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

Bank Rankings by Total Assets

Tracking the Financial Performance of the Top Banks

By Arthur Keen [source]

About this dataset

This dataset contains the top 100 global banks ranked by total assets on December 31, 2017. With a detailed list of key information for each bank's rank, country, balance sheet and US Total Assets (in billions), this data will be invaluable for those looking to research and study the current status of some of the world's leading financial organizations. From billion-dollar mega-banks such as JP Morgan Chase to small, local savings & loans institutions like BancorpSouth; this comprehensive overview allows researchers and analysts to gain a better understanding of who holds power in the world economy today

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How to use the dataset

This dataset contains the rank and total asset information of the top 100 global banks as of December 31, 2017. It is a useful resource for researchers who wish to study how key financial institutions' asset information relate to each other across countries.

Using this dataset is relatively straightforward – it consists of three columns - rank (the order in which each bank appears in the list), country (the country in which the bank is located) and total assets US billions (the total value expressed in US dollars). Additionally, there is a fourth column containing the balance sheet information for each bank as well.

In order to make full use of this dataset, one should analyse it by creating comparison grids based on different factors such as region, size or ownership structures. This can provide an interesting insight into how financial markets are structured within different economies and allow researchers to better understand some banking sector dynamics that are particularly relevant for certain countries or regions. Additionally, one can compare any two banks side-by-side using their respective balance sheets or distribution plot graphs based on size or concentration metrics by leverage or other financial ratios as well.

Overall, this dataset provides useful resources that can be put into practice through data visualization making an interesting reference point for trends analysis and forecasting purposes focusing on certain banking activities worldwide

Research Ideas

• Analyzing the differences in total assets across countries. By comparing and contrasting data, patterns could be found that give insight into the factors driving differences in banks’ assets between different markets.

• Using predictive models to identify which banks are more likely to perform better based on their balance sheet data, such as by predicting future profits or cashflows of said banks.

• Leveraging the information on holdings and investments of “top-ranked” banks as a guide for personal investments decisions or informing investment strategies of large financial institutions or hedge funds

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: top50banks2017-03-31.csv | Column name | Description | |:----------------------|:------------------------------------------------------------------------| | rank | The rank of the bank globally based on total assets. (Integer) | | country | The country where the bank is located. (String) | | total_assets_us_b | The total assets of a bank expressed in billions of US dollars. (Float) | | balance_sheet | A snapshot of banking activities for a specific date. (Date) |

File: top100banks2017-12-31.csv | Column name | Description | |:----------------------|:--------------------------------------------...

The Gross Domestic Product (GDP) in European Union was worth 18590.72 billion US dollars in 2023, according to official data from the World Bank. The GDP value of European Union represents 17.63 percent of the world economy. This dataset provides the latest reported value for - European Union GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

This dataset provides key economic indicators for five of the world's largest economies, based on their nominal Gross Domestic Product (GDP) in 2022. It includes the GDP values, population, GDP growth rates, per capita GDP, and each country's share of the global economy.

Columns: Country: Name of the country. GDP (nominal, 2022): The total nominal GDP in 2022, represented in USD. GDP (abbrev.): The abbreviated GDP in trillions of USD. GDP growth: The percentage growth in GDP compared to the previous year. Population: Total population of each country in 2022. GDP per capita: The GDP per capita, representing average economic output per person in USD. Share of world GDP: The percentage of global GDP contributed by each country. Key Highlights: The dataset includes some of the largest global economies, such as the United States, China, Japan, Germany, and India. The data can be used to analyze the economic standing of countries in terms of overall GDP and per capita wealth. It offers insights into the relative growth rates and population sizes of these leading economies. This dataset is ideal for exploring economic trends, performing country-wise comparisons, or studying the relationship between population size and GDP growth.

The Gross Domestic Product (GDP) in the United States was worth 27720.71 billion US dollars in 2023, according to official data from the World Bank. The GDP value of the United States represents 26.29 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

About this Dataset

This dataset contains 25 columns which are: 1. Country: Corresponding country. 2. Poverty headcount ratio at $2.15 a day (2017 PPP) (% of population): Poverty in country. 3. Life expectancy at birth, total (years): Expected life from birth. 4. Population, total: Population of Country. 5. Population growth (annual %): Population growth each year. 6. Net migration: is the difference between the number of immigrants and the number of emigrants divided by the population. 7. Human Capital Index (HCI) (scale 0-1): is an annual measurement prepared by the World Bank. HCI measures which countries are best in mobilizing their human capital, the economic and professional potential of their citizens. The index measures how much capital each country loses through lack of education and health. 8. GDP (current US$)current US$constant US$current LCUconstant LCU: Gross domestic product is a monetary measure of the market value of all the final goods and services produced in a specific time period by a country or countries. 9. GDP per capita (current US$)current US$constant US$current LCUconstant LCU: the sum of gross value added by all resident producers in the economy plus any product taxes (less subsidies) not included in the valuation of output, divided by mid-year population. 10. GDP growth (annual %): The annual average rate of change of the gross domestic product (GDP) at market prices based on constant local currency, for a given national economy, during a specified period of time. 11. Unemployment, total (% of total labor force) (modeled ILO estimate) 12. Inflation, consumer prices (annual %) 13. Personal remittances, received (% of GDP) 14. CO2 emissions (metric tons per capita) 15. Forest area (% of land area) 16. Access to electricity (% of population) 17. Annual freshwater withdrawals, total (% of internal resources) 18. Electricity production from renewable sources, excluding hydroelectric (% of total) 19. People using safely managed sanitation services (% of population) 20. Intentional homicides (per 100,000 people) 21. Central government debt, total (% of GDP) 22. Statistical performance indicators (SPI): Overall score (scale 0-100) 23. Individuals using the Internet (% of population) 24. Proportion of seats held by women in national parliaments (%) 25. Foreign direct investment, net inflows (% of GDP): is when an investor becomes a significant or lasting investor in a business or corporation in a foreign country, which can be a boost to the global economy.

Category

Economic

Keywords

Row Count

217

Price

$5.50

This dataset contains the Global Green Economy Index for the period 2014-2018. Data from Dual Citizen LLC. Follow datasource.kapsarc.org for timely data to advance energy economics research.1. The results are expressed as percentiles representing an aggregate result from the four main dimensions of the GGEI: leadership & climate change; efficiency sectors; markets & investment; and environment. 2. The percentile results below should not be simply compared to those from prior GGEI editions as the 2018 GGEI covers 50 more countries than the 2016 edition. 3. The "time series available" column represents the period for which we have GGEI data for a given country. 4. Data collection and analysis for the 2018 GGEI was conducted by Agnes Magnusson, Philip McNally and Victor Milla and led by Jeremy Tamanini.5. The Global Green Economy Index™ (GGEI) is a trademark of Dual Citizen LLC.

The Gross Domestic Product (GDP) in Japan was worth 4204.49 billion US dollars in 2023, according to official data from the World Bank. The GDP value of Japan represents 3.99 percent of the world economy. This dataset provides - Japan GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset is about book subjects. It has 2 rows and is filtered where the books is The guru guide to the knowledge economy : the best ideas for operating profitably in a hyper-competitive world. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

The average for 2023 based on 154 countries was 95 percent. The highest value was in Luxembourg: 394.22 percent and the lowest value was in Sudan: 2.47 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

The average for 2023 based on 193 countries was -0.07 points. The highest value was in Liechtenstein: 1.61 points and the lowest value was in Syria: -2.75 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the countries in this dataset have a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

VARIABLE DESCRIPTIONS:

unid: ISO numeric country code (used by the United Nations)

wbid: ISO alpha country code (used by the World Bank)

SES: Country socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174)

country: Short country name

year: Survey year

gdppc: GDP per capita: Single time-series (imputed)

yrseduc: Completed years of education in the adult (15+) population

region5: Five category regional coding schema

regionUN: United Nations regional coding schema

DATA SOURCES:

The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita:

1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls.

2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm

3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/

4. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.

5. United Nations Population Division. 2009.

A range of indicators for a selection of cities from the New York City Global City database.

Dataset includes the following:

Geography

City Area (km2)

Metro Area (km2)

People

City Population (millions)

Metro Population (millions)

Foreign Born

Annual Population Growth

Economy

GDP Per Capita (thousands $, PPP rates, per resident)

Primary Industry

Secondary Industry

Share of Global 500 Companies (%)

Unemployment Rate

Poverty Rate

Transportation

Public Transportation

Mass Transit Commuters

Major Airports

Major Ports

Education

Students Enrolled in Higher Education

Percent of Population with Higher Education (%)

Higher Education Institutions

Tourism

Total Tourists Annually (millions)

Foreign Tourists Annually (millions)

Domestic Tourists Annually (millions)

Annual Tourism Revenue ($US billions)

Hotel Rooms (thousands)

Health

Infant Mortality (Deaths per 1,000 Births)

Life Expectancy in Years (Male)

Life Expectancy in Years (Female)

Physicians per 100,000 People

Number of Hospitals

Anti-Smoking Legislation

Culture

Number of Museums

Number of Cultural and Arts Organizations

Environment

Green Spaces (km2)

Air Quality

Laws or Regulations to Improve Energy Efficiency

Retrofitted City Vehicle Fleet

Bike Share Program

Description:

This comprehensive dataset provides a historical overview of India's key statistical indicators across multiple domains. The data has been sourced from https://www.macrotrends.net, which aggregates information from reputable sources like the United Nations (UN), World Bank, and other authoritative organizations.

Contents:

1. Population: Demographic data including population size, growth rates, and age distribution.
2. Economy: Economic indicators such as GDP, GDP per capita, inflation rates, and employment figures.
3. Trade: Information on imports, exports, trade balances, and international trade partnerships.
4. Health: Health-related statistics encompassing life expectancy, disease prevalence, and healthcare infrastructure.
5. Education: Educational metrics including literacy rates, school enrollment, and education expenditure.
6. Development: Human development indices, poverty rates, and access to basic amenities.
7. Labor Force: Labor market statistics comprising employment rates, workforce composition, and wage trends.
8. Environment: Environmental data covering factors like carbon emissions, pollution, and natural resource usage.
9. Crime: Crime rates and trends, including various types of criminal activities.
10. Immigration: Information on immigration patterns, citizenship, and foreign-born populations.
11. Other: Miscellaneous data on various aspects of India's socio-economic landscape.

Disclaimer and Terms of Use:

The historical data provided in this dataset is intended solely for informational purposes and is not meant for trading purposes or as financial advice. Neither Macrotrends LLC nor any of our information providers will be liable for any damages relating to your use of the data provided. Users are encouraged to verify the data's accuracy and refer to the original sources for any critical decisions or analyses.

Analysis of ‘Country Socioeconomic Status Scores: 1880-2010’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sdorius/globses on 14 February 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains estimates of the socioeconomic status (SES) position of each of 149 countries covering the period 1880-2010. Measures of SES, which are in decades, allow for a 130 year time-series analysis of the changing position of countries in the global status hierarchy. SES scores are the average of each country’s income and education ranking and are reported as percentile rankings ranging from 1-99. As such, they can be interpreted similarly to other percentile rankings, such has high school standardized test scores. If country A has an SES score of 55, for example, it indicates that 55 percent of the world’s people live in a country with a lower average income and education ranking than country A. ISO alpha and numeric country codes are included to allow users to merge these data with other variables, such as those found in the World Bank’s World Development Indicators Database and the United Nations Common Database.

See here for a working example of how the data might be used to better understand how the world came to look the way it does, at least in terms of status position of countries.

VARIABLE DESCRIPTIONS: UNID: ISO numeric country code (used by the United Nations) WBID: ISO alpha country code (used by the World Bank) SES: Socioeconomic status score (percentile) based on GDP per capita and educational attainment (n=174) country: Short country name year: Survey year SES: Socioeconomic status score (1-99) for each of 174 countries gdppc: GDP per capita: Single time-series (imputed) yrseduc: Completed years of education in the adult (15+) population popshare: Total population shares

DATA SOURCES: The dataset was compiled by Shawn Dorius (sdorius@iastate.edu) from a large number of data sources, listed below. GDP per Capita: 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. Maddison population data in 000s; GDP & GDP per capita data in (1990 Geary-Khamis dollars, PPPs of currencies and average prices of commodities). Maddison data collected from: http://www.ggdc.net/MADDISON/Historical_Statistics/horizontal-file_02-2010.xls. 2. World Development Indicators Database Years of Education 1. Morrisson and Murtin.2009. 'The Century of Education'. Journal of Human Capital(3)1:1-42. Data downloaded from http://www.fabricemurtin.com/ 2. Cohen, Daniel & Marcelo Cohen. 2007. 'Growth and human capital: Good data, good results' Journal of economic growth 12(1):51-76. Data downloaded from http://soto.iae-csic.org/Data.htm 3. Barro, Robert and Jong-Wha Lee, 2013, "A New Data Set of Educational Attainment in the World, 1950-2010." Journal of Development Economics, vol 104, pp.184-198. Data downloaded from http://www.barrolee.com/ Total Population 1. Maddison, Angus. 2004. 'The World Economy: Historical Statistics'. Organization for Economic Co-operation and Development: Paris. 13.
2. United Nations Population Division. 2009.

--- Original source retains full ownership of the source dataset ---

The Gross Domestic Product (GDP) in Nigeria was worth 362.81 billion US dollars in 2023, according to official data from the World Bank. The GDP value of Nigeria represents 0.34 percent of the world economy. This dataset provides the latest reported value for - Nigeria GDP - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In 2020, global gross domestic product declined by 6.7 percent as a result of the coronavirus (COVID-19) pandemic outbreak. In Latin America, overall GDP loss amounted to 8.5 percent.

Analysis of ‘China Largest Companies’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/china-largest-companiese on 28 January 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

From the Forbes Global 2000 list​ last updated on May 2013. Forbes publishes an annual list of the world's 2000 largest publicly listed corporations. ​The Forbes Global 2000 weigh​s​ sales, profits, assets and market value​ equally​ so companies can be ranked by size. Figures for all companies are in US dollars.

​Source: Economy Watch

This dataset was created by Finance and contains around 100 samples along with Profits ($billion), Market Value ($billion), technical information and other features such as: - Sales ($billion) - Assets ($billion) - and more.

How to use this dataset

• Analyze Global Rank in relation to Profits ($billion)
• Study the influence of Market Value ($billion) on Sales ($billion)
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Finance

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--- Original source retains full ownership of the source dataset ---

Iran is a country locating in Middle east. Iran is located in a strategic region at the crossroads of Europe, Asia, and Africa. This has made it a major center of trade and commerce for centuries. Iran is also a member of the United Nations, the Non-Aligned Movement, and the Organization of Islamic Cooperation.

Despite its rich history, large population, and abundant economic potential, Iran is a lower-middle-income country (according to the World Bank). It has large reserves of raw materials, including oil, gas, and minerals, but unfortunately, it does not fully utilize these resources.

This dataset is all the data about Iran in the world bank website. Here is a summary:

Economic data(2022/23) - GDP (current US$): 463billion - GDPpercapita(currentUS): $5,211 - Inflation, GDP deflator (annual %): 31.5% - Oil rents (% of GDP): 25.6% - Gini index: 38.8 (2019)

Social data - Population, total: 88.5 million (2022) - Population growth (annual %): 1.1% (2022) - Net migration: 28,080 (2021) - Life expectancy at birth, total (years): 77 (2021) - Human Capital Index (HCI) (scale 0-1): 0.63 (2020)

Environmental data - CO2 emissions (metric tons per capita): 7.2 (2021) - Renewable energy consumption (% of total final energy consumption): 3.6% (2021) - Forest area (% of land area): 7.8% (2020)

You can access the data in this link. There is also lots of plots and other fun tools which you should try.

[World Bank notes] The World Bank systematically assesses the appropriateness of official exchange rates as conversion factors. In Iran, multiple or dual exchange rate activity exists and must be accounted for appropriately in underlying statistics. An alternative estimate (“alternative conversion factor” - PA.NUS.ATLS) is thus calculated as a weighted average of the different exchange rates in use in Iran. Doing so better reflects economic reality and leads to more accurate cross-country comparisons and country classifications by income level. For Iran, this applies to 1972-2022. Alternative conversion factors are used in the Atlas methodology and elsewhere in World Development Indicators as single-year conversion factors.

It is noted that the reporting period for national accounts data is designated as either calendar year basis (CY) or fiscal year basis (FY). For Iran, it is fiscal year based (fiscal year-end: March 20).

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