Information about the rural district Wittenberg:

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

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Population numbers in the rural district Wittenberg 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 Wittenberg
Map of the district Wittenberg with the population per municipality.. 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 the district Wittenberg with the population per municipality. The numbers at the map represent the following municipalities: 1: municipality city Coswig (Anhalt), 2: municipality city Wittenberg, 3: municipality city Zahna-Elster, 4: municipality city Oranienbaum-Wörlitz, 5: municipality city Jessen (Elster), 6: municipality city Kemberg, 7: municipality city Gräfenhainichen, 8: municipality city Annaburg, 9: municipality city Bad Schmiedeberg.

Population per age group
The percentage of inhabitants per age group in the rural district Wittenberg

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Rural district Wittenberg, 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 rural district Wittenberg

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Rural district Wittenberg, 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 rural district Wittenberg.

Data about more than 100 topics!

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

BusinessValueUnitYear
Businesses109Number2017
Active persons9.057Number2017
Gross wages€302.395Euro2017
DwellingsValueUnitYear
Houses 1 room1.305Number2019
Houses 2 rooms4.238Number2019
Houses 3 rooms14.721Number2019
Houses 4 rooms22.185Number2019
Houses 5 rooms14.913Number2019
Houses 6 rooms8.203Number2019
Houses 7+ rooms 6.732Number2019
Houses 1-2 rooms5.543Number2019
Houses 3-4 rooms36.906Number2019
Houses 5+ rooms29.848Number2019
1-2 rooms8%Percentage2019
3-4 rooms51%Percentage2019
5+ rooms41%Percentage2019
ElectionsValueUnitYear
Voters Bundestag108564,00Number2017
Voter turnout Bundestag70Number2017
Votes valid Bundestag74.666Number2017
Votes Bundestag CDU/CSU24.931Number2017
Votes Bundestag SPD10.605Number2017
Votes Bundestag GRÜNE2.074Number2017
Votes Bundestag FDP5.110Number2017
Votes Bundestag DIE LINKE12.559Number2017
Votes Bundestag AfD14.885Number2017
Votes Bundestag other parties4.502Number2017
Votes Bundestag total74.666Number2017
% Votes Bundestag CDU/CSU23%Percentage2017
% Votes Bundestag SPD10%Percentage2017
% Votes Bundestag GRÜNE2%Percentage2017
% Votes Bundestag FDP5%Percentage2017
% Votes Bundestag DIE LINKE12%Percentage2017
% Votes Bundestag AfD14%Percentage2017
% Votes Bundestag other parties4%Percentage2017
EmploymentValueUnitYear
Employees50.701Number2019
Employees male26.563Number2019
Employees female24.138Number2019
Employees foreigner1.715Number2019
Employees male foreigner1.192Number2019
Employees female foreigner523Number2019
Unemployed4.606Number2018
Unemployed foreigners337Number2018
Unemployed severely disabled290Number2018
Unemployed 15-2080Number2018
Unemployed 15-25307Number2018
Unemployed 55-651.294Number2018
Unemployed long-term1.712Number2018
% Unemployed4%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 receivers57.702Number2015
Income total€1.706.894Euro2015
Income tax€236.168Euro2015
PopulationValueUnitYear
Population125.840Number2019
Men61.933Number2019
Women63.907Number2019
% Men49%Percentage2019
% Women51%Percentage2019
0-1817.473Number2019
18-3010.174Number2019
30-4520.113Number2019
45-6031.197Number2019
18-6061.484Number2019
60-7527.374Number2019
60+46.883Number2019
Average age50Average number2019
Average age male48Average number2019
Average age female51Average number2019
Births909Number2018
Births male478Number2018
Births female431Number2018
1K Births7Number per 1000 inhabitants2018
Deaths1.865Number2018
Deaths male944Number2018
Deaths female921Number2018
1K Deaths15Number2018
0-32.803Number2019
Girls 0-31.351Number2019
Boys 0-31.452Number2019
3-62.876Number2019
Girls 3-61.418Number2019
Boys 3-61.458Number2019
6-103.982Number2019
10-154.852Number2019
15-182.960Number2019
18-201.846Number2019
20-253.534Number2019
25-304.794Number2019
30-356.968Number2019
35-406.917Number2019
40-456.228Number2019
45-508.230Number2019
50-5510.931Number2019
55-6012.036Number2019
60-6510.979Number2019
65-7516.395Number2019
Women 65-708.570Number2019
Men 65-707.825Number2019
75+19.509Number2019
Women 75+11.949Number2019
Men 75+7.560Number2019
% 0-108%Percentage2019
% 10-186%Percentage2019
% 18-308%Percentage2019
% 30-4516%Percentage2019
% 45-6025%Percentage2019
% 60+37%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 code15091Code2019
Region code 8 digits15091Code15091
Sorting code150910000000Code150910000000
Sorting code 8 digits15091000Code15091000
Region nameWittenbergName2019
Regional level4Categorical type2019
Region typeDistrictCategorical type2019
Region type detailrural districtCategorical type2019
Region name with typerural district WittenbergName2019
Region name in GermanLandkreis WittenbergName2019
Direct subregions9Number2019
NUTS codeDEE0ECode2019
Area1.930Area in km²2019
ReligionValueUnitYear
Roman Catholic church4.683Number2011
Protestant church22.752Number2011
Other or none105.559Number2011
% Roman Catholic church4%Percentage2011
% Protestant church17%Percentage2011
% Other or none79%Percentage2011
Roman Catholic church German4.544Number2011
Protestant church German22.703Number2011
Other or none German104.549Number2011
% Roman Catholic church German3%Percentage2011
% Protestant church German17%Percentage2011
% Other or none German Foreign79%Percentage2011
Roman Catholic church Foreign139Number2011
Protestant church Foreign49Number2011
Other or none Foreign1.010Number2011
% Roman Catholic church Foreign12%Percentage2011
% Protestant church Foreign4%Percentage2011
% Other or none Foreign84%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.

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