Information about the municipality city Dingelstädt:

Population numbers per year
The number of inhabitants in the municipality city Dingelstädt

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Population numbers in the municipality city Dingelstädt 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 Dingelstädt
Map of Rural district Eichsfeld with the population per municipality.Municipality Dingelstädt 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 Dingelstädt 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 Dingelstädt 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 city Dingelstädt

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Municipality city Dingelstädt, 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 Dingelstädt

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Municipality city Dingelstädt, 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 Dingelstädt.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businesses10Number2017
Active persons789Number2017
Gross wages€24.780Euro2017
DwellingsValueUnitYear
Houses 1 room66Number2019
Houses 2 rooms152Number2019
Houses 3 rooms439Number2019
Houses 4 rooms672Number2019
Houses 5 rooms438Number2019
Houses 6 rooms290Number2019
Houses 7+ rooms 291Number2019
Houses 1-2 rooms218Number2019
Houses 3-4 rooms1.111Number2019
Houses 5+ rooms1.019Number2019
1-2 rooms9%Percentage2019
3-4 rooms47%Percentage2019
5+ rooms43%Percentage2019
ElectionsValueUnitYear
Voters Bundestag3623,00Number2017
Voter turnout Bundestag58Number2017
Votes valid Bundestag2.085Number2017
Votes Bundestag CDU/CSU762Number2017
Votes Bundestag SPD255Number2017
Votes Bundestag GRÜNE78Number2017
Votes Bundestag FDP213Number2017
Votes Bundestag DIE LINKE214Number2017
Votes Bundestag AfD447Number2017
Votes Bundestag other parties116Number2017
Votes Bundestag total2.085Number2017
% Votes Bundestag CDU/CSU21%Percentage2017
% Votes Bundestag SPD7%Percentage2017
% Votes Bundestag GRÜNE2%Percentage2017
% Votes Bundestag FDP6%Percentage2017
% Votes Bundestag DIE LINKE6%Percentage2017
% Votes Bundestag AfD12%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employeesno dataNumber2018
Employees maleno dataNumber2018
Employees femaleno dataNumber2018
Employees foreignerno dataNumber2018
Employees male foreignerno dataNumber2018
Employees female foreignerno dataNumber2018
Unemployed105Number2018
Unemployed foreigners8Number2018
Unemployed severely disabled12Number2018
Unemployed 15-202Number2018
Unemployed 15-2510Number2018
Unemployed 55-6532Number2018
Unemployed long-term44Number2018
% Unemployed2%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 receivers1.920Number2015
Income total€59.833Euro2015
Income tax€8.004Euro2015
PopulationValueUnitYear
Population4.335Number2019
Men2.168Number2019
Women2.167Number2019
% Men50%Percentage2019
% Women50%Percentage2019
0-18787Number2019
18-30431Number2019
30-45831Number2019
45-60851Number2019
18-602.113Number2019
60-75898Number2019
60+1.435Number2019
Average age46Average number2019
Average age male44Average number2019
Average age female47Average number2019
Births42Number2018
Births male17Number2018
Births female25Number2018
1K Births10Number per 1000 inhabitants2018
Deaths47Number2018
Deaths male31Number2018
Deaths female16Number2018
1K Deaths11Number2018
0-3138Number2019
Girls 0-373Number2019
Boys 0-365Number2019
3-6134Number2019
Girls 3-657Number2019
Boys 3-677Number2019
6-10175Number2019
10-15216Number2019
15-18124Number2019
18-2061Number2019
20-25156Number2019
25-30214Number2019
30-35280Number2019
35-40283Number2019
40-45268Number2019
45-50246Number2019
50-55294Number2019
55-60311Number2019
60-65324Number2019
65-75574Number2019
Women 65-70300Number2019
Men 65-70274Number2019
75+537Number2019
Women 75+324Number2019
Men 75+213Number2019
% 0-1010%Percentage2019
% 10-188%Percentage2019
% 18-3010%Percentage2019
% 30-4519%Percentage2019
% 45-6020%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 code160615003025Code2019
Region code 8 digits16061025Code16061025
Sorting code160615003025Code160615003025
Sorting code 8 digits16061025Code16061025
Region nameDingelstädtName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipality cityCategorical type2019
Region name with typemunicipality city DingelstädtName2019
Region name in GermanGemeinde Stadt DingelstädtName2019
Direct subregionsno dataNumber2019
NUTS codeDEG06Code2019
Area20Area in km²2019
ReligionValueUnitYear
Roman Catholic church3.417Number2011
Protestant church311Number2011
Other or none679Number2011
% Roman Catholic church78%Percentage2011
% Protestant church7%Percentage2011
% Other or none15%Percentage2011
Roman Catholic church German3.414Number2011
Protestant church German311Number2011
Other or none German651Number2011
% Roman Catholic church German78%Percentage2011
% Protestant church German7%Percentage2011
% Other or none German Foreign15%Percentage2011
Roman Catholic church Foreign3Number2011
Protestant church Foreign0Number2011
Other or none Foreign28Number2011
% Roman Catholic church Foreign10%Percentage2011
% Protestant church Foreign0%Percentage2011
% Other or none Foreign90%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.