Information about the municipality Marth:

View the information on over 100 topics about the municipality Marth! With charts, links to more information & an overview of all figures in 1 table.
View the information on over 100 topics about the municipality Marth! With charts, links to more information & an overview of all figures in 1 table.
Population numbers per year
The number of inhabitants in the municipality Marth

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Population numbers in the municipality Marth 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 Marth
Map of Rural district Eichsfeld with the population per municipality.Municipality Marth 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 Eichsfeld with the population per municipality.Municipality Marth is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Sonnenstein, 2: municipality Ecklingerode, 3: municipality Brehme, 4: municipality Wehnde, 5: municipality Am Ohmberg ...Show more... Map of Rural district Eichsfeld with the population per municipality.Municipality Marth is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Sonnenstein, 2: municipality Ecklingerode, 3: municipality Brehme, 4: municipality Wehnde, 5: municipality Am Ohmberg, 6: municipality Tastungen, 7: municipality Teistungen, 8: municipality Ferna, 9: municipality Haynrode, 10: municipality Berlingerode, 11: municipality Glasehausen, 12: municipality Buhla, 13: municipality Reinholterode, 14: municipality Freienhagen, 15: municipality Steinbach, 16: municipality city Leinefelde-Worbis, 17: municipality Hohes Kreuz, 18: municipality Breitenworbis, 19: municipality Rohrberg, 20: municipality Kirchworbis, 21: municipality Schachtebich, 22: municipality Rustenfelde, 23: municipality Bodenrode-Westhausen, 24: municipality Wingerode, 25: municipality Gernrode, 26: municipality Burgwalde, 27: municipality Kirchgandern, 28: municipality Steinheuterode, 29: municipality Gerterode, 30: municipality Marth, 31: municipality Hausen, 32: municipality Hohengandern, 33: municipality city Heilbad Heiligenstadt, 34: municipality Arenshausen, 35: municipality Deuna, 36: municipality Niederorschel, 37: municipality Birkenfelde, 38: municipality Uder, 39: municipality Thalwenden, 40: municipality Geisleden, 41: municipality Kleinbartloff, 42: municipality Kallmerode, 43: municipality Bornhagen, 44: municipality Kreuzebra, 45: municipality Schönhagen, 46: municipality Lenterode, 47: municipality Röhrig, 48: municipality Gerbershausen, 49: municipality Heuthen, 50: municipality Lutter, 51: municipality Fretterode, 52: municipality Wüstheuterode, 53: municipality Silberhausen, 54: municipality Lindewerra, 55: municipality city Dingelstädt, 56: municipality Kefferhausen, 57: municipality Eichstruth, 58: municipality Dietzenrode/Vatterode, 59: municipality Bernterode (bei Heilbad Heiligenstadt), 60: municipality Wahlhausen, 61: municipality Dieterode, 62: municipality Mackenrode, 63: municipality Helmsdorf, 64: municipality Krombach, 65: municipality Asbach-Sickenberg, 66: municipality Schwobfeld, 67: municipality Wachstedt, 68: municipality Küllstedt, 69: municipality Wiesenfeld, 70: municipality Schimberg, 71: municipality Volkerode, 72: municipality Großbartloff, 73: municipality Büttstedt, 74: municipality Sickerode, 75: municipality Pfaffschwende, 76: municipality Effelder, 77: municipality Kella, 78: municipality Geismar ...Show less...

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

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Municipality Marth, 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 Marth

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Municipality Marth, 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 Marth.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businessesno dataNumber2015
Active personsno dataNumber2015
Gross wagesno dataEuro2015
DwellingsValueUnitYear
Houses 1 room2Number2019
Houses 2 rooms5Number2019
Houses 3 rooms14Number2019
Houses 4 rooms35Number2019
Houses 5 rooms24Number2019
Houses 6 rooms27Number2019
Houses 7+ rooms 35Number2019
Houses 1-2 rooms7Number2019
Houses 3-4 rooms49Number2019
Houses 5+ rooms86Number2019
1-2 rooms5%Percentage2019
3-4 rooms35%Percentage2019
5+ rooms61%Percentage2019
ElectionsValueUnitYear
Voters Bundestag274,00Number2017
Voter turnout Bundestag61Number2017
Votes valid Bundestag164Number2017
Votes Bundestag CDU/CSU67Number2017
Votes Bundestag SPD18Number2017
Votes Bundestag GRÜNE9Number2017
Votes Bundestag FDP8Number2017
Votes Bundestag DIE LINKE14Number2017
Votes Bundestag AfD34Number2017
Votes Bundestag other parties14Number2017
Votes Bundestag total164Number2017
% Votes Bundestag CDU/CSU24%Percentage2017
% Votes Bundestag SPD7%Percentage2017
% Votes Bundestag GRÜNE3%Percentage2017
% Votes Bundestag FDP3%Percentage2017
% Votes Bundestag DIE LINKE5%Percentage2017
% Votes Bundestag AfD12%Percentage2017
% Votes Bundestag other parties5%Percentage2017
EmploymentValueUnitYear
Employees150Number2019
Employees male91Number2019
Employees female59Number2019
Employees foreigner0Number2019
Employees male foreigner0Number2019
Employees female foreigner0Number2019
Unemployed10Number2018
Unemployed foreigners0Number2018
Unemployed severely disabled0Number2018
Unemployed 15-200Number2018
Unemployed 15-251Number2018
Unemployed 55-651Number2018
Unemployed long-term1Number2018
% 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 55-650%Percentage of the population2018
% Unemployed long-term0%Percentage of the population2018
IncomeValueUnitYear
Income receivers140Number2015
Income total€4.826Euro2015
Income tax€608Euro2015
PopulationValueUnitYear
Population338Number2019
Men197Number2019
Women141Number2019
% Men58%Percentage2019
% Women42%Percentage2019
0-1855Number2019
18-3037Number2019
30-4580Number2019
45-6090Number2019
18-60207Number2019
60-7554Number2019
60+76Number2019
Average age43Average number2019
Average age male41Average number2019
Average age female45Average number2019
Births1Number2018
Births male1Number2018
Births female0Number2018
1K Births3Number per 1000 inhabitants2018
Deaths6Number2018
Deaths male2Number2018
Deaths female4Number2018
1K Deaths18Number2018
0-37Number2019
Girls 0-33Number2019
Boys 0-34Number2019
3-64Number2019
Girls 3-61Number2019
Boys 3-63Number2019
6-1011Number2019
10-1522Number2019
15-1811Number2019
18-2010Number2019
20-2514Number2019
25-3013Number2019
30-3522Number2019
35-4036Number2019
40-4522Number2019
45-5027Number2019
50-5537Number2019
55-6026Number2019
60-6521Number2019
65-7533Number2019
Women 65-7015Number2019
Men 65-7018Number2019
75+22Number2019
Women 75+12Number2019
Men 75+10Number2019
% 0-107%Percentage2019
% 10-1810%Percentage2019
% 18-3011%Percentage2019
% 30-4524%Percentage2019
% 45-6027%Percentage2019
% 60+22%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 code160615008069Code2019
Region code 8 digits16061069Code16061069
Sorting code160615008069Code160615008069
Sorting code 8 digits16061069Code16061069
Region nameMarthName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality MarthName2019
Region name in GermanGemeinde MarthName2019
Direct subregionsno dataNumber2019
NUTS codeDEG06Code2019
Area5Area in km²2019
ReligionValueUnitYear
Roman Catholic church254Number2011
Protestant church24Number2011
Other or none65Number2011
% Roman Catholic church74%Percentage2011
% Protestant church7%Percentage2011
% Other or none19%Percentage2011
Roman Catholic church German254Number2011
Protestant church German24Number2011
Other or none German59Number2011
% Roman Catholic church German75%Percentage2011
% Protestant church German7%Percentage2011
% Other or none German Foreign18%Percentage2011
Roman Catholic church Foreign0Number2011
Protestant church Foreign0Number2011
Other or none Foreign6Number2011
% Roman Catholic church Foreign0%Percentage2011
% Protestant church Foreign0%Percentage2011
% Other or none Foreign100%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.