Seven deadly sins

Visualizing data





Using data to visualize greed in Denmark. School assignment @ DMJX May 2022

illustration of greedy monster in form of a G

Section #1


Is God Watching?

One of the deadly sins is greed. But what does greed mean in todays society?

burning cash illustration
A selfish and excessive desire for more of something (such as money) than is needed motivated by naked ambition and greed. Paul Piff, a social psychologist at UC Berkeley, found that people who “had more” were less ethical, and more likely to lie, cheat, or steal. Interestingly, it wasn’t that more greedy people made it to higher social class, but that getting to a higher social class reinforced those behaviors, making people more likely to be greedy.

Section #2

Choropleth map

Greed of Danish Municipalities

Using data from Statistics Denmark (Danmark Statistik) we came up with an algorithm to calculate a greed index for Danish municipalities. The algorithm uses a weighted average of 4 datasets with a distribution of Danish municipalities from the year 2019.



The Datasets

Dataset #1: STRAF11

The first dataset is "STRAF11: Anmeldte forbrydelser efter område og overtrædelsesart" - Reported crimes based on area and kind of crime. We choose 2 views from this dataset. The first being theft and the second being money related crimes. The numbers from theft is the sum of "Andre tyverier", "Tyveri/brugstyveri af køretøj", "Tyveri/brugstyveri af knallert", "Tyveri/brugstyveri af cykel" and "Tyveri/brugstyveri af andet", whereas the numbers from crime related crimes is the sum of "Underslæb", "Hæleri", "Grov skattesvig mv." and "Forbrydelse vedrørende penge og bevismateriale", "Skatte- og afgiftslove mv.". All from 2019 and divided by number of citizens to get theft pr. citizen and money related crimes pr. citizen.

Municipality Theft cases Population Cases pr. citizen
København 45,745 627,321 0.073
Frederiksberg 4,146 104,225 0.040
Dragør 228 14,365 0.016
Tårnby 2,281 42,998 0.053
Albertslund 960 27,768 0.035
Ballerup 1,582 48,449 0.033
Brøndby 947 35,224 0.027
Gentofte 2,666 75,112 0.035
Gladsaxe 1,841 69,552 0.026
Glostrup 945 22,842 0.041
Herlev 1,114 28,900 0.039
Hvidovre 1,751 53,492 0.033
Høje-Taastrup 1,455 50,826 0.029
Ishøj 755 22,959 0.033
Lyngby-Taarbæk 2,336 56,105 0.042
Rødovre 1461 40,357 0.036
Vallensbæk 356 16,655 0.021
Allerød 458 25,686 0.018
... ... ... ...

Dataset #2: BIL54

The second dataset is "BIL54: Bestand af motorkøretøjer efter område, køretøjstype, brugerforhold og drivmiddel" - Collection of motorized vehicles based on area, type of vehicle, type of use and fuel source. For this dataset we choose personal vehicles for private use. Then, we took the average value of the months from year 2019 and divided by the number of citizens to get personal vehicles pr. citizen.

Municipality # of Cars Population Cars pr. Citizen
København 122,438 627,321 0.195
Frederiksberg 25,33 104,225 0.243
Dragør 6,52 14,365 0.454
Tårnby 15,635 42,998 0.364
Albertslund 9,388 27,768 0.338
Ballerup 18,538 48,449 0.383
Brøndby 12,763 35,224 0.362
Gentofte 29,285 75,112 0.390
Gladsaxe 23,904 69,552 0.344
Glostrup 8,705 22,842 0.381
Herlev 10,757 28,900 0.372
Hvidovre 18,137 53,492 0.339
Høje-Taastrup 20,01 50,826 0.394
Ishøj 8,154 22,959 0.355
Lyngby-Taarbæk 20,931 56,105 0.373
Rødovre 14,053 40,357 0.348
Vallensbæk 6,477 16,655 0.389
Allerød 11,882 25,686 0.463
... ... ... ...

Dataset #3: FORMUE2

The third dataset is "FORMUE2: Familiefordelt nettoformue efter område og komponenttype" - Fortune distributed by family based on area and type of asset. For this dataset we used the raw numbers from year 2019.

Municipality Family Fortune
København 1,534,339
Frederiksberg 2,727,068
Dragør 4,165,247
Tårnby 2,406,733
Albertslund 1,616,375
Ballerup 2,162,556
Brøndby 1,641,361
Gentofte 6,600,417
Gladsaxe 2,366,187
Glostrup 1,886,689
Herlev 2,044,867
Hvidovre 2,017,982
Høje-Taastrup 2,005,200
Ishøj 1,512,444
Lyngby-Taarbæk 4,253,608
Rødovre 1,959,823
Vallensbæk 2,775,709
Allerød 4,037,498
... ...

Dataset #4: FOLK1A

The fourth data set we used was "FOLK1A: Folketal den 1. i kvartalet efter område, køn, alder og civilstand" - Number of citizens 1st day pr. quarter based on area, sex, age and civil status. We used this dataset to calculate the pr. citizen values.

Municipality Population
København 627,321
Frederiksberg 104,225
Dragør 14,365
Tårnby 42,998
Albertslund 27,768
Ballerup 48,449
Brøndby 35,224
Gentofte 75,112
Gladsaxe 69,552
Glostrup 22,842
Herlev 28,900
Hvidovre 53,492
Høje-Taastrup 50,826
Ishøj 22,959
Lyngby-Taarbæk 56,105
Rødovre 40,357
Vallensbæk 16,655
Allerød 25,686
... ...

Combining Datasets

To combine the 4 different views we got, we mapped them to a common range of 0-100. We then weighted them like this: Theft = 2, Money related crimes = 2, Collection of vehicles = 1, Family fortune = 1. This collective value is then remapped into the common range of 0-100 once again. This is our algorithm.

pie chart of weights

Section #3


Have the Danes Become More Greedy?

Using data from Statistics Denmark (Danmark Statistik) we decided to examine if the danes have become more greedy over the past years? We used the datasets:

Dataset #1: STRAF11
Dataset #2: BIL54
Dataset #3: FORMUE2

Money and Tax Related Crimes

graph over crimes

Collection of Vehicles

graph over cars

Family Fortune

graph over fortune
graph monster
Compairing the Graphs
By compairing the graphs, the danes have become more greedy over the last few years. Even though the pandemic was raging the danes carried on with their selfish desire of wanting more. What a shame?

Section #4

Choropleth map

Opt Out of Danish Church

This map shows how religious the Danish citizens are, or the lack of it. The yellow spots indicate people unsubscribing to the Danish church. Is there a correlation between committing a sin of greed and how detached one is, to the church? Not strong, although interesting.



Section #5


The Greedy Team

caroline mugshot






Act of greed

One night some years ago I stole a French bulldog. I brought him home because I wanted him. Luckily it wasn’t a real dog. It was a porcelain dog.

caroline mugshot






Act of greed

My name is Cornelius, and when I was 15 years old I committed a crime in the name of greed. I stole approximately 150kr worth of liquorice. I walked around Aldi with my friends, and when we got to the counter, the cashier already knew - I got busted. I was not good apparently.

caroline mugshot






Act of greed

I borrowed my parents rejsekort without paying.

caroline mugshot






Act of greed

When I was about 10 years old I committed a crime.
On a trip to a “Legeland” with the after-school-club for primary school kids I played the arcade machine where you can win Toys and teddybears. After losing all my pocket money to the machine I got greedy and stuck my arm in the machine to get a toy out. I ended up stealing a teddy bear. Eventually a pedagogue busted me.