The DXY exchange rate rose to 97.4248 on September 18, 2025, up 0.57% from the previous session. Over the past month, the United States Dollar has weakened 0.86%, and is down by 3.23% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on September of 2025.

When converted to the value of one US dollar in 2020, goods and services that cost one dollar in 1700 would cost just over 63 dollars in 2020, this means that one dollar in 1700 was worth approximately 63 times more than it is today. This data can be used to calculate how much goods and services from the years shown would cost today, by multiplying the price from then by the number shown in the graph. For example, an item that cost 50 dollars in 1970 would theoretically cost 335.5 US dollars in 2020 (50 x 6.71 = 335.5), although it is important to remember that the prices of individual goods and services inflate at different rates than currency, therefore this graph must only be used as a guide.

The EUR/USD exchange rate fell to 1.1797 on September 18, 2025, down 0.24% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 1.34%, and is up by 5.72% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on September of 2025.

Money Supply M0 in the United States decreased to 5740300 USD Million in July from 5748800 USD Million in June of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

View the live USD/MXN rate, historical performance, and forecasts for the Mexican Peso. Stay up to date with charts, data, and analysis from Trading Economics.

The dataset of INR to Dollar exchange rates from 2003 to 2024 downloaded from Yahoo Finance likely contains historical exchange rate data for the Indian Rupee (INR) against the US Dollar (USD) over the specified time period. Here's a general description of what you might find in such a dataset:

1. Date: Each entry in the dataset likely includes a date or timestamp indicating when the exchange rate was recorded.

2. Exchange Rate: The dataset should include the exchange rate value, representing the number of Indian Rupees equivalent to one US Dollar on the corresponding date.

3. Time Period: The dataset should cover exchange rate data for each trading day or a specified frequency (e.g., weekly, monthly) from 2003 to 2024.

4. Additional Information: Depending on the source and format of the dataset, it may include additional information such as opening, high, low, and closing exchange rates for each day, as well as volume and adjusted closing prices.

5. Currency Pair: The dataset focuses specifically on the exchange rate between the Indian Rupee (INR) and the US Dollar (USD), allowing users to analyze trends and fluctuations in the value of the Indian Rupee relative to the US Dollar over time.

6. The dataset of INR to Dollar exchange rates from 2003 to 2024 downloaded from Yahoo Finance likely contains historical exchange rate data for the Indian Rupee (INR) against the US Dollar (USD) over the specified time period. Here's a general description of what you might find in such a dataset:

7. Date: Each entry in the dataset likely includes a date or timestamp indicating when the exchange rate was recorded.

8. Exchange Rate: The dataset should include the exchange rate value, representing the number of Indian Rupees equivalent to one US Dollar on the corresponding date.

9. Time Period: The dataset should cover exchange rate data for each trading day or a specified frequency (e.g., weekly, monthly) from 2003 to 2024.

10. Additional Information: Depending on the source and format of the dataset, it may include additional information such as opening, high, low, and closing exchange rates for each day, as well as volume and adjusted closing prices.

11. Currency Pair: The dataset focuses specifically on the exchange rate between the Indian Rupee (INR) and the US Dollar (USD), allowing users to analyze trends and fluctuations in the value of the Indian Rupee relative to the US Dollar over time.

12. Data Quality: It's important to consider the reliability and accuracy of the data. Ensure that the dataset is sourced from a reputable financial data provider like Yahoo Finance and that any missing or erroneous data points are appropriately handled.

Overall, this dataset can be used for various analytical purposes, including trend analysis, forecasting, and risk management in the context of currency exchange markets and international finance.: It's important to consider the reliability and accuracy of the data. Ensure that the dataset is sourced from a reputable financial data provider like Yahoo Finance and that any missing or erroneous data points are appropriately handled.

Overall, this dataset can be used for various analytical purposes, including trend analysis, forecasting, and risk management in the context of currency exchange markets and international finance.

Inflation Rate in the United States increased to 2.90 percent in August from 2.70 percent in July of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset contains news headlines relevant to key forex pairs: AUDUSD, EURCHF, EURUSD, GBPUSD, and USDJPY. The data was extracted from reputable platforms Forex Live and FXstreet over a period of 86 days, from January to May 2023. The dataset comprises 2,291 unique news headlines. Each headline includes an associated forex pair, timestamp, source, author, URL, and the corresponding article text. Data was collected using web scraping techniques executed via a custom service on a virtual machine. This service periodically retrieves the latest news for a specified forex pair (ticker) from each platform, parsing all available information. The collected data is then processed to extract details such as the article's timestamp, author, and URL. The URL is further used to retrieve the full text of each article. This data acquisition process repeats approximately every 15 minutes.

To ensure the reliability of the dataset, we manually annotated each headline for sentiment. Instead of solely focusing on the textual content, we ascertained sentiment based on the potential short-term impact of the headline on its corresponding forex pair. This method recognizes the currency market's acute sensitivity to economic news, which significantly influences many trading strategies. As such, this dataset could serve as an invaluable resource for fine-tuning sentiment analysis models in the financial realm.

We used three categories for annotation: 'positive', 'negative', and 'neutral', which correspond to bullish, bearish, and hold sentiments, respectively, for the forex pair linked to each headline. The following Table provides examples of annotated headlines along with brief explanations of the assigned sentiment.

Examples of Annotated Headlines


    Forex Pair
    Headline
    Sentiment
    Explanation




    GBPUSD 
    Diminishing bets for a move to 12400 
    Neutral
    Lack of strong sentiment in either direction


    GBPUSD 
    No reasons to dislike Cable in the very near term as long as the Dollar momentum remains soft 
    Positive
    Positive sentiment towards GBPUSD (Cable) in the near term


    GBPUSD 
    When are the UK jobs and how could they affect GBPUSD 
    Neutral
    Poses a question and does not express a clear sentiment


    JPYUSD
    Appropriate to continue monetary easing to achieve 2% inflation target with wage growth 
    Positive
    Monetary easing from Bank of Japan (BoJ) could lead to a weaker JPY in the short term due to increased money supply


    USDJPY
    Dollar rebounds despite US data. Yen gains amid lower yields 
    Neutral
    Since both the USD and JPY are gaining, the effects on the USDJPY forex pair might offset each other


    USDJPY
    USDJPY to reach 124 by Q4 as the likelihood of a BoJ policy shift should accelerate Yen gains 
    Negative
    USDJPY is expected to reach a lower value, with the USD losing value against the JPY


    AUDUSD

RBA Governor Lowe’s Testimony High inflation is damaging and corrosive

    Positive
    Reserve Bank of Australia (RBA) expresses concerns about inflation. Typically, central banks combat high inflation with higher interest rates, which could strengthen AUD.

Moreover, the dataset includes two columns with the predicted sentiment class and score as predicted by the FinBERT model. Specifically, the FinBERT model outputs a set of probabilities for each sentiment class (positive, negative, and neutral), representing the model's confidence in associating the input headline with each sentiment category. These probabilities are used to determine the predicted class and a sentiment score for each headline. The sentiment score is computed by subtracting the negative class probability from the positive one.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Lost Creek. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Lost Creek, the median income for all workers aged 15 years and older, regardless of work hours, was $41,429 for males and $33,359 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 19% between the median incomes of males and females in Lost Creek. With women, regardless of work hours, earning 81 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetown of Lost Creek.

- Full-time workers, aged 15 years and older: In Lost Creek, among full-time, year-round workers aged 15 years and older, males earned a median income of $54,306, while females earned $35,341, leading to a 35% gender pay gap among full-time workers. This illustrates that women earn 65 cents for each dollar earned by men in full-time roles. This level of income gap emphasizes the urgency to address and rectify this ongoing disparity, where women, despite working full-time, face a more significant wage discrepancy compared to men in the same employment roles.

Remarkably, across all roles, including non-full-time employment, women displayed a lower gender pay gap percentage. This indicates that Lost Creek offers better opportunities for women in non-full-time positions.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Lost Creek median household income by race. You can refer the same here

The United States recorded a trade deficit of 78.31 USD Billion in July of 2025. This dataset provides the latest reported value for - United States Balance of Trade - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The USD/ILS exchange rate rose to 3.3392 on September 18, 2025, up 0.11% from the previous session. Over the past month, the Israeli Shekel has strengthened 1.57%, and is up by 10.87% over the last 12 months. Israeli Shekel - values, historical data, forecasts and news - updated on September of 2025.

View economic output, reported as the nominal value of all new goods and services produced by labor and property located in the U.S.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Long Lost Lake township. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Long Lost Lake township, the median income for all workers aged 15 years and older, regardless of work hours, was $73,750 for males and $44,861 for females.

These income figures highlight a substantial gender-based income gap in Long Lost Lake township. Women, regardless of work hours, earn 61 cents for each dollar earned by men. This significant gender pay gap, approximately 39%, underscores concerning gender-based income inequality in the township of Long Lost Lake township.

- Full-time workers, aged 15 years and older: In Long Lost Lake township, for full-time, year-round workers aged 15 years and older, the Census Bureau did not report the median income for both males and females due to an insufficient number of sample observations.

As income data for both males and females was unavailable, conducting a comprehensive analysis of gender-based pay disparity in the township of Long Lost Lake township was not possible.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Long Lost Lake township median household income by race. You can refer the same here

Context

The Turkish Lira is losing its value against U.S. Dollar constantly. As of October 22, 2021, 1 USD = 9.61 Turkish Lira (TRY). On the other hand, interest rates are quite high, especially for the Turkish Lira.

I set out to investigate if I had $100000 in 2010 and invested this money in different interest rates in both Turkish Lira (TRY) and US Dollar (USD), which investment would bring more gain in 2021.

Content

The data has been gathered from Türkiye Cumhuriyeti Merkez Bankasi (TCMB), aka the Turkish FED, website. The data shows the historical interest rates as well as USD/TRY conversion rates between July 2010 and July 2021. The original data’s all column names and relative explanations were Turkish, so the columns are renamed and the data is cleaned.

There are ten cleaned columns on the dataset: Date, 1-month TRY interest rates, 3 months TRY interest rates, 6 months TRY interest rates, 1-year TRY interest rates, 1 month USD interest rates, 3 months USD interest rates, 6 months USD interest rates, 1 year USD interest rates, USD/TRY Buying Conversion Rate, USD/TRY Selling Conversion Rate.

** USD Buying means, the customer is selling USD to the bank/ exchange office ** USD Selling means, the customer is buying USD to the bank/ exchange office

Inspiration

Would it be more beneficial if I converted my $100000 in July 2010 to Turkish Lira, which is the equivalent of 153631.36 TRY using July 2010’s rates and invested with Turkish high-interest rates or kept my money as U.S. Dollars and invested with relatively lower U.S. Dollar interest rates until July 2021? $100000 is equivalent to 861294.12 TRY in July 2021.

The USD/TRY exchange rate rose to 41.3032 on September 18, 2025, up 0.13% from the previous session. Over the past month, the Turkish Lira has weakened 1.06%, and is down by 21.18% over the last 12 months. Turkish Lira - values, historical data, forecasts and news - updated on September of 2025.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Lost Nation. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Lost Nation, the median income for all workers aged 15 years and older, regardless of work hours, was $45,208 for males and $22,778 for females.

These income figures highlight a substantial gender-based income gap in Lost Nation. Women, regardless of work hours, earn 50 cents for each dollar earned by men. This significant gender pay gap, approximately 50%, underscores concerning gender-based income inequality in the city of Lost Nation.

- Full-time workers, aged 15 years and older: In Lost Nation, among full-time, year-round workers aged 15 years and older, males earned a median income of $51,667, while females earned $36,719, leading to a 29% gender pay gap among full-time workers. This illustrates that women earn 71 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Lost Nation.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2023
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Lost Nation median household income by race. You can refer the same here

The USD/CAD exchange rate rose to 1.3799 on September 18, 2025, up 0.21% from the previous session. Over the past month, the Canadian Dollar has strengthened 0.49%, but it's down by 1.74% over the last 12 months. Canadian Dollar - values, historical data, forecasts and news - updated on September of 2025.

About this dataset

Context

The dataset illustrates the median household income in Lost Nation, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Lost Nation decreased by $7,540 (12.88%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 6 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

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 Lost Nation median household income. You can refer the same here

Administrative unitsRepresents the administrative units used for GDP per capita (PPP) and HDI data products. National administrative units have id 1-999, sub-national ones 1001-admin_areas_GDP_HDI.ncGDP_per_capita_PPP_1990_2015The GDP per capita (PPP) dataset represents average gross domestic production per capita in a given administrative area unit. GDP is given in 2011 international US dollars. Gap-filled sub-national data were used, supplemented by national data where necessary. Datagaps were filled by using national temporal pattern. Dataset has global extent at 5 arc-min resolution for the 26-year period of 1990-2015. Detail description is given in a linked article and metadata is provided as an attribute in the NetCDF file itself.GDP_PPP_1990_2015_5arcminThis global dataset represents the gross domestic production (GDP) of each grid cell. GDP is given in 2011 international US dollars. The data is derived from GDP per capita (PPP) which is multiplied by gridded population data HYDE 3.2 (the years of population data not available (1991-1999) were linearly interpolated at grid scale based on data from years 1990 and 2000). Dataset has global extent at 5 arc-min resolution for the 26-year period of 1990-2015. Detail description is given in a linked article and metadata is provided as an attribute in the NetCDF file itself.HDI_1990_2015HDI is a composite index of average achievement in key dimensions of human development (dimensionless indicator between 0 and 1). This index is based on method introduced 2010 and updated 2011. The subnational data for HDI were collected from multiple national-level datasets, and national-level HDI was collected from UNDP. Years with missing data were interpolated over time thin plate spines, assuming smooth trend over time. The dataset has a global extent at 5 arc-min resolution, and the annual data is available for each year over 1990-2015. HDI sub-national data covers 39 countries and 66% of global population in 2015.pedigree_GDP_per_capita_PPP_1990_2015This is the source data for GDP per capita (PPP), published as an indication of accuracy and precision. Reports the scale (national, sub-national) and type (reported, interpolated, extrapolated) of each year of data. Detail description is given in a linked article and metadata is provided as an attribute in the NetCDF file itself.pedigree_HDI_1990_2015This is the source data for Human Development Index (HDI), published as an indication of accuracy and precision. Reports the scale (national, sub-national) and type (reported, interpolated, extrapolated) of each year of data. Detail description is given in a linked article and metadata is provided as an attribute in the NetCDF file itself. Detail description is given in a linked article and metadata is provided as an attribute in the NetCDF file itself.GDP_PPP_30arcsecThe GDP (PPP) data represents average gross domestic production of each grid cell. GDP is given in 2011 international US dollars. The data is derived from GDP per capita (PPP), which is multiplied by gridded population data from Global Human Settlement (GHS). Dataset has a global extent at 30 arc-second resolution for three time steps: 1990, 2000, and 2015. Detail description is given in a linked article and metadata is provided as an attribute in the NetCDF file itself.kummu_etal_scidata_codeThis file contains the scripts for data handling and production An increasing amount of high-resolution global spatial data are available, and used for various assessments. However, key economic and human development indicators are still mainly provided only at national level, and downscaled by users for gridded spatial analyses. Instead, it would be beneficial to adopt data for sub-national administrative units where available, supplemented by national data where necessary. To this end, we present gap-filled multiannual datasets in gridded form for Gross Domestic Product (GDP) and Human Development Index (HDI). To provide a consistent product over time and space, the sub-national data were only used indirectly, scaling the reported national value and thus, remaining representative of the official statistics. This resulted in annual gridded datasets for GDP per capita (PPP), total GDP (PPP), and HDI, for the whole world at 5 arc-min resolution for the 25-year period of 1990–2015. Additionally, total GDP (PPP) is provided with 30 arc-sec resolution for three time steps (1990, 2000, 2015).

The USD/RUB exchange rate fell to 83.0953 on September 18, 2025, down 1.08% from the previous session. Over the past month, the Russian Ruble has weakened 2.87%, but it's up by 9.85% over the last 12 months. Russian Ruble - values, historical data, forecasts and news - updated on September of 2025.