The Consumer Price Index (CPI) for food is a component of the all-items CPI. The CPI measures the average change over time in the prices paid by urban consumers for a representative market basket of consumer goods and services. While the all-items CPI measures the price changes for all consumer goods and services, including food, the CPI for food measures the changes in the retail prices of food items only.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.

This is a version of the gas prices dataset used in the following paper: Data Polygamy: The Many-Many Relationships among Urban Spatio-Temporal Data Sets, F. Chirigati, H. Doraiswamy, T. Damoulas, and J. Freire. In Proceedings of the 2016 ACM SIGMOD International Conference on Management of Data (SIGMOD), 2016 The dataset includes records of the average gasoline price in dollars per gallon for New York, from 2000 to 2014. The original data is available at the U.S. Energy Information Administration.

Gold fell to 3,333.04 USD/t.oz on July 2, 2025, down 0.16% from the previous day. Over the past month, Gold's price has fallen 0.61%, but it is still 41.30% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on July of 2025.

New housing price index (NHPI). Monthly data are available from January 1981. The table presents data for the most recent reference period and the last four periods. The base period for the index is (201612=100).

Annual descriptive price statistics for each calendar year 2005 – 2023 for 11 Local Government Districts in Northern Ireland. The statistics include: • Minimum sale price • Lower quartile sale price • Median sale price • Simple Mean sale price • Upper Quartile sale price • Maximum sale price • Number of verified sales Prices are available where at least 30 sales were recorded in the area within the calendar year which could be included in the regression model i.e. the following sales are excluded: • Non Arms-Length sales • sales of properties where the habitable space are less than 30m2 or greater than 1000m2 • sales less than £20,000. Annual median or simple mean prices should not be used to calculate the property price change over time. The quality (where quality refers to the combination of all characteristics of a residential property, both physical and locational) of the properties that are sold may differ from one time period to another. For example, sales in one quarter could be disproportionately skewed towards low-quality properties, therefore producing a biased estimate of average price. The median and simple mean prices are not ‘standardised’ and so the varying mix of properties sold in each quarter could give a false impression of the actual change in prices. In order to calculate the pure property price change over time it is necessary to compare like with like, and this can only be achieved if the ‘characteristics-mix’ of properties traded is standardised. To calculate pure property change over time please use the standardised prices in the NI House Price Index Detailed Statistics file.

United States Median Home Sale Price: All Residential: Richmond, VA data was reported at 289.000 USD th in Jul 2020. This records an increase from the previous number of 275.000 USD th for Jun 2020. United States Median Home Sale Price: All Residential: Richmond, VA data is updated monthly, averaging 224.000 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 289.000 USD th in Jul 2020 and a record low of 163.000 USD th in Feb 2012. United States Median Home Sale Price: All Residential: Richmond, VA data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB056: Median Home Sale Price: by Metropolitan Areas.

Explore our extensive dataset of groceries and essentials from Albertsons, offering detailed information on a wide range of products available at this prominent retailer.

This dataset includes product names, categories, descriptions, prices, and availability, providing a thorough overview of Albertsons' grocery and essential items.

Perfect for market analysis, inventory management, and competitive research, this dataset helps businesses and analysts track pricing trends, monitor stock levels, and understand consumer preferences.

Enhance your insights into the grocery retail market with this valuable collection of Albertsons product data.

The main stock market index of United States, the US500, rose to 6231 points on July 3, 2025, gaining 0.06% from the previous session. Over the past month, the index has climbed 4.36% and is up 11.93% 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 July of 2025.

The dataset shows GDP at Factor Cost, Consumption of Fixed Capital, NDP at Factor Cost, Indirect Taxes less Subsidies, GDP at Market Prices, NDP at Market Prices, Net Factor Income from Abroad, GNP at Factor Cost, NNP at Factor Cost, GNP at Market Prices, NNP at Market Prices, PFCE, PFCE in the Domestic Market, GFCE, Personal Disposable Income, GDP of Public sector, NDP of Public Sector, Gross Domestic Capital Formation, Net Domestic Capital Formation, Gross Domestic Saving, Net Domestic Saving, Per Capita GNP at Factor Cost (Rs), Per Capita NNP at Factor Cost (Rs), Net National Disposable Income, GNP at Basic Prices, Gross Capital Formation, Gross National Disposable Income, GVA at Basic Prices, Gross Savings, Net Capital Formation, Net Savings, NNP at Basic Prices, NVA at Basic Prices, Per Capita GDP, Per Capita GNP, Per Capita NNI, Per Capita PFCE, Per Capita GNDI, Other current transfers (net) from ROW, per capita GNI at factor cost, Net taxes on Products, Gross Domestic Product, Net Domestic Product, Primary income receivable from ROW (net), Gross National Income, Net National Income, Per Capita GNI at current prices

1. Overview

This dataset provides monthly stock price data for the MAG7 over the past 20 years (2004–2024). The data includes key financial metrics such as opening price, closing price, highest and lowest prices, trading volume, and percentage change. The dataset is valuable for financial analysis, stock trend forecasting, and portfolio optimization.

2. What is MAG7 ?

MAG7 refers to the seven largest and most influential technology companies in the U.S. stock market : - Microsoft (MSFT) - Apple (AAPL) - Google (Alphabet, GOOGL) - Amazon (AMZN) - Nvidia (NVDA) - Meta (META) - Tesla (TSLA)

These companies are known for their market dominance, technological innovation, and significant impact on global stock indices such as the S&P 500 and Nasdaq-100.

3. Dataset Details

The dataset consists of historical monthly stock prices of MAG7, retrieved from Investing.com. It provides an overview of how these stocks have performed over two decades, reflecting market trends, economic cycles, and technological shifts.

4. Columns Descriptions

• Date The recorded month and year (DD-MM-YYYY)
• Price The closing price of the stock at the end of the month
• Open The price at which the stock opened at the beginning of the month
• High The highest stock price recorded in the month
• Low The lowest stock price recorded in the month
• Vol. The total trading volume for the month
• Change % The percentage change in stock price compared to the previous month # 5. Data Source & Format The dataset was obtained from Investing.com and downloaded in CSV format. The data has been processed to ensure consistency and accuracy, with date formats standardized for time-series analysis. # 6. Potential Use Cases This dataset can be used for :
• 📈 Stock price trend analysis over 20 years
• 📊 Building financial models for long-term investing
• 🔎 Machine learning applications in stock market prediction
• 📉 Evaluating market volatility and economic impact on MAG7 stocks

7. Limitations & Considerations

• ⚠️ The dataset is limited to monthly data, meaning short-term price fluctuations are not captured.
• ⚠️ Trading volume (Vol.) may vary in availability due to differences in reporting.
• ⚠️ External factors such as stock splits, dividends, and market crashes are not explicitly noted but may impact historical trends.

Property Price: Intra Family Sales: Owner Occupied Flats: Free data was reported at 1,434.000 DKK th in Jun 2018. This records a decrease from the previous number of 1,489.000 DKK th for Mar 2018. Property Price: Intra Family Sales: Owner Occupied Flats: Free data is updated quarterly, averaging 926.500 DKK th from Mar 1992 (Median) to Jun 2018, with 106 observations. The data reached an all-time high of 1,489.000 DKK th in Mar 2018 and a record low of 356.000 DKK th in Jun 1995. Property Price: Intra Family Sales: Owner Occupied Flats: Free data remains active status in CEIC and is reported by Statistics Denmark. The data is categorized under Global Database’s Denmark – Table DK.P001: Property Price.

Gasoline rose to 2.10 USD/Gal on July 1, 2025, up 1.85% from the previous day. Over the past month, Gasoline's price has risen 1.77%, but it is still 18.30% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gasoline - values, historical data, forecasts and news - updated on July of 2025.

This dataset contains data on all Real Property parcels that have sold since 2013 in Allegheny County, PA.

Before doing any market analysis on property sales, check the sales validation codes. Many property "sales" are not considered a valid representation of the true market value of the property. For example, when multiple lots are together on one deed with one price they are generally coded as invalid ("H") because the sale price for each parcel ID number indicates the total price paid for a group of parcels, not just for one parcel. See the Sales Validation Codes Dictionary for a complete explanation of valid and invalid sale codes.

Sales Transactions Disclaimer: Sales information is provided from the Allegheny County Department of Administrative Services, Real Estate Division. Content and validation codes are subject to change. Please review the Data Dictionary for details on included fields before each use. Property owners are not required by law to record a deed at the time of sale. Consequently the assessment system may not contain a complete sales history for every property and every sale. You may do a deed search at http://www.alleghenycounty.us/re/index.aspx directly for the most updated information. Note: Ordinance 3478-07 prohibits public access to search assessment records by owner name. It was signed by the Chief Executive in 2007.

USDA Economic Research Service (ERS) compares prices paid by consumers for food with prices received by farmers for corresponding commodities. This data set reports these comparisons for a variety of foods sold through retail food stores such as supermarkets and super centers. Comparisons are made for individual foods and groupings of individual foods-market baskets-that represent what a typical U.S. household buys at retail in a year. The retail costs of these baskets are compared with the money received by farmers for a corresponding basket of agricultural commodities.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.

United States Road: Carbon Pricing Score: Excluding Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data was reported at 36.430 % in 2018. United States Road: Carbon Pricing Score: Excluding Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data is updated yearly, averaging 36.430 % from Dec 2018 (Median) to 2018, with 1 observations. The data reached an all-time high of 36.430 % in 2018 and a record low of 36.430 % in 2018. United States Road: Carbon Pricing Score: Excluding Emissions from the Combustion of Biomass: EUR 120 per Tonne of CO2 data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Effective Carbon Rates: by Sector: OECD Member: Annual. The carbon pricing score answers the question how close countries are to price carbon in line with carbon costs. EUR 60 is a midpoint estimate for carbon costs in 2020, and a low-end estimate for 2030. Pricing all emissions at least at EUR 60 in 2020 shows that a country is on a good track to reach the goals of the Paris Agreement to decarbonise by mid-century economically. EUR 30 is a historic low-end estimate for carbon costs, and EUR 120 is a midrange estimate for carbon costs in 2030.; The carbon pricing score answers the question how close countries price carbon emissions in line with carbon costs. EUR 120 per tonne CO2 is a central estimate for carbon costs in 2030.More generally, a carbon pricing score of 100% shows that a country prices all carbon emissions at the carbon cost estimate or more, and a carbon pricing score of 0% shows that a country does not price any carbon emissions.The carbon pricing score by country, by sector answers the question how close countries price carbon emissions in line with carbon costs within a given sector.For additional information, see Effective Carbon Rates 2021

This table contains 909 series, with data for years 1981 - 2012 (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 ...) Seasonal adjustment (2 items: Seasonally adjusted at annual rates; Trading-day adjusted ...) Prices (2 items: Chained (2002) dollars; 2002 constant prices ...) North American Industry Classification System (NAICS) (303 items: All industries; Business sector industries; Business sector; goods; Business sector; services ...).

How much do fruits and vegetables cost? ERS estimated average prices for 153 commonly consumed fresh and processed fruits and vegetables.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web page with links to Excel files For complete information, please visit https://data.gov.

Description

This dataset provides detailed stock price data for IBM and Oracle over a 20-year period from January 2004, to January, 2024. This dataset contains historical stock data for Oracle Corporation (ORCL) and International Business Machines Corporation (IBM). This comprehensive dataset is ideal for financial analysis, investment research, and time series forecasting. The data is recorded at a 5-day interval, offering a comprehensive view of the stock performance of these two technology giants.

Data Overview

The dataset includes the following columns: - Date: The date of the stock price record. - Open: The opening price of the stock on that date. - High: The highest price of the stock on that date. - Low: The lowest price of the stock on that date. - Close: The closing price of the stock on that date. - Adj Close: The adjusted closing price of the stock on that date, accounting for corporate actions. - Volume: The number of shares traded on that date. - Stock: The ticker symbol (IBM or ORCL) indicating which company's stock data is represented.

Use Cases

This dataset is ideal for: - Financial Analysis: Conducting historical performance analysis of IBM and Oracle stocks. - Machine Learning: Training models for stock price prediction. - Comparative Studies: Comparing the market behavior and trends of IBM and Oracle over two decades. - Investment Strategies: Backtesting investment strategies using historical data.

Data Source

The stock data was fetched using the Yahoo Finance API through the yfinance library in Python.

Context

This dataset was created by our in-house web scraping and data mining teams at PromptCloud and DataStock. This dataset is a sample of the full dataset that can be seen on our data repository. The property listing is one of the key factors most people are on the lookout for these days. Real-Estate data is required by many to make sure they can quote the correct price and keep the competitive pricing is present.

You can download the full dataset from our data repository at DataStock. I am attaching the link of the dataset below. Link: https://app.datastock.shop/?site_name=Property_Listing_from_Homes.com

Content

Total Records Count : 798088  Domain Name : homes.com  Date Range : 01st Mar 2020 - 31st May 2020   File Extension : xml

Available Fields : uniq_id, crawl_timestamp, ad_title, location, price, bedrooms, bathrooms, sqft, overview, home_details, mls_number, listing_source, listing_agent, offered_by, image_urls

Acknowledgments

We wouldn't be here without the help of our in house web scraping and data mining teams at PromptCloud and DataStock.

Inspiration

This dataset was created keeping in mind our data scientists and researchers across the world.