Financial Times Interactive Data LLC offers a vast repository of economic and financial data, providing valuable insights into global markets and trading. With a focus on delivering timely and accurate information, the company has established itself as a go-to source for financial institutions, investors, and researchers seeking to stay ahead of the curve.

our vast database is comprised of historic financial statements, economic indicators, and proprietary data from leading sources, including government agencies, regulatory bodies, and industry associations. By providing access to this trove of information, Financial Times Interactive Data LLC enables its clients to make informed decisions, identify trends, and uncover new opportunities in the rapidly evolving world of finance.

This dataset comprises approximately 130 news articles collected on the 20th of May, 2023, from the finance section of the Financial Times newspaper. Just found it useful for doing some sentiment analysis testing, thought I'd publish to Kaggle. Too small to be that useful, but great for validation

Also includes Premium content!!!

Disclaimer!

This goes against the FT's ToS. When I scraped it, they were much more lax and it was much easier. Unfortunately, this means I probably won't expand it as I was planning to upload a huge scrape of ~10,000 articles.

Update ~ 08/05/2024

Made into a CSV.

United Kingdom Index: FT 30 data was reported at 2,946.000 01Jul1935=100 in Nov 2018. This records a decrease from the previous number of 2,975.400 01Jul1935=100 for Oct 2018. United Kingdom Index: FT 30 data is updated monthly, averaging 1,966.600 01Jul1935=100 from Jan 1975 (Median) to Nov 2018, with 527 observations. The data reached an all-time high of 4,156.800 01Jul1935=100 in Dec 1999 and a record low of 236.900 01Jul1935=100 in Jan 1975. United Kingdom Index: FT 30 data remains active status in CEIC and is reported by Financial Times. The data is categorized under Global Database’s United Kingdom – Table UK.Z001: Financial Times Stock Exchange: Indices.

Dataset Card

This is the fine-tuning dataset used in the paper RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.

  Source

Project Page: https://rdt-robotics.github.io/rdt-robotics/ Paper: https://arxiv.org/pdf/2410.07864 Code: https://github.com/thu-ml/RoboticsDiffusionTransformer Model: https://huggingface.co/robotics-diffusion-transformer/rdt-1b

  Uses

Download all archive files and use the following command to extract: cat rdt_data.tar.gz.* |… See the full description on the dataset page: https://huggingface.co/datasets/robotics-diffusion-transformer/rdt-ft-data.

Index: FT Wilshire 5000 data was reported at 55,521.820 NA in Apr 2025. This records a decrease from the previous number of 55,933.380 NA for Mar 2025. Index: FT Wilshire 5000 data is updated monthly, averaging 8,357.320 NA from Dec 1970 (Median) to Apr 2025, with 653 observations. The data reached an all-time high of 60,880.810 NA in Nov 2024 and a record low of 550.040 NA in Sep 1974. Index: FT Wilshire 5000 data remains active status in CEIC and is reported by Wilshire Advisors, LLC. The data is categorized under Global Database’s United States – Table US.Z020: Wilshire Advisors, LLC: Index.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

Khaquan/ft-data dataset hosted on Hugging Face and contributed by the HF Datasets community

ESRI line feature class representing City of Somerville, Massachusetts 1-foot contour intervals.

5150 Global import shipment records of Ft Filter with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

143 Global export shipment records of Ft Filter with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

IMF World Economic Outlook (WEO) database. The "http://www.imf.org/external/ns/cs.aspx?id=29">IMF World Economic Outlook is a twice-yearly survey by IMF staff that presents IMF staff economists' analyses of global economic developments during the near and medium term. Associated with the report is the "http://www.imf.org/external/ns/cs.aspx?id=28">World Economic Outlook Database, a country-level dataset of major macro-economic variables (GDP, Unemployment, Debt etc). It is the data from that database which is provided here.

Data

The source database is made of annual values for each country on 45 indicators since 1980. In addition the database includes the IMF projects approximately 6 years into the future.

We extract this data and normalize into 2 files:

• Indicators - data/indicators.csv - the list of indicators
• Values - data/values.csv - set of values for each indicator, country, year tuple.

Sources

Note the XLS files actual turn out to be tsv files!

• Listing page for WEO Database
• 2014 - http://www.imf.org/external/pubs/ft/weo/2014/01/weodata/index.aspx
  • http://www.imf.org/external/pubs/ft/weo/2014/01/weodata/WEOApr2014all.xls
• 2011 - http://www.imf.org/external/pubs/ft/weo/2011/02/weodata/index.aspx
  • http://www.imf.org/external/pubs/ft/weo/2011/02/weodata/WEOSep2011all.xls

Preparation

Code to extract the data from the source WEO Database is in the scripts directory.

sumukshashidhar-archive/openreview-reviews-ft-data dataset hosted on Hugging Face and contributed by the HF Datasets community

Turkey Internet Banking: Financial Transactions (FT): Value data was reported at 955,666.208 TRY mn in Mar 2018. This records a decrease from the previous number of 957,452.151 TRY mn for Dec 2017. Turkey Internet Banking: Financial Transactions (FT): Value data is updated quarterly, averaging 310,124.586 TRY mn from Mar 2007 (Median) to Mar 2018, with 45 observations. The data reached an all-time high of 957,452.151 TRY mn in Dec 2017 and a record low of 101,558.822 TRY mn in Mar 2007. Turkey Internet Banking: Financial Transactions (FT): Value data remains active status in CEIC and is reported by The Banks Association of Turkey. The data is categorized under Global Database’s Turkey – Table TR.KA010: Internet Banking Statistics.

Table of values used to parameterize and evaluate the Ft Carson NetZero integrated Model with published reference sources for each value. This dataset is associated with the following publication: Procter, A., O. Kaplan , and R. Araujo. Net Zero Fort Carson: Integrating Energy, Water, and Waste Strategies to Lower the Environmental Impact of a Military Base. JOURNAL OF INDUSTRIAL ECOLOGY. Berkeley Electronic Press, Berkeley, CA, USA, online, (2015).

This data set contains the Coordinated Energy and Water Cycle Observation Project (CEOP) Enhanced Observing Period 3 (EOP-3) Global Energy and Water Cycle Experiment (GEWEX) Americas Prediction Project (GAPP) Ft. Peck 30 Minute Flux Data Set. This data set contains 30 minute data from the single Ft. Peck station from the Ft. Peck reference site for the CEOP EOP-3 time period. This dataset only contains the first half of the EOP-3 time period (i.e. 1 October 2002 through 31 March 2003). This data set contains both ASCII data and netCDF data. The ASCII data file covers the entire time period for all stations. The netCDF data file covers the entire time period with one netCDF file for each station.

United Kingdom Index: Month Average: FT 30 data was reported at 3,282.127 01Jul1935=100 in Jul 2018. This records a decrease from the previous number of 3,311.805 01Jul1935=100 for Jun 2018. United Kingdom Index: Month Average: FT 30 data is updated monthly, averaging 1,873.659 01Jul1935=100 from Jan 1970 (Median) to Jul 2018, with 583 observations. The data reached an all-time high of 4,083.182 01Jul1935=100 in Jul 1999 and a record low of 160.100 01Jul1935=100 in Dec 1974. United Kingdom Index: Month Average: FT 30 data remains active status in CEIC and is reported by Financial Times. The data is categorized under Global Database’s UK – Table UK.Z001: Financial Times Stock Exchange: Indices.

Turkey Internet Banking: Financial Transactions (FT): Volume data was reported at 70,111.037 Unit th in Mar 2018. This records a decrease from the previous number of 71,088.577 Unit th for Dec 2017. Turkey Internet Banking: Financial Transactions (FT): Volume data is updated quarterly, averaging 51,094.553 Unit th from Mar 2007 (Median) to Mar 2018, with 45 observations. The data reached an all-time high of 77,091.081 Unit th in Dec 2016 and a record low of 26,614.775 Unit th in Mar 2007. Turkey Internet Banking: Financial Transactions (FT): Volume data remains active status in CEIC and is reported by The Banks Association of Turkey. The data is categorized under Global Database’s Turkey – Table TR.KA010: Internet Banking Statistics.

DISCOVERAQ_Colorado_Ground_FortCollins_Data contains data collected at the Fort Collins ground site during the Colorado (Denver) deployment of NASA's DISCOVER-AQ field study. This data product contains data for only the Colorado deployment and data collection is complete.Understanding the factors that contribute to near surface pollution is difficult using only satellite-based observations. The incorporation of surface-level measurements from aircraft and ground-based platforms provides the crucial information necessary to validate and expand upon the use of satellites in understanding near surface pollution. Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) was a four-year campaign conducted in collaboration between NASA Langley Research Center, NASA Goddard Space Flight Center, NASA Ames Research Center, and multiple universities to improve the use of satellites to monitor air quality for public health and environmental benefit. Through targeted airborne and ground-based observations, DISCOVER-AQ enabled more effective use of current and future satellites to diagnose ground level conditions influencing air quality.DISCOVER-AQ employed two NASA aircraft, the P-3B and King Air, with the P-3B completing in-situ spiral profiling of the atmosphere (aerosol properties, meteorological variables, and trace gas species). The King Air conducted both passive and active remote sensing of the atmospheric column extending below the aircraft to the surface. Data from an existing network of surface air quality monitors, AERONET sun photometers, Pandora UV/vis spectrometers and model simulations were also collected. Further, DISCOVER-AQ employed many surface monitoring sites, with measurements being made on the ground, in conjunction with the aircraft. The B200 and P-3B conducted flights in Baltimore-Washington, D.C. in 2011, Houston, TX in 2013, San Joaquin Valley, CA in 2013, and Denver, CO in 2014. These regions were targeted due to being in violation of the National Ambient Air Quality Standards (NAAQS).The first objective of DISCOVER-AQ was to determine and investigate correlations between surface measurements and satellite column observations for the trace gases ozone (O3), nitrogen dioxide (NO2), and formaldehyde (CH2O) to understand how satellite column observations can diagnose surface conditions. DISCOVER-AQ also had the objective of using surface-level measurements to understand how satellites measure diurnal variability and to understand what factors control diurnal variability. Lastly, DISCOVER-AQ aimed to explore horizontal scales of variability, such as regions with steep gradients and urban plumes.

Turkey Internet Banking: FT: Value: Electronic Fund Transfers data was reported at 469,430.261 TRY mn in Jun 2018. This records a decrease from the previous number of 481,120.381 TRY mn for Mar 2018. Turkey Internet Banking: FT: Value: Electronic Fund Transfers data is updated quarterly, averaging 157,458.586 TRY mn from Mar 2007 (Median) to Jun 2018, with 46 observations. The data reached an all-time high of 481,120.381 TRY mn in Mar 2018 and a record low of 39,818.650 TRY mn in Mar 2007. Turkey Internet Banking: FT: Value: Electronic Fund Transfers data remains active status in CEIC and is reported by The Banks Association of Turkey. The data is categorized under Global Database’s Turkey – Table TR.KA010: Internet Banking Statistics.

Turkey Internet Banking: Financial Transactions (FT): Payments: Volume data was reported at 38,792.957 Unit th in Jun 2018. This records a decrease from the previous number of 44,034.061 Unit th for Mar 2018. Turkey Internet Banking: Financial Transactions (FT): Payments: Volume data is updated quarterly, averaging 35,506.495 Unit th from Mar 2007 (Median) to Jun 2018, with 46 observations. The data reached an all-time high of 51,622.393 Unit th in Mar 2015 and a record low of 11,709.385 Unit th in Mar 2007. Turkey Internet Banking: Financial Transactions (FT): Payments: Volume data remains active status in CEIC and is reported by The Banks Association of Turkey. The data is categorized under Global Database’s Turkey – Table TR.KA010: Internet Banking Statistics.