Uranium decreased 8.70 USD/LBS or 11.92% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Uranium - values, historical data, forecasts and news - updated on March of 2025.

Graph and download economic data for Global price of Uranium (PURANUSDM) from Jan 1990 to Feb 2025 about uranium, World, and price.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Uranium Energy (YCA): The Sun's Yellow Cake, or Just a Fool's Gold Investment?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Nuclear Energy Index decreased 2.51 USD or 9.38% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Nuclear Energy Index.

3639 Global import shipment records of Uranium with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

The Alaska Geochemical Database Version 3.0 (AGDB3) contains new geochemical data compilations in which each geologic material sample has one best value determination for each analyzed species, greatly improving speed and efficiency of use. Like the Alaska Geochemical Database Version 2.0 before it, the AGDB3 was created and designed to compile and integrate geochemical data from Alaska to facilitate geologic mapping, petrologic studies, mineral resource assessments, definition of geochemical baseline values and statistics, element concentrations and associations, environmental impact assessments, and studies in public health associated with geology. This relational database, created from databases and published datasets of the U.S. Geological Survey (USGS), Atomic Energy Commission National Uranium Resource Evaluation (NURE), Alaska Division of Geological & Geophysical Surveys (DGGS), U.S. Bureau of Mines, and U.S. Bureau of Land Management serves as a data archive in support of Alaskan geologic and geochemical projects and contains data tables in several different formats describing historical and new quantitative and qualitative geochemical analyses. The analytical results were determined by 112 laboratory and field analytical methods on 396,343 rock, sediment, soil, mineral, heavy-mineral concentrate, and oxalic acid leachate samples. Most samples were collected by personnel of these agencies and analyzed in agency laboratories or, under contracts, in commercial analytical laboratories. These data represent analyses of samples collected as part of various agency programs and projects from 1938 through 2017. In addition, mineralogical data from 18,138 nonmagnetic heavy-mineral concentrate samples are included in this database. The AGDB3 includes historical geochemical data archived in the USGS National Geochemical Database (NGDB) and NURE National Uranium Resource Evaluation-Hydrogeochemical and Stream Sediment Reconnaissance databases, and in the DGGS Geochemistry database. Retrievals from these databases were used to generate most of the AGDB data set. These data were checked for accuracy regarding sample location, sample media type, and analytical methods used. In other words, the data of the AGDB3 supersedes data in the AGDB and the AGDB2, but the background about the data in these two earlier versions are needed by users of the current AGDB3 to understand what has been done to amend, clean up, correct and format this data. Corrections were entered, resulting in a significantly improved Alaska geochemical dataset, the AGDB3. Data that were not previously in these databases because the data predate the earliest agency geochemical databases, or were once excluded for programmatic reasons, are included here in the AGDB3 and will be added to the NGDB and Alaska Geochemistry. The AGDB3 data provided here are the most accurate and complete to date and should be useful for a wide variety of geochemical studies. The AGDB3 data provided in the online version of the database may be updated or changed periodically.

Four-figure standard atomic weights of the chemical elements are shown for 1961, 1975, 1983, 2007, 2009, 2011, 2013, 2015, and the current value for 2016. Values between 1975 and 2015 are only shown when there is a change in value with respect to the previous column.

This data release compiles the whole-rock geochemistry, X-ray diffraction, and electron microscopy analyses of samples collected from the uranium ore bodies of two mined-out deposits in the Grand Canyon region of northwestern Arizona - the Hack II and Pigeon deposits. The samples are grab samples of ore collected underground at each mine by the U.S. Geological Survey (USGS) during the mid-1980s, while each mine was active. The Hack II and Pigeon mines were remediated after their closure, so these data, analyses of samples in the archives of the USGS, are provided as surviving, although limited representations of these ore bodies. The Hack II and Pigeon deposits are similar to numerous other uranium deposits hosted by solution-collapse breccia pipes in the Grand Canyon region of northwest Arizona. The uranium-copper deposits occur within matrix-supported columns of breccia (a "breccia pipe") that formed by solution and collapse of sedimentary strata (Wenrich, 1985; Alpine, 2010). The regions north and south of the Grand Canyon host hundreds of solution-collapse breccia pipes (Van Gosen and others, 2016). Breccia refers to the broken rock that fills these features, and pipe refers to their vertical, pipe-like shape. The breccia pipes average about 300 ft (90 m) in diameter and can extend vertically for as much as 3,000 ft (900 m), from their base in the Mississippian Redwall Limestone to as stratigraphically high as the Triassic Chinle Formation. The breccia fragments are blocks and pieces of rock units that have fallen downward, now resting below their original stratigraphic level. In contrast to many other types of breccia pipes, there are no igneous rocks associated with the northwestern Arizona breccia pipes, nor have igneous processes contributed to their formation. Many of these breccia pipes contain concentrated deposits of uranium, copper, arsenic, barium, cobalt, lead, molybdenum, nickel, antimony, strontium, vanadium, and zinc minerals (Wenrich, 1985), which is reflected in this data set. The Hack II and Pigeon mines were two of thirteen breccia pipe deposits in the Grand Canyon region mined for uranium from the 1950s to present (2020) (Alpine, 2010; Van Gosen and others, 2016). While hundreds of breccia pipes in the region have been identified (Van Gosen and others, 2016), six decades of exploration across the region has found that most are not mineralized or substantially mineralized, and only a small percentage of the breccia pipes contain economic uranium deposits. The most recent mining operation in a breccia pipe deposit in the region is the Canyon mine, located about 6.1 miles (10 km) south-southeast of Tusayan, Arizona. In 2018, Energy Fuels completed a mine shaft and other mining facilities at the Canyon deposit, a copper- uranium-bearing breccia pipe (Van Gosen and others, 2020); however, this mining operation is currently (2020) inactive, awaiting higher market prices for uranium oxide. The Hack II deposit is one of four breccia pipes mined in Hack Canyon near its intersection with Robinson Canyon (Chenoweth, 1988; Otton and Van Gosen, 2010), approximately 30 miles (48 km) southwest of Fredonia and 9 miles (14.5 km) north-northwest of Kanab Creek. Hack Canyon incised and exposed part of the "Hacks" (or "Hack Canyon") breccia pipe, which was discovered and mined as a surface mine in the early 1900s for copper and silver. The original Hacks mine and adjacent Hack I deposit were later mined underground for uranium from 1950 to 1954 (Chenoweth, 1988). The Hack II deposit was discovered in the late 1970s along Hack Canyon about 1 mile (1.6 km) upstream of the Hacks and Hack I mines. The Hack II mine is located at latitude 36.58219 north, longitude -112.81059 west (datum of WGS84). Mining began at Hack II in 1981 and ended in May 1987. The USGS collected the ore samples reported in this data release in 1984 from underground exposures in the Hack II mine while it was in operation. Reclamation of the four mines in the area (Hacks, Hack I, Hack II, and Hack III) was planned and completed from March 1987 to April 1988, including infilling of the shafts and adits. Total production from the Hack II mine was reported as 7.00 million pounds (3.2 million kilograms) of uranium oxide from ore that had an average grade of 0.70 percent uranium oxide. This represents the largest uranium production from a breccia pipe deposit in the Grand Canyon region thus far (Otton and Van Gosen, 2010). The Pigeon mine was discovered along Kanab Creek in 1980. The site was prepared and developed from 1982 to 1984, and mining began in December 1984. The pipe was mined out in late 1989 and reclamation begun shortly thereafter. The former mine site is located at latitude 36.7239 north, longitude -112.5275 south (datum of WGS84). The Pigeon mine reportedly produced 5.7 million pounds (2.6 million kilograms) of ore that had an average grade of 0.65 percent uranium oxide. The five Pigeon deposit samples reported in this data release were collected by the USGS from underground exposures in the Pigeon mine in 1985, while the mine was in operation. Fourteen samples of Hack II ore and two samples of Pigeon ore were analyzed for major and trace elements by a laboratory contracted by the USGS. Concentrations for 59 elements were determined by Inductively Coupled Plasma-Optical Emission Spectrometry (ICP-OES). Additionally, carbonate carbon (inorganic carbon), total carbon, total sulfur, iron oxide, and mercury concentrations were determined using other element-specific analytical techniques. These 16 samples and an additional four Hack II ore samples and three Pigeon ore samples were analyzed by X-ray diffraction (XRD) to determine their mineralogy. Polished thin sections cut from six of the Hack II ore samples were examined using a scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS) to identify the ore minerals and observe their relationships at high magnification. The EDS vendor's auto identification algorithm was used for peak assignments; the user did not attempt to verify every peak identification. The spectra for each EDS measurement are provided in separate documents in Portable Data Format (pdf), one document for each of the six samples that were examined by SEM-EDS. The interpreted mineral phase(s), which is based solely on the judgement of the user, is given below each spectrum. References cited above: Alpine, A.E., ed., 2010, Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5025, 353 p., 1 plate, scale 1:375,000. Available at http://pubs.usgs.gov/sir/2010/5025/ Chenoweth, W.L., 1988, The production history and geology of the Hacks, Ridenour, Riverview and Chapel breccia pipes, northwestern Arizona: U.S. Geological Survey Open-File Report 88-648, 60 p. Available at https://pubs.usgs.gov/of/1988/0648/report.pdf Otton, J.K., and Van Gosen, B.S., 2010, Uranium resource availability in breccia pipes in northern Arizona, in Alpine, A.E., ed., Hydrological, geological, and biological site characterization of breccia pipe uranium deposits in northern Arizona: U.S. Geological Survey Scientific Investigations Report 2010-5025, p. 23-41. Available at http://pubs.usgs.gov/sir/2010/5025/ Van Gosen, B.S., Johnson, M.R., and Goldman, M.A., 2016, Three GIS datasets defining areas permissive for the occurrence of uranium-bearing, solution-collapse breccia pipes in northern Arizona and southeast Utah: U.S. Geological Survey data release, https://doi.org/10.5066/F76D5R3Z Van Gosen, B.S., Benzel, W.M., and Campbell, K.M., 2020, Geochemical and X-ray diffraction analyses of drill core samples from the Canyon uranium-copper deposit, a solution-collapse breccia pipe, Grand Canyon area, Coconino County, Arizona: U.S. Geological Survey data release, https://doi.org/10.5066/P9UUILQI Wenrich, K.J., 1985, Mineralization of breccia pipes in northern Arizona: Economic Geology, v. 80, no. 6, p. 1722-1735, https://doi.org/10.2113/gsecongeo.80.6.1722