Information about the municipality city Neustadt-Glewe:

Population numbers per year
The number of inhabitants in the municipality city Neustadt-Glewe

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Population numbers in the municipality city Neustadt-Glewe 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 Neustadt-Glewe
Map of Rural district Ludwigslust-Parchim with the population per municipality.Municipality Neustadt-Glewe 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 Ludwigslust-Parchim with the population per municipality.Municipality Neustadt-Glewe is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Blankenberg, 2: municipality Kloster Tempzin, 3: municipality Dobin am See, 4: municipality Witzin, 5: municipality city Brüel ...Show more... Map of Rural district Ludwigslust-Parchim with the population per municipality.Municipality Neustadt-Glewe is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Blankenberg, 2: municipality Kloster Tempzin, 3: municipality Dobin am See, 4: municipality Witzin, 5: municipality city Brüel, 6: municipality city Sternberg, 7: municipality Mustin, 8: municipality Cambs, 9: municipality Kuhlen-Wendorf, 10: municipality Weitendorf, 11: municipality Borkow, 12: municipality Leezen, 13: municipality Langen Brütz, 14: municipality Dabel, 15: municipality Kobrow, 16: municipality Gneven, 17: municipality Hohen Pritz, 18: municipality Demen, 19: municipality Dobbertin, 20: municipality Wittenförden, 21: municipality Pinnow, 22: municipality Klein Rogahn, 23: municipality Barnin, 24: municipality Raben Steinfeld, 25: municipality Bülow, 26: municipality city Crivitz, 27: municipality Mestlin, 28: municipality Techentin, 29: municipality Zülow, 30: municipality city Zarrentin am Schaalsee, 31: municipality Stralendorf, 32: municipality city Goldberg, 33: municipality Pampow, 34: municipality Zölkow, 35: municipality Neu Poserin, 36: municipality Dümmer, 37: municipality Sukow, 38: municipality Plate, 39: municipality Zapel, 40: municipality Wittendörp, 41: municipality Warsow, 42: municipality Holthusen, 43: municipality Schossin, 44: municipality Friedrichsruhe, 45: municipality Obere Warnow, 46: municipality Lüttow-Valluhn, 47: municipality Passow, 48: municipality Gallin-Kuppentin, 49: municipality Lübesse, 50: municipality Tramm, 51: municipality Sülstorf, 52: municipality Werder, 53: municipality Hülseburg, 54: municipality Gammelin, 55: municipality Bandenitz, 56: municipality Kogel, 57: municipality Alt Zachun, 58: municipality Banzkow, 59: municipality Granzin, 60: municipality Gallin, 61: municipality Domsühl, 62: municipality Barkhagen, 63: municipality city Plau am See, 64: municipality Bobzin, 65: municipality Lewitzrand, 66: municipality Uelitz, 67: municipality city Wittenburg, 68: municipality Hoort, 69: municipality Greven, 70: municipality city Lübz, 71: municipality Rom, 72: municipality Kirch Jesar, 73: municipality city Hagenow, 74: municipality Rastow, 75: municipality Kritzow, 76: municipality Schwanheide, 77: municipality Gresse, 78: municipality city Parchim, 79: municipality Bengerstorf, 80: municipality Vellahn, 81: municipality Gischow, 82: municipality Setzin, 83: municipality Moraas, 84: municipality Toddin, 85: municipality city Neustadt-Glewe, 86: municipality Spornitz, 87: municipality Kreien, 88: municipality Lüblow, 89: municipality Wöbbelin, 90: municipality Pätow-Steegen, 91: municipality Strohkirchen, 92: municipality Nostorf, 93: municipality Brenz, 94: municipality Gehlsbach, 95: municipality city Boizenburg/Elbe, 96: municipality Kuhstorf, 97: municipality Tessin b. Boizenburg, 98: municipality Neu Gülze, 99: municipality Dersenow, 100: municipality Picher, 101: municipality Siggelkow, 102: municipality Ganzlin, 103: municipality Pritzier, 104: municipality Warlitz, 105: municipality Groß Godems, 106: municipality Brahlstorf, 107: municipality Redefin, 108: municipality Bresegard bei Picher, 109: municipality Warlow, 110: municipality Besitz, 111: municipality Blievenstorf, 112: municipality Stolpe, 113: municipality Tessenow, 114: municipality Groß Laasch, 115: municipality Teldau, 116: municipality Groß Krams, 117: municipality Karrenzin, 118: municipality Marnitz, 119: municipality Muchow, 120: municipality city Ludwigslust, 121: municipality Belsch, 122: municipality Alt Krenzlin, 123: municipality Suckow, 124: municipality Göhlen, 125: municipality city Lübtheen, 126: municipality Möllenbeck, 127: municipality Zierzow, 128: municipality Ziegendorf, 129: municipality Karstädt, 130: municipality Leussow, 131: municipality Prislich, 132: municipality Brunow, 133: municipality Balow, 134: municipality Bresegard bei Eldena, 135: municipality Dambeck, 136: municipality Eldena, 137: municipality Kremmin, 138: municipality Karenz, 139: municipality Vielank, 140: municipality city Grabow, 141: municipality Grebs-Niendorf, 142: municipality Malliß, 143: municipality Malk Göhren, 144: municipality Gorlosen, 145: municipality Milow, 146: municipality Neu Kaliß, 147: municipality city Dömitz ...Show less...

Population per age group
The percentage of inhabitants per age group in the municipality city Neustadt-Glewe

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Municipality city Neustadt-Glewe, 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 city Neustadt-Glewe

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Municipality city Neustadt-Glewe, 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 city Neustadt-Glewe.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businesses7Number2017
Active persons395Number2017
Gross wages€12.261Euro2017
DwellingsValueUnitYear
Houses 1 room163Number2019
Houses 2 rooms406Number2019
Houses 3 rooms809Number2019
Houses 4 rooms1.007Number2019
Houses 5 rooms666Number2019
Houses 6 rooms309Number2019
Houses 7+ rooms 210Number2019
Houses 1-2 rooms569Number2019
Houses 3-4 rooms1.816Number2019
Houses 5+ rooms1.185Number2019
1-2 rooms16%Percentage2019
3-4 rooms51%Percentage2019
5+ rooms33%Percentage2019
ElectionsValueUnitYear
Voters Bundestag5332,00Number2017
Voter turnout Bundestag55Number2017
Votes valid Bundestag2.868Number2017
Votes Bundestag CDU/CSU870Number2017
Votes Bundestag SPD526Number2017
Votes Bundestag GRÜNE93Number2017
Votes Bundestag FDP150Number2017
Votes Bundestag DIE LINKE405Number2017
Votes Bundestag AfD666Number2017
Votes Bundestag other parties158Number2017
Votes Bundestag total2.868Number2017
% Votes Bundestag CDU/CSU16%Percentage2017
% Votes Bundestag SPD10%Percentage2017
% Votes Bundestag GRÜNE2%Percentage2017
% Votes Bundestag FDP3%Percentage2017
% Votes Bundestag DIE LINKE8%Percentage2017
% Votes Bundestag AfD12%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employees3.089Number2019
Employees male1.606Number2019
Employees female1.483Number2019
Employees foreigner516Number2019
Employees male foreigner281Number2019
Employees female foreigner235Number2019
Unemployed212Number2018
Unemployed foreigners27Number2018
Unemployed severely disabled14Number2018
Unemployed 15-207Number2018
Unemployed 15-2521Number2018
Unemployed 55-6550Number2018
Unemployed long-term56Number2018
% Unemployed3%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 receivers3.099Number2015
Income total€86.557Euro2015
Income tax€11.679Euro2015
PopulationValueUnitYear
Population7.009Number2019
Men3.542Number2019
Women3.467Number2019
% Men51%Percentage2019
% Women49%Percentage2019
0-181.056Number2019
18-30798Number2019
30-451.361Number2019
45-601.572Number2019
18-603.731Number2019
60-751.394Number2019
60+2.222Number2019
Average age46Average number2019
Average age male45Average number2019
Average age female47Average number2019
Births47Number2018
Births male23Number2018
Births female24Number2018
1K Births7Number per 1000 inhabitants2018
Deaths85Number2018
Deaths male45Number2018
Deaths female40Number2018
1K Deaths12Number2018
0-3164Number2019
Girls 0-392Number2019
Boys 0-372Number2019
3-6201Number2019
Girls 3-691Number2019
Boys 3-6110Number2019
6-10245Number2019
10-15280Number2019
15-18166Number2019
18-20118Number2019
20-25312Number2019
25-30368Number2019
30-35476Number2019
35-40499Number2019
40-45386Number2019
45-50404Number2019
50-55558Number2019
55-60610Number2019
60-65523Number2019
65-75871Number2019
Women 65-70452Number2019
Men 65-70419Number2019
75+828Number2019
Women 75+472Number2019
Men 75+356Number2019
% 0-109%Percentage2019
% 10-186%Percentage2019
% 18-3011%Percentage2019
% 30-4519%Percentage2019
% 45-6022%Percentage2019
% 60+32%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 code130765660105Code2019
Region code 8 digits13076105Code13076105
Sorting code130765660105Code130765660105
Sorting code 8 digits13076105Code13076105
Region nameNeustadt-GleweName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipality cityCategorical type2019
Region name with typemunicipality city Neustadt-GleweName2019
Region name in GermanGemeinde Stadt Neustadt-GleweName2019
Direct subregionsno dataNumber2019
NUTS codeDE80OCode2019
Area94Area 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.