The exercise initially calls for the creation of an Irish population heatmap. A couple of pieces of information are required for this task. Firstly, a dataset containing the population of Ireland broken down by county and secondly some geographical data providing the county boundaries in the form of a KML (Keyhole Mark-up Language) file. “KML is a file format used to display geographic data in an Earth browser such as Google Earth.” (Google Developers, 2016).
The population of Ireland dataset can be found at: http://www.cso.ie/en/statistics/population/populationofeachprovincecountyandcity2011/. It should be pointed out that the Central Statistics Office (CSO) is a great resource with a wealth of information ready and waiting for interpretation.
The dataset was copied into a spreadsheet to prepare it for a fusion table. It is important to familiarise oneself with the dataset to ensure a good understanding of the information being observed. At this point, there is some scrubbing (data clean up) to be done. The dataset not only contains county information but also includes provinces, cities breakdown and county breakdown (Tipperary – North / South). There are a couple of other errors which are fixed in order to achieve the most accurate result. Logging in to Google Fusion tables, click add new table on the file menu. This loads your data to a table which identifies your counties on the map by way of a marker or dot. We now need to provide some geographical information to create a visualisation of our population data.
The second dataset is the county boundary geographical information, downloaded from: http://www.independent.ie/editorial/test/map_lead.kml. Open this file in a fusion table to examine the data. Some errors in the data were identified and corrected, such as counties being labelled incorrectly. From the population data table, select merge table and from here select the map table. This dataset is then merged with the population data to create a population map by county. To create the heatmap effect the spread of population needs to be split into number ranges (buckets), in this case 6 were chosen. With a lighter colour applied to smaller population number and a darker colour to the highest population area.
Now we can see that the density of the Irish population appears to be at its highest along the east and south east coast. However, Cork which has the second highest county population has a relatively low county density because it is the largest county by land mass. A way to combat this anomaly, could be to include city density figures which would provide a more accurate image of population density.
I’m curious to know more about the population of Ireland, say for example – the index of disposal income across all counties. The disposable income index is useful as one can see which counties are above and below the state average of 100. The resulting visualisations of all counties above the state average and counties below the state average paint a very interesting picture. This analysis is supported by the CSO in their County Incomes and Regional GDP report for 2011, whereby they find the following:
“Greater uncertainty at county level.” While the county figures involve uncertainty they do provide useful indication of the degree of variability at county level. Dublin, Kildare, Limerick and Cork are the only counties where per capita disposable income exceeds the state average in 2011 similar to 2010.” (CSO, 2016)
But there are no real answers here so it may be useful to take the analysis a step further by examining the employment levels across the country at that time.
Final Push for Answers
In order to examine employment levels across the county, the number of people in the labour force age 15 or over, Census 2011 was examined. The expectation was, there would be a wide differential of the number of people in the labour force as a percentage of county population. However, the results are surprising, in that the number of people in the labour force per county ranges from 45% for Donegal to 51% for Dublin.
In many respects, no clear answer has emerged from the data as to why Dublin, Kildare, Limerick and Cork exceed the state average per capita income index of over 100%. One could theorise, that these locations are well served by motorway networks, such as M7 Dublin/Limerick route and the M7/M8 Dublin/Cork route, both of which pass through Kildare.
This exercise as a whole has clearly demonstrated the power of Fusion Tables as a tool for data visualisation and analysis. Its free, relatively simple to use and yields quite powerful visual results. Of course a tool is only as good as the data that is inputted. A strong understanding of the data subject matter one is working with is essential in order to take account of the many contributing factors that shape that data. A useful aphorism to bear in mind, usually attributed to Mark Twain or Benjamin Disraeli : “There are lies, damned lies and statistics”, www.twainquotes.com.
“What is KML”, available at https://developers.google.com/kml/, (accessed 21/02/2016)
“County Incomes and Regional GDP”, available at http://www.cso.ie/en/releasesandpublications/er/cirgdp/countyincomesandregionalgdp2011/ (accessed 21/02/2016).