This dataset contains monthly retail price data for a wide range of consumer products sold in various Canadian provinces over several years. It has been enriched with tax, category, and classification metadata for deeper insights.

Usefulness of the Dataset

This dataset can be used for:

Purpose and Use Cases

This dataset is ideal for:

🏛️ Policy Analysis

Understand how federal and provincial taxes shape price access — especially for essentials like milk, bread, or medications.

🧍‍♀️ Consumer Insights

See how costs for personal care, food, and baby goods evolve month-over-month in each region.

💸 Inflation & Seasonality

Analyze how monthly or yearly trends (e.g., holiday spikes or inflation events) affect product pricing.

🌍 Social Impact Studies

Measure product accessibility gaps between provinces for low-income consumers or high-tax regions.

🛍️ Retail & Budget Planning

Guide families, retailers, or policymakers on where and when to buy or subsidize certain products.

In 2025, around ** percent of people said the higher prices were going to impact their plans on Valentine's and/ or Galentine's Day. ** percent of people said it would not change their plans.

When surveyed between March and April 2024, some ** percent of baby boomers in the U.S. stated that they experienced an increase in food and beverages prices compared to a year earlier. Among Gen Z, the share who experience food and drink inflation was ** percent.

View monthly updates and historical trends for Case-Shiller Home Price High Tier Index: Chicago, IL. Source: Standard and Poor's. Track economic data with…

This dataset contains the predicted prices of the asset High over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

Graph and download economic data for Home Price Index (High Tier) for Portland, Oregon (POXRHTNSA) from Jan 1987 to Sep 2025 about high tier, Portland, HPI, housing, price index, indexes, price, and USA.

The FAO vegetable oil Price Index* reached 178.32 index points in June of 2008 during the financial crisis. During the pandemic, the price index rose to 184.56 points in October of 2021. After the start of the war in Ukraine, the index jumped to over 251 points in March of 2022. As of September 2025, the index had slightly declined to 167.9 points. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page. For further information about the Russian invasion of Ukraine, please visit our dedicated page on the topic.

In Q3 2025, North America, the High Density Polyethylene Price Index fell by 3.6% quarter-over-quarter, reflecting subdued demand and ample supply. Check detailed insights for Europe, MEA, South America and APAC.

Home Value Insights: A Beginner's Regression Dataset

This dataset is designed for beginners to practice regression problems, particularly in the context of predicting house prices. It contains 1000 rows, with each row representing a house and various attributes that influence its price. The dataset is well-suited for learning basic to intermediate-level regression modeling techniques.

Features:

1. Square_Footage: The size of the house in square feet. Larger homes typically have higher prices.
2. Num_Bedrooms: The number of bedrooms in the house. More bedrooms generally increase the value of a home.
3. Num_Bathrooms: The number of bathrooms in the house. Houses with more bathrooms are typically priced higher.
4. Year_Built: The year the house was built. Older houses may be priced lower due to wear and tear.
5. Lot_Size: The size of the lot the house is built on, measured in acres. Larger lots tend to add value to a property.
6. Garage_Size: The number of cars that can fit in the garage. Houses with larger garages are usually more expensive.
7. Neighborhood_Quality: A rating of the neighborhood’s quality on a scale of 1-10, where 10 indicates a high-quality neighborhood. Better neighborhoods usually command higher prices.
8. House_Price (Target Variable): The price of the house, which is the dependent variable you aim to predict.

Potential Uses:

1. Beginner Regression Projects: This dataset can be used to practice building regression models such as Linear Regression, Decision Trees, or Random Forests. The target variable (house price) is continuous, making this an ideal problem for supervised learning techniques.

2. Feature Engineering Practice: Learners can create new features by combining existing ones, such as the price per square foot or age of the house, providing an opportunity to experiment with feature transformations.

3. Exploratory Data Analysis (EDA): You can explore how different features (e.g., square footage, number of bedrooms) correlate with the target variable, making it a great dataset for learning about data visualization and summary statistics.

4. Model Evaluation: The dataset allows for various model evaluation techniques such as cross-validation, R-squared, and Mean Absolute Error (MAE). These metrics can be used to compare the effectiveness of different models.

Versatility:

• The dataset is highly versatile for a range of machine learning tasks. You can apply simple linear models to predict house prices based on one or two features, or use more complex models like Random Forest or Gradient Boosting Machines to understand interactions between variables.

• It can also be used for dimensionality reduction techniques like PCA or to practice handling categorical variables (e.g., neighborhood quality) through encoding techniques like one-hot encoding.

• This dataset is ideal for anyone wanting to gain practical experience in building regression models while working with real-world features.

In Q3 2025, North America, the Recycled High-Density Polyethylene Price Index fell by 19.63% quarter-over-quarter, oversupply prevailed. Check detailed insights for Europe, MEA and APAC.

Coffee fell to 408.66 USd/Lbs on December 2, 2025, down 0.95% from the previous day. Over the past month, Coffee's price has risen 0.50%, and is up 38.54% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on December of 2025.

Geneva stands out as Europe's most expensive city for apartment purchases in early 2025, with prices reaching a staggering 15,720 euros per square meter. This Swiss city's real estate market dwarfs even high-cost locations like Zurich and London, highlighting the extreme disparities in housing affordability across the continent. The stark contrast between Geneva and more affordable cities like Nantes, France, where the price was 3,700 euros per square meter, underscores the complex factors influencing urban property markets in Europe. Rental market dynamics and affordability challenges While purchase prices vary widely, rental markets across Europe also show significant differences. London maintained its position as the continent's priciest city for apartment rentals in 2023, with the average monthly costs for a rental apartment amounting to 36.1 euros per square meter. This figure is double the rent in Lisbon, Portugal or Madrid, Spain, and substantially higher than in other major capitals like Paris and Berlin. The disparity in rental costs reflects broader economic trends, housing policies, and the intricate balance of supply and demand in urban centers. Economic factors influencing housing costs The European housing market is influenced by various economic factors, including inflation and energy costs. As of April 2025, the European Union's inflation rate stood at 2.4 percent, with significant variations among member states. Romania experienced the highest inflation at 4.9 percent, while France and Cyprus maintained lower rates. These economic pressures, coupled with rising energy costs, contribute to the overall cost of living and housing affordability across Europe. The volatility in electricity prices, particularly in countries like Italy where rates are projected to reach 153.83 euros per megawatt hour by February 2025, further impacts housing-related expenses for both homeowners and renters.

All-time high price data for Broccoli, including the peak value, date achieved, and current comparison metrics.

The District of Columbia holds the record for the highest price per ounce of high quality marijuana in the United States, as of January 2025, with an average price of some 590 U.S. dollars per ounce. Recreational cannabis use Recreational cannabis is not legal in all U.S. states; however, many consumers use the drug illicitly. A recent survey indicated that over half of U.S. adults think that cannabis should be legalized and taxed like alcohol and tobacco. Recreational cannabis is often used by consumers for relaxation, stress relief, and creativity, to name a few. Surveys have shown that a majority of recreation users use marijuana for relaxation. Legal marijuana market potential It is projected that by 2025 the sales of legal cannabis in the U.S. will generate approximately 25 billion dollars in revenue. The regulation of marijuana includes the taxation of all sales. There is potential for the U.S. cannabis market to generate significant taxes and boost the economy. It is estimated that the taxes from legal marijuana sales would exceed the taxes earned from U.S. sales taxes by a significant amount.

This dataset contains the predicted prices of the asset HIGH RESONANCE over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.

This dataset provides values for PRODUCER PRICES reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Graph and download economic data for Home Price Index (High Tier) for Washington D.C. (WDXRHTNSA) from Jan 1987 to Sep 2025 about high tier, Washington, HPI, housing, price index, indexes, price, and USA.

Highstreet price data for 2025-11-28 including currency, value, high, low, open, close, and percentage difference.

European Union - Producer prices in industry: High-technology manufacturing was 99.40 points in December of 2023, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for European Union - Producer prices in industry: High-technology manufacturing - last updated from the EUROSTAT on November of 2025. Historically, European Union - Producer prices in industry: High-technology manufacturing reached a record high of 101.00 points in April of 2017 and a record low of 91.70 points in December of 2020.

Based on professional technical analysis and AI models, deliver precise price‑prediction data for higher on 2025-12-12. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.