The Cricket Graphs

Everyone in India is crazy about cricket. International cricket to be exact. This passion was triggered by a freak World Cup Championship win in 1983, and its dominance in India has continued unabated since. Of late, successful triumphs in T20 World Championship, The ICC Test Rankings, IPL and most recently, the ICC World Cup 2011 has taken support for the game in India through the roof.

However, this post is not about the ascendancy of cricket in India. It takes to the various types of graphs we see in the telly to help us further analyze the game. Commentators have given them colourful names. The two most notable and common are "The Manhattan", which is the column graph, and "Worm" - which is the line chart.

I didn't have the time to look up official India and Australian sides, nor the details of an official match between them. I knew a 50 over per-side match will be too bulky to create as a dashboard chart, so I zeroed in on a 20 over per-side format.

After an hour of restructuring the data, and working on them, the charts are made as follows:

First, "The Worm"

Then, "The Manhattan"

And finally, a comparative runs per over and wickets chart.

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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 Pie-Doughnut Combination: A Fan Plot

Happy to be back after a pretty busy beginning to the new year. I had this completed almost immediately following the preceding post but was otherwise hard-pressed to find a suitable time to post it. Soon after writing the Florence Nightingale Circumplex Chart post, I started searching for more varieties of charts that can be created using combinations of Pie-Doughnut charts. Soon enough, I found one through Naomi B. Robbins' comment in a Jorge Camoes' post . The referenced PDF article attempts to use Fan Plot to display relative quantities and differences using the R statistical language as is shown in the image below. Impassive of its benefits and/or disadvantages, I created it in Excel.

Somnath's Excel Charts

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