Information about the municipality Brunn:

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

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Population numbers in the municipality Brunn for the years 2012 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 Brunn
Map of Rural district Mecklenburgische Seenplatte with the population per municipality.Municipality Brunn 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 Mecklenburgische Seenplatte with the population per municipality.Municipality Brunn is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Nossendorf, 2: municipality Kletzin, 3: municipality city Demmin, 4: municipality city Dargun, 5: municipality Warrenzin ...Show more... Map of Rural district Mecklenburgische Seenplatte with the population per municipality.Municipality Brunn is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Nossendorf, 2: municipality Kletzin, 3: municipality city Demmin, 4: municipality city Dargun, 5: municipality Warrenzin, 6: municipality Siedenbrünzow, 7: municipality Schönfeld, 8: municipality Utzedel, 9: municipality Verchen, 10: municipality Beggerow, 11: municipality city Neukalen, 12: municipality Bartow, 13: municipality Hohenmocker, 14: municipality Meesiger, 15: municipality Borrentin, 16: municipality Sarow, 17: municipality Sommersdorf, 18: municipality Breest, 19: municipality Hohenbollentin, 20: municipality Gnevkow, 21: municipality Golchen, 22: municipality Kummerow, 23: municipality Altenhagen, 24: municipality Lindenberg, 25: municipality Burow, 26: municipality Gültz, 27: municipality Grammentin, 28: municipality Kentzlin, 29: municipality city Malchin, 30: municipality Werder, 31: municipality Siedenbollentin, 32: municipality Kriesow, 33: municipality Tützpatz, 34: municipality Grapzow, 35: municipality Röckwitz, 36: municipality Pripsleben, 37: municipality city Stavenhagen, 38: municipality Ivenack, 39: municipality Beseritz, 40: municipality city Altentreptow, 41: municipality Basedow, 42: municipality Duckow, 43: municipality Grischow, 44: municipality Gülzow, 45: municipality Wolde, 46: municipality Gielow, 47: municipality Brunn, 48: municipality Ritzerow, 49: municipality Vollrathsruhe, 50: municipality Jürgenstorf, 51: municipality Wildberg, 52: municipality city Friedland, 53: municipality Neddemin, 54: municipality Galenbeck, 55: municipality Datzetal, 56: municipality Groß Teetzleben, 57: municipality Zettemin, 58: municipality Knorrendorf, 59: municipality Moltzow, 60: municipality Faulenrost, 61: municipality Staven, 62: municipality Genzkow, 63: municipality Klocksin, 64: municipality Briggow, 65: municipality Kittendorf, 66: municipality Neverin, 67: municipality Breesen, 68: municipality Trollenhagen, 69: municipality Rosenow, 70: municipality Woggersin, 71: municipality Hohen Wangelin, 72: municipality Bredenfelde, 73: municipality Neuenkirchen, 74: municipality Peenehagen, 75: municipality Zirzow, 76: municipality Varchentin, 77: municipality Schönbeck, 78: municipality Mölln, 79: municipality Grabowhöfe, 80: municipality Blankenhof, 81: municipality Schönhausen, 82: municipality Voigtsdorf, 83: municipality Sponholz, 84: municipality Kublank, 85: municipality Torgelow am See, 86: municipality Nossentiner Hütte, 87: municipality Groß Plasten, 88: municipality Jabel, 89: municipality city Neubrandenburg, 90: municipality Möllenhagen, 91: municipality Groß Miltzow, 92: municipality Pragsdorf, 93: municipality Wulkenzin, 94: municipality Kuckssee, 95: municipality Neetzka, 96: municipality Alt Schwerin, 97: municipality Cölpin, 98: municipality Silz, 99: municipality city Penzlin, 100: municipality Schloen-Dratow, 101: municipality Ankershagen, 102: municipality Lindetal, 103: municipality city Waren (Müritz), 104: municipality city Malchow, 105: municipality Petersdorf, 106: municipality Göhren-Lebbin, 107: municipality city Burg Stargard, 108: municipality Klink, 109: municipality Holldorf, 110: municipality Kargow, 111: municipality Groß Nemerow, 112: municipality Penkow, 113: municipality city Woldegk, 114: municipality Hohenzieritz, 115: municipality Sietow, 116: municipality Klein Vielen, 117: municipality Zislow, 118: municipality Walow, 119: municipality Kratzeburg, 120: municipality Fünfseen, 121: municipality Gotthun, 122: municipality Blumenholz, 123: municipality Möllenbeck, 124: municipality Groß Kelle, 125: municipality Blankensee, 126: municipality Leizen, 127: municipality Ludorf, 128: municipality Stuer, 129: municipality city Röbel/Müritz, 130: municipality Rechlin, 131: municipality Altenhof, 132: municipality Carpin, 133: municipality Bütow, 134: municipality Grünow, 135: municipality city Neustrelitz, 136: municipality Fincken, 137: municipality Bollewick, 138: municipality Vipperow, 139: municipality Feldberger Seenlandschaft, 140: municipality Userin, 141: municipality Melz, 142: municipality Zepkow, 143: municipality Massow, 144: municipality Priborn, 145: municipality city Mirow, 146: municipality Wredenhagen, 147: municipality Wokuhl-Dabelow, 148: municipality Lärz, 149: municipality Grabow-Below, 150: municipality Buchholz, 151: municipality Kieve, 152: municipality Godendorf, 153: municipality city Wesenberg, 154: municipality Priepert, 155: municipality Wustrow, 156: municipality Schwarz ...Show less...

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

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Municipality Brunn, 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 Brunn

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Municipality Brunn, 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 Brunn.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businessesno dataNumber2015
Active personsno dataNumber2015
Gross wagesno dataEuro2015
DwellingsValueUnitYear
Houses 1 room8Number2019
Houses 2 rooms52Number2019
Houses 3 rooms89Number2019
Houses 4 rooms84Number2019
Houses 5 rooms114Number2019
Houses 6 rooms99Number2019
Houses 7+ rooms 69Number2019
Houses 1-2 rooms60Number2019
Houses 3-4 rooms173Number2019
Houses 5+ rooms282Number2019
1-2 rooms12%Percentage2019
3-4 rooms34%Percentage2019
5+ rooms55%Percentage2019
ElectionsValueUnitYear
Voters Bundestag843,00Number2017
Voter turnout Bundestag65Number2017
Votes valid Bundestag534Number2017
Votes Bundestag CDU/CSU220Number2017
Votes Bundestag SPD63Number2017
Votes Bundestag GRÜNE7Number2017
Votes Bundestag FDP34Number2017
Votes Bundestag DIE LINKE77Number2017
Votes Bundestag AfD113Number2017
Votes Bundestag other parties20Number2017
Votes Bundestag total534Number2017
% Votes Bundestag CDU/CSU26%Percentage2017
% Votes Bundestag SPD7%Percentage2017
% Votes Bundestag GRÜNE1%Percentage2017
% Votes Bundestag FDP4%Percentage2017
% Votes Bundestag DIE LINKE9%Percentage2017
% Votes Bundestag AfD13%Percentage2017
% Votes Bundestag other parties2%Percentage2017
EmploymentValueUnitYear
Employees435Number2019
Employees male213Number2019
Employees female222Number2019
Employees foreigner4Number2019
Employees male foreigner4Number2019
Employees female foreigner0Number2019
Unemployed43Number2018
Unemployed foreigners1Number2018
Unemployed severely disabled5Number2018
Unemployed 15-201Number2018
Unemployed 15-252Number2018
Unemployed 55-6514Number2018
Unemployed long-term17Number2018
% 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-term2%Percentage of the population2018
IncomeValueUnitYear
Income receivers429Number2015
Income total€13.302Euro2015
Income tax€1.663Euro2015
PopulationValueUnitYear
Population1.035Number2019
Men508Number2019
Women527Number2019
% Men49%Percentage2019
% Women51%Percentage2019
0-18183Number2019
18-3072Number2019
30-45196Number2019
45-60269Number2019
18-60537Number2019
60-75233Number2019
60+315Number2019
Average age45Average number2019
Average age male45Average number2019
Average age female46Average number2019
Births8Number2018
Births male6Number2018
Births female2Number2018
1K Births8Number per 1000 inhabitants2018
Deaths9Number2018
Deaths male4Number2018
Deaths female5Number2018
1K Deaths9Number2018
0-324Number2019
Girls 0-313Number2019
Boys 0-311Number2019
3-637Number2019
Girls 3-617Number2019
Boys 3-620Number2019
6-1042Number2019
10-1547Number2019
15-1833Number2019
18-2017Number2019
20-2525Number2019
25-3030Number2019
30-3575Number2019
35-4052Number2019
40-4569Number2019
45-5077Number2019
50-5576Number2019
55-60116Number2019
60-65101Number2019
65-75132Number2019
Women 65-7060Number2019
Men 65-7072Number2019
75+82Number2019
Women 75+49Number2019
Men 75+33Number2019
% 0-1010%Percentage2019
% 10-188%Percentage2019
% 18-307%Percentage2019
% 30-4519%Percentage2019
% 45-6026%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 code130715157019Code2019
Region code 8 digits13071019Code13071019
Sorting code130715157019Code130715157019
Sorting code 8 digits13071019Code13071019
Region nameBrunnName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality BrunnName2019
Region name in GermanGemeinde BrunnName2019
Direct subregionsno dataNumber2019
NUTS codeDE80JCode2019
Area48Area in km²2019
ReligionValueUnitYear
Roman Catholic churchno dataNumberno data
Protestant churchno dataNumberno data
Other or noneno dataNumberno data
% Roman Catholic churchno dataPercentageno data
% Protestant churchno dataPercentageno data
% Other or noneno dataPercentageno data
Roman Catholic church Germanno dataNumberno data
Protestant church Germanno dataNumberno data
Other or none Germanno dataNumberno data
% Roman Catholic church Germanno dataPercentageno data
% Protestant church Germanno dataPercentageno data
% Other or none German Foreignno dataPercentageno data
Roman Catholic church Foreignno dataNumberno data
Protestant church Foreignno dataNumberno data
Other or none Foreignno dataNumberno data
% Roman Catholic church Foreignno dataPercentageno data
% Protestant church Foreignno dataPercentageno data
% Other or none Foreignno dataPercentageno data
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.