The SNL Global Banking data delivers harmonized line items and key ratios for banks across the globe.

The Big Data Analytics in Banking Market is Segmented by Type of Solutions (Data Discovery and Visualization (DDV) and Advanced Analytics (AA)), and Geography (North America, Europe, Asia-Pacific, Latin America, Middle East and Africa). The Market Sizes and Forecasts are Provided in Terms of Value (USD Million) for all the Above Segments.

The files (R and CSV) contain the replication data for our analysis of a set of 2,355 death duty forms from the Netherlands in 1921, presented in our article “Exploring Modern Bank Penetration in the Netherlands in the 20th Century,” published in Economic History Review. A detailed description of this dataset is available in Ruben Peeters and Amaury de Vicq. “Inheritance Taxation Records in the Netherlands in 1921: The Memories Database” (forthcoming in 2023). The database itself is currently stored on the servers of University of Antwerp as part of the datafiles of the Social History of Finance Reserach Group. The paper also uses two other datasets, Tafel Vbis and the Dutch Banking Database (1880-1940). The Tafel Vbis dataset is described in a published paper by Ruben Peeters and Amaury de Vicq: de Vicq, A., & Peeters, R. (2020). “Introduction to the ‘Tafel v-bis’ Dataset: Death Duty Summary Information for The Netherlands, 1921,” Research Data Journal for the Humanities and Social Sciences, 5(1), 1-19. doi: https://doi.org/10.1163/24523666-bja10007. The Tafel Vbis datafiles are currently stored on the servers of University of Antwerp as part of the datafiles of the Social History of Finance Reserach Group, Odysseus Group. The Dutch Banking Database is described and published by DANS, and should be cited as follows: Vicq, A. de; Gelderblom, Prof. dr. O.; Jonker, Prof. dr. J. (2021): Dutch Banking Database, 1880-1940. DANS. https://doi.org/10.17026/dans-xre-kfdf

The Banking Bureau of the Department of Insurance Securities and Banking (DISB) regulates District of Columbia Chartered Banks, mortgage companies, and consumer finance companies. The Bureau strives to ensure a sound and thriving financial services community that provides the products, credit, and capital vital to the needs of District of Columbia residents and businesses. DISB charters and regulates District of Columbia banks and other DC depository financial institutions. DISB also regulates non-depository financial institutions such as mortgage lenders and brokers, money transmitters, consumer finance companies, and check cashers. The data is updated as needed.

DB: Land Bank of Taiwan: Total Credits data was reported at 2,010,979.000 NTD mn in Sep 2018. This records an increase from the previous number of 2,002,011.000 NTD mn for Aug 2018. DB: Land Bank of Taiwan: Total Credits data is updated monthly, averaging 1,600,953.000 NTD mn from Nov 1999 (Median) to Sep 2018, with 227 observations. The data reached an all-time high of 2,010,979.000 NTD mn in Sep 2018 and a record low of 1,007,315.000 NTD mn in Feb 2000. DB: Land Bank of Taiwan: Total Credits data remains active status in CEIC and is reported by Banking Bureau, Financial Supervisory Commission. The data is categorized under Global Database’s Taiwan – Table TW.KB032: Condensed Financial Structure: Domestic Banks.

A database of binding affinities for the protein-ligand complexes in the Protein Data Bank (PDB). The PDBbind database is a collection of the experimentally measured binding affinities exclusively for the protein-ligand complexes available in the Protein Data Bank (PDB). It thus provides a link between energetic and structural information of those complexes and may be of great value to various molecular recognition studies. This site was last updated in 2007. The updated version of the resource is maintained by the Shanghai Institute of Organic Chemistry (http://www.pdbbind.org.cn).

Global matrices of bilateral migrant stocks spanning the period 1960-2000, disaggregated by gender and based primarily on the foreign-born concept are presented. Over one thousand census and population register records are combined to construct decennial matrices corresponding to the last five completed census rounds.For the first time, a comprehensive picture of bilateral global migration over the last half of the twentieth century emerges. The data reveal that the global migrant stock increased from 92 to 165 million between 1960 and 2000. South-North migration is the fastest growing component of international migration in both absolute and relative terms. The United States remains the most important migrant destination in the world, home to one fifth of the world™s migrants and the top destination for migrants from no less than sixty sending countries. Migration to Western Europe remains largely from elsewhere in Europe. The oil-rich Persian Gulf countries emerge as important destinations for migrants from the Middle East, North Africa and South and South-East Asia. Finally, although the global migrant stock is still predominantly male, the proportion of women increased noticeably between 1960 and 2000.

This statistics bank shows how business has made use of ordinary and extraordinary support schemes throughout the corona crisis.

A number of measures were initiated to increase activity in Norwegian business, prevent unnecessary closures and to get as many people as possible into work during the corona crisis. Several actors in the industry-oriented instrument apparatus were given additional tasks and new extraordinary measures were created, such as the compensation scheme through the Tax Agency.

In order to be able to monitor the use of the measures, the Ministry of Trade and Fisheries has commissioned Innovation Norway to expand its reporting to include regularly updated data on how the measures affect business. Innovation Norway has, with assistance from Societal Economic Analysis, also obtained information on schemes other than its own in order to get a more complete picture of the use of measures.

The statistics bank contains statistics on allocations per week from the business-oriented policy apparatus. The statistics bank is updated every month and contains data from week 1 of 2020.

Russia Banking Cards Statistics: Bryansk Region: Corporate: Number of Transactions data was reported at 51.600 Unit th in Dec 2016. This records an increase from the previous number of 45.400 Unit th for Sep 2016. Russia Banking Cards Statistics: Bryansk Region: Corporate: Number of Transactions data is updated quarterly, averaging 17.200 Unit th from Mar 2001 (Median) to Dec 2016, with 64 observations. The data reached an all-time high of 51.600 Unit th in Dec 2016 and a record low of 0.000 Unit th in Jun 2001. Russia Banking Cards Statistics: Bryansk Region: Corporate: Number of Transactions data remains active status in CEIC and is reported by The Central Bank of the Russian Federation. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAI002: Banking Cards Statistics: Central Federal District.

Content

The Global Financial Inclusion Database provides 800 country-level indicators of financial inclusion summarized for all adults and disaggregated by key demographic characteristics-gender, age, education, income, and rural residence. Covering more than 140 economies, the indicators of financial inclusion measure how people save, borrow, make payments and manage risk.

The reference citation for the data is: Demirguc-Kunt, Asli, Leora Klapper, Dorothe Singer, and Peter Van Oudheusden. 2015. “The Global Findex Database 2014: Measuring Financial Inclusion around the World.” Policy Research Working Paper 7255, World Bank, Washington, DC.

Context

This is a dataset hosted by the World Bank. The organization has an open data platform found here and they update their information according the amount of data that is brought in. Explore the World Bank using Kaggle and all of the data sources available through the World Bank organization page!

• Update Frequency: This dataset is updated daily.

Acknowledgements

This dataset is maintained using the World Bank's APIs and Kaggle's API.

Cover photo by ZACHARY STAINES on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

Context

The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank

Content

This dataset combines key education statistics from a variety of sources to provide a look at global literacy, spending, and access.

For more information, see the World Bank website.

Fork this kernel to get started with this dataset.

Acknowledgements

https://bigquery.cloud.google.com/dataset/bigquery-public-data:world_bank_health_population

http://data.worldbank.org/data-catalog/ed-stats

https://cloud.google.com/bigquery/public-data/world-bank-education

Citation: The World Bank: Education Statistics

Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Banner Photo by @till_indeman from Unplash.

Inspiration

Of total government spending, what percentage is spent on education?

A toxicology database that focuses on the toxicology of potentially hazardous chemicals. It provides information on human exposure, industrial hygiene, emergency handling procedures, environmental fate, regulatory requirements, nanomaterials, and related areas. The information in HSDB has been assessed by a Scientific Review Panel.

Turkey Banking Sector: DF: LC: Non Residents: Banks: Domestic data was reported at 18,320,058.000 TRY th in Nov 2018. This records a decrease from the previous number of 21,184,835.000 TRY th for Oct 2018. Turkey Banking Sector: DF: LC: Non Residents: Banks: Domestic data is updated monthly, averaging 8,224,374.500 TRY th from Dec 2005 (Median) to Nov 2018, with 156 observations. The data reached an all-time high of 29,490,057.000 TRY th in Apr 2018 and a record low of 1,182,872.000 TRY th in Apr 2007. Turkey Banking Sector: DF: LC: Non Residents: Banks: Domestic data remains active status in CEIC and is reported by Central Bank of the Republic of Turkey. The data is categorized under Global Database’s Turkey – Table TR.KB046: Balance Sheet: Banking Sector: Selected Items.

Jordan Banking System: Domestic Assets: Claims: Financial Institutions data was reported at 604.700 JOD mn in Sep 2018. This records an increase from the previous number of 585.400 JOD mn for Aug 2018. Jordan Banking System: Domestic Assets: Claims: Financial Institutions data is updated monthly, averaging 187.900 JOD mn from Jan 2000 (Median) to Sep 2018, with 225 observations. The data reached an all-time high of 604.700 JOD mn in Sep 2018 and a record low of 68.400 JOD mn in Jul 2000. Jordan Banking System: Domestic Assets: Claims: Financial Institutions data remains active status in CEIC and is reported by Central Bank of Jordan. The data is categorized under Global Database’s Jordan – Table JO.KA007: Monetary Survey: Banking System.

Graph and download economic data for Overnight Bank Funding Volume (OBFRVOL) from 2016-03-01 to 2025-03-24 about ibf, overnight, banks, depository institutions, and USA.

Banking Cards Statistics: North Western Federal District (NW): Corporate: Transactions Amount: Others data was reported at 4,755.115 RUB mn in Sep 2023. This records an increase from the previous number of 4,233.435 RUB mn for Jun 2023. Banking Cards Statistics: North Western Federal District (NW): Corporate: Transactions Amount: Others data is updated quarterly, averaging 19.499 RUB mn from Mar 2008 (Median) to Sep 2023, with 63 observations. The data reached an all-time high of 4,755.115 RUB mn in Sep 2023 and a record low of 0.011 RUB mn in Jun 2008. Banking Cards Statistics: North Western Federal District (NW): Corporate: Transactions Amount: Others data remains active status in CEIC and is reported by Bank of Russia. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAI003: Banking Cards Statistics: North Western Federal District.

The World Bank’s Prospects Group has constructed a comprehensive international database of potential growth. The database covers up to 173 countries for 1981-2021, and includes nine measures of potential growth of which the following eight are published:

• Multivariate filter (MVF)
• Hodrick-Prescott filter (HP)
• Christiano-Fitzgerald filter (CF)
• Baxter-King filter (BK)
• Butterworth filter (BW)
• Unobserved Components Model (UCM)
• 5-year ahead expectations (based on IMF’s WEO database vintages)
• Production function approach together with its decomposition: capital, labor and total factor productivity (TFP)

Kilic Celik, Kose, Ohnsorge, and Ruch (2023) provide detailed information on the database, document the steady decline in global potential growth over the past decade, and show the impact of adverse shock on potential growth.

Graph and download economic data for Net Percentage of Domestic Banks Tightening Standards for Commercial and Industrial Loans to Large and Middle-Market Firms (DRTSCILM) from Q2 1990 to Q1 2025 about tightening standards, commercial, domestic, Net, percent, loans, industry, and USA.

Russia Banking Cards Statistics: Primorsky Territory: Corporate: Transactions Amount data was reported at 7,950.300 RUB mn in Dec 2016. This records a decrease from the previous number of 8,383.570 RUB mn for Sep 2016. Russia Banking Cards Statistics: Primorsky Territory: Corporate: Transactions Amount data is updated quarterly, averaging 3,087.875 RUB mn from Mar 2001 (Median) to Dec 2016, with 64 observations. The data reached an all-time high of 8,560.400 RUB mn in Dec 2007 and a record low of 4.350 RUB mn in Mar 2001. Russia Banking Cards Statistics: Primorsky Territory: Corporate: Transactions Amount data remains active status in CEIC and is reported by The Central Bank of the Russian Federation. The data is categorized under Russia Premium Database’s Monetary and Banking Statistics – Table RU.KAI009: Banking Cards Statistics: Far East Federal District.

Brazil Banking: Consolidated II: Assets: Securities & Financial Derivatives data was reported at 18,991,651.000 BRL th in Mar 2019. This records an increase from the previous number of 16,533,943.000 BRL th for Dec 2018. Brazil Banking: Consolidated II: Assets: Securities & Financial Derivatives data is updated quarterly, averaging 6,966,876.000 BRL th from Mar 2000 (Median) to Mar 2019, with 77 observations. The data reached an all-time high of 21,297,165.000 BRL th in Dec 2015 and a record low of 1,003,079.000 BRL th in Sep 2003. Brazil Banking: Consolidated II: Assets: Securities & Financial Derivatives data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Banking Sector – Table BR.KBB003: Financial Institutions: Assets and Liabilities: Banking: Consolidated II.