Sales data for all Islanders Board Of Industry & Service (IBIS) stores.

Content

An Adidas sales dataset is a collection of data that includes information on the sales of Adidas products. This type of dataset may include details such as the number of units sold, the total sales revenue, the location of the sales, the type of product sold, and any other relevant information.

Adidas sales data can be useful for a variety of purposes, such as analyzing sales trends, identifying successful products or marketing campaigns, and developing strategies for future sales. It can also be used to compare Adidas sales to those of competitors, or to analyze the effectiveness of different marketing or sales channels.

There are a variety of sources that could potentially provide an Adidas sales dataset, including Adidas itself, market research firms, government agencies, or other organizations that track sales data. The specific data points included in an Adidas sales dataset may vary depending on the source and the purpose for which it is being used.

Dataset Glossary (Column-Wise) - Retailer : Represents the business or individual that sells Adidas products directly to consumers.

• Retailer ID : A unique identifier assigned to each retailer in the dataset.

• Invoice Date : The date when a particular invoice or sales transaction took place.

• Region : Refers to a specific geographical area or district where the sales activity or retail operations occur.

• State : Represents a specific administrative division or territory within a country.

• City : Refers to an urban area or municipality where the sales activity or retail operations are conducted.

• Product : Represents the classification or grouping of Adidas products.

• Price per Unit : The cost or price associated with a single unit of a product.

• Units Sold : The quantity or number of units of a particular product sold during a specific sales transaction.

• Total Sales : The overall revenue generated from the sales transactions.

• Operating Profit : The profit earned by the retailer from its normal business operations.

• Sales Method : The approach or channel used by the retailer to sell its products or services.

Dataset

This dataset was created by Mark Medhat

Released under Apache 2.0

Contents

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The Office of Policy and Management maintains a listing of all real estate sales with a sales price of $2,000 or greater that occur between October 1 and September 30 of each year. For each sale record, the file includes: town, property address, date of sale, property type (residential, apartment, commercial, industrial or vacant land), sales price, and property assessment. Data are collected in accordance with Connecticut General Statutes, section 10-261a and 10-261b: https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261a and https://www.cga.ct.gov/current/pub/chap_172.htm#sec_10-261b. Annual real estate sales are reported by grand list year (October 1 through September 30 each year). For instance, sales from 2018 GL are from 10/01/2018 through 9/30/2019. Some municipalities may not report data for certain years because when a municipality implements a revaluation, they are not required to submit sales data for the twelve months following implementation.

Dataset

This dataset was created by Ashish Pandey

Contents

Analysis of ‘E-Commerce Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/benroshan/ecommerce-data on 28 January 2022.

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

Hello

Ever been excited to see a sales dataset ? Well, this data is perfectly curated to perform sales analysis. We have an e-commerce sales dataset from India with 3 csv files -List of Orders, Order details, Sales target

What's inside?

1. List of Orders-This dataset contains purchase information. The information includes ID, Date of Purchase and customer details
2. Order Details- This dataset contains order ID, with the order price, quantity,profit, category and subcategory of product
3. Sales target-This dataset contains sales target amount and date for each product category

Acknowledgements

Dataset received from my University, Original Author unknown

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

This table contains 3 series, with data for years 2016 - 2017 (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 item: Canada); Sales (3 items: Retail trade; Electronic shopping and mail-order houses; Retail E-commerce sales).

Dataset

This dataset was created by Pratyusha Kar

Released under CC0: Public Domain

Contents

Update Frequency: Yearly

Access to Residential, Condominium, Commercial, Apartment properties and vacant land sales history data.

To download XML and JSON files, click the CSV option below and click the down arrow next to the Download button in the upper right on its page.

A dataset containing the 100 latest settled sales in CSV format for Young as at January-2025, data sourced from the NSW Valuer General, geocoded and analyzed by AreaSearch.

This dataset contains one .csv file that can be used as a new benchmark data for the solving of real-world sales forecasting problem. All data are real and obtained experimentally in production environment in one of the biggest retail company in Bosnia and Herzegovina. The available data in this dataset are in period from 2010 to 2018.

Use our constantly updated Walmart products dataset to get a complete snapshot of new products, categories, pricing, and consumer reviews. You may purchase the entire dataset or a customized subset, depending on your needs. Popular use cases: Identify product inventory gaps and increased demand for certain products, analyze consumer sentiment and define a pricing strategy by locating similar products and categories among your competitors. The dataset includes all major data points: product, SKU, GTIN, currency,timestamp, price,a nd more. Get your Walmart dataset today!

Analysis of ‘Avocado Prices’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/neuromusic/avocado-prices on 28 January 2022.

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

Context

It is a well known fact that Millenials LOVE Avocado Toast. It's also a well known fact that all Millenials live in their parents basements.

Clearly, they aren't buying home because they are buying too much Avocado Toast!

But maybe there's hope... if a Millenial could find a city with cheap avocados, they could live out the Millenial American Dream.

Content

This data was downloaded from the Hass Avocado Board website in May of 2018 & compiled into a single CSV. Here's how the Hass Avocado Board describes the data on their website:

The table below represents weekly 2018 retail scan data for National retail volume (units) and price. Retail scan data comes directly from retailers’ cash registers based on actual retail sales of Hass avocados. Starting in 2013, the table below reflects an expanded, multi-outlet retail data set. Multi-outlet reporting includes an aggregation of the following channels: grocery, mass, club, drug, dollar and military. The Average Price (of avocados) in the table reflects a per unit (per avocado) cost, even when multiple units (avocados) are sold in bags. The Product Lookup codes (PLU’s) in the table are only for Hass avocados. Other varieties of avocados (e.g. greenskins) are not included in this table.

Some relevant columns in the dataset:

• Date - The date of the observation
• AveragePrice - the average price of a single avocado
• type - conventional or organic
• year - the year
• Region - the city or region of the observation
• Total Volume - Total number of avocados sold
• 4046 - Total number of avocados with PLU 4046 sold
• 4225 - Total number of avocados with PLU 4225 sold
• 4770 - Total number of avocados with PLU 4770 sold

Acknowledgements

Many thanks to the Hass Avocado Board for sharing this data!!

http://www.hassavocadoboard.com/retail/volume-and-price-data

Inspiration

In which cities can millenials have their avocado toast AND buy a home?

Was the Avocadopocalypse of 2017 real?

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

A dataset containing sales trends in CSV format for Dubbo - East as at January-2025, based on sales data sourced from the NSW Valuer General, geocoded and analyzed by AreaSearch.

A dataset containing sales trends in CSV format for Wollongong - East as at January-2025, based on sales data sourced from the NSW Valuer General, geocoded and analyzed by AreaSearch.

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• Developing a customized solution: Our experts create a custom framework to extract public data using our in-house web scraping infrastructure.
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A dataset containing sales trends in CSV format for Roselands as at January-2025, based on sales data sourced from the NSW Valuer General, geocoded and analyzed by AreaSearch.