling cartogram maintains neither shape, topology nor object centroids, though it has proven to be a very effective cartogram method. To create a Dorling cartogram, instead of enlarging or shrinking the objects themselves, the cartographer will replace the objects with a uniform shape, usually a circle, of the appropriate size." I had the data for Obesity in the United States handy, so I decided to give it a try before using it in my project. I opted to use Bubble charts because data points within a series may need to be of varied shapes based on

Florence Nightingale Circumplex Chart

I was taken to the Florence Nightingale's Wiki page during a recent research, and one of the interesting things I noted was her contribution to statistics. It came to me as a pleasant surprise that she is credited with inventing the polar area diagram , or occasionally the Nightingale rose diagram, which is equivalent to a modern circular histogram. Following the completion of my project and in my weekend to spare, I devoted time to recreating the chart in Excel. It took a combination of Doughnut-Pie-and XY charts and close to four hours to finish it. The colours are a bit darker, the values are approximate and the labels differently oriented, yet the chart looks fairly close to the original as is shown by the picture below.

The Cricket Graphs: The Forgotten Chart

The fun of receiving feedback to blog posts is that one isn't quite sure what they might come up against. While mostly it provides fascinating discussions, insightful comments or explanatory questions, there is also the odd occasion when it throws up unusual requests. The other day I received an email in response to my post, The Cricket Graphs . The sender wanted me to create a "Partnership" chart, which would show the runs scored by the pair of batsmen for every wicket and the balls faced. I went searching for data on the Cricinfo website , and picked out the 3rd ODI between the South African and Australian cricket teams which was played out in Kingsmead, Durban on October 28, 2011. The Partnership details were taken from the page titled Partnerships Table and the total balls faced by individual batsmen from the Scorecard. Constructing the graphs was a somewhat tricky affair, with two potential bar charts in two axes representing Balls and Runs, which had me w

Somnath's Excel Charts

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