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Retail Demand Prediction Dataset
Retail & Consumer Behavior
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Free
About
This dataset provides essential sales and related contextual information for a retail store chain with multiple outlets across the country. Its primary purpose is to facilitate data analysis and the development of machine learning models for sales forecasting, helping to resolve issues in inventory management by matching demand with supply. It is an ideal resource for data scientists seeking to gain useful insights and build predictive models for future sales periods.
Columns
- Store: A unique identifier for each retail store.
- Date: Represents the week of sales, indicating the specific weekly period for the recorded data.
- Weekly_Sales: The total sales for the given store during that particular week.
- Holiday_Flag: A binary indicator showing whether the week in question was a holiday week (1 for holiday, 0 for non-holiday).
- Temperature: The recorded temperature on the day the sales data was collected.
- Fuel_Price: The cost of fuel in the region corresponding to the store during the sales week.
- CPI: Stands for Consumer Price Index, providing an economic indicator for the period.
- Unemployment: The unemployment rate in the region during the sales week.
Distribution
The dataset is typically provided in a CSV format, specifically referenced as "Walmart Data Analysis and Forcasting.csv". It has a file size of 363.73 kB and contains 8 columns. There are 6,435 valid records across all columns. Specific numbers for rows/records are consistent across all listed columns. The dataset is expected to be updated monthly.
Usage
This dataset is well-suited for a variety of analytical and predictive tasks, including:
- Conducting Exploratory Data Analysis (EDA) to uncover trends and patterns in retail sales.
- Developing and evaluating machine learning models for sales forecasting for future months or years.
- Gaining useful insights into factors influencing retail sales, such as holidays, temperature, fuel prices, and economic indicators.
- Assisting with inventory management by enabling better demand prediction and supply alignment.
Coverage
The dataset covers sales data for a retail store chain operating across various locations within a country. The time range spans 143 unique weeks of sales, with an expected monthly update frequency. Specific geographic or demographic details beyond "across the country" are not detailed in the available information.
License
CC0: Public Domain
Who Can Use It
This dataset is primarily intended for data scientists. It is particularly useful for those looking to:
- Perform data analysis to derive actionable insights.
- Build and test prediction models for retail sales.
- Address real-world business challenges such as inventory management and demand forecasting. The dataset is also suitable for beginners in data analysis and machine learning.
Dataset Name Suggestions
- Walmart Sales Forecasting Data
- Retail Demand Prediction Dataset
- Store Inventory Management Data
- Weekly Retail Sales Analytics
Attributes
Original Data Source: Walmart Sales Forecasting Data
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