Information about the municipality Maikammer:

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

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Population numbers in the municipality Maikammer 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 Maikammer
Map of Rural district Südliche Weinstraße with the population per municipality.Municipality Maikammer 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 Südliche Weinstraße with the population per municipality.Municipality Maikammer is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Kirrweiler (Pfalz), 2: municipality Maikammer, 3: municipality Sankt Martin, 4: municipality Gommersheim, 5: municipality Altdorf ...Show more... Map of Rural district Südliche Weinstraße with the population per municipality.Municipality Maikammer is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Kirrweiler (Pfalz), 2: municipality Maikammer, 3: municipality Sankt Martin, 4: municipality Gommersheim, 5: municipality Altdorf, 6: municipality city Edenkoben, 7: municipality Venningen, 8: municipality Böbingen, 9: municipality Rhodt unter Rietburg, 10: municipality Hainfeld, 11: municipality Edesheim, 12: municipality Weyher in der Pfalz, 13: municipality Ramberg, 14: municipality Freimersheim (Pfalz), 15: municipality Großfischlingen, 16: municipality Roschbach, 17: municipality Burrweiler, 18: municipality Kleinfischlingen, 19: municipality Flemlingen, 20: municipality Dernbach, 21: municipality Gleisweiler, 22: municipality Walsheim, 23: municipality Böchingen, 24: municipality Albersweiler, 25: municipality Frankweiler, 26: municipality Eußerthal, 27: municipality Siebeldingen, 28: municipality Knöringen, 29: municipality Hochstadt (Pfalz), 30: municipality Essingen, 31: municipality city Annweiler am Trifels, 32: municipality Rinnthal, 33: municipality Birkweiler, 34: municipality Bornheim, 35: municipality Ranschbach, 36: municipality Wernersberg, 37: municipality Offenbach an der Queich, 38: municipality Leinsweiler, 39: municipality Ilbesheim bei Landau in der Pfalz, 40: municipality Völkersweiler, 41: municipality Eschbach, 42: municipality Waldrohrbach, 43: municipality Waldhambach, 44: municipality Impflingen, 45: municipality Göcklingen, 46: municipality Gossersweiler-Stein, 47: municipality Insheim, 48: municipality Herxheimweyher, 49: municipality Münchweiler am Klingbach, 50: municipality Herxheim bei Landau/Pfalz, 51: municipality Klingenmünster, 52: municipality Oberschlettenbach, 53: municipality Rohrbach, 54: municipality Heuchelheim-Klingen, 55: municipality Silz, 56: municipality Gleiszellen-Gleishorbach, 57: municipality Vorderweidenthal, 58: municipality Billigheim-Ingenheim, 59: municipality Pleisweiler-Oberhofen, 60: municipality Niederhorbach, 61: municipality Birkenhördt, 62: municipality city Bad Bergzabern, 63: municipality Barbelroth, 64: municipality Oberhausen, 65: municipality Hergersweiler, 66: municipality Kapellen-Drusweiler, 67: municipality Böllenborn, 68: municipality Dörrenbach, 69: municipality Dierbach, 70: municipality Oberotterbach, 71: municipality Niederotterbach, 72: municipality Schweigen-Rechtenbach, 73: municipality Schweighofen, 74: municipality Kapsweyer, 75: municipality Steinfeld ...Show less...

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

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Municipality Maikammer, 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 Maikammer

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Municipality Maikammer, 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 Maikammer.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businesses1Number2017
Active persons0Number2017
Gross wages€0Euro2017
DwellingsValueUnitYear
Houses 1 room60Number2019
Houses 2 rooms122Number2019
Houses 3 rooms333Number2019
Houses 4 rooms440Number2019
Houses 5 rooms459Number2019
Houses 6 rooms330Number2019
Houses 7+ rooms 457Number2019
Houses 1-2 rooms182Number2019
Houses 3-4 rooms773Number2019
Houses 5+ rooms1.246Number2019
1-2 rooms8%Percentage2019
3-4 rooms35%Percentage2019
5+ rooms57%Percentage2019
ElectionsValueUnitYear
Voters Bundestag3424,00Number2017
Voter turnout Bundestag76Number2017
Votes valid Bundestag1.723Number2017
Votes Bundestag CDU/CSU739Number2017
Votes Bundestag SPD301Number2017
Votes Bundestag GRÜNE159Number2017
Votes Bundestag FDP192Number2017
Votes Bundestag DIE LINKE96Number2017
Votes Bundestag AfD160Number2017
Votes Bundestag other parties76Number2017
Votes Bundestag total1.723Number2017
% Votes Bundestag CDU/CSU22%Percentage2017
% Votes Bundestag SPD9%Percentage2017
% Votes Bundestag GRÜNE5%Percentage2017
% Votes Bundestag FDP6%Percentage2017
% Votes Bundestag DIE LINKE3%Percentage2017
% Votes Bundestag AfD5%Percentage2017
% Votes Bundestag other parties2%Percentage2017
EmploymentValueUnitYear
Employees1.626Number2019
Employees male840Number2019
Employees female786Number2019
Employees foreigner151Number2019
Employees male foreigner99Number2019
Employees female foreigner52Number2019
Unemployed80Number2018
Unemployed foreigners25Number2018
Unemployed severely disabled7Number2018
Unemployed 15-202Number2018
Unemployed 15-259Number2018
Unemployed 55-6520Number2018
Unemployed long-term23Number2018
% Unemployed2%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 55-650%Percentage of the population2018
% Unemployed long-term1%Percentage of the population2018
IncomeValueUnitYear
Income receivers2.181Number2015
Income total€94.425Euro2015
Income tax€16.924Euro2015
PopulationValueUnitYear
Population4.336Number2019
Men2.143Number2019
Women2.193Number2019
% Men49%Percentage2019
% Women51%Percentage2019
0-18668Number2019
18-30496Number2019
30-45720Number2019
45-601.114Number2019
18-602.330Number2019
60-75808Number2019
60+1.338Number2019
Average age46Average number2019
Average age male45Average number2019
Average age female48Average number2019
Births43Number2018
Births male20Number2018
Births female23Number2018
1K Births10Number per 1000 inhabitants2018
Deaths41Number2018
Deaths male21Number2018
Deaths female20Number2018
1K Deaths9Number2018
0-3116Number2019
Girls 0-346Number2019
Boys 0-370Number2019
3-6110Number2019
Girls 3-652Number2019
Boys 3-658Number2019
6-10141Number2019
10-15184Number2019
15-18117Number2019
18-20111Number2019
20-25199Number2019
25-30186Number2019
30-35229Number2019
35-40240Number2019
40-45251Number2019
45-50272Number2019
50-55450Number2019
55-60392Number2019
60-65315Number2019
65-75493Number2019
Women 65-70251Number2019
Men 65-70242Number2019
75+530Number2019
Women 75+310Number2019
Men 75+220Number2019
% 0-108%Percentage2019
% 10-187%Percentage2019
% 18-3011%Percentage2019
% 30-4517%Percentage2019
% 45-6026%Percentage2019
% 60+31%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 rate€311Euro2018
Property tax B rateno dataEurono data
Trade tax rateno dataEurono data
Real tax raising forceno dataEurono data
Trade tax levy€443.624Euro2018
Trade tax net€2.044.048Euro2018
Community share in income taxno dataEurono data
Community share in sales taxno dataEurono data
Tax revenueno dataEurono data
RegionalValueUnitYear
Region code073375006052Code2019
Region code 8 digits07337052Code07337052
Sorting code073375006052Code073375006052
Sorting code 8 digits07337052Code07337052
Region nameMaikammerName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality MaikammerName2019
Region name in GermanGemeinde MaikammerName2019
Direct subregionsno dataNumber2019
NUTS codeDEB3HCode2019
Area14Area in km²2019
ReligionValueUnitYear
Roman Catholic church2.367Number2011
Protestant church1.015Number2011
Other or none847Number2011
% Roman Catholic church56%Percentage2011
% Protestant church24%Percentage2011
% Other or none20%Percentage2011
Roman Catholic church German2.295Number2011
Protestant church German1.015Number2011
Other or none German716Number2011
% Roman Catholic church German57%Percentage2011
% Protestant church German25%Percentage2011
% Other or none German Foreign18%Percentage2011
Roman Catholic church Foreign72Number2011
Protestant church Foreign0Number2011
Other or none Foreign131Number2011
% Roman Catholic church Foreign35%Percentage2011
% Protestant church Foreign0%Percentage2011
% Other or none Foreign65%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.