About this dataset

Context

The dataset tabulates the New Germany population by gender and age. The dataset can be utilized to understand the gender distribution and demographics of New Germany.

Content

The dataset constitues the following two datasets across these two themes

• New Germany, MN Population Breakdown by Gender
• New Germany, MN Population Breakdown by Gender and Age

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

About this dataset

Context

The dataset tabulates the German town population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of German town. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 151 (62.14% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the German town population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in German town is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the German town is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for German town Population by Age. You can refer the same here

This dataset contains data regarding COVID-19 cases in Germany by Landkreise (district). It was originally published by the Robert Koch-Institut (RKI).For each Landkreis, data is available about: number of cases (cumulative), number of cases per 100 000 persons (cumulative or only the last seven days), percentage of cases (cumulative number of cases among the Landkreis population), number of deaths (cumulative) and death rate (percentage of deaths among the cases).The dataset also contains various geo-administrative information, such as populations, geographical shapes and administrative codes.Enrichment:Dates given in German format have been converted to ISO datetime.

This data collection contains electoral and demographic data at several levels of aggregation (kreis, land/regierungsberzirk, and wahlkreis) for Germany in the Weimar Republic period of 1919-1933. Two datasets are available. Part 1, 1919 Data, presents raw and percentagized election returns at the wahlkreis level for the 1919 election to the Nationalversammlung. Information is provided on the number and percentage of eligible voters and the total votes cast for parties such as the German National People's Party, German People's Party, Christian People's Party, German Democratic Party, Social Democratic Party, and Independent Social Democratic Party. Part 2, 1920-1933 Data, consists of returns for elections to the Reichstag, 1920-1933, and for the Reichsprasident elections of 1925 and 1932 (including runoff elections in each year), returns for two national referenda, held in 1926 and 1929, and data pertaining to urban population, religion, and occupations, taken from the German Census of 1925. This second dataset contains data at several levels of aggregation and is a merged file. Crosstemporal discrepancies, such as changes in the names of the geographical units and the disappearance of units, have been adjusted for whenever possible. Variables in this file provide information for the total number and percentage of eligible voters and votes cast for parties, including the German Nationalist People's Party, German People's Party, German Center Party, German Democratic Party, German Social Democratic Party, German Communist Party, Bavarian People's Party, Nationalist-Socialist German Workers' Party (Hitler's movement), German Middle Class Party, German Business and Labor Party, Conservative People's Party, and other parties. Data are also provided for the total number and percentage of votes cast in the Reichsprasident elections of 1925 and 1932 for candidates Jarres, Held, Ludendorff, Braun, Marx, Hellpach, Thalman, Hitler, Duesterburg, Von Hindenburg, Winter, and others. Additional variables provide information on occupations in the country, including the number of wage earners employed in agriculture, industry and manufacturing, trade and transportation, civil service, army and navy, clergy, public health, welfare, domestic and personal services, and unknown occupations. Other census data cover the total number of wage earners in the labor force and the number of female wage earners employed in all occupations. Also provided is the percentage of the total population living in towns with 5,000 inhabitants or more, and the number and percentage of the population who were Protestants, Catholics, and Jews.

Germany DE: Population: Female: Aged 15-64 data was reported at 25,940,226.000 Person in 2023. This records a decrease from the previous number of 26,244,031.000 Person for 2022. Germany DE: Population: Female: Aged 15-64 data is updated yearly, averaging 26,508,473.000 Person from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 27,619,973.000 Person in 1998 and a record low of 25,711,613.000 Person in 1971. Germany DE: Population: Female: Aged 15-64 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Female population between the ages 15 to 64. Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.;World Bank staff estimates using the World Bank's total population and age/sex distributions of the United Nations Population Division's World Population Prospects: 2024 Revision.;Sum;Relevance to gender indicator: Knowing how many girls, adolescents and women there are in a population helps a country in determining its provision of services.

About this dataset

Context

The dataset tabulates the German township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of German township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of German township was 4,485, a 1.23% decrease year-by-year from 2022. Previously, in 2022, German township population was 4,541, a decline of 1.43% compared to a population of 4,607 in 2021. Over the last 20 plus years, between 2000 and 2023, population of German township decreased by 1,149. In this period, the peak population was 5,634 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the German township is shown in this column.
• Year on Year Change: This column displays the change in German township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for German township Population by Year. You can refer the same here

WhatsApp was the leading actively used messenger service in Germany in 2021. Almost 84 percent of users confirmed this. While WhatsApp is foremost a messaging service, certain features indicate similarities with social media networks, as sharing and posting between users still occurs, just not necessarily on a publicly accessible website. Delivering the message For most of the population, modern life is unimaginable without messenger apps. Texting has become much more varied as a form of communication thanks to extended file and content sharing options within messages. There is no doubt that WhatsApp is a popular messaging app in Germany. In 2023, almost 85 percent of people were messaging on WhatsApp every day. By 2025, it is estimated that over 53 million people will be using WhatsApp in Germany, suggesting it's popularity as a messaging app will not diminish with time. Personal data While Facebook is extremely popular in many different countries, long-term questions and concerns from users continue to arise, with personal data security being one of the leading topics of discussion. In general, the there have been many breaches of personal data online. At the same time, social media continues to enjoy rising popularity and use among the German population, both in a private and professional context.

Germany DE: Internet Users: Individuals: % of Population data was reported at 92.476 % in 2023. This records an increase from the previous number of 91.630 % for 2022. Germany DE: Internet Users: Individuals: % of Population data is updated yearly, averaging 73.660 % from Dec 1990 (Median) to 2023, with 34 observations. The data reached an all-time high of 92.476 % in 2023 and a record low of 0.126 % in 1990. Germany DE: Internet Users: Individuals: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Telecommunication. Internet users are individuals who have used the Internet (from any location) in the last 3 months. The Internet can be used via a computer, mobile phone, personal digital assistant, games machine, digital TV etc.;International Telecommunication Union (ITU) World Telecommunication/ICT Indicators Database;Weighted average;Please cite the International Telecommunication Union for third-party use of these data.

This is NOT a raw population dataset. We use our proprietary stack to combine detailed 'WorldPop' UN-adjusted, sex and age structured population data with a spatiotemporal OD matrix.

The result is a dataset where each record indicates how many people can be reached in a fixed timeframe (2 Hours in this case) from that record's location.

The dataset is broken down into sex and age bands at 5 year intervals, e.g - male 25-29 (m_25) and also contains a set of features detailing the representative percentage of the total that the count represents.

The dataset provides 76174 records, one for each sampled location. These are labelled with a h3 index at resolution 7 - this allows easy plotting and filtering in Kepler.gl / Deck.gl / Mapbox, or easy conversion to a centroid (lat/lng) or the representative geometry of the hexagonal cell for integration with your geospatial applications and analyses.

A h3 resolution of 7, is a hexagonal cell area equivalent to: - ~1.9928 sq miles - ~5.1613 sq km

Higher resolutions or alternate geographies are available on request.

More information on the h3 system is available here: https://eng.uber.com/h3/

WorldPop data provides for a population count using a grid of 1 arc second intervals and is available for every geography.

More information on the WorldPop data is available here: https://www.worldpop.org/

One of the main use cases historically has been in prospecting for site selection, comparative analysis and network validation by asset investors and logistics companies. The data structure makes it very simple to filter out areas which do not meet requirements such as: - being able to access 70% of the German population within 4 hours by Truck and show only the areas which do exhibit this characteristic.

Clients often combine different datasets either for different timeframes of interest, or to understand different populations, such as that of the unemployed, or those with particular qualifications within areas reachable as a commute.

This statistic shows the data volume development in mobile phone networks in Germany from 2009 to 2023. In 2023, the average monthly data volume per mobile subscription amounted to 7.2 gigabytes.

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Context

Official COVID19 data for Germany publicized by Robert Koch Institute Offizieller Datensatz des Rober-Koch-Instituts zu COVID19-Fällen in Deutschland

I'm just linking the official upload location to Kaggle.

There already is a COVID19 dashboard with a map for Germany, based on that data: https://npgeo-corona-npgeo-de.hub.arcgis.com/ But there certainly are more statistical questions to be answered.

I also started gathering and adding some additional data (not by RKI).

As for the columns labels in two of the three sets: they are very confusing and they are not even explained on the official upload website. Fortunately @sebastianhelm put some work into researching them: https://www.kaggle.com/mreverybody/covid19-data-germany-robert-koch-institute/discussion/142140#808487

Content

RKI data is uploaded here (For the actual download link for the CSV seed download button on the site): - https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/dd4580c810204019a7b8eb3e0b329dd6_0?selectedAttribute=Datenstand - https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/ef4b445a53c1406892257fe63129a8ea_0?geometry=-19.734%2C46.270%2C35.989%2C55.886 - https://npgeo-corona-npgeo-de.hub.arcgis.com/datasets/917fc37a709542548cc3be077a786c17_0

Additional data: - Political measures taken and events / incidents: https://github.com/mafleischer/covid19-robert-koch-data/blob/master/additional_data/covid19_events_measures.csv Sources: https://www.deutschland.de/de/news/coronavirus-in-deutschland-informationen#

Acknowledgements

Rober Koch Institute for making the data public https://www.rki.de/

Inspiration

There are only few official and neutral sources concerning COVID19 cases in Germany, but many false claims and panic going around in the public. Although the RKI data is publically available it is not propagated well and it is a bit hard to come across.

Germany DE: International Migrant Stock: % of Population data was reported at 14.879 % in 2015. This records an increase from the previous number of 14.429 % for 2010. Germany DE: International Migrant Stock: % of Population data is updated yearly, averaging 11.828 % from Dec 1990 (Median) to 2015, with 6 observations. The data reached an all-time high of 14.879 % in 2015 and a record low of 7.518 % in 1990. Germany DE: International Migrant Stock: % of Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. International migrant stock is the number of people born in a country other than that in which they live. It also includes refugees. The data used to estimate the international migrant stock at a particular time are obtained mainly from population censuses. The estimates are derived from the data on foreign-born population--people who have residence in one country but were born in another country. When data on the foreign-born population are not available, data on foreign population--that is, people who are citizens of a country other than the country in which they reside--are used as estimates. After the breakup of the Soviet Union in 1991 people living in one of the newly independent countries who were born in another were classified as international migrants. Estimates of migrant stock in the newly independent states from 1990 on are based on the 1989 census of the Soviet Union. For countries with information on the international migrant stock for at least two points in time, interpolation or extrapolation was used to estimate the international migrant stock on July 1 of the reference years. For countries with only one observation, estimates for the reference years were derived using rates of change in the migrant stock in the years preceding or following the single observation available. A model was used to estimate migrants for countries that had no data.;United Nations Population Division, Trends in Total Migrant Stock: 2008 Revision.;Weighted average;

Germany Population: German data was reported at 71,347,057.000 Person in 2023. This records a decrease from the previous number of 71,623,366.000 Person for 2022. Germany Population: German data is updated yearly, averaging 73,207,573.500 Person from Dec 1970 (Median) to 2023, with 54 observations. The data reached an all-time high of 75,212,869.000 Person in 2004 and a record low of 56,478,581.000 Person in 1986. Germany Population: German data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.G001: Population. Population prior to 1990 covers West Germany only.

In late May 1939, just three months before the Second World War began in Europe, Germany's workforce was made up of almost 25 million men, 15 million women, and a very small number of foreign workers. The share of German men in the workforce decreased each year thereafter, as more were conscripted into the armed forces, and there were approximately 11 million fewer German male citizens in the workforce by September 1944. The number of German women fluctuated, but remained between 14 and 15 million throughout the given period, and it exceeded the number of German men in 1944. Despite the number of German men in the workforce dropping by 45 percent, the total number of workers in German was consistently around 36 million between 1940 and 1944, as this difference was offset by foreign and forced laborers. These workers were mostly drafted from annexed territories in Eastern Europe, and prisoners were transferred from concentration and POW camps to meet the labor demands in various areas of Germany.

When asked about "View on personal future", 29 percent of German respondents answer "Fairly optimistic". This online survey was conducted in 2023, among 35,938 consumers.Find this and more survey data on view on personal future in our Consumer Insights tool. Filter by countless demographics, drill down to your own, hand-tailored target audience, and compare results across countries worldwide.

This dataset features three gridded population dadasets of Germany on a 10m grid. The units are people per grid cell.

Datasets

DE_POP_VOLADJ16: This dataset was produced by disaggregating national census counts to 10m grid cells based on a weighted dasymetric mapping approach. A building density, building height and building type dataset were used as underlying covariates, with an adjusted volume for multi-family residential buildings.

DE_POP_TDBP: This dataset is considered a best product, based on a dasymetric mapping approach that disaggregated municipal census counts to 10m grid cells using the same three underyling covariate layers.

DE_POP_BU: This dataset is based on a bottom-up gridded population estimate. A building density, building height and building type layer were used to compute a living floor area dataset in a 10m grid. Using federal statistics on the average living floor are per capita, this bottom-up estimate was created.

Please refer to the related publication for details.

Temporal extent

The building density layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: http://doi.org/10.1594/PANGAEA.920894)

The building height layer is representative for ca. 2015 (doi: 10.5281/zenodo.4066295)

The building types layer is based on Sentinel-2 time series data from 2018 and Sentinel-1 time series data from 2017 (doi: 10.5281/zenodo.4601219)

The underlying census data is from 2018.

Data format

The data come in tiles of 30x30km (see shapefile). The projection is EPSG:3035. The images are compressed GeoTiff files (*.tif). There is a mosaic in GDAL Virtual format (*.vrt), which can readily be opened in most Geographic Information Systems.

Further information

For further information, please see the publication or contact Franz Schug (franz.schug@geo.hu-berlin.de).
A web-visualization of this dataset is available here.

Publication

Schug, F., Frantz, D., van der Linden, S., & Hostert, P. (2021). Gridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates. PLOS ONE. DOI: 10.1371/journal.pone.0249044

Acknowledgements

Census data were provided by the German Federal Statistical Offices.

Funding
This dataset was produced with funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (MAT_STOCKS, grant agreement No 741950).

What’s Included

Welcome to the German Brainstorming Prompt-Response Dataset, a meticulously curated collection of 2000 prompt and response pairs. This dataset is a valuable resource for enhancing the creative and generative abilities of Language Models (LMs), a critical aspect in advancing generative AI.

These prompt and completion pairs cover a broad range of topics, including science, history, technology, geography, literature, current affairs, and more. Each prompt is accompanied by a response, providing valuable information and insights to enhance the language model training process. Both the prompt and response were manually curated by native German people, and references were taken from diverse sources like books, news articles, websites, and other reliable references.

This dataset encompasses various prompt types, including instruction type, continuation type, and in-context learning (zero-shot, few-shot) type. Additionally, you'll find prompts and responses containing rich text elements, such as tables, code, JSON, etc., all in proper markdown format.

The German version is grammatically accurate without any spelling or grammatical errors. No copyrighted, toxic, or harmful content is used during the construction of this dataset.

Germany DE: Population Living in Slums: % of Urban Population data was reported at 0.010 % in 2018. This stayed constant from the previous number of 0.010 % for 2016. Germany DE: Population Living in Slums: % of Urban Population data is updated yearly, averaging 0.010 % from Dec 2016 (Median) to 2018, with 2 observations. The data reached an all-time high of 0.010 % in 2018 and a record low of 0.010 % in 2018. Germany DE: Population Living in Slums: % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Population living in slums is the proportion of the urban population living in slum households. A slum household is defined as a group of individuals living under the same roof lacking one or more of the following conditions: access to improved water, access to improved sanitation, sufficient living area, housing durability, and security of tenure, as adopted in the Millennium Development Goal Target 7.D. The successor, the Sustainable Development Goal 11.1.1, considers inadequate housing (housing affordability) to complement the above definition of slums/informal settlements.;United Nations Human Settlements Programme (UN-HABITAT);Weighted average;

Germany DE: Refugee Population: by Country or Territory of Origin data was reported at 209.000 Person in 2023. This records an increase from the previous number of 162.000 Person for 2022. Germany DE: Refugee Population: by Country or Territory of Origin data is updated yearly, averaging 162.000 Person from Dec 1991 (Median) to 2023, with 33 observations. The data reached an all-time high of 1,297.000 Person in 1999 and a record low of 5.000 Person in 1992. Germany DE: Refugee Population: by Country or Territory of Origin data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Germany – Table DE.World Bank.WDI: Population and Urbanization Statistics. Refugees are people who are recognized as refugees under the 1951 Convention Relating to the Status of Refugees or its 1967 Protocol, the 1969 Organization of African Unity Convention Governing the Specific Aspects of Refugee Problems in Africa, people recognized as refugees in accordance with the UNHCR statute, people granted refugee-like humanitarian status, and people provided temporary protection. Asylum seekers--people who have applied for asylum or refugee status and who have not yet received a decision or who are registered as asylum seekers--are excluded. Palestinian refugees are people (and their descendants) whose residence was Palestine between June 1946 and May 1948 and who lost their homes and means of livelihood as a result of the 1948 Arab-Israeli conflict. Country of origin generally refers to the nationality or country of citizenship of a claimant.;United Nations High Commissioner for Refugees (UNHCR), Refugee Data Finder at https://www.unhcr.org/refugee-statistics/.;Sum;