The available database includes various variables, the type of accommodation (apartment, duplex, attic, etc.), information on prices, living space (and therefore the price per square meter calculated for each ad), and the location of the real estate of course. It would be interesting that, in a few clicks, you could access to maps to asses if you pay too much for your accommodation. The maps presented below constitute a first approach of this problematic because many factors should be taken into account in the definition of the price of a dwelling.
Just over 34,000 entries were collected in one month, with an increase of about 3,000 additional ads per week across Switzerland. Advertisements for apartments s.s., duplexes, attics, roof flats and single houses represent respectively 80%, 4%, 4%, 3% and 2.5% of the advertisements. The database lists total / partial values (e.g. no mean with a single value) for 37 / 42 %, 5 / 7 %, 5 / 6.5 %, 3 / 6 %, 2.5 / 4.5 % of the Swiss municipalities, for apartments s.s., duplexes, attics, roof flats and finally single houses. seule
Values for price, iving space and price per square meter come with their minimum and maximum values as well as average and median values when possible. Considering the median allows to suppress the impact of extreme values (low or high) that strongly influence the mean as shown in the following figure where two values at more than 26 deviate very significantly the mean from the median. In other words, the median tends to be approximately on the mode of an unimodal distribution (which is almost always the case for our data).
At this stage some remarks on the validity of certain data presented are needed. First of all, let us keep in mind that the source, Homegate, does not present exhaustively all the properties offered for renting in Switzerland. Private landlord may potentially not want to go through this type of circuit. Then, the data presented on the different maps below are strongly dependent on the number of ads harvested per commune. The lower the number of advertisements, the more the representativeness of the presented value, coded as color, should be taken cautiously.
Finally, some quick comments on the contribution of this kind of visualization. Keep in mind that the size of the database remains relatively small for types of ads other than apartments (s.s.).
If you consider the apartments type s.s. for which the data are quite large, average and median prices illustrate well the bipolarity of the high cost of housing in Switzerland, with the areas of the Geneva lake and lakes of Zürich and Zug. As for the iving space of the apartments, it is an aspect little known (at least for me). However, the minimum values (<23m2) are present in almost all the 10 most populous Swiss cities (please note that data for St. Gallen were not collected due to a url issue). Finally, for prices per square meter, if one considers the average and median prices, the same bipolarity as previously mentioned is visible.
So, are you paying too much for your accommodation according to the m2?
Let’s take myself as an example! We pay 23CHF per m2 for our apartment , which is 3 francs above the median price for the town where we live. However, we have all public transport nearby, we are in a very good area with many amenities, we have a garden, a magnificent view … these “plus” have evidently a cost! It is necessary to understand that the values presented in these maps are calculated at the commune level. The variations according to the neighborhoods, the distance to public transport, the “amenities” of your dwelling (garden ?, chimney?, parking place?…), all this additional information do not appear here. Nevertheless, you can already get a good view of your own situation!