The main stock market index of United States, the US500, rose to 6818 points on December 2, 2025, gaining 0.08% from the previous session. Over the past month, the index has declined 0.50%, though it remains 12.70% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

This dataset encapsulates a detailed examination of market dynamics over a five-year period, focusing on the fluctuation of prices and trading volumes across a diversified portfolio. It covers various sectors including energy commodities like natural gas and crude oil, metals such as copper, platinum, silver, and gold, cryptocurrencies including Bitcoin and Ethereum, and key stock indices and companies like the S&P 500, Nasdaq 100, Apple, Tesla, Microsoft, Google, Nvidia, Berkshire Hathaway, Netflix, Amazon, and Meta Platforms. This dataset serves as a valuable resource for analyzing trends and patterns in global markets.

Date: The date of the recorded data, formatted as DD-MM-YYYY. Natural_Gas_Price: Price of natural gas in USD per million British thermal units (MMBtu). Natural_Gas_Vol.: Trading volume of natural gas Crude_oil_Price: Price of crude oil in USD per barrel. Crude_oil_Vol.: Trading volume of crude oil Copper_Price: Price of copper in USD per pound. Copper_Vol.: Trading volume of copper Bitcoin_Price: Price of Bitcoin in USD. Bitcoin_Vol.: Trading volume of Bitcoin Platinum_Price: Price of platinum in USD per troy ounce. Platinum_Vol.: Trading volume of platinum Ethereum_Price: Price of Ethereum in USD. Ethereum_Vol.: Trading volume of Ethereum S&P_500_Price: Price index of the S&P 500. Nasdaq_100_Price: Price index of the Nasdaq 100. Nasdaq_100_Vol.: Trading volume for the Nasdaq 100 index Apple_Price: Stock price of Apple Inc. in USD. Apple_Vol.: Trading volume of Apple Inc. stock Tesla_Price: Stock price of Tesla Inc. in USD. Tesla_Vol.: Trading volume of Tesla Inc. stock Microsoft_Price: Stock price of Microsoft Corporation in USD. Microsoft_Vol.: Trading volume of Microsoft Corporation stock Silver_Price: Price of silver in USD per troy ounce. Silver_Vol.: Trading volume of silver Google_Price: Stock price of Alphabet Inc. (Google) in USD. Google_Vol.: Trading volume of Alphabet Inc. stock Nvidia_Price: Stock price of Nvidia Corporation in USD. Nvidia_Vol.: Trading volume of Nvidia Corporation stock Berkshire_Price: Stock price of Berkshire Hathaway Inc. in USD. Berkshire_Vol.: Trading volume of Berkshire Hathaway Inc. stock Netflix_Price: Stock price of Netflix Inc. in USD. Netflix_Vol.: Trading volume of Netflix Inc. stock Amazon_Price: Stock price of Amazon.com Inc. in USD. Amazon_Vol.: Trading volume of Amazon.com Inc. stock Meta_Price: Stock price of Meta Platforms, Inc. (formerly Facebook) in USD. Meta_Vol.: Trading volume of Meta Platforms, Inc. stock Gold_Price: Price of gold in USD per troy ounce. Gold_Vol.: Trading volume of gold

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Stock Data of Top USA Companies: Apple, Tesla, Amazon

👨‍💻 Author: Azhar Saleem

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Dataset Description

This dataset provides daily stock data for some of the top companies in the USA stock market, including major players like Apple, Microsoft, Amazon, Tesla, and others. The data is collected from Yahoo Finance, covering each company’s historical data from its starting date until today. This comprehensive dataset enables in-depth analysis of key financial indicators and stock trends for each company, making it valuable for multiple applications.

Column Descriptions

The dataset contains the following columns, consistent across all companies:

• Date: The date of the stock data entry.
• Open: The stock's opening price for the day.
• High: The highest price reached during the trading day.
• Low: The lowest price during the trading day.
• Close: The stock’s closing price for the day.
• Volume: The total number of shares traded on that day.
• Dividends: Any dividends paid out on that day.
• Stock Splits: Records stock split events, if any, on that day.

Potential Use Cases

1. Machine Learning & Deep Learning:

   • Stock Price Prediction: Use historical prices to train models for forecasting future stock prices.
   • Sentiment Analysis and Price Correlation: Combine with external sentiment data to predict price movements based on market sentiment.
   • Anomaly Detection: Detect unusual price patterns or volume spikes using classification algorithms.

2. Data Science:

   • Trend Analysis: Identify long-term trends for each company or compare trends between companies.
   • Volatility Analysis: Calculate volatility to assess risk and return patterns over time.
   • Correlation Analysis: Compare stock performance across companies to study market relationships.

3. Data Analysis:

   • Historical Performance: Review historical data to understand growth trends, market impact of stock splits, and dividends.
   • Seasonal Patterns: Analyze data for seasonal trends or recurring patterns across years.
   • Investment Strategy Backtesting: Test various investment strategies based on historical data to assess potential profitability.

4. Financial Research:

   • Economic Impact Studies: Investigate how major events affected stock prices across top companies.
   • Sector-Specific Analysis: Identify performance differences across sectors, such as tech, healthcare, and retail.

This dataset is a powerful tool for analysts, researchers, and financial enthusiasts, offering versatility across multiple domains from stock analysis to algorithmic trading models.

The main stock market index of United States, the US500, rose to 6825 points on December 2, 2025, gaining 0.18% from the previous session. Over the past month, the index has declined 0.39%, though it remains 12.82% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on December of 2025.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

The main stock market index of United States, the US500, rose to 6849 points on November 28, 2025, gaining 0.54% from the previous session. Over the past month, the index has declined 0.60%, though it remains 13.54% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on November of 2025.

This table contains 14 series, with data starting from 1953 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Stock market statistics (14 items: Toronto Stock Exchange; value of shares traded; United States common stocks; Dow-Jones industrials; high; United States common stocks; Dow-Jones industrials; low; Toronto Stock Exchange; volume of shares traded ...).

Total-Current-Assets Time Series for Robinhood Markets Inc. Robinhood Markets, Inc. operates financial services platform in the United States. Its platform allows users to invest in stocks, exchange-traded funds (ETFs), American depository receipts, options, gold, and cryptocurrencies. The company offers fractional trading, recurring investments, fully-paid securities lending, access to investing on margin, cash sweep, instant withdrawals, retirement program, around-the-clock trading, joint investing accounts, event contracts, and future contract services. It also provides various learning and education solutions comprise Snacks, an accessible digest of business news stories for a new generation of investors.; Learn, which is an online collection of guides, feature tutorials, and financial dictionary; Newsfeeds that offer access to free, premium news from sites from various sites, such as Barron's, Reuters, and Dow Jones. In addition, the company offers In-App Education, a resource that covers investing fundamentals, including why people invest, a stock market overview, and tips on how to define investing goals, as well as allows customers to understand the basics of investing before their first trade; and Crypto Learn and Earn, an educational module available to various crypto customers through Robinhood Learn to teach customers the basics related to cryptocurrency. Further, it provides Robinhood credit cards, cash card and spending accounts, and wallets. The company also owns and operates a digital currency marketplace that allows companies and individuals from all around the world to buy and sell bitcoin, litecoin, ethereum, ripple, and bitcoin cash. Robinhood Markets, Inc. was incorporated in 2013 and is headquartered in Menlo Park, California.

United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

This dataset provides financial information for a selection of companies listed on the S&P 500 index in the United States. It includes key metrics such as last recorded stock prices, highest and lowest stock prices, absolute and percentage changes, and trading volumes. The data is collected at a specific point in time and offers insights into the stock market performance of S&P 500 companies.

The main stock market index of United States, the US500, rose to 6842 points on October 31, 2025, gaining 0.29% from the previous session. Over the past month, the index has climbed 1.95% and is up 19.43% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on October of 2025.

Looking to analyze the real estate market across the USA? Our Redfin real estate dataset provides a detailed sample of property listings, including prices, addresses, property features, and images. This dataset is perfect for analysts, developers, and real estate enthusiasts looking to gain insights into housing trends and market dynamics.

The dataset includes fields such as price, currency, address, property details, number of beds and baths, square footage, listing status, images, and more, giving you a robust foundation for analysis.

You can explore the full dataset and download the sample from Redfin real estate dataset. This makes it easy to integrate into your analytics pipelines, machine learning models, or market research projects.

Whether you're building a property analytics dashboard, testing real estate algorithms, or simply exploring housing trends, this dataset provides rich, up-to-date information directly from Redfin listings across the USA.

Start analyzing the USA housing market today with our Redfin dataset sample and make data-driven decisions with confidence.

Discover the "Job.com USA Jobs Dataset," a detailed resource that provides an in-depth look at the job market in the United States.

This dataset is sourced from Job.com, a leading employment platform in the USA, and includes comprehensive information on job listings across various industries and regions.

Key Features:

• Extensive Job Listings: Features a wide range of job postings from different sectors and industries, offering a comprehensive overview of employment opportunities across the United States.
• Detailed Information: Each listing includes important details such as job titles, company names, job descriptions, locations, employment types (full-time, part-time, remote, contract), required qualifications, and salary data.
• Insights into Market Trends: Analyze current trends in the US job market, including in-demand skills, leading employers, popular job roles, and geographic distribution of job opportunities.
• Ideal for Research and Analysis: This dataset is perfect for researchers, HR professionals, and data analysts interested in studying labor market trends, developing recruitment strategies, or understanding the employment dynamics in the USA.

The Job.com USA Jobs Dataset offers valuable insights into the American job market, making it a crucial resource for job seekers, employers, and researchers alike. Use this dataset to stay ahead of market trends, explore employment opportunities, and gain a deeper understanding of job market dynamics in the United States.

Techsalerator’s News Event Data in Latin America offers a detailed and extensive dataset designed to provide businesses, analysts, journalists, and researchers with an in-depth view of significant news events across the Latin American region. This dataset captures and categorizes key events reported from a wide array of news sources, including press releases, industry news sites, blogs, and PR platforms, offering valuable insights into regional developments, economic changes, political shifts, and cultural events.

Key Features of the Dataset: Comprehensive Coverage:

The dataset aggregates news events from numerous sources such as company press releases, industry news outlets, blogs, PR sites, and traditional news media. This broad coverage ensures a wide range of information from multiple reporting channels. Categorization of Events:

News events are categorized into various types including business and economic updates, political developments, technological advancements, legal and regulatory changes, and cultural events. This categorization helps users quickly locate and analyze information relevant to their interests or sectors. Real-Time Updates:

The dataset is updated regularly to include the most recent events, ensuring users have access to the latest news and can stay informed about current developments. Geographic Segmentation:

Events are tagged with their respective countries and regions within Latin America. This geographic segmentation allows users to filter and analyze news events based on specific locations, facilitating targeted research and analysis. Event Details:

Each event entry includes comprehensive details such as the date of occurrence, source of the news, a description of the event, and relevant keywords. This thorough detailing helps in understanding the context and significance of each event. Historical Data:

The dataset includes historical news event data, enabling users to track trends and perform comparative analysis over time. This feature supports longitudinal studies and provides insights into how news events evolve. Advanced Search and Filter Options:

Users can search and filter news events based on criteria such as date range, event type, location, and keywords. This functionality allows for precise and efficient retrieval of relevant information. Latin American Countries Covered: South America: Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Central America: Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Caribbean: Cuba Dominican Republic Haiti (Note: Primarily French-speaking but included due to geographic and cultural ties) Jamaica Trinidad and Tobago Benefits of the Dataset: Strategic Insights: Businesses and analysts can use the dataset to gain insights into significant regional developments, economic conditions, and political changes, aiding in strategic decision-making and market analysis. Market and Industry Trends: The dataset provides valuable information on industry-specific trends and events, helping users understand market dynamics and emerging opportunities. Media and PR Monitoring: Journalists and PR professionals can track relevant news across Latin America, enabling them to monitor media coverage, identify emerging stories, and manage public relations efforts effectively. Academic and Research Use: Researchers can utilize the dataset for longitudinal studies, trend analysis, and academic research on various topics related to Latin American news and events. Techsalerator’s News Event Data in Latin America is a crucial resource for accessing and analyzing significant news events across the region. By providing detailed, categorized, and up-to-date information, it supports effective decision-making, research, and media monitoring across diverse sectors.

United States graph database market size reached USD 537.9 Million in 2024. Looking forward, IMARC Group expects the market to reach USD 2,754.7 Million by 2033, exhibiting a growth rate (CAGR) of 19.7% during 2025-2033​. The widespread adoption of this innovative approach, as it offers numerous advantages over traditional database solutions in terms of computing power, storage, indexing, querying, etc., is primarily driving the market growth across the country.

IMARC Group provides an analysis of the key trends in each segment of the market, along with forecasts at the country level for ​2025-2033​. Our report has categorized the market based on component, type of database, analysis type, deployment model, application, and industry vertical.

Monthly and long-term United States Demand data: historical series and analyst forecasts curated by FocusEconomics.

Huge US Stocks prices + 1292 columns extra data from Indicators. This Dataset provides historical Open, High, Low, Close, and Volume (OHLCV) prices of stocks traded in the United States financial markets AND calculated 1292 columns of indicators. You can use all this hyge data for stock price predictions.

Columns with Momentum Indicator values ADX - Average Directional Movement Index ADXR - Average Directional Movement Index Rating APO - Absolute Price Oscillator AROON - Aroon AROONOSC - Aroon Oscillator BOP - Balance Of Power CCI - Commodity Channel Index CMO - Chande Momentum Oscillator DX - Directional Movement Index MACD - Moving Average Convergence/Divergence MACDEXT - MACD with controllable MA type MACDFIX - Moving Average Convergence/Divergence Fix 12/26 MFI - Money Flow Index MINUS_DI - Minus Directional Indicator MINUS_DM - Minus Directional Movement MOM - Momentum PLUS_DI - Plus Directional Indicator PLUS_DM - Plus Directional Movement PPO - Percentage Price Oscillator ROC - Rate of change : ((price/prevPrice)-1)*100 ROCP - Rate of change Percentage: (price-prevPrice)/prevPrice ROCR - Rate of change ratio: (price/prevPrice) ROCR100 - Rate of change ratio 100 scale: (price/prevPrice)*100 RSI - Relative Strength Index STOCH - Stochastic STOCHF - Stochastic Fast STOCHRSI - Stochastic Relative Strength Index TRIX - 1-day Rate-Of-Change (ROC) of a Triple Smooth EMA ULTOSC - Ultimate Oscillator WILLR - Williams' %R

Columns with Volatility Indicator values ATR - Average True Range NATR - Normalized Average True Range TRANGE - True Range

Columns with Volume Indicator values AD - Chaikin A/D Line ADOSC - Chaikin A/D Oscillator OBV - On Balance Volume

Columns with Overlap Studies values BBANDS - Bollinger Bands DEMA - Double Exponential Moving Average EMA - Exponential Moving Average HT_TRENDLINE - Hilbert Transform - Instantaneous Trendline KAMA - Kaufman Adaptive Moving Average MA - Moving average MAMA - MESA Adaptive Moving Average MAVP - Moving average with variable period MIDPOINT - MidPoint over period MIDPRICE - Midpoint Price over period SAR - Parabolic SAR SAREXT - Parabolic SAR - Extended SMA - Simple Moving Average T3 - Triple Exponential Moving Average (T3) TEMA - Triple Exponential Moving Average TRIMA - Triangular Moving Average WMA - Weighted Moving Average

Columns with Cycle Indicator values HT_DCPERIOD - Hilbert Transform - Dominant Cycle Period HT_DCPHASE - Hilbert Transform - Dominant Cycle Phase HT_PHASOR - Hilbert Transform - Phasor Components HT_SINE - Hilbert Transform - SineWave HT_TRENDMODE - Hilbert Transform - Trend vs Cycle Mode

If you want to download actual data - on today for example, then you can use python code from my github. tickers = ['CE.US', 'WELL.US', 'GRMN.US', 'IEX.US', 'CAG.US', 'BEN.US', 'ATO.US', 'WY.US', 'TSCO.US', 'COR.US', 'MOS.US', 'SWKS.US', 'ORCL.US', 'URI.US', 'INCY.US', 'MPC.US', 'HD.US', 'PPG.US', 'NUE.US', 'DDOG.US', 'HSIC.US', 'CAT.US', 'HSY.US', 'MKTX.US', 'CCEP.US', 'GWW.US', 'LEN.US', 'IFF.US', 'GL.US', 'MDB.US', 'SNPS.US', 'KR.US', 'DVN.US', 'SYY.US', 'USB.US', 'DRI.US', 'PARA.US', 'FMC.US', 'UBER.US', 'WRK.US', 'DLR.US', 'SO.US', 'AMGN.US', 'MA.US', 'STT.US', 'BWA.US', 'KVUE.US', 'GFS.US', 'BBY.US', 'BK.US', 'MRVL.US', 'VFC.US', 'EIX.US', 'ADSK.US', 'ZBH.US', 'MU.US', 'HUBB.US', 'PEAK.US', 'CVX.US', 'CPB.US', 'GILD.US', 'BXP.US', 'DD.US', 'MCD.US', 'KDP.US', 'GE.US', 'PKG.US', 'HST.US', 'WTW.US', 'XOM.US', 'ED.US', 'SPG.US', 'PFG.US', 'LVS.US', 'FAST.US', 'ROST.US', 'TTD.US', 'CNC.US', 'PGR.US', 'CMI.US', 'TEAM.US', 'MELI.US', 'BKR.US', 'EBAY.US', 'CPRT.US', 'MSFT.US', 'HOLX.US', 'ABBV.US', 'AMZN.US', 'FE.US', 'WYNN.US', 'KMI.US', 'APA.US', 'CRWD.US', 'DPZ.US', 'EQT.US', 'NOC.US', 'TAP.US', 'ETR.US', 'T.US', 'OMC.US', 'MTCH.US', 'TRMB.US', 'EXPE.US', 'DTE.US', 'PNR.US', 'LH.US', 'ALL.US', 'CTRA.US', 'VMC.US', 'XRAY.US', 'NWS.US', 'GOOGL.US', 'WEC.US', 'BIIB.US', 'LLY.US', 'BMY.US', 'STE.US', 'NI.US', 'MKC.US', 'AMT.US', 'CFG.US', 'LW.US', 'HIG.US', 'ETSY.US', 'AON.US', 'ULTA.US', 'DVA.US', 'LKQ.US', 'MPWR.US', 'TEL.US', 'FICO.US', 'CVS.US', 'CMA.US', 'NVDA.US', 'TDG.US', 'AWK.US', 'PSA.US', 'FOXA.US', 'ON.US', 'ODFL.US', 'NVR.US', 'ROP.US', 'TFX.US', 'HLT.US', 'EXPD.US', 'FOX.US', 'D.US', 'AMAT.US', 'AZO.US', 'DLTR.US', 'TT.US', 'SBUX.US', 'JNJ.US', 'HAS.US', 'DASH.US', 'NRG.US', 'JNPR.US', 'BIO.US', 'AMD.US', 'NFLX.US', 'VLTO.US', 'BRO.US', 'REGN.US', 'WRB.US', 'LRCX.US', 'SYK.US', 'MCO.US', 'CSGP.US', 'TROW.US', 'ETN.US', 'RTX.US', 'CRM.US', 'SIRI.US', 'UPS.US', 'HES.US', 'RSG.US', 'PEP.US', 'MET.US', 'HON.US', 'IQV.US', 'JPM.US', 'DG.US', 'CBRE.US', 'NDSN.US', 'DOW.US', 'SBAC.US', 'TSN.US', 'IT.US', 'WM.US', 'TPR.US', 'IBM.US', 'CHTR.US', 'HAL.US', 'ROL.US', 'FDS.US', 'SHW.US', 'EW.US', 'RJF.US', 'APH.US', 'AIZ.US', 'ZBRA.US', 'SRE.US', 'CTAS.US', 'PXD.US', 'MTD.US', 'NOW.US', 'MAS.US', 'FFIV.US', 'ELV.US', 'SYF.US', 'CSCO.US', 'APTV...

The Dog Food Data Extracted from Chewy (USA) dataset contains 4,500 detailed records of dog food products sourced from one of the leading pet supply platforms in the United States, Chewy. This dataset is ideal for businesses, researchers, and data analysts who want to explore and analyze the dog food market, including product offerings, pricing strategies, brand diversity, and customer preferences within the USA.

The dataset includes essential information such as product names, brands, prices, ingredient details, product descriptions, weight options, and availability. Organized in a CSV format for easy integration into analytics tools, this dataset provides valuable insights for those looking to study the pet food market, develop marketing strategies, or train machine learning models.

Key Features:

• Record Count: 4,500 dog food product records.
• Data Fields: Product names, brands, prices, descriptions, ingredients .. etc. Find more fields under data points section.
• Format: CSV, easy to import into databases and data analysis tools.
• Source: Extracted from Chewy’s official USA platform.
• Geography: Focused on the USA dog food market.

Use Cases:

• Market Research: Analyze trends and preferences in the USA dog food market, including popular brands, price ranges, and product availability.
• E-commerce Analysis: Understand how Chewy presents and prices dog food products, helping businesses compare their own product offerings.
• Competitor Analysis: Compare different brands and products to develop competitive strategies for dog food businesses.
• Machine Learning Models: Use the dataset for machine learning tasks such as product recommendation systems, demand forecasting, and price optimization.

Graph and download economic data for Median Sales Price of Houses Sold for the United States (MSPUS) from Q1 1963 to Q2 2025 about sales, median, housing, and USA.

Total-Current-Assets Time Series for Murphy USA Inc. Murphy USA Inc., together with subsidiaries, engages in marketing of retail motor fuel products and convenience merchandise. The company operates retail stores under the Murphy USA, Murphy Express, and QuickChek brands, as well as operates non-fuel convenience stores. It operates retail gasoline stores principally in the Southeast, Southwest, and Midwest areas of the United States. The company was founded in 1996 and is headquartered in El Dorado, Arkansas.