Amsterdammers like old canal houses and dislike 1950s architecture

17 February 2015

The research bureau of the Amsterdam city government (O+S) has published an Excel file containing a wealth of data about Amsterdam’s neighbourhoods. Among other things, it tells us how beautiful Amsterdammers think houses in their neighbourhood are. The average ratings are shown on the map below.

According to locals, the most beautiful houses are to be found around the Leliegracht (rated 8.7 out of 10) in the western canal belt. The ugliest are at the messy margins of the city, for example around the Weespertrekvaart in the Omval neighbourhood.

It will hardly come as a surprise that there’s a pretty strong correlation between the value of houses and how beautiful locals think they are. Either Amsterdammers have a posh taste in houses, or beautiful houses are expensive because people are willing to pay more for them (probably it’s a bit of both).

It so happened I had recently come across a new dataset from Statistics Netherlands (CBS) containing data on the construction period of houses by 4-digit postcode. I linked this data to the O+S data (for the challenges involved see the Method section below). The scatterplot shows neighbourhoods by share of houses from a specified period, and rating.

A few conclusions can be drawn:

My first reaction to these findings was disappointment in my fellow Amsterdammers. Mainly for these reasons:

A deeper dive into the data resulted in a somewhat more nuanced view. For some of the neighbourhoods, data is available at a more detailed level than the level I used in my analysis.

As for the Amsterdam School: a pretty sensational example is the Tellegenbuurt in the neighbourhood Diamantbuurt, which gets a mediocre 7 out of 10 rating (just above the median rating of 6.9). However, the more detailed data shows that at least the western part of the Tellegenbuurt gets a somewhat better 7.4. Similarly, the iconic het Schip housing block is in the Spaarndammer- and Zeeheldenbuurt, where locals rate the houses a 6.9, but the western parts of the Spaarndammerbuurt proper get a rating of 7.5.

I still think Amsterdammers undervalue the 1906–1930 period, but at least they do seem to show some appreciation for some of the most-acclaimed highlights of the period.

As for the 1980s: this was a period of urban renewal. It resulted in dull housing blocks in otherwise decent-looking neighbourhoods such as the Dapperbuurt, the Oostelijke Eilanden and the eastern part of the Indische buurt. This mixture may explain why these neighbourhoods don’t necessarily get very low ratings.


The ratings of houses were collected in 2013, by asking the question «How do you rate the houses in your neighbourhood? (1=very ugly, 10=very beautiful)». The O+S file containing these ratings is available here and the CBS file containing data on period of construction here.

The main challenge consisted in linking the two datasets. Fortunately, the CBS also has a file containing neighbourhood data with the most prevalent 4-digit postcode (and also information on the share of houses that have that postcode). The link between postcode and neighbourhood is imperfect but not too bad. For example, in 57 out of the 97 neighbourhoods in my final analysis, over 90% of the addresses have the postcode associated with the neighbourhood.

Somewhat surprisingly, the O+S spelling of neighbourhoods is in some cases slightly different from the CBS (why?!). For example, Bijlmer oost (e,g,k) versus Bijlmer-Oost (E, G, K). I created a separate table to link the different spellings.

I used R to merge the files and check for correlations between share of houses from a specific period and rating of the houses (code on Github). One shouldn’t expect too strong correlations for two reasons: first, the share of houses from a certain period will be at best just one among many factors that have an influence on rating and second, because of the noise created by the imperfect link between postcode and neighbourhood.

For share of pre–1906 houses there was the strongest correlation with the rating of the houses (.51). For 1945–1960 the correlation was -.32 and for post–2011 it was -.39. There was an even weaker, but still statistically significant, correlation for the 1960s (-.22).

I initially created a map with Qgis, but then I decided the map needed some interactivity. I created a new version with Leaflet and D3, using this tutorial to figure out the basics of Leaflet and how to combine it with D3. The initial result wasn’t pretty, but then I found the black and white tiles by Stamen (better than the OSM black and white) and now I think it looks better (although I guess maps overlaid with a choropleth will always look a bit smudgy).

Source: dirkmjk | Categories: Data, Maps, D3.js, Leaflet, R