Information about the municipality Nonnweiler:

View the information on over 100 topics about the municipality Nonnweiler! With charts, links to more information & an overview of all figures in 1 table.
View the information on over 100 topics about the municipality Nonnweiler! 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 Nonnweiler

One moment please, your device is loading the charts...

Population numbers in the municipality Nonnweiler 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 Nonnweiler
Map of Rural district St. Wendel with the population per municipality.Municipality Nonnweiler 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 St. Wendel with the population per municipality.Municipality Nonnweiler is highlighted with a red edge. The numbers at the map represent the following municipalities: 1: municipality Nonnweiler, 2: municipality Nohfelden, 3: municipality Freisen, 4: municipality Oberthal, 5: municipality Namborn, 6: municipality Tholey, 7: municipality city St. Wendel, 8: municipality Marpingen.

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

One moment please, your device is loading the charts...

Municipality Nonnweiler, 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 Nonnweiler

One moment please, your device is loading the charts...

Municipality Nonnweiler, 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 Nonnweiler.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businesses10Number2017
Active persons2.758Number2017
Gross wages€94.402Euro2017
DwellingsValueUnitYear
Houses 1 room10Number2019
Houses 2 rooms150Number2019
Houses 3 rooms349Number2019
Houses 4 rooms660Number2019
Houses 5 rooms778Number2019
Houses 6 rooms921Number2019
Houses 7+ rooms 1.320Number2019
Houses 1-2 rooms160Number2019
Houses 3-4 rooms1.009Number2019
Houses 5+ rooms3.019Number2019
1-2 rooms4%Percentage2019
3-4 rooms24%Percentage2019
5+ rooms72%Percentage2019
ElectionsValueUnitYear
Voters Bundestag7108,00Number2017
Voter turnout Bundestag82Number2017
Votes valid Bundestag5.692Number2017
Votes Bundestag CDU/CSU2.130Number2017
Votes Bundestag SPD1.718Number2017
Votes Bundestag GRÜNE219Number2017
Votes Bundestag FDP429Number2017
Votes Bundestag DIE LINKE500Number2017
Votes Bundestag AfD495Number2017
Votes Bundestag other parties201Number2017
Votes Bundestag total5.692Number2017
% Votes Bundestag CDU/CSU30%Percentage2017
% Votes Bundestag SPD24%Percentage2017
% Votes Bundestag GRÜNE3%Percentage2017
% Votes Bundestag FDP6%Percentage2017
% Votes Bundestag DIE LINKE7%Percentage2017
% Votes Bundestag AfD7%Percentage2017
% Votes Bundestag other parties3%Percentage2017
EmploymentValueUnitYear
Employees3.327Number2019
Employees male1.832Number2019
Employees female1.495Number2019
Employees foreigner134Number2019
Employees male foreigner81Number2019
Employees female foreigner53Number2019
Unemployed120Number2018
Unemployed foreigners17Number2018
Unemployed severely disabled5Number2018
Unemployed 15-201Number2018
Unemployed 15-257Number2018
Unemployed 55-6532Number2018
Unemployed long-term32Number2018
% Unemployed1%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 receivers4.244Number2015
Income total€148.506Euro2015
Income tax€22.896Euro2015
PopulationValueUnitYear
Population8.477Number2019
Men4.286Number2019
Women4.191Number2019
% Men51%Percentage2019
% Women49%Percentage2019
0-181.196Number2019
18-301.014Number2019
30-451.326Number2019
45-602.197Number2019
18-604.537Number2019
60-751.680Number2019
60+2.744Number2019
Average age47Average number2019
Average age male46Average number2019
Average age female49Average number2019
Births75Number2018
Births male37Number2018
Births female38Number2018
1K Births9Number per 1000 inhabitants2018
Deaths120Number2018
Deaths male66Number2018
Deaths female54Number2018
1K Deaths14Number2018
0-3186Number2019
Girls 0-378Number2019
Boys 0-3108Number2019
3-6193Number2019
Girls 3-6103Number2019
Boys 3-690Number2019
6-10242Number2019
10-15341Number2019
15-18234Number2019
18-20161Number2019
20-25399Number2019
25-30454Number2019
30-35441Number2019
35-40449Number2019
40-45436Number2019
45-50568Number2019
50-55810Number2019
55-60819Number2019
60-65710Number2019
65-75970Number2019
Women 65-70476Number2019
Men 65-70494Number2019
75+1.064Number2019
Women 75+621Number2019
Men 75+443Number2019
% 0-107%Percentage2019
% 10-187%Percentage2019
% 18-3012%Percentage2019
% 30-4516%Percentage2019
% 45-6026%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 code100460115115Code2019
Region code 8 digits10046115Code10046115
Sorting code100460115115Code100460115115
Sorting code 8 digits10046115Code10046115
Region nameNonnweilerName2019
Regional level6Categorical type2019
Region typeMunicipalityCategorical type2019
Region type detailmunicipalityCategorical type2019
Region name with typemunicipality NonnweilerName2019
Region name in GermanGemeinde NonnweilerName2019
Direct subregionsno dataNumber2019
NUTS codeDEC06Code2019
Area66Area in km²2019
ReligionValueUnitYear
Roman Catholic church6.841Number2011
Protestant church1.025Number2011
Other or none978Number2011
% Roman Catholic church77%Percentage2011
% Protestant church12%Percentage2011
% Other or none11%Percentage2011
Roman Catholic church German6.757Number2011
Protestant church German999Number2011
Other or none German887Number2011
% Roman Catholic church German78%Percentage2011
% Protestant church German12%Percentage2011
% Other or none German Foreign10%Percentage2011
Roman Catholic church Foreign84Number2011
Protestant church Foreign26Number2011
Other or none Foreign91Number2011
% Roman Catholic church Foreign42%Percentage2011
% Protestant church Foreign13%Percentage2011
% Other or none Foreign45%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.

  • Top