Information about the municipality Kuhfelde:

Population numbers per year
The number of inhabitants in the municipality Kuhfelde

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Population numbers in the municipality Kuhfelde 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 Kuhfelde
Map of Rural district Altmarkkreis Salzwedel with the population per municipality.Municipality Kuhfelde 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 Rural district Altmarkkreis Salzwedel with the population per municipality.Municipality Kuhfelde is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality city Arendsee (Altmark), 2: municipality city Salzwedel, 3: municipality Dähre, 4: municipality Wallstawe, 5: municipality Kuhfelde ...Show more... Map of Rural district Altmarkkreis Salzwedel with the population per municipality.Municipality Kuhfelde is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality city Arendsee (Altmark), 2: municipality city Salzwedel, 3: municipality Dähre, 4: municipality Wallstawe, 5: municipality Kuhfelde, 6: municipality Diesdorf, 7: municipality Apenburg-Winterfeld, 8: municipality Rohrberg, 9: municipality city Kalbe (Milde), 10: municipality Beetzendorf, 11: municipality Jübar, 12: municipality city Klötze, 13: municipality city Gardelegen ...Show less...

Population per age group
The percentage of inhabitants per age group in the municipality Kuhfelde

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Municipality Kuhfelde, 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 municipality Kuhfelde

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Municipality Kuhfelde, 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 municipality Kuhfelde.

Data about more than 100 topics!

The table below shows data for more than 100 topics as most recently available for the municipality Kuhfelde. Select a category to display the related topics:

BusinessValueUnitYear
Businessesno dataNumber2015
Active personsno dataNumber2015
Gross wagesno dataEuro2015
DwellingsValueUnitYear
Houses 1 room0Number2019
Houses 2 rooms12Number2019
Houses 3 rooms76Number2019
Houses 4 rooms129Number2019
Houses 5 rooms121Number2019
Houses 6 rooms107Number2019
Houses 7+ rooms 104Number2019
Houses 1-2 rooms12Number2019
Houses 3-4 rooms205Number2019
Houses 5+ rooms332Number2019
1-2 rooms2%Percentage2019
3-4 rooms37%Percentage2019
5+ rooms60%Percentage2019
ElectionsValueUnitYear
Voters Bundestag894,00Number2017
Voter turnout Bundestag63Number2017
Votes valid Bundestag554Number2017
Votes Bundestag CDU/CSU204Number2017
Votes Bundestag SPD91Number2017
Votes Bundestag GRÜNE22Number2017
Votes Bundestag FDP35Number2017
Votes Bundestag DIE LINKE81Number2017
Votes Bundestag AfD97Number2017
Votes Bundestag other parties24Number2017
Votes Bundestag total554Number2017
% Votes Bundestag CDU/CSU23%Percentage2017
% Votes Bundestag SPD10%Percentage2017
% Votes Bundestag GRÜNE2%Percentage2017
% Votes Bundestag FDP4%Percentage2017
% Votes Bundestag DIE LINKE9%Percentage2017
% Votes Bundestag AfD11%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employees517Number2019
Employees male282Number2019
Employees female235Number2019
Employees foreigner21Number2019
Employees male foreigner0Number2019
Employees female foreigner0Number2019
Unemployed41Number2018
Unemployed foreigners1Number2018
Unemployed severely disabled2Number2018
Unemployed 15-200Number2018
Unemployed 15-252Number2018
Unemployed 55-6513Number2018
Unemployed long-term14Number2018
% Unemployed4%Percentage2018
% Unemployed foreigners0%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-term1%Percentage of the population2018
IncomeValueUnitYear
Income receivers516Number2015
Income total€16.199Euro2015
Income tax€2.144Euro2015
PopulationValueUnitYear
Population1.084Number2019
Men549Number2019
Women535Number2019
% Men51%Percentage2019
% Women49%Percentage2019
0-18167Number2019
18-3093Number2019
30-45185Number2019
45-60319Number2019
18-60597Number2019
60-75223Number2019
60+320Number2019
Average age46Average number2019
Average age male45Average number2019
Average age female48Average number2019
Births4Number2018
Births male1Number2018
Births female3Number2018
1K Births4Number per 1000 inhabitants2018
Deaths15Number2018
Deaths male12Number2018
Deaths female3Number2018
1K Deaths14Number2018
0-325Number2019
Girls 0-311Number2019
Boys 0-314Number2019
3-628Number2019
Girls 3-613Number2019
Boys 3-615Number2019
6-1036Number2019
10-1547Number2019
15-1831Number2019
18-2021Number2019
20-2527Number2019
25-3045Number2019
30-3558Number2019
35-4060Number2019
40-4567Number2019
45-5071Number2019
50-55124Number2019
55-60124Number2019
60-6587Number2019
65-75136Number2019
Women 65-7073Number2019
Men 65-7063Number2019
75+97Number2019
Women 75+59Number2019
Men 75+38Number2019
% 0-108%Percentage2019
% 10-187%Percentage2019
% 18-309%Percentage2019
% 30-4517%Percentage2019
% 45-6029%Percentage2019
% 60+30%Percentage2019
Real estateValueUnitYear
Property tax A revenueno dataEurono data
Property tax B revenueno dataEurono data
Trade tax actual revenueno dataEurono data
Property tax A basic amountno dataEurono data
Property tax B basic amountno dataEurono data
Trade tax basic amountno dataEurono data
Property tax A rateno dataEurono data
Property tax B rateno dataEurono data
Trade tax rateno dataEurono data
Real tax raising forceno dataEurono data
Trade tax levyno dataEurono data
Trade tax netno dataEurono data
Community share in income taxno dataEurono data
Community share in sales taxno dataEurono data
Tax revenueno dataEurono data
RegionalValueUnitYear
Region code150815051290Code2019
Region code 8 digits15081290Code15081290
Sorting code150815051290Code150815051290
Sorting code 8 digits15081290Code15081290
Region nameKuhfeldeName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality KuhfeldeName2019
Region name in GermanGemeinde KuhfeldeName2019
Direct subregionsno dataNumber2019
NUTS codeDEE04Code2019
Area46Area in km²2019
ReligionValueUnitYear
Roman Catholic church18Number2011
Protestant church345Number2011
Other or none808Number2011
% Roman Catholic church2%Percentage2011
% Protestant church29%Percentage2011
% Other or none69%Percentage2011
Roman Catholic church German18Number2011
Protestant church German342Number2011
Other or none German799Number2011
% Roman Catholic church German2%Percentage2011
% Protestant church German30%Percentage2011
% Other or none German Foreign69%Percentage2011
Roman Catholic church Foreign0Number2011
Protestant church Foreign3Number2011
Other or none Foreign9Number2011
% Roman Catholic church Foreign0%Percentage2011
% Protestant church Foreign25%Percentage2011
% Other or none Foreign75%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.

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