Information about the municipality Melz:

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

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Population numbers in the municipality Melz 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 Melz
Map of Rural district Mecklenburgische Seenplatte with the population per municipality.Municipality Melz 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 Melz 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 Melz 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 Melz

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Municipality Melz, 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 Melz

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Municipality Melz, 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 Melz.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businessesno dataNumber2015
Active personsno dataNumber2015
Gross wagesno dataEuro2015
DwellingsValueUnitYear
Houses 1 room3Number2019
Houses 2 rooms15Number2019
Houses 3 rooms34Number2019
Houses 4 rooms30Number2019
Houses 5 rooms51Number2019
Houses 6 rooms19Number2019
Houses 7+ rooms 16Number2019
Houses 1-2 rooms18Number2019
Houses 3-4 rooms64Number2019
Houses 5+ rooms86Number2019
1-2 rooms11%Percentage2019
3-4 rooms38%Percentage2019
5+ rooms51%Percentage2019
ElectionsValueUnitYear
Voters Bundestag293,00Number2017
Voter turnout Bundestag56Number2017
Votes valid Bundestag163Number2017
Votes Bundestag CDU/CSU51Number2017
Votes Bundestag SPD28Number2017
Votes Bundestag GRÜNE3Number2017
Votes Bundestag FDP11Number2017
Votes Bundestag DIE LINKE34Number2017
Votes Bundestag AfD33Number2017
Votes Bundestag other parties3Number2017
Votes Bundestag total163Number2017
% Votes Bundestag CDU/CSU17%Percentage2017
% Votes Bundestag SPD10%Percentage2017
% Votes Bundestag GRÜNE1%Percentage2017
% Votes Bundestag FDP4%Percentage2017
% Votes Bundestag DIE LINKE12%Percentage2017
% Votes Bundestag AfD11%Percentage2017
% Votes Bundestag other parties1%Percentage2017
EmploymentValueUnitYear
Employees133Number2019
Employees male67Number2019
Employees female66Number2019
Employees foreigner3Number2019
Employees male foreigner3Number2019
Employees female foreigner0Number2019
Unemployed15Number2018
Unemployed foreigners0Number2018
Unemployed severely disabled4Number2018
Unemployed 15-200Number2018
Unemployed 15-251Number2018
Unemployed 55-653Number2018
Unemployed long-term9Number2018
% Unemployed4%Percentage2018
% Unemployed foreigners0%Percentage of the population2018
% Unemployed severely disabled1%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-term3%Percentage of the population2018
IncomeValueUnitYear
Income receivers146Number2015
Income total€4.493Euro2015
Income tax€627Euro2015
PopulationValueUnitYear
Population339Number2019
Men179Number2019
Women160Number2019
% Men53%Percentage2019
% Women47%Percentage2019
0-1845Number2019
18-3017Number2019
30-4557Number2019
45-60109Number2019
18-60183Number2019
60-7567Number2019
60+111Number2019
Average age50Average number2019
Average age male48Average number2019
Average age female51Average number2019
Births2Number2018
Births male1Number2018
Births female1Number2018
1K Births6Number per 1000 inhabitants2018
Deaths4Number2018
Deaths male3Number2018
Deaths female1Number2018
1K Deaths12Number2018
0-36Number2019
Girls 0-31Number2019
Boys 0-35Number2019
3-69Number2019
Girls 3-66Number2019
Boys 3-63Number2019
6-108Number2019
10-1516Number2019
15-186Number2019
18-200Number2019
20-256Number2019
25-3011Number2019
30-3525Number2019
35-4023Number2019
40-459Number2019
45-5022Number2019
50-5545Number2019
55-6042Number2019
60-6531Number2019
65-7536Number2019
Women 65-7021Number2019
Men 65-7015Number2019
75+44Number2019
Women 75+21Number2019
Men 75+23Number2019
% 0-107%Percentage2019
% 10-186%Percentage2019
% 18-305%Percentage2019
% 30-4517%Percentage2019
% 45-6032%Percentage2019
% 60+33%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 code130715159097Code2019
Region code 8 digits13071097Code13071097
Sorting code130715159097Code130715159097
Sorting code 8 digits13071097Code13071097
Region nameMelzName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality MelzName2019
Region name in GermanGemeinde MelzName2019
Direct subregionsno dataNumber2019
NUTS codeDE80JCode2019
Area18Area 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.