Information about the independent city district Dortmund:

Information about the independent city district Dortmund:

View the information on over 100 topics about the independent city district Dortmund! With charts, links to more information & an overview of all figures in 1 table.
View the information on over 100 topics about the independent city district Dortmund! With charts, links to more information & an overview of all figures in 1 table.
Population numbers per year
The number of inhabitants in the independent city district Dortmund

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Population numbers in the independent city district Dortmund for the years 2009 thru 2019.

The number of inhabitants is the number of persons as registered in the population register on January 1st.

Population at the map of Dortmund
Map of State North Rhine-Westphalia with the population per district.District Dortmund is highlighted with a red edge.. This page shows a lot of information about residents (such as the distribution by age groups, family composition, gender, native or German with an immigration background, ...), homes (numbers, types, price development, use, type of property, ...) and more (car ownership, energy consumption, ...) based on open data from the German Federal Agency for Cartography, the Federal Statistical Office (DESTATIS), the Regional Statistical Offices and various other sources!

Map of State North Rhine-Westphalia with the population per district.District Dortmund is highlighted with a red edge. The numbers at the map represent the following districts: 1: district Minden-Lübbecke, 2: district Steinfurt, 3: district Herford, 4: independent city district Bielefeld, 5: district Lyppe ...Show more... Map of State North Rhine-Westphalia with the population per district.District Dortmund is highlighted with a red edge. The numbers at the map represent the following districts: 1: district Minden-Lübbecke, 2: district Steinfurt, 3: district Herford, 4: independent city district Bielefeld, 5: district Lyppe, 6: district Borken, 7: independent city district Münster, 8: district Gütersloh, 9: district Warendorf, 10: district Coesfeld, 11: district Höxter, 12: district Recklinghausen, 13: independent city district Hamm, 14: district Paderborn, 15: district Cleves, 16: district Wesel, 17: district Unna, 18: independent city district Bottrop, 19: district Soest, 20: independent city district Gelsenkirchen, 21: independent city district Herne, 22: independent city district Dortmund, 23: independent city district Oberhausen, 24: independent city district Bochum, 25: independent city district Duisburg, 26: independent city district Essen, 27: independent city district Mülheim an der Ruhr, 28: independent city district Hagen, 29: district Ennepe-Ruhr-Kreis, 30: independent city district Krefeld, 31: district Hochsauerlandkreis, 32: district Viersen, 33: district Märkischer Kreis, 34: district Mettmann, 35: independent city district Wuppertal, 36: independent city district Düsseldorf, 37: independent city district Remscheid, 38: independent city district Mönchengladbach, 39: independent city district Solingen, 40: district Rhein-Kreis Neuss, 41: district Olpe, 42: independent city district Leverkusen, 43: district Heinsberg, 44: district Rheinisch-Bergischer Kreis, 45: district Oberbergischer Kreis, 46: independent city district Cologne, 47: district Siegen-Wittgenstein, 48: district Rhein-Erft-Kreis, 49: district Düren, 50: district Rhein-Sieg-Kreis, 51: district Städteregion Aachen, 52: independent city district Bonn, 53: district Euskirchen ...Show less...

Population per age group
The percentage of inhabitants per age group in the independent city district Dortmund

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Independent city district Dortmund, 2019, age groups.

Population, age groups: percentage of inhabitants per age category.

The number of rooms per house (dwelling)
The number of rooms of the houses in the independent city district Dortmund

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Independent city district Dortmund, 2019, number of rooms per house.

The percentage shows the relative share of houses per category based on the numer of rooms: 1 to 2 rooms, 3 to 4 rooms or 5 rooms or more. This is based on the total number of rooms as identified for all dwellings in the independent city district Dortmund.

Data about more than 100 topics!

The table below shows data for more than 100 topics as most recently available for the independent city district Dortmund. Select a category to display the related topics:

BusinessValueUnitYear
Businesses173Number2017
Active persons20.620Number2017
Gross wages€1.079.243Euro2017
DwellingsValueUnitYear
Houses 1 room12.597Number2019
Houses 2 rooms44.717Number2019
Houses 3 rooms94.342Number2019
Houses 4 rooms89.346Number2019
Houses 5 rooms40.390Number2019
Houses 6 rooms19.949Number2019
Houses 7+ rooms 15.614Number2019
Houses 1-2 rooms57.314Number2019
Houses 3-4 rooms183.688Number2019
Houses 5+ rooms75.953Number2019
1-2 rooms18%Percentage2019
3-4 rooms58%Percentage2019
5+ rooms24%Percentage2019
ElectionsValueUnitYear
Voters Bundestag414616,00Number2017
Voter turnout Bundestag72Number2017
Votes valid Bundestag297.339Number2017
Votes Bundestag CDU/CSU72.789Number2017
Votes Bundestag SPD92.937Number2017
Votes Bundestag GRÜNE24.892Number2017
Votes Bundestag FDP32.596Number2017
Votes Bundestag DIE LINKE28.430Number2017
Votes Bundestag AfD30.707Number2017
Votes Bundestag other parties14.988Number2017
Votes Bundestag total297.339Number2017
% Votes Bundestag CDU/CSU18%Percentage2017
% Votes Bundestag SPD22%Percentage2017
% Votes Bundestag GRÜNE6%Percentage2017
% Votes Bundestag FDP8%Percentage2017
% Votes Bundestag DIE LINKE7%Percentage2017
% Votes Bundestag AfD7%Percentage2017
% Votes Bundestag other parties4%Percentage2017
EmploymentValueUnitYear
Employees215.842Number2019
Employees male119.310Number2019
Employees female96.532Number2019
Employees foreigner31.498Number2019
Employees male foreigner20.775Number2019
Employees female foreigner10.723Number2019
Unemployed32.033Number2018
Unemployed foreigners11.517Number2018
Unemployed severely disabled2.674Number2018
Unemployed 15-20552Number2018
Unemployed 15-252.727Number2018
Unemployed 55-655.414Number2018
Unemployed long-term12.906Number2018
% Unemployed5%Percentage2018
% Unemployed foreigners2%Percentage of the population2018
% Unemployed severely disabled0%Percentage of the population2018
% Unemployed 15-200%Percentage of the population2018
% Unemployed 15-250%Percentage of the population2018
% Unemployed 55-651%Percentage of the population2018
% Unemployed long-term2%Percentage of the population2018
IncomeValueUnitYear
Income receivers274.941Number2015
Income total€9.376.172Euro2015
Income tax€1.619.242Euro2015
PopulationValueUnitYear
Population587.010Number2019
Men288.386Number2019
Women298.624Number2019
% Men49%Percentage2019
% Women51%Percentage2019
0-1895.527Number2019
18-3093.954Number2019
30-45112.299Number2019
45-60128.337Number2019
18-60334.590Number2019
60-7593.072Number2019
60+156.893Number2019
Average age44Average number2019
Average age male42Average number2019
Average age female45Average number2019
Births5.898Number2018
Births male3.000Number2018
Births female2.898Number2018
1K Births10Number per 1000 inhabitants2018
Deaths7.040Number2018
Deaths male3.448Number2018
Deaths female3.592Number2018
1K Deaths12Number2018
0-317.540Number2019
Girls 0-38.626Number2019
Boys 0-38.914Number2019
3-616.302Number2019
Girls 3-68.063Number2019
Boys 3-68.239Number2019
6-1020.060Number2019
10-1525.603Number2019
15-1816.022Number2019
18-2011.989Number2019
20-2538.180Number2019
25-3043.785Number2019
30-3540.436Number2019
35-4037.559Number2019
40-4534.304Number2019
45-5039.349Number2019
50-5546.209Number2019
55-6042.779Number2019
60-6536.684Number2019
65-7556.388Number2019
Women 65-7030.221Number2019
Men 65-7026.167Number2019
75+63.821Number2019
Women 75+38.634Number2019
Men 75+25.187Number2019
% 0-109%Percentage2019
% 10-187%Percentage2019
% 18-3016%Percentage2019
% 30-4519%Percentage2019
% 45-6022%Percentage2019
% 60+27%Percentage2019
Real estateValueUnitYear
Property tax A revenue€177.750Euro2018
Property tax B revenue€122.062.775Euro2018
Trade tax actual revenue€366.344.298Euro2018
Property tax A basic amount€54.692Euro2018
Property tax B basic amount€20.010.291Euro2018
Trade tax basic amount€75.534.907Euro2018
Property tax A rate€325Euro2018
Property tax B rate€610Euro2018
Trade tax rate€485Euro2018
Real tax raising force€398.394.173Euro2018
Trade tax levy€54.838.819Euro2018
Trade tax net€311.505.479Euro2018
Community share in income tax€251.143.670Euro2018
Community share in sales tax€59.497.133Euro2018
Tax revenue€654.196.157Euro2018
RegionalValueUnitYear
Region code05913Code2019
Region code 8 digits05913Code05913
Sorting code059130000000Code059130000000
Sorting code 8 digits05913000Code05913000
Region nameDortmundName2019
Regional level4Categorical type2019
Region typeDistrictCategorical type2019
Region type detailindependent city districtCategorical type2019
Region name with typeindependent city district DortmundName2019
Region name in GermanKreisfreie Stadt DortmundName2019
Direct subregions1Number2019
NUTS codeDEA52Code2019
Area281Area in km²2019
ReligionValueUnitYear
Roman Catholic church162.520Number2011
Protestant church184.189Number2011
Other or none224.434Number2011
% Roman Catholic church28%Percentage2011
% Protestant church32%Percentage2011
% Other or none39%Percentage2011
Roman Catholic church German149.673Number2011
Protestant church German182.919Number2011
Other or none German168.665Number2011
% Roman Catholic church German30%Percentage2011
% Protestant church German36%Percentage2011
% Other or none German Foreign34%Percentage2011
Roman Catholic church Foreign12.847Number2011
Protestant church Foreign1.270Number2011
Other or none Foreign55.769Number2011
% Roman Catholic church Foreign18%Percentage2011
% Protestant church Foreign2%Percentage2011
% Other or none Foreign80%Percentage2011
Open data sources used

Data is used from multiple German open data providers. See this description of the sources with the definitions of all regional topics.

Sources & definitions
Under development
Work is in progress to add more information to this page

This page will be further expanded with more topics in clear graphs. This will be done in several iterations in the coming weeks.