This resource provides tools to dynamically compare and manipulate tens of millions of statistical data series available in the Data-Planet repository. The interactive database allows users to create tables, maps, and figures from a variety data sources covering banking, criminal justice, education, energy, food and agriculture, government, health, housing and construction, industry and commerce, labor and employment, natural resources and environment, income, cost of living, stocks, transportation, and more. Data holdings for the United States are significant with some data available at state, county, or local geographies. International data, available at the country level, include population, food and agriculture, labor, trade, and more. Data are organized by subject and source.
Data Citation Index is a searchable collection of data sets and data studies from a select list of repositories in the Life Sciences, Social Sciences, Physical Sciences, and Arts & Humanities. Includes citations to publications reporting research that utlitizes the data.
Categorized into market sectors, Statista provides access to statistical data and comparisons for an eclectic, wide-ranging, and continually updated array of topics, using both publicly accessible and proprietary sources. About 20 percent of the total data in Statista comes from sources available free online, such as the World Bank and the U.S. Census. But the data also includes numerous other exclusive sources including industry, marketing, and trade groups. The chief types of data are related to marketing, demographics, and government information.
SAGE Research Methods Datasets is a collection of teaching datasets and instructional guides that give students a chance to learn data analysis by practicing themselves. This bank of topical, engaging practice datasets, indexed by method and data type, are optimized to use in classroom exercises or in exam papers, saving faculty members hours spent sourcing and cleaning data themselves.
This is an open-access data resource. US and global financial and statistical datasets covering a variety of asset classes (equities, foreign exchange rate, etc.) and derived market indicators (e.g., volatility). Suitable for machine learning and big data research. You may also refer to the market data integration guide for sample Python code snippets.