Google Fusion Tables

The task sounded easy at first:

To create a heatmap of the population in Ireland in Google Fusion Tables, describing the process in a blog post and saying a few words about the information gained.

Google apps are usually self-explanatory, self-guided, easy and fun to use. I was interested in an easy-to-use visualization tool to facilitate rudimentary data analysis. However, my hope of playing with a bit of data and visualizing surprising or random correlation was thwarted – mainly by the realization how difficult the process is and how deadlines always approach when you nearly got it.

My first difficulty was to not understand where to get the raw data from. I assumed, as maps are a particular strengths of google, that it will be easy to get a Irish county map from google. And it might be, but I could not find it. I also had a long look at huge data sets on the CSO site – so huge in fact, that I couldn’t see the wood for the trees, or in this case the tree for the woods, as it was so much incredible detailed data (age, gender, religion) that I wasn’t sure about the overall population of a county.

The counties themselves turned also out to be difficult – I never really understood the Ulster, Munster etc thing and how they relate to Clare, and Donegal etc. I never even understood if Dublin is it’s own county or not. Now I know.

So I needed two files, one a map of the counties, one a list of the counties with the associated population. I found a blog of a former participant (Thank you, Brian for sharing your advise) saying that he used a map in *.kml format from the irishindependent.ie website, and his population data from a summary table on the census website. I uploaded these onto the google drive, and merged them in the google fusion app with the merge function, and all kind of things happened but never the ones I wanted it to do. The county borders weren’t shown, or only the county borders were shown without any other information. Some of the heatspots were in the UK, one in the US, and one somewhere in the north of Germany (where, I know now, is a place called Carlow).

1 carlow is in germanyEven with my  rudimentary knowledge of Irish geography I thought it unlikely that Ireland expands that far and I needed to find out how to clean up my data (I cannot exclude the possibility, however, that there is a large Irish community in the north of Germany, as there seem to be a high  density of Irish pubs). I managed to figure out how to correct the Louth and Longford from the UK to the Isle of Ireland. I realized that in my original file a left-over (undeleted) “or” was understood by the app to mean OR for Oregon, which produced the heat-spot in the US.

1 Or is it in oregon

I also realized that there is two spellings for Laois, which shouldn’t have surprised me as the Irish always like to put in a few extra letters if there is space, so I aligned all the spellings.

As still nothing happened, I did some more research, to find that I failed by not merging them not by the matching columns (by name of county) but somehow to matched a description with the name of county. A mistake that shouldn’t have happened as we learnt about foreign and primary keys in the data base course.

Then I just needed to go through the options, and after trying a series of different colours, I decided to go for a gradient.

Uploading and merging the relatively small data sets takes a fairly long time, but I guess it takes a lot shorter and having to produce vectorized maps yourself.

The first map I produced revealed the information that Dublin is the area with the densest population, followed by Cork. I found this information rather non-revealing as most of the country seemed to be the same shade, and Dublin seems to be the outlier.

2 alles pale I made an inverse heat map where areas that were least populated were the most ‘outstanding’ . However, with the expectation how  a heatmap worked this turned out to be confusing.

3 focus on countrysideSo, in line with the traditional heat maps, I went back to the reddish colours for the densely populated areas, but changed the gradient to a finer gradient for the less populated areas.

And this is my final, hopefully clickable Google Fusion Heat Map:

final

The information yielded is that most of Ireland is sparsely populated, with the exception of Dublin and Cork.

Next steps for information would be to find historical data and see changes over time.

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