Fusion tables at first just looks like another kind of excel but once you dive into it, you can see there are some differences which can be taken advantage of.
One of the obvious ones is map creation (as you will see below), with data from the tables being able to display on the map, no doubt helped by Google maps being under the same ownership.
For the assignment, the first thing I did is go to the CSO website to get the census (by county) for Ireland 2011. Then I copied and pasted the data into an excel sheet.
The original data has more than you need such as subsections of counties and provinces. This isn’t an issue (good if anything) but the one exception is Tipperary as it had North and South Tipperary data but not the total, so I had to make one with the two figures together, with the odd bit of other cleaning.
Next I uploaded both tables separately as Fusion Tables, with the file stored in my Google Drive. Once uploaded I did the second major advantage of fusion tables, merging. Its sort of hinted in the name, but you are able to merge or ‘fuse’ two tables together to combine their data in a way that suits you. As someone who comes from a programming background, this reminds me of databases, or more specially the joining of tables in a database. You join on a common piece of data so the data matches up properly and as expected.
So in this case I clicked ‘File’ and then ‘Merge’ on one of the tables, and then selected the second file from the list to merge with. I joined the data on the county name which was “Location Name” and “NAME_1” from their respective tables. Lastly I chose which columns to keep. I kept all the population data and just kept the geometry data from the counties, which is all I need for my map.
Once confirmed, the two tables are merged together, leaving a merged table with columns and data from both tables. This also means the map, now has the geographic information to put borders around each county on the map. With this part now, I filled each county with a colour depending on how high the population of that county is (or I guess was). I set a range of values, associating each with a colour, that covered the lowest to the highest values. I tried to pick a combination that highlighted clearly the highest and lowest counties, while not having most of the countries just one colour. Lastly, I enabled a key to be displayed so you can see what range each colour is. Clicking on a county gives relevant data including the county name, population, and population of each gender.