I’ve always been excited about numbeo.com database and possibilities of this data visualisation as a map. Here I present a small project I’ve done in a couple of days by a variety of software: FME with python, QGIS, Excel and Adobe Photoshop.
There is currently a real estate boom in Poland and I thought that it could be a good subject to visualize. We can observe that to live in a large city you have to pay two times more than in smaller cities.
Methodology and Software
The hardest part is probably to scrape the numbeo.com dataset. I’m a beginner at python but I managed to run a script that is taking a piece of data that is interesting, here is the link. Such edited code was embedded by me into FME 2019 (Feature Manipulation Engine). In that software I’m extracting the data and transforming it to geospatial format, actually, it’s GeoJSON. I’ve created a GitHub webpage for sharing .fmw file with anyone interested.
After obtaining the dataset, there was a time for GIS part. For most projects like this, I use ArcGIS but now I wanted to explore QGIS symbolization and labelling options. I have to admit that working in this opensource software is more flexible and faster at some point. Nevertheless, I felt a lack of parameters I got used to in ArcGIS, for example, precise buffering around point.
Finally, the last part of the work consisted of exporting a map to graphic format and import it into Adobe Photoshop software. It’s my favourite part of the work because you can not only observe and manipulate the dataset, but also arrange the view and affect the reception. On the graphic, I have attached a full table of the dataset and some statistics to compare against border countries. In the end, I drew an element in the south-west side of the map which is gathering all presented data points into one to summarize the work.
I have hope that some of you would find fun or usefulness in reading this map. If not in the knowledge that it brings than maybe in a pleasant view.