About this dataset

Context

The dataset tabulates the Russia town 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 Russia town 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 Russia town was 2,268, a 0.40% increase year-by-year from 2022. Previously, in 2022, Russia town population was 2,259, a decline of 0.40% compared to a population of 2,268 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Russia town decreased by 219. In this period, the peak population was 2,603 in the year 2011. 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 Russia town is shown in this column.
• Year on Year Change: This column displays the change in Russia town 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 Russia town Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Russia 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 Russia 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 1,472 (58.46% 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 Russia town population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Russia town is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Russia 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 Russia town Population by Age. You can refer the same here

Large Scale International Boundaries

Version 11.1 Release Date: August 22, 2022

Overview

The Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. These data and their derivatives are the only international boundary lines approved for U.S. Government use. They reflect U.S. Government policy, and not necessarily de facto limits of control. This dataset is a National Geospatial Data Asset.

Details

Sources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery of the data involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.

Attributes

The dataset uses the following attributes: Attribute Name Explanation Country Code Country-level codes are from the Geopolitical Entities, Names, and Codes Standard (GENC). The Q2 code denotes a line representing a boundary associated with an area not in GENC. Country Names Names approved by the U.S. Board on Geographic Names (BGN). Names for lines associated with a Q2 code are descriptive and are not necessarily BGN-approved. Label Required text label for the line segment where scale permits Rank/Status Rank 1: International Boundary Rank 2: Other Line of International Separation Rank 3: Special Line Notes Explanation of any applicable special circumstances Cartographic Usage Depiction of the LSIB requires a visual differentiation between the three categories of boundaries: International Boundaries (Rank 1), Other Lines of International Separation (Rank 2), and Special Lines (Rank 3). Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary. Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues. Please direct inquiries to internationalboundaries@state.gov.

Credits

The lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre. Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.

Changes from Prior Release

This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Changes to lines include: • Akrotiri (UK) / Cyprus • Albania / Montenegro • Albania / Greece • Albania / North Macedonia • Armenia / Turkey • Austria / Czechia • Austria / Slovakia • Austria / Hungary • Austria / Slovenia • Austria / Germany • Austria / Italy • Austria / Switzerland • Azerbaijan / Turkey • Azerbaijan / Iran • Belarus / Latvia • Belarus / Russia • Belarus / Ukraine • Belarus / Poland • Bhutan / India • Bhutan / China • Bulgaria / Turkey • Bulgaria / Romania • Bulgaria / Serbia • Bulgaria / Romania • China / Tajikistan • China / India • Croatia / Slovenia • Croatia / Hungary • Croatia / Serbia • Croatia / Montenegro • Czechia / Slovakia • Czechia / Poland • Czechia / Germany • Finland / Russia • Finland / Norway • Finland / Sweden • France / Italy • Georgia / Turkey • Germany / Poland • Germany / Switzerland • Greece / North Macedonia • Guyana / Suriname • Hungary / Slovenia • Hungary / Serbia • Hungary / Romania • Hungary / Ukraine • Iran / Turkey • Iraq / Turkey • Italy / Slovenia • Italy / Switzerland • Italy / Vatican City • Italy / San Marino • Kazakhstan / Russia • Kazakhstan / Uzbekistan • Kosovo / north Macedonia • Kosovo / Serbia • Kyrgyzstan / Tajikistan • Kyrgyzstan / Uzbekistan • Latvia / Russia • Latvia / Lithuania • Lithuania / Poland • Lithuania / Russia • Moldova / Ukraine • Moldova / Romania • Norway / Russia • Norway / Sweden • Poland / Russia • Poland / Ukraine • Poland / Slovakia • Romania / Ukraine • Romania / Serbia • Russia / Ukraine • Syria / Turkey • Tajikistan / Uzbekistan

This release also contains topology fixes, land boundary terminus refinements, and tripoint adjustments.

Copyright Notice and Disclaimer

While U.S. Government works prepared by employees of the U.S. Government as part of their official duties are not subject to Federal copyright protection (see 17 U.S.C. § 105), copyrighted material incorporated in U.S. Government works retains its copyright protection. The works on or made available through download from the U.S. Department of State’s website may not be used in any manner that infringes any intellectual property rights or other proprietary rights held by any third party. Use of any copyrighted material beyond what is allowed by fair use or other exemptions may require appropriate permission from the relevant rightsholder. With respect to works on or made available through download from the U.S. Department of State’s website, neither the U.S. Government nor any of its agencies, employees, agents, or contractors make any representations or warranties—express, implied, or statutory—as to the validity, accuracy, completeness, or fitness for a particular purpose; nor represent that use of such works would not infringe privately owned rights; nor assume any liability resulting from use of such works; and shall in no way be liable for any costs, expenses, claims, or demands arising out of use of such works.

About this dataset

Context

The dataset tabulates the Russia population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Russia. The dataset can be utilized to understand the population distribution of Russia by age. For example, using this dataset, we can identify the largest age group in Russia.

Key observations

The largest age group in Russia, OH was for the group of age Under 5 years years with a population of 91 (12.41%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Russia, OH was the 60 to 64 years years with a population of 14 (1.91%). 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 groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Russia is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Russia total population. 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 Russia Population by Age. You can refer the same here

This database provides construction of Large Urban Regions (LUR) in Russia. A Large Urban Region (LUR) can be defined as an aggregation of continuous statistical units around a core that are economically dependent on this core and linked to it by economic and social strong interdependences. The main purpose of this delineation is to make cities comparable on the national and world scales and to make comparative social-economic urban studies. Aggregating different municipal districts around a core city, we construct a single large urban region, which allows to include all the area of economic influence of a core into one statistical unit (see Rogov & Rozenblat, 2020 for more details) thus, changing a city position in a global urban hierarchy. In doing so we use four principal urban concepts (Pumain et al., 1992): political definition, morphological definition, functional definition and conurbation that we call Large Urban Region. We constructed Russian LURs using criteria such as population distribution, road networks, access to an airport, distance from a core, presence of multinational firms. In this database, we provide population data for LURs and their administrative units.

Dataset Card for Russia Ukraine Conflict

  Dataset Summary

Context

On 24 February 2022, Russia invaded Ukraine in a major escalation of the Russo-Ukrainian War that began in 2014. The invasion caused Europe's largest refugee crisis since World War II, with more than 6.3 million Ukrainians fleeing the country and a third of the population displaced (Source: Wikipedia).

Content

This dataset is a collection of 407 news articles from NYT and Guardians related to ongoing… See the full description on the dataset page: https://huggingface.co/datasets/hugginglearners/russia-ukraine-conflict-articles.

About this dataset

Context

The dataset tabulates the population of Russia town by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Russia town. The dataset can be utilized to understand the population distribution of Russia town by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Russia town. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Russia town.

Key observations

Largest age group (population): Male # 65-69 years (154) | Female # 0-4 years (129). 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 groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Russia town population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Russia town is shown in the following column.
• Population (Female): The female population in the Russia town is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Russia town for each age group.

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 Russia town Population by Gender. You can refer the same here

The Gross Domestic Product (GDP) in Russia was worth 2173.84 billion US dollars in 2024, according to official data from the World Bank. The GDP value of Russia represents 2.05 percent of the world economy. This dataset provides the latest reported value for - Russia GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Youtube/Youtube Shorts Comments Dataset (Russian & English)

  Brief Description

A large dataset of approximately 290,000 comments collected from YouTube Shorts videos in Russian and English. Each comment is stored on its own line.

  Dataset Description

The dataset contains raw text comments, one comment per line. It is suitable for training language models, text analysis, or other NLP tasks.

  Data Format

File type: plain text (.txt) Each comment occupies… See the full description on the dataset page: https://huggingface.co/datasets/akaruineko/shorts_youtube-comments.

🇷🇺 Russian Public Domain 🇷🇺

Russian-Public Domain or Russian-PD is a large collection aiming to aggregate all Russian monographies and periodicals in the public domain.

  Dataset summary

The collection contains 8525 titles making up 995,163,165 words recovered from the Internet Archive. Each parquet file has the full text of 2,000 books selected at random.

  Curation method

The composition of the dataset adheres to the criteria for public domain works in the… See the full description on the dataset page: https://huggingface.co/datasets/PleIAs/Russian-PD.

NEREL dataset

  Dataset Description

NEREL dataset (https://doi.org/10.48550/arXiv.2108.13112) is a Russian dataset for named entity recognition and relation extraction. NEREL is significantly larger than existing Russian datasets: to date it contains 56K annotated named entities and 39K annotated relations. Its important difference from previous datasets is annotation of nested named entities, as well as relations within nested entities and at the discourse level. NEREL can… See the full description on the dataset page: https://huggingface.co/datasets/iluvvatar/NEREL.

This post contains a database of Russian numeral constructions from the RuTenTen corpus (https://www.sketchengine.co.uk/rutenten-russian-corpus/). The constructions are of the following type: paucal numeral (2, 3 or 4) followed by an adjective and a feminine noun. Abstract: With the advent of large web-based corpora, Russian linguistics steps into the era of “big data”. But how useful are large datasets in our field? What are the advantages? Which problems arise? The present study seeks to shed light on these questions based on an investigation of the Russian paucal construction in the RuTenTen corpus, a web-based corpus with more than ten billion words. The focus is on the choice between adjectives in the nominative (dve/tri/četyre starye knigi) and genitive (dve/tri/četyre staryx knigi) in paucal constructions with the numerals dve, tri or četyre and a feminine noun. Three generalizations emerge. First, the large RuTenTen dataset enables us to identify predictors that could not be explored in smaller corpora. In particular, it is shown that predicates, modifiers, prepositions and word-order affect the case of the adjective. Second, we identify situations where the RuTenTen data cannot be straightforwardly reconciled with findings from earlier studies or there appear to be discrepancies between different statistical models. In such cases, further research is called for. The effect of the numeral (dve, tri vs. četyre) and verbal government are relevant examples. Third, it is shown that adjectives in the nominative have more easily learnable predictors that cover larger classes of examples and show clearer preferences for the relevant case. It is therefore suggested that nominative adjectives have the potential to outcompete adjectives in the genitive over time. Although these three generalizations are valuable additions to our knowledge of Russian paucal constructions, three problems arise. Large internet-based corpora like the RuTenTen corpus (a) are not balanced, (b) involve a certain amount of “noise”, and (c) do not provide metadata. As a consequence of this, it is argued, it may be wise to exercise some caution with regard to conclusions based on “big data”.

Датасет собранный из олимпиад по физике разного уровня, class означает происхождение задачи по уровню олимпиады. Dataset collected from physics olympiads of different levels, class means the origin of the problem by the level of the olympiad. @misc{nikolich2024vikhr, title={Vikhr: The Family of Open-Source Instruction-Tuned Large Language Models for Russian}, author={Aleksandr Nikolich and Konstantin Korolev and Artem Shelmanov and Igor Kiselev}, year={2024}… See the full description on the dataset page: https://huggingface.co/datasets/Vikhrmodels/russian_physics.

Cultura-Ru-Edu

The Cultura-Ru-Edu dataset consists of Russian educational web pages filtered from the uonlp/CulturaX dataset. The dataset creation was inspired by HuggingFaceFW/fineweb-edu, but with a focus on the Russian language. By filtering the dataset based on educational criteria, the Cultura-Ru-Edu dataset is both high-quality and large enough to train a Russian-focused language model for tasks requiring knowledge of the world.

  Dataset curation

To create this… See the full description on the dataset page: https://huggingface.co/datasets/deepvk/cultura_ru_edu.

Nexdata has off-the-shelf 35,000 hours Machine Learning (ML) Data of 16kHz conversational speech, covering 100+ countries including English, German, French, Spanish, Italian, Portuguese, Korean, Japanese, Hindi, Russia and etc.

United States Imports from Russia of Fertilizers was US$1.3 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Imports from Russia of Fertilizers - data, historical chart and statistics - was last updated on July of 2025.

Bathymetric contours were generated from soundings collected during surveys and cruises by the Hydrographic Office, National Ocean Survey, and Coast and Geodetic Survey. The region covered by the map is the Bering Sea Shelf from Bristol Bay, Alaska to the Gulf of Anadyr, Russia. Bathymetry is in meters at 10 m intervals, with 5 m supplemental contours. The digitized portion includes the Anadyr Gulf and Bering Strait in Russian waters (west of the Exclusive Economic Zone), to supplement digitized National Ocean Service maps of U.S. waters (Coastal Shelf Bathymetry of the Bering, Chukchi, and Beaufort Seas). The original paper map was produced by the Geological Society of America and published in 1974. The map is no longer in print from the Geological Society of America (3300 Penrose Place, Boulder, CO 80301) but may be available at natural resource agency libraries that include literature on Alaska and/or Russia. In 1997, the USGS digitized the bathymetric contours for research purposes.

China Exports to Russia was US$115.28 Billion during 2024, according to the United Nations COMTRADE database on international trade. China Exports to Russia - data, historical chart and statistics - was last updated on June of 2025.

This dataset provides values for GOLD RESERVES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

About this dataset

Context

The dataset tabulates the Russia township population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Russia township. The dataset can be utilized to understand the population distribution of Russia township by age. For example, using this dataset, we can identify the largest age group in Russia township.

Key observations

The largest age group in Russia Township, Minnesota was for the group of age 50 to 54 years years with a population of 14 (29.79%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Russia Township, Minnesota was the 20 to 24 years years with a population of 0 (0%). 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 groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Russia township is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Russia township total population. 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 Russia township Population by Age. You can refer the same here