Inflation Rate in the United States increased to 3 percent in September from 2.90 percent in August of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context:

Inflation is a critical economic indicator that reflects the overall increase in prices of goods and services within an economy over a specific period. Understanding inflation trends on a global scale is crucial for economists, policymakers, investors, and businesses. This dataset provides comprehensive insights into the inflation rates of various countries for the year 2022. The data is sourced from reputable international organizations and government reports, making it a valuable resource for economic analysis and research.

Content:

This dataset includes four essential columns:

1.**Countries:** The names of countries for which inflation data is recorded. Each row represents a specific country.

2.**Inflation, 2022:** The inflation rate for each country in the year 2022. Inflation rates are typically expressed as a percentage and indicate the average increase in prices for that year.

3.**Global Rank:** The rank of each country based on its inflation rate in 2022. Countries with the highest inflation rates will have a lower rank, while those with lower inflation rates will have a higher rank.

4.**Available Data:** A binary indicator (Yes/No) denoting whether complete and reliable data for inflation in 2022 is available for a particular country. This column helps users identify the data quality and coverage.

Potential Use Cases:

-**Economic Analysis:** Researchers and economists can use this dataset to analyze inflation trends globally, identify countries with high or low inflation rates, and make comparisons across regions.

-**Investment Decisions:** Investors and financial analysts can incorporate inflation data into their risk assessments and investment strategies.

-**Business Planning:** Companies operating in multiple countries can assess the impact of inflation on their costs and pricing strategies, helping them make informed decisions.

Data Accuracy: Efforts have been made to ensure the accuracy and reliability of the data; however, users are encouraged to cross-reference this dataset with official sources for critical decision-making processes.

Updates: This dataset will be periodically updated to include the latest available inflation data, making it an ongoing resource for tracking global inflation trends.

Acknowledgments: We would like to express our gratitude to the numerous agencies and organizations that collect and publish inflation data, contributing to the transparency and understanding of economic conditions worldwide.

License: This dataset is provided under an open data license, allowing users to freely use and share the data while adhering to the specified licensing terms.

Feel free to adapt and expand upon this template to create a comprehensive and informative dataset description for your Kaggle publication on global inflation rates for 2022.

This dataset is about books. It has 1 row and is filtered where the book is Choice in currency : a way to stop inflation. It features 7 columns including author, publication date, language, and book publisher.

Inflation is generally defined as the continued increase in the average prices of goods and services in a given region. Following the extremely high global inflation experienced in the 1980s and 1990s, global inflation has been relatively stable since the turn of the millennium, usually hovering between three and five percent per year. There was a sharp increase in 2008 due to the global financial crisis now known as the Great Recession, but inflation was fairly stable throughout the 2010s, before the current inflation crisis began in 2021. Recent years Despite the economic impact of the coronavirus pandemic, the global inflation rate fell to 3.26 percent in the pandemic's first year, before rising to 4.66 percent in 2021. This increase came as the impact of supply chain delays began to take more of an effect on consumer prices, before the Russia-Ukraine war exacerbated this further. A series of compounding issues such as rising energy and food prices, fiscal instability in the wake of the pandemic, and consumer insecurity have created a new global recession, and global inflation in 2024 is estimated to have reached 5.76 percent. This is the highest annual increase in inflation since 1996. Venezuela Venezuela is the country with the highest individual inflation rate in the world, forecast at around 200 percent in 2022. While this is figure is over 100 times larger than the global average in most years, it actually marks a decrease in Venezuela's inflation rate, which had peaked at over 65,000 percent in 2018. Between 2016 and 2021, Venezuela experienced hyperinflation due to the government's excessive spending and printing of money in an attempt to curve its already-high inflation rate, and the wave of migrants that left the country resulted in one of the largest refugee crises in recent years. In addition to its economic problems, political instability and foreign sanctions pose further long-term problems for Venezuela. While hyperinflation may be coming to an end, it remains to be seen how much of an impact this will have on the economy, how living standards will change, and how many refugees may return in the coming years.

Description:

This dataset provides key economic indicators from various countries between 2010 and 2023. The dataset includes monthly data on inflation rates, GDP growth rates, unemployment rates, interest rates, and stock market index values. The data has been sourced from reputable global financial institutions and is suitable for economic analysis, machine learning models, and forecasting economic trends.

Data Sources:

The data has been generated to simulate real-world economic conditions, mimicking information from trusted sources like: - World Bank for GDP growth and inflation data - International Monetary Fund (IMF) for macroeconomic data - OECD for labor market statistics - National Stock Exchanges for stock market index values

Columns:

1. Date: The specific date (in Year/Month/Day format) representing when the data was collected.
2. Country: The country the data pertains to (e.g., USA, Germany, Japan).
3. Inflation Rate (%): The rate of inflation for that country, showing how fast prices for goods and services are increasing.
4. GDP Growth Rate (%): The percentage growth of the country’s Gross Domestic Product (GDP), indicating economic expansion or contraction.
5. Unemployment Rate (%): The percentage of the working-age population that is unemployed.
6. Interest Rate (%): The central bank's interest rate, used to control inflation and influence the economy.
7. Stock Index Value: The value of the country’s main stock market index, reflecting the performance of the stock market.

Potential Uses: - Economic Analysis: Researchers and analysts can use this dataset to study trends in inflation, GDP growth, unemployment, and other economic factors. - Machine Learning: This dataset can be used to train models for predicting economic trends or market performance. Financial Forecasting: Investors and economists can leverage this data for forecasting market movements based on economic conditions. - Comparative Studies: The dataset allows comparisons across countries and regions, offering insights into global economic performance.

Core consumer prices in Egypt increased 12.10 percent in October of 2025 over the same month in the previous year. This dataset provides - Egypt Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

The Federal Reserve sets interest rates to promote conditions that achieve the mandate set by the Congress — high employment, low and stable inflation, sustainable economic growth, and moderate long-term interest rates. Interest rates set by the Fed directly influence the cost of borrowing money. Lower interest rates encourage more people to obtain a mortgage for a new home or to borrow money for an automobile or for home improvement. Lower rates encourage businesses to borrow funds to invest in expansion such as purchasing new equipment, updating plants, or hiring more workers. Higher interest rates restrain such borrowing by consumers and businesses.

Content

This dataset includes data on the economic conditions in the United States on a monthly basis since 1954. The federal funds rate is the interest rate at which depository institutions trade federal funds (balances held at Federal Reserve Banks) with each other overnight. The rate that the borrowing institution pays to the lending institution is determined between the two banks; the weighted average rate for all of these types of negotiations is called the effective federal funds rate. The effective federal funds rate is determined by the market but is influenced by the Federal Reserve through open market operations to reach the federal funds rate target. The Federal Open Market Committee (FOMC) meets eight times a year to determine the federal funds target rate; the target rate transitioned to a target range with an upper and lower limit in December 2008. The real gross domestic product is calculated as the seasonally adjusted quarterly rate of change in the gross domestic product based on chained 2009 dollars. The unemployment rate represents the number of unemployed as a seasonally adjusted percentage of the labor force. The inflation rate reflects the monthly change in the Consumer Price Index of products excluding food and energy.

Acknowledgements

The interest rate data was published by the Federal Reserve Bank of St. Louis' economic data portal. The gross domestic product data was provided by the US Bureau of Economic Analysis; the unemployment and consumer price index data was provided by the US Bureau of Labor Statistics.

Inspiration

How does economic growth, unemployment, and inflation impact the Federal Reserve's interest rates decisions? How has the interest rate policy changed over time? Can you predict the Federal Reserve's next decision? Will the target range set in March 2017 be increased, decreased, or remain the same?

Inflation occurs when there is a sustained increase in the general price level of goods and services in an economy over time. It impacts various aspects of the economy, including purchasing power, consumer behaviour, savings, and investment. Moderate inflation is typically a sign of a healthy, growing economy, as it encourages spending and investment. However, high or unpredictable inflation can erode the value of money, disrupt financial planning, and lead to economic uncertainty.

To analyze the impact of inflation, we need to compare it with other economic indicators. So, to analyze the impact of inflation on the economy, we will compare it with the exchange rates over time. This comparison is important because exchange rates are influenced by inflation differentials between countries, such that higher inflation in a country generally leads to a weaker currency relative to countries with lower inflation.

Inflation Rate in India decreased to 0.25 percent in October from 1.44 percent in September of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Central Bank of Uruguay: Inflation Target: Upper Limit data was reported at 7.000 % in Jul 2020. This stayed constant from the previous number of 7.000 % for Jun 2020. Central Bank of Uruguay: Inflation Target: Upper Limit data is updated monthly, averaging 7.000 % from Apr 2007 (Median) to Jul 2020, with 160 observations. The data reached an all-time high of 7.000 % in Jul 2020 and a record low of 6.000 % in Jun 2014. Central Bank of Uruguay: Inflation Target: Upper Limit data remains active status in CEIC and is reported by Central Bank of Uruguay. The data is categorized under Global Database’s Uruguay – Table UY.I001: Consumer Price Index: Inflation Target .

Inflation Rate in Pakistan decreased to 6.10 percent in November from 6.20 percent in October of 2025. This dataset provides the latest reported value for - Pakistan Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Inflation Rate in Argentina decreased to 31.30 percent in October from 31.80 percent in September of 2025. This dataset provides the latest reported value for - Argentina Inflation Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

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 Cut And Shoot. 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 Cut And Shoot, the median income for all workers aged 15 years and older, regardless of work hours, was $42,153 for males and $28,313 for females.

These income figures highlight a substantial gender-based income gap in Cut And Shoot. Women, regardless of work hours, earn 67 cents for each dollar earned by men. This significant gender pay gap, approximately 33%, underscores concerning gender-based income inequality in the city of Cut And Shoot.

- Full-time workers, aged 15 years and older: In Cut And Shoot, among full-time, year-round workers aged 15 years and older, males earned a median income of $76,250, while females earned $38,942, leading to a 49% gender pay gap among full-time workers. This illustrates that women earn 51 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 similar gender pay gap percentage. This indicates a consistent gender pay gap scenario across various employment types in Cut And Shoot, showcasing a consistent income pattern irrespective of employment status.

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 Cut And Shoot median household income by race. You can refer the same here

The history of inflation in Uruguay has been a constant challenge for the country's economy. Throughout much of the 20th century, Uruguay experienced high levels of inflation, especially in the 1960s and 1970s. Chronic inflation severely affected the purchasing power of citizens and eroded economic stability. However, starting in the 1990s, the country implemented measures to control inflation, including adopting an inflation targeting regime and a more prudent fiscal policy. These measures had a positive impact, achieving a significant reduction in inflation and greater economic stability in Uruguay in recent decades. Although challenges persist, the fight against inflation has been a key objective for the country, aiming to ensure sustainable growth and improve the well-being of its population.

This dataset was generated by the National Institute of Statistic of Uruguay. They are the ones collecting the information to create the Consumer Price Index.

Their web page is: https://www.gub.uy/instituto-nacional-estadistica/datos-y-estadisticas/estadisticas/series-historicas-ipc-base-octubre-2022100

And the name of the original file is: IPC general, Total País (desde 07/1937), Montevideo e Interior (desde 12/2010), base Octubre 2022=100

On November 15, 2021, President Biden signed the Bipartisan Infrastructure Law (BIL), which invests more than $13 billion directly in Tribal communities across the country and makes Tribal communities eligible for billions more. For further explanation of the law please visit https://www.congress.gov/bill/117th-congress/house-bill/3684/text. These resources go to many Federal agencies to expand access to clean drinking water for Native communities, ensure every Native American has access to high-speed internet, tackle the climate crisis, advance environmental justice, and invest in Tribal communities that have too often been left behind. On August 16, 2022, President Biden signed the Inflation Reduction Act into law, marking the most significant action Congress has taken on clean energy and climate change in the nation’s history. With the stroke of his pen, the President redefined American leadership in confronting the existential threat of the climate crisis and set forth a new era of American innovation and ingenuity to lower consumer costs and drive the global clean energy economy forward. More information on this can be found here: https://www.whitehouse.gov/cleanenergy/inflation-reduction-act-guidebook/ .This dataset illustrates the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022 and 2023.The points illustrated in this dataset are the locations of Bureau of Indian Affairs projects funded by the Bipartisan Infrastructure Law and Inflation Reduction Act in Fiscal Year 2022 and 2023. The locations for the points in this layer were provided by the persons involved in the following groups: Division of Water and Power, DWP, Ecosystem Restoration, Irrigation, Power, Water Sanitation, Dam Safety, Branch of Geospatial Support, Bureau of Indian Affairs, BIA. GIS point feature class was created by Bureau of Indian Affairs - Branch Of Geospatial Support (BOGS), Division of Water and Power (DWP), Ecosystem Restoration, Irrigation, Bureau of Indian Affairs (BIA), Tribal Leaders Directory: https://www.bia.gov/service/tribal-leaders-directory/tld-csvexcel-dataset, The Department of the Interior | Strategic Hazard Identification and Risk Assessment Project: https://www.doi.gov/emergency/shira#main-content Please feel free to contact BOGS at 1-877-293-9494 geospatial@bia.gov

This research note reconsiders the question of whether central bank independence (CBI) and fixed exchange rates (FIX) function as substitutes or complements. We argue that these monetary institutions have neither served as substitutes nor performed as complements for either inflation control or exchange rate stability. In terms of their substitutability, our statistical evidence shows that while CBI has been used for inflation control, FIX has been more directed toward exchange rate stability using updated datasets with these monetary institutions measured both on a de jure and de facto basis with nearly global country/year coverage from 1970 to 2020. In terms of their complementarity, our results also demonstrate that CBI was not more effective at reducing inflation when paired with greater FIX, and FIX was not more effective at promoting exchange rate stability when paired with greater CBI. If anything, both are less effective when paired with the other monetary institution.

Data was cleaned and prepared for a data visualization comparing the Federal Funds Rate to the 10-Year Breakeven Inflation Rate. The purpose of this project was to visualize a perspective of the Federal Reserve. With the Federal Reserve raising rates to control inflation, many are debating when will the Federal Reserve pause raising rates or cut rates. The 10-Year Breakeven Inflation Rate is still well above the Federal Reserve's FAIT (Flexible Average Inflation Targeting) of 2% for that reason the Federal Reserve still has room to play with the Funds Rate.

Time series data for the statistic Inflation_Rate and country Kazakhstan. Indicator Definition:Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly. The Laspeyres formula is generally used.The statistic "Inflation Rate" stands at 8.84 percent as of 12/31/2024. Regarding the One-Year-Change of the series, the current value constitutes a decrease of -5.89 percentage points compared to the value the year prior.The 1 year change in percentage points is -5.89.The 3 year change in percentage points is 0.798.The 5 year change in percentage points is 3.51.The 10 year change in percentage points is 1.99.The Serie's long term average value is 75.65 percent. It's latest available value, on 12/31/2024, is 66.81 percentage points lower, compared to it's long term average value.The Serie's change in percentage points from it's minimum value, on 12/31/2012, to it's latest available value, on 12/31/2024, is +3.64.The Serie's change in percentage points from it's maximum value, on 12/31/1994, to it's latest available value, on 12/31/2024, is -1,868.53.

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 Lower Pottsgrove 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 Lower Pottsgrove township, the median income for all workers aged 15 years and older, regardless of work hours, was $55,539 for males and $37,649 for females.

These income figures highlight a substantial gender-based income gap in Lower Pottsgrove township. Women, regardless of work hours, earn 68 cents for each dollar earned by men. This significant gender pay gap, approximately 32%, underscores concerning gender-based income inequality in the township of Lower Pottsgrove township.

- Full-time workers, aged 15 years and older: In Lower Pottsgrove township, among full-time, year-round workers aged 15 years and older, males earned a median income of $76,221, while females earned $66,627, resulting in a 13% gender pay gap among full-time workers. This illustrates that women earn 87 cents for each dollar earned by men in full-time positions. While this gap shows a trend where women are inching closer to wage parity with men, it also exhibits a noticeable income difference for women working full-time in the township of Lower Pottsgrove township.

Interestingly, when analyzing income across all roles, including non-full-time employment, the gender pay gap percentage was higher for women compared to men. It appears that full-time employment presents a more favorable income scenario for women compared to other employment patterns in Lower Pottsgrove township.

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 Lower Pottsgrove township median household income by race. You can refer the same here

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 Lower Turkeyfoot 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 Lower Turkeyfoot township, the median income for all workers aged 15 years and older, regardless of work hours, was $37,500 for males and $26,250 for females.

These income figures indicate a substantial gender-based pay disparity, showcasing a gap of approximately 30% between the median incomes of males and females in Lower Turkeyfoot township. With women, regardless of work hours, earning 70 cents to each dollar earned by men, this income disparity reveals a concerning trend toward wage inequality that demands attention in thetownship of Lower Turkeyfoot township.

- Full-time workers, aged 15 years and older: In Lower Turkeyfoot township, among full-time, year-round workers aged 15 years and older, males earned a median income of $52,500, while females earned $35,313, leading to a 33% gender pay gap among full-time workers. This illustrates that women earn 67 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 Lower Turkeyfoot township 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 Lower Turkeyfoot township median household income by race. You can refer the same here