The benchmark interest rate in the United Kingdom was last recorded at 4.25 percent. This dataset provides - United Kingdom Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Our Realtor.com (Multiple Listing Service) dataset represents one of the most exhaustive collections of real estate data available to the industry. It consolidates data from over 500 MLS aggregators across various regions, providing an unparalleled view of the property market.

Features:

Property Listings: Each listing provides comprehensive details about a property. This includes its physical address, number of bedrooms and bathrooms, square footage, lot size, type of property (e.g., single-family home, condo, townhome), and more.

Photographs and Virtual Tours: Visuals are crucial in the property market. Most listings are accompanied by high-quality photographs and, in many cases, virtual or 3D tours that allow potential buyers to explore properties remotely.

Pricing Information: Listings provide asking prices, and the dataset frequently updates to reflect price changes. Historical price data, which includes initial listing prices and any subsequent reductions or increases, is also available.

Transaction Histories: For sold properties, the dataset provides information about the date of sale, the sale price, and any discrepancies between the listing and sale prices.

Agent and Broker Information: Each listing typically has associated details about the property's real estate professional. This might include their name, contact details, and affiliated brokerage.

Open House Schedules: Open house dates and times are listed for properties that are actively being shown to potential buyers.

1. Analytical Insights:

Market Trends: By analyzing the dataset over time, one can glean insights into market dynamics, such as the rate of price appreciation or depreciation in certain areas, the average time properties stay on the market, and seasonality effects.

Neighborhood Data: With comprehensive geographical data, it becomes possible to understand neighborhood-specific trends. This is invaluable for potential buyers or real estate investors looking to identify burgeoning markets.

Price Comparisons: Realtors and potential buyers can benchmark properties against similar listings in the same area to determine if a property is priced appropriately.

1. Utility:

For Industry Professionals and Analysts: Beyond buyers and sellers, the dataset is a trove of information for real estate agents, brokers, analysts, and investors. They can harness this data to craft strategies, predict market movements, and serve their clients better.

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.

AGNC: Will Mortgage REIT Thrive in a Rising Rate Environment?

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

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.

Success.ai offers a cutting-edge solution for businesses and organizations seeking Company Financial Data on private and public companies. Our comprehensive database is meticulously crafted to provide verified profiles, including contact details for financial decision-makers such as CFOs, financial analysts, corporate treasurers, and other key stakeholders. This robust dataset is continuously updated and validated using AI technology to ensure accuracy and relevance, empowering businesses to make informed decisions and optimize their financial strategies.

Key Features of Success.ai's Company Financial Data:

Global Coverage: Access data from over 70 million businesses worldwide, including public and private companies across all major industries and regions. Our datasets span 250+ countries, offering extensive reach for your financial analysis and market research.

Detailed Financial Profiles: Gain insights into company financials, including revenue, profit margins, funding rounds, and operational costs. Profiles are enriched with key contact details, including work emails, phone numbers, and physical addresses, ensuring direct access to decision-makers.

Industry-Specific Data: Tailored datasets for sectors such as financial services, manufacturing, technology, healthcare, and energy, among others. Each dataset is customized to meet the unique needs of industry professionals and analysts.

Real-Time Accuracy: With continuous updates powered by AI-driven validation, our financial data maintains a 99% accuracy rate, ensuring you have access to the most reliable and up-to-date information available.

Compliance and Security: All data is collected and processed in strict adherence to global compliance standards, including GDPR, ensuring ethical and lawful usage.

Why Choose Success.ai for Company Financial Data?

Best Price Guarantee: We pride ourselves on offering the most competitive pricing in the industry, ensuring you receive unparalleled value for comprehensive financial data.

AI-Validated Accuracy: Our advanced AI algorithms meticulously verify every data point to ensure precision and reliability, helping you avoid costly errors in your financial decision-making.

Customized Data Solutions: Whether you need data for a specific region, industry, or type of business, we tailor our datasets to align perfectly with your requirements.

Scalable Data Access: From small startups to global enterprises, our platform caters to businesses of all sizes, delivering scalable solutions to suit your operational needs.

Comprehensive Use Cases for Financial Data:

1. Strategic Financial Planning:

Leverage our detailed financial profiles to create accurate budgets, forecasts, and strategic plans. Gain insights into competitors’ financial health and market positions to make data-driven decisions.

1. Mergers and Acquisitions (M&A):

Access key financial details and contact information to streamline your M&A processes. Identify potential acquisition targets or partners with verified profiles and financial data.

1. Investment Analysis:

Evaluate the financial performance of public and private companies for informed investment decisions. Use our data to identify growth opportunities and assess risk factors.

1. Lead Generation and Sales:

Enhance your sales outreach by targeting CFOs, financial analysts, and other decision-makers with verified contact details. Utilize accurate email and phone data to increase conversion rates.

1. Market Research:

Understand market trends and financial benchmarks with our industry-specific datasets. Use the data for competitive analysis, benchmarking, and identifying market gaps.

APIs to Power Your Financial Strategies:

Enrichment API: Integrate real-time updates into your systems with our Enrichment API. Keep your financial data accurate and current to drive dynamic decision-making and maintain a competitive edge.

Lead Generation API: Supercharge your lead generation efforts with access to verified contact details for key financial decision-makers. Perfect for personalized outreach and targeted campaigns.

Tailored Solutions for Industry Professionals:

Financial Services Firms: Gain detailed insights into revenue streams, funding rounds, and operational costs for competitor analysis and client acquisition.

Corporate Finance Teams: Enhance decision-making with precise data on industry trends and benchmarks.

Consulting Firms: Deliver informed recommendations to clients with access to detailed financial datasets and key stakeholder profiles.

Investment Firms: Identify potential investment opportunities with verified data on financial performance and market positioning.

What Sets Success.ai Apart?

Extensive Database: Access detailed financial data for 70M+ companies worldwide, including small businesses, startups, and large corporations.

Ethical Practices: Our data collection and processing methods are fully comp...

Using two different samples – one based on newspaper advertisements, the other Internet-based – we identify some price anomalies in the used car market in the Netherlands. First, prices of used cars depend on their age in calendar years rather than months. Second, there is some evidence that crossing 100,000 km induces a sudden additional price reduction. Third, a new license plate format, something with no intrinsic value whatsoever, increases a car’s price by about 4%. We discuss possible explanations for these results.

The benchmark interest rate in Australia was last recorded at 3.85 percent. This dataset provides - Australia Interest Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Explore a diverse range of fashion items, home goods, and more, with insights into pricing, availability, ratings, and reviews. Popular use cases include trend forecasting, pricing optimization, and inventory management in the fast-fashion market.

The Shein.com Products dataset provides a detailed overview of the extensive product range available on Shein, offering key insights into the fast-fashion market. This dataset includes essential details such as product names, prices, discounts, descriptions, materials, product images, SKUs (Stock Keeping Units), low-stock indicators, and more.

Ideal for eCommerce professionals, fashion analysts, and market strategists, this dataset supports trend analysis, pricing strategies, and inventory management. Whether you're benchmarking competitors, identifying emerging trends, or optimizing your product offerings, the Shein.com Products dataset delivers valuable insights to stay ahead in the dynamic fashion industry.

Dataset Features

• product_name: The name/title of the product listed.
• description: A brief description of the product, including features or materials.
• initial_price: The original price of the product before any discounts.
• final_price: The actual selling price after applying discounts.
• currency: The currency in which the price is listed (e.g., USD).
• in_stock: Availability status of the product (True if in stock, otherwise False).
• color: Available color(s) for the product.
• size: Size(s) available (e.g., S, M, L, or custom sizes).
• reviews_count: Number of user reviews the product has received.
• main_image: URL to the primary product image.
• category_url: Link to the category page the product belongs to.
• url: Direct link to the product page.
• category_tree: Hierarchical path of the product category.
• country_code: Country code indicating where the product is available.
• domain: The Shein domain where the product was found (e.g., shein.com, shein.uk).
• image_count: Total number of product images.
• image_urls: List/array of URLs for all images related to the product.
• model_number: The product’s model or SKU number.
• offers: Details of promotions or discounts available.
• other_attributes: Miscellaneous product features or labels (e.g., eco-friendly, plus-size).
• product_id: Unique identifier for the product.
• rating: Average user rating (typically on a 5-star scale).
• related_products: List of similar or related products.
• root_category: The broadest category classification (e.g., "Women", "Home").
• top_reviews: Highlighted customer reviews.
• category: Specific product category (e.g., "Bikinis", "T-Shirts").
• brand: Brand name (often "Shein" or sub-brands).
• all_available_sizes: List of all size options for the product.
• category_details: Additional metadata about the product category.
• initial_price_usd: Original price converted to USD.
• final_price_usd: Final price converted to USD.
• discount_price: Price discount amount (initial - final).
• discount_price_usd: Discount amount in USD.
• colors: All color variants of the product.
• store_details: Information about the store or seller.
• shipping_details: Information about shipping costs and delivery time.
• shipping_type: Type of shipping offered (e.g., standard, express).
• product_parent_id: ID representing a grouped product variant.
• tags: Keywords or tags associated with the product.
• model_data: Additional attributes from the product model (could include fit, cut, etc.).

Distribution

• Data Volume: 40 Columns and 42.35 M Rows
• Format: CSV

Usage

This dataset is ideal for a wide range of practical and analytical applications: - Trend Forecasting: Identify emerging fashion trends based on product popularity and review sentiment.
- Pricing Optimization: Analyze discount strategies and dynamic pricing patterns.
- Inventory Management: Monitor stock availability and detect low-stock patterns.
- Recommendation Systems: Build personalized fashion recommendations using product attributes and user ratings.
- Market Benchmarking: Compare Shein's offerings with competitors or across regions.
- Computer Vision: Use product images for training models in visual fashion recognition.

Coverage

• Geographic Coverage: Global
• Time Range: Varies by data collection; generally recent and can be updated periodically.

License

CUSTOM

Please review the respective licenses below:

1. Data Provider's License
   • Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: For training ML models like price predictors, review sentiment classifiers, or image-based search engines.
• Researchers:

This dataset provides transaction volume, value, and price for the voluntary carbon market (VCM) by project category, project standard, project region, nature-based vs. engineered projects, reductions vs. removals projects.As source mentioned, these data on voluntary carbon market dynamics come from EM’s database of voluntarily disclosed over-the-counter (OTC) carbon credit transactions, which are shared with EM by an international network of more than 180 “EM Respondents,” including project developers, investors, and intermediaries with headquarters in over 40 countries and representing carbon credit sales from thousands of nature-based and technological carbon projects in over 100 countries.

Analysis of ‘Market Prices of Onion 2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ravisane1/market-price-of-onion-2020 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

ONION TEARS

It is so wacky that how 1.25 Billion people can’t control the mighty power of insignificant product like ONION? The Small red bulb has power to bring down the government to its knees, be it BJP or Congress, it does not differentiate. We have seen governments crashing in year 1980, 1998 and 2010 mainly due to onion shortage.

This year in September 2020 onion prices rocketed to a new level.

REACTION OF GOVERNMENT

The knee jerk reaction of government is to ban the exports and raid onion traders. Which simply leads to unreliability of Indian exports in international markets and dissuading of small onion traders to exit the onion trade. India on Sep 14 prohibited the export of all varieties of onion except those cut, sliced or in powder form. “The export of all varieties of onion…is prohibited with immediate effect,” the Directorate General of Foreign Trade (DGFT) said in a notification. The ban includes Bangalore rose onions and Krishnapuram onions.

Read more at: https://economictimes.indiatimes.com/news/economy/agriculture/india-bans-export-of-all-varieties-of-onion/articleshow/78109131.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst

Content

This dataset has daily/weekly market prices of onion from various markets of India for the year 2020. The data is collected from data.gov.in website. It consists of 9 columns- *Name of State, District, Market, Name of commodity, Variety of onion, Arrival Date, Min Price, Max Price, Modal Price.

Inspiration

Can we kagglers analyze the dataset and do some EDA to find reason behind this problem?

--- Original source retains full ownership of the source dataset ---

Success.ai's B2B Leads Data for Global Professionals provides unparalleled access to a robust database of over 700M LinkedIn Profiles and 170 million verified professional profiles, specifically tailored for B2B Lead Generation, marketing and outreach. Featuring accurate work emails, phone numbers, and enriched professional profiles, this data is an essential tool for driving B2B marketing, sales initiatives, talent acquisition, and more. Our offering is continuously updated with cutting-edge AI validation technology to ensure unmatched precision and relevance for all your business needs.

Key Features of Success.ai's Professional Contact Data

1. Extensive Data Coverage Gain access to a meticulously curated database of 170M+ contact profiles, including 50M verified phone numbers and thousands of IT-related company profiles in the US. This dataset allows businesses to seamlessly engage with decision-makers, technology experts, and influencers in the IT domain.

2. AI-Powered Accuracy Our data is rigorously validated using AI technology, guaranteeing a 99% accuracy rate for emails and phone numbers. This minimizes wasted resources and ensures your campaigns reach the right professionals at the right time.

3. Tailored for IT Professionals Designed specifically for the needs of the IT industry, our data spans professionals in software development, IT consulting, cloud computing, cybersecurity, and more, allowing you to target specific niches and build meaningful connections.

4. Flexible Data Delivery Options Choose from API integrations, custom flat files, or direct database access to fit your operational workflows. Success.ai ensures seamless integration into your existing systems, saving you time and reducing complexities.

5. Compliance and Security Adhering to GDPR, CCPA, and other global compliance standards, Success.ai prioritizes ethical data sourcing, so you can confidently utilize our data to grow your business.

Why Choose Success.ai for Professional Leads Contact Data?

• Best Price Guarantee We offer the most competitive pricing in the market, providing high-value data solutions without breaking your budget.

• Diverse Strategic Applications Our dataset supports a wide range of business objectives, including:

B2B Marketing: Execute hyper-targeted campaigns with verified email and phone data. Sales Outreach: Empower sales teams to connect directly with IT decision-makers and influencers. Talent Recruitment: Gain insights into top professionals and optimize your recruitment strategies. Lead Generation: Enhance your pipeline with validated and up-to-date contact details. Customer Insights: Understand your audience with demographic and firmographic data for strategic market research.

• Advanced Technology Integration With tools like the Enrichment API and Lead Generation API, Success.ai enables real-time data updates and efficient CRM enrichment. Conduct up to 860,000 API calls daily, making it the ideal solution for enterprises managing high-volume lead generation.

• Data Highlights 170M+ Verified B2B Contact Profiles 50M Verified Phone Numbers 30M+ Company Profiles 700M Global Professional Profiles

Use Cases

• Marketing Excellence: Use precise contact data to deliver campaigns across the US market.
• Enhanced Recruitment: Find and engage with top-tier talent through accurate and up-to-date professional profiles.
• Sales Enablement: Equip your sales team with validated contact details for high-conversion outreach.

• Data-Driven Decisions: Make smarter business decisions with accurate demographic and firmographic data.

• What Sets Success.ai Apart? Success.ai combines AI-powered accuracy, extensive coverage, and flexible delivery methods to provide businesses with a strategic advantage in the competitive B2B landscape. With our verified B2B Leads data, you can:

Expand your business network effortlessly. Minimize bounce rates and outreach inefficiencies. Align your campaigns with top industry professionals to maximize ROI.

Get started today with Success.ai’s data solutions and transform how you find B2B Leads Data that converts!

No one beats us on price. Period.

Graph and download economic data for Real Residential Property Prices for Canada (QCAR628BIS) from Q1 1970 to Q1 2025 about Canada, residential, HPI, housing, real, price index, indexes, and price.

Crude Oil rose to 68.75 USD/Bbl on July 11, 2025, up 3.27% from the previous day. Over the past month, Crude Oil's price has risen 1.04%, but it is still 16.37% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on July of 2025.

Gold rose to 3,354.76 USD/t.oz on July 11, 2025, up 0.92% from the previous day. Over the past month, Gold's price has fallen 0.92%, but it is still 39.14% 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.

Silver rose to 38.37 USD/t.oz on July 11, 2025, up 3.65% from the previous day. Over the past month, Silver's price has risen 5.59%, and is up 24.68% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on July of 2025.

Nickel fell to 15,235 USD/T on July 11, 2025, down 0.33% from the previous day. Over the past month, Nickel's price has risen 0.86%, but it is still 9.62% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Nickel - values, historical data, forecasts and news - updated on July of 2025.

The yield on US 10 Year Note Bond Yield rose to 4.41% on July 11, 2025, marking a 0.06 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.04 points and is 0.23 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. US 10 Year Treasury Bond Note Yield - values, historical data, forecasts and news - updated on July of 2025.

France's main stock market index, the FR40, fell to 7829 points on July 11, 2025, losing 0.92% from the previous session. Over the past month, the index has climbed 0.83% and is up 1.36% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on July of 2025.

The DXY exchange rate rose to 97.9584 on July 14, 2025, up 0.11% from the previous session. Over the past month, the United States Dollar has weakened 0.32%, and is down by 6.03% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on July of 2025.

United Kingdom's main stock market index, the GB100, fell to 8941 points on July 11, 2025, losing 0.38% from the previous session. Over the past month, the index has climbed 0.63% and is up 8.34% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated on July of 2025.