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A Decade of Global Exchange Rates and National Prosperity

Finance & Banking Analytics

Tags and Keywords

Currency

Exchange

Gdp

Population

Economics

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A Decade of Global Exchange Rates and National Prosperity Dataset on Opendatabay data marketplace

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About

Monitoring global economic health and currency stability requires a multidimensional view of national performance. Assessing exchange rates alongside vital indicators such as Gross Domestic Product (GDP) and population size provides a detailed perspective on how different economies interact with the United States Dollar. By combining high-frequency exchange rate data with decadal socioeconomic metrics, this resource enables a thorough exploration of global market trends and national prosperity from 2010 through the early 2020s.

Columns

  • Country Name: The full name of the nation for which the economic data is recorded.
  • Currency Code: The standard three-letter ISO code representing the national currency.
  • Currency Name: The descriptive title of the currency, providing the full name and relevant details.
  • Date: The specific calendar day, month, and year for the recorded exchange rate or economic indicator.
  • Exchange Rate: The value of the national currency relative to one US Dollar.
  • GDP(nominal) Per Capita: The gross domestic product of a country divided by its midyear population, measured in nominal terms until 2020.
  • GDP: The total market value of all final goods and services produced within a country, recorded until 2020.
  • Population: The total number of inhabitants residing in the country, recorded until 2020.

Distribution

The data is provided in a single CSV file titled National Currencies Per US Dollar.csv, with a file size of 202.11 kB. It contains 2,795 records structured across 8 columns. The dataset maintains a high standard of data integrity, with 100% validity for core identification fields like country names and currency codes. It has been awarded a usability score of 10.00 and is considered a static resource with no further updates expected.

Usage

This resource is suitable for performing longitudinal studies on the relationship between a nation's currency strength and its socioeconomic outputs. Researchers can use the data to model how population growth or GDP fluctuations correlate with exchange rate volatility. It also serves as a robust foundation for building economic dashboards that track the performance of specific regions or currency unions, such as the Eurozone, against the US Dollar over more than a decade.

Coverage

The geographic scope includes 215 unique countries and 145 different currencies. Temporally, the socioeconomic indicators for GDP and population cover the period from 2010 to 2020. The exchange rate records provide more recent daily granularity, spanning from 1 December 2020 to 17 March 2022. Users should note that while identification fields are complete, some economic indicators contain missing values for specific years where data was unavailable from the original sources.

License

CC BY-NC-SA 4.0

Who Can Use It

Financial analysts can leverage these figures to assess the economic stability of emerging markets and international trade environments. Academic researchers in the fields of macroeconomics and international relations may find the combined dataset useful for investigating global development patterns. Additionally, data science students can utilise this structured history to practice data cleaning, statistical modelling, and time-series analysis on real-world economic indicators.

Dataset Name Suggestions

  • Global Currency Exchange and Socioeconomic Indicators (2010–2022)
  • National Currencies Per US Dollar: GDP and Population History
  • World Bank and Google Finance: Global Economic Performance Metrics
  • A Decade of Global Exchange Rates and National Prosperity
  • Longitudinal Study of Currency Values and GDP (2010-2022)

Attributes

Listing Stats

VIEWS

0

DOWNLOADS

0

LISTED

21/12/2025

REGION

GLOBAL

Universal Data Quality Score Logo UDQSQUALITY

5 / 5

VERSION

1.0

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Free

Download Dataset in CSV Format