This assignment’s main task is to analyse the dispersion of the population within the Republic of Ireland. In fact, it is divided in 26 different counties all of different sizes regarding population and size.
This assignment was done through fusion tables, which serve as a filter in order to summarise larger amounts of data into, in this specific example, an interactive map that illustrates the necessary information for this assignment. In order to be able to create the map, I firstly had to gather the mandatory data. Thankfully, our data analytics teacher had provided us with a document which included two links:
-The Irish Population by county in 2011¹
-A Irish Keyhole Markup Language file, which serves as a geographic file to represent data in under the form of an earth browser such as google maps²
After collecting the needed information, I created two new fusion tables of my google account to then merge them together. Once this has been done, I was able to view the map showing the Republic of Ireland, its counties, and their population. The next step simply involved copying and pasting the map’s link into my blog. Evidently, as it was my first data analytics assignment, I encountered some difficulties with the map. In fact, the data I had received divided Tipperary into north and south, while the KLM file analysed the county as a whole. I resolved this issue by simply adding up the male, female and total population of both north Tipperary and south Tipperary.
When analysing the data gathered on the map, I realised that only three counties fall into the category with above 300,000 habitants are Dublin (1,273,069 inhabitants), Galway (250,653 inhabitants) and Cork (519,032 inhabitants), all counties with major cities³. On the other hand, counties in the center of the Republic of Ireland all possess a population with less than 100,000 inhabitants. These counties are the following:
-Sligo (65,393 inhabitants)
-Leitrim (31,798 inhabitants)
-Roscommon (64,065 inhabitants)
-Longford (39,000 inhabitants)
-Westmeath (86,164 inhabitants)
-Offaly (76,687 inhabitants)
-Laois (80,559 inhabitants)
-Kilkenny (95,419 inhabitants)
-Cavan (73,183 inhabitants)
-Monaghan (30,483 inhabitants) – this county is located in the north of the Republic of Ireland, just south of the border.
I believe that the main reason for the fact that these counties’ populations are so low is due tot he fact that they are located in the countryside and that there doesn’t appear to be any major cities in this area. It is quit standard that these types of rural regions, in any country, tends to be less populated than the urban areas.
Furthermore, this intensity map could include more information than it already does. I would find it interesting if I could have included an analysis on the different age groups in each counties to visualise which counties have a more “young” population. My beliefs are that urban areas will tend to have a younger age group than urban areas, due to the accessibility of goods and services, the availability of jobs and higher level education establishments. Moreover, I would have liked to add statistics on the most popular professions in each county, as well as the current workforce.
To conclude this assignment, my findings were exactly what I had expected prior to my research. As I explained earlier in this post, I forecasted that urban areas would have a higher population than rural areas, due to the higher level of activities found in bigger cities, such as availability of work, accessibility of goods and services, size of airports, amounts of universities and higher education establishments, etc. I believe that this assignment was a perfect way to ease into the subject of data analytics, as the information collected and the final products were easy to visualise and to explain.
As for recommendations, I would have liked to have the knowledge and skill to include more information into my interactive map, as I believe that there are many more aspects to study when looking at the dispersion of the population in the Republic of Ireland. Furthermore, I underestimated how long it would take to complete this assignment on both the data collection, the mapping, and the analysis for my blog post. I would recommend, as well as remember for my next assignment, to plan more time ahead for my assignment.