According to the data, Walmart's net sales were forecast to be around *** billion U.S. dollars in 2021, following the upsurge in 2020 that was driven by COVID-19. From 2021 onwards, Walmart's net sales were forecast to increase with each consecutive year. By 2026, it was forecast that Walmart's net sales would grow to ***** billion U.S. dollars, which includes store-based and e-commerce net sales.

In 2025, grocery sales accounted for 59.7 percent of the net sales of Walmart U.S. in the United States. In contrast, only 13.5 percent corresponded to health and wellness. WalmartWalmart was founded in 1962 by Sam Walton when he and his brother James “Bud” Walton opened the first Wal-Mart Discount City in Rogers, Arkansas. Since then, Walmart has grown to become the largest publicly-owned retail company in the world. In the United States, the company includes Walmart discount stores, supercenters, neighborhood markets, and Sam’s Club warehouse membership clubs. Beginning in the early 1990s, Walmart went to great lengths to increase their market share. They introduced a full line of groceries into their stores, diversified their market by appealing to certain ethnic groups through bilingual advertisements, and took steps to promote the awareness of environmental issues. Company divisionsWalmart deals in a wide variety of products, such as groceries, apparel, furniture, home appliances, and electronics. The company operates through three distinct business segments: Walmart U.S., Walmart International, and Sam’s Club. Walmart’s strongest segment, in terms of revenue, is Walmart U.S., which operates retail stores in the company’s domestic market of the United States. This segment also includes Walmart’s U.S. eCommerce website: walmart.com. In 2023, Walmart U.S. had net sales of 442 billion U.S. dollars.. The company’s Walmart International and Sam’s Club business divisions operate globally generating revenue through retail, wholesale, membership club, and online product sales. As of fiscal year 2024, around 13 percent of Walmart’s net sales came from Sam's Club division.

Dataset Description :

This is the historical data that covers sales from 2010-02-05 to 2012-11-01, in the file Walmart_Store_sales. Within this file you will find the following fields:

Store - the store number

Date - the week of sales

Weekly_Sales - sales for the given store

Holiday_Flag - whether the week is a special holiday week 1 – Holiday week 0 – Non-holiday week

Temperature - Temperature on the day of sale

Fuel_Price - Cost of fuel in the region

CPI – Prevailing consumer price index

Unemployment - Prevailing unemployment rate

Holiday Events Super Bowl: 12-Feb-10, 11-Feb-11, 10-Feb-12, 8-Feb-13 Labour Day: 10-Sep-10, 9-Sep-11, 7-Sep-12, 6-Sep-13 Thanksgiving: 26-Nov-10, 25-Nov-11, 23-Nov-12, 29-Nov-13 Christmas: 31-Dec-10, 30-Dec-11, 28-Dec-12, 27-Dec-13

Analysis Tasks

Basic Statistics tasks

1) Which store has maximum sales

2) Which store has maximum standard deviation i.e., the sales vary a lot. Also, find out the coefficient of mean to standard deviation

3) Which store/s has good quarterly growth rate in Q3’2012

4) Some holidays have a negative impact on sales. Find out holidays which have higher sales than the mean sales in non-holiday season for all stores together

5) Provide a monthly and semester view of sales in units and give insights

Statistical Model

For Store 1 – Build prediction models to forecast demand

Linear Regression – Utilize variables like date and restructure dates as 1 for 5 Feb 2010 (starting from the earliest date in order). Hypothesize if CPI, unemployment, and fuel price have any impact on sales.

Change dates into days by creating new variable.

Select the model which gives best accuracy.

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!

Historical sales data for 45 Walmart stores located in different regions are available. There are certain events and holidays which impact sales on each day. The business is facing a challenge due to unforeseen demands and runs out of stock some times, due to inappropriate machine learning algorithm. Walmart would like to predict the sales and demand accurately. An ideal ML algorithm will predict demand accurately and ingest factors like economic conditions including CPI, Unemployment Index, etc. The objective is to determine the factors affecting the sales and to analyze the impact of markdowns around holidays on the sales.

Holiday Events Super Bowl: 12-Feb-10, 11-Feb-11, 10-Feb-12, 8-Feb-13 Labour Day: 10-Sep-10, 9-Sep-11, 7-Sep-12, 6-Sep-13 Thanksgiving: 26-Nov-10, 25-Nov-11, 23-Nov-12, 29-Nov-13 Christmas: 31-Dec-10, 30-Dec-11, 28-Dec-12, 27-Dec-13

Analysis Tasks

Basic Statistics tasks 1) Which store has maximum sales

2) Which store has maximum standard deviation i.e., the sales vary a lot. Also, find out the coefficient of mean to standard deviation

3) Which store/s has good quarterly growth rate in Q3’2012

4) Some holidays have a negative impact on sales. Find out holidays which have higher sales than the mean sales in non-holiday season for all stores together

5) Provide a monthly and semester view of sales in units and give insights

Statistical Model For Store 1 – Build prediction models to forecast demand (Linear Regression – Utilize variables like date and restructure dates as 1 for 5 Feb 2010 (starting from the earliest date in order). Hypothesize if CPI, unemployment, and fuel price have any impact on sales.) Change dates into days by creating new variable. Select the model which gives best accuracy.

Introduction

Walmart Statistics: Walmart Inc., established by Sam Walton in 1962, has grown to become the world's largest retailer, renowned for its "Everyday Low Prices" strategy. Headquartered in Bentonville, Arkansas, Walmart operates over 10,500 stores and numerous eCommerce websites across 19 countries, serving approximately 240 million customers each week.

The company's vast product range includes groceries, apparel, electronics, and more, catering to diverse consumer needs. Beyond retail, Walmart is committed to sustainability, aiming for 100% renewable energy by 2030 and zero emissions by 2040. With over 2.1 million associates globally, Walmart remains a pivotal force in retail and employment, continually evolving to meet modern challenges and opportunities.

This article will guide you accordingly, as it includes more information about the global market based on recent data and analyses from different sources.

Get access to the Walmart Basic Product Details Dataset, which includes essential information on a wide range of products available at Walmart.

This comprehensive dataset features product names, categories, descriptions, prices, and more. Ideal for market analysis, competitive research, and e-commerce applications.

Download now to enhance your data-driven strategies and insights with detailed Walmart product information.

The dataset having basic details of a dataset like title, id, image, price and descripton.

Records count: 2.5 million +

From 2020 to 2025, Walmart sales in India were forecast to grow over ** percent. Meanwhile, by 2025, the company's sales in Argentina were estimated to decreased by nearly ** percent.

Context

Hey folks, Two days ago, I decided to work with a Walmart dataset. Like predict something or visualize something by dataset of Walmart. So this dataset I think the same I wanna work with. Guys give support and do some notebooks so that I will know many techniques of visualization and Analyzation.

Content

The Data set contains three csv files : * myCity.csv * walmart.csv * walmartSample.csv

Inspiration

Dataset is inspired or Source is https://data.world/ There is one more dataset on Kaggle which tells about the same but this is the updated version of that dataset.

In the fiscal year ended January 31, 2024, Walmart's global net sales amounted to 642.6 billion U.S. dollars, an increase of approximately six percent in comparison to a year earlier.

Walmart Walmart was founded in 1962 by Sam Walton when he and his brother James “Bud” Walton opened the first Wal-Mart Discount City in Rogers, Arkansas. Since then, Walmart has grown to become the largest publicly-owned retail company in the world. In the United States, the company includes Walmart discount stores, supercenters, neighborhood markets, and Sam’s Club warehouse membership clubs. The company also has many international operations. Walmart is considered a variety store which focuses on low prices featuring apparel as well as hard goods, and has been committed to upholding their basic value of customer service. Beginning in the early 1990s, Walmart went to great lengths to increase their market share. They introduced a full line of groceries into their stores, diversified their market by appealing to certain ethnic groups through bilingual advertisements, and took steps to promote the awareness of environmental issues.As of 2024, Walmart operated 10,616 stores worldwide; with 4,615 of those stores located in the United States alone.

Analysis of ‘Walmart Dataset (Retail)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/rutuspatel/walmart-dataset-retail on 28 January 2022.

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

Dataset Description :

This is the historical data that covers sales from 2010-02-05 to 2012-11-01, in the file Walmart_Store_sales. Within this file you will find the following fields:

Store - the store number

Date - the week of sales

Weekly_Sales - sales for the given store

Holiday_Flag - whether the week is a special holiday week 1 – Holiday week 0 – Non-holiday week

Temperature - Temperature on the day of sale

Fuel_Price - Cost of fuel in the region

CPI – Prevailing consumer price index

Unemployment - Prevailing unemployment rate

Holiday Events Super Bowl: 12-Feb-10, 11-Feb-11, 10-Feb-12, 8-Feb-13 Labour Day: 10-Sep-10, 9-Sep-11, 7-Sep-12, 6-Sep-13 Thanksgiving: 26-Nov-10, 25-Nov-11, 23-Nov-12, 29-Nov-13 Christmas: 31-Dec-10, 30-Dec-11, 28-Dec-12, 27-Dec-13

Analysis Tasks

Basic Statistics tasks

1) Which store has maximum sales

2) Which store has maximum standard deviation i.e., the sales vary a lot. Also, find out the coefficient of mean to standard deviation

3) Which store/s has good quarterly growth rate in Q3’2012

4) Some holidays have a negative impact on sales. Find out holidays which have higher sales than the mean sales in non-holiday season for all stores together

5) Provide a monthly and semester view of sales in units and give insights

Statistical Model

For Store 1 – Build prediction models to forecast demand

Linear Regression – Utilize variables like date and restructure dates as 1 for 5 Feb 2010 (starting from the earliest date in order). Hypothesize if CPI, unemployment, and fuel price have any impact on sales.

Change dates into days by creating new variable.

Select the model which gives best accuracy.

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

The dataset comprises transactional information from previous 5 years from Walmart retail stores, with diverse details such as customer demographics, order specifics, product attributes, and sales logistics. It includes data on the city where purchases were made, customer age, names, and segments, along with any applied discounts and the quantity of products ordered. Each transaction is uniquely identified by an order ID, accompanied by order date, priority, and shipping details like mode, cost, and dates. Product-related information encompasses base margins, categories, containers, names, and sub-categories, enabling insights into profitability, sales, and regional performance. The dataset also provides granular details such as profit margins, unit prices, and ZIP codes, facilitating analysis at multiple levels like customer behavior, product performance, and operational efficiencies within Walmart's retail ecosystem.

The columns in dataset are:

1. City: The city where the purchase was made.
2. Customer Age: Age of the customer making the purchase.
3. Customer Name: Name of the customer.
4. Customer Segment: Segment to which the customer belongs (like retail, wholesale, etc.).
5. Discount: Any discount applied to the purchase.
6. Number of Records: The count of records for each transaction.
7. Order Date: Date when the order was placed.
8. Order ID: Unique identifier for each order.
9. Order Priority: Priority level of the order (like high, medium, low).
10. Order Quantity: Quantity of products ordered.
11. Product Base Margin: Base margin percentage for the product.
12. Product Category: Category to which the product belongs (like electronics, groceries, etc.).
13. Product Container: Container type of the product.
14. Product Name: Name of the product.
15. Product Sub-Category: Sub-category to which the product belongs.
16. Profit: Profit earned from the transaction.
17. Region: Region where the purchase was made.
18. Row ID: Unique identifier for each row.
19. Sales: Total sales amount.
20. Ship Date: Date when the order was shipped.
21. Ship Mode: Mode of shipping (like standard, express, etc.).
22. Shipping Cost: Cost associated with shipping.
23. State: State where the purchase was made.
24. Unit Price: Price per unit of the product.
25. Zip Code: ZIP code of the customer or store location.

Walmart reported $177.4B in Sales Revenues for its fiscal quarter ending in July of 2025. Data for Walmart | WMT - Sales Revenues including historical, tables and charts were last updated by Trading Economics this last August in 2025.

Discover the Walmart Products Free Dataset, featuring 2,000 records in CSV format. This dataset includes detailed information about various Walmart products, such as names, prices, categories, and descriptions.

It’s perfect for data analysis, e-commerce research, and machine learning projects. Download now and kickstart your insights with accurate, real-world data.

Description:

One of the leading retail stores in the US, Walmart, would like to predict the sales and demand accurately. There are certain events and holidays which impact sales on each day. There are sales data available for 45 stores of Walmart. The business is facing a challenge due to unforeseen demands and runs out of stock some times, due to the inappropriate machine learning algorithm. An ideal ML algorithm will predict demand accurately and ingest factors like economic conditions including CPI, Unemployment Index, etc.

Walmart runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of all, which are the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks. Part of the challenge presented by this competition is modeling the effects of markdowns on these holiday weeks in the absence of complete/ideal historical data. Historical sales data for 45 Walmart stores located in different regions are available.

Acknowledgements

The dataset is taken from world.data

Objective:

• Understand the Dataset.
• Time Series Forecasting.
• Anomaly Detection.
• Build Regression models to predict the sales w.r.t single & multiple features.
• Also evaluate the models & compare their respective scores like R2, RMSE, etc.

https://raw.githubusercontent.com/Masterx-AI/Project_Retail_Analysis_with_Walmart/main/Wallmart1.jpg" alt="">

Description:

One of the leading retail stores in the US, Walmart, would like to predict the sales and demand accurately. There are certain events and holidays which impact sales on each day. There are sales data available for 45 stores of Walmart. The business is facing a challenge due to unforeseen demands and runs out of stock some times, due to the inappropriate machine learning algorithm. An ideal ML algorithm will predict demand accurately and ingest factors like economic conditions including CPI, Unemployment Index, etc.

Walmart runs several promotional markdown events throughout the year. These markdowns precede prominent holidays, the four largest of all, which are the Super Bowl, Labour Day, Thanksgiving, and Christmas. The weeks including these holidays are weighted five times higher in the evaluation than non-holiday weeks. Part of the challenge presented by this competition is modeling the effects of markdowns on these holiday weeks in the absence of complete/ideal historical data. Historical sales data for 45 Walmart stores located in different regions are available.

Acknowledgements

The dataset is taken from Kaggle.

Objective:

• Understand the Dataset & cleanup (if required).
• Build Regression models to predict the sales w.r.t single & multiple features.
• Also evaluate the models & compare their respective scores like R2, RMSE, etc.

Walmart Inc. engages in the operation of retail, wholesale, other units, and eCommerce worldwide. The company operates through three segments: Walmart U.S., Walmart International, and Sam's Club. It operates supercenters, supermarkets, hypermarkets, warehouse clubs, cash and carry stores, and discount stores under Walmart and Walmart Neighborhood Market brands; membership-only warehouse clubs; ecommerce websites, such as walmart.com.mx, walmart.ca, flipkart.com, PhonePe and other sites; and mobile commerce applications. The company offers grocery and consumables, including dairy, meat, bakery, deli, produce, dry, chilled or frozen packaged foods, alcoholic and nonalcoholic beverages, floral, snack foods, candy, other grocery items, health and beauty aids, paper goods, laundry and home care, baby care, pet supplies, and other consumable items; fuel, tobacco and other categories. It is also involved in the provision of health and wellness products covering pharmacy, optical and hearing services, and over-the-counter drugs and other medical products; and home and apparel including home improvement, outdoor living, gardening, furniture, apparel, jewelry, tools and power equipment, housewares, toys, seasonal items, mattresses and tire and battery centers. In addition, the company offers consumer electronics and accessories, software, video games, office supplies, appliances, and third-party gift cards. Further, it operates digital payment platforms; and offers financial services and related products, including money transfers, bill payments, money orders, check cashing, prepaid access, co-branded credit cards, installment lending, and earned wage access. Additionally, the company markets lines of merchandise under private brands, including Allswell, Athletic Works, Equate, and Free Assembly. The company was formerly known as Wal-Mart Stores, Inc. and changed its name to Walmart Inc. in February 2018. Walmart Inc. was founded in 1945 and is based in Bentonville, Arkansas.

Walmart products sample dataset having 1000+ records in CSV format. Download monthly dataset for walmart data and it having around 100K+ records.

Get 50% discount for all datasets. Link

Walmart reported $37.34B in Cost of Sales for its fiscal quarter ending in July of 2025. Data for Walmart | WMT - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last August in 2025.

This is a layer provided by the Walmart Emergency Operations Center (EOC) to view store/club status.