Information about the independent city district Bielefeld:

Information about the independent city district Bielefeld:

View the information on over 100 topics about the independent city district Bielefeld! 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 Bielefeld! 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 Bielefeld

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Population numbers in the independent city district Bielefeld 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 Bielefeld
Map of State North Rhine-Westphalia with the population per district.District Bielefeld 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 Bielefeld 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 Bielefeld 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 Bielefeld

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Independent city district Bielefeld, 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 Bielefeld

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Independent city district Bielefeld, 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 Bielefeld.

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 Bielefeld. Select a category to display the related topics:

BusinessValueUnitYear
Businesses170Number2017
Active persons21.473Number2017
Gross wages€1.006.348Euro2017
DwellingsValueUnitYear
Houses 1 room7.264Number2019
Houses 2 rooms20.183Number2019
Houses 3 rooms43.040Number2019
Houses 4 rooms47.497Number2019
Houses 5 rooms26.473Number2019
Houses 6 rooms13.963Number2019
Houses 7+ rooms 12.990Number2019
Houses 1-2 rooms27.447Number2019
Houses 3-4 rooms90.537Number2019
Houses 5+ rooms53.426Number2019
1-2 rooms16%Percentage2019
3-4 rooms53%Percentage2019
5+ rooms31%Percentage2019
ElectionsValueUnitYear
Voters Bundestag237576,00Number2017
Voter turnout Bundestag76Number2017
Votes valid Bundestag177.777Number2017
Votes Bundestag CDU/CSU48.916Number2017
Votes Bundestag SPD45.103Number2017
Votes Bundestag GRÜNE19.748Number2017
Votes Bundestag FDP20.524Number2017
Votes Bundestag DIE LINKE19.943Number2017
Votes Bundestag AfD15.987Number2017
Votes Bundestag other parties7.556Number2017
Votes Bundestag total177.777Number2017
% Votes Bundestag CDU/CSU21%Percentage2017
% Votes Bundestag SPD19%Percentage2017
% Votes Bundestag GRÜNE8%Percentage2017
% Votes Bundestag FDP9%Percentage2017
% Votes Bundestag DIE LINKE8%Percentage2017
% Votes Bundestag AfD7%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employees128.488Number2019
Employees male69.504Number2019
Employees female58.984Number2019
Employees foreigner16.055Number2019
Employees male foreigner10.048Number2019
Employees female foreigner6.007Number2019
Unemployed12.552Number2018
Unemployed foreigners4.094Number2018
Unemployed severely disabled741Number2018
Unemployed 15-20199Number2018
Unemployed 15-251.114Number2018
Unemployed 55-652.338Number2018
Unemployed long-term5.527Number2018
% Unemployed4%Percentage2018
% Unemployed foreigners1%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 receivers158.302Number2015
Income total€5.979.119Euro2015
Income tax€1.075.327Euro2015
PopulationValueUnitYear
Population333.786Number2019
Men161.078Number2019
Women172.708Number2019
% Men48%Percentage2019
% Women52%Percentage2019
0-1857.293Number2019
18-3055.534Number2019
30-4564.013Number2019
45-6070.856Number2019
18-60190.403Number2019
60-7549.044Number2019
60+86.090Number2019
Average age43Average number2019
Average age male42Average number2019
Average age female44Average number2019
Births3.418Number2018
Births male1.732Number2018
Births female1.686Number2018
1K Births10Number per 1000 inhabitants2018
Deaths3.623Number2018
Deaths male1.746Number2018
Deaths female1.877Number2018
1K Deaths11Number2018
0-310.142Number2019
Girls 0-35.036Number2019
Boys 0-35.106Number2019
3-69.430Number2019
Girls 3-64.565Number2019
Boys 3-64.865Number2019
6-1012.176Number2019
10-1515.773Number2019
15-189.772Number2019
18-207.652Number2019
20-2522.925Number2019
25-3024.957Number2019
30-3523.577Number2019
35-4020.970Number2019
40-4519.466Number2019
45-5021.997Number2019
50-5525.334Number2019
55-6023.525Number2019
60-6519.711Number2019
65-7529.333Number2019
Women 65-7015.792Number2019
Men 65-7013.541Number2019
75+37.046Number2019
Women 75+22.440Number2019
Men 75+14.606Number2019
% 0-1010%Percentage2019
% 10-188%Percentage2019
% 18-3017%Percentage2019
% 30-4519%Percentage2019
% 45-6021%Percentage2019
% 60+26%Percentage2019
Real estateValueUnitYear
Property tax A revenue€305.792Euro2018
Property tax B revenue€78.852.686Euro2018
Trade tax actual revenue€233.189.767Euro2018
Property tax A basic amount€101.931Euro2018
Property tax B basic amount€11.947.377Euro2018
Trade tax basic amount€48.581.201Euro2018
Property tax A rate€300Euro2018
Property tax B rate€660Euro2018
Trade tax rate€480Euro2018
Real tax raising force€252.101.454Euro2018
Trade tax levy€35.269.952Euro2018
Trade tax net€197.919.815Euro2018
Community share in income tax€147.309.435Euro2018
Community share in sales tax€38.863.879Euro2018
Tax revenue€403.004.816Euro2018
RegionalValueUnitYear
Region code05711Code2019
Region code 8 digits05711Code05711
Sorting code057110000000Code057110000000
Sorting code 8 digits05711000Code05711000
Region nameBielefeldName2019
Regional level4Categorical type2019
Region typeDistrictCategorical type2019
Region type detailindependent city districtCategorical type2019
Region name with typeindependent city district BielefeldName2019
Region name in GermanKreisfreie Stadt BielefeldName2019
Direct subregions1Number2019
NUTS codeDEA41Code2019
Area259Area in km²2019
ReligionValueUnitYear
Roman Catholic church53.197Number2011
Protestant church134.832Number2011
Other or none138.841Number2011
% Roman Catholic church16%Percentage2011
% Protestant church41%Percentage2011
% Other or none42%Percentage2011
Roman Catholic church German48.225Number2011
Protestant church German133.962Number2011
Other or none German108.015Number2011
% Roman Catholic church German17%Percentage2011
% Protestant church German46%Percentage2011
% Other or none German Foreign37%Percentage2011
Roman Catholic church Foreign4.972Number2011
Protestant church Foreign870Number2011
Other or none Foreign30.826Number2011
% Roman Catholic church Foreign14%Percentage2011
% Protestant church Foreign2%Percentage2011
% Other or none Foreign84%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.