Description: This dataset offers a granular, item-level view of daily sales from a diverse group of 50 restaurants, spanning a full year from January 2024 to January 2025. It serves as a comprehensive resource for time-series analysis, demand forecasting, and investigating the various factors that influence customer purchasing habits across different restaurant types, including Cafes, Casual Dining, Fine Dining, Food Stalls, and Kopitiams.

Each row represents the total quantity sold of a specific menu item at a single restaurant on a given day. The dataset is enriched with valuable contextual information, such as weather conditions, promotions, and special events. It also includes detailed financial metrics for each menu item, including the typical ingredient cost, the observed market price, and the actual selling price, making it ideal for analyzing pricing strategies and promotional effectiveness.

Potential Uses: This versatile dataset is well-suited for a variety of analytical projects:

1.**Sales Forecasting**: Develop time-series models (e.g., ARIMA, Prophet) to predict daily sales volumes for specific menu items, individual restaurants, or different restaurant types.

2.**Demand Analysis**: Analyze how external factors like weather conditions and special events impact sales across various item categories and restaurant types.

3.**Promotion Effectiveness**: Evaluate the impact of promotions by comparing the quantity sold and profitability on days with and without promotional activities.

4.**Menu Engineering**: Identify the most and least popular menu items to make data-driven decisions regarding menu optimization, inventory management, and marketing focus. By analyzing item popularity against profitability, restaurants can strategically design their menus to maximize revenue.

5.**Customer Behavior Insights**: Uncover patterns in sales data to understand customer preferences. For instance, determine if certain meal types are more popular on weekends versus weekdays or how pricing impacts choice across different dining segments.

6.**Comparative Analysis**: Compare sales performance, pricing strategies, and menu popularity across different restaurants and restaurant types (e.g., Casual Dining vs. Fine Dining) to identify key drivers of success.

The dataset includes following fields: (Food) Item, Category, Sub Category, Item Name, Price, Cost. The purpose of this dataset is to practice data visualization in tools like power bi and python.

Graph and download economic data for Retail Sales: Restaurants and Other Eating Places (MRTSSM7225USN) from Jan 1992 to Aug 2025 about restaurant, retail trade, sales, retail, and USA.

In 2024, the month with the highest Quick Service Restaurant (QSR) sales in the United States was May, reaching around ** billion U.S. dollars. Meanwhile, the months of August and July ranked second and third, with QSR sales surpassing **** and **** billion U.S. dollars respectively.

In 2024, full service restaurant sales in the United States reached *** billion U.S. dollars, showing growth over the previous year. This figure was forecast by the source to grow to *** billion U.S. dollars in 2025.

Graph and download economic data for Retail Sales: Full Service Restaurants (MRTSSM7221USN) from Jan 1992 to Jan 2020 about restaurant, retail trade, sales, retail, services, and USA.

Dataset

This dataset was created by Casey Morgan

Contents

Dataset Title: Imperial Dragon Restaurant Sales Data Description: This synthetic dataset contains over 1,000 simulated sales transactions for "Imperial Dragon," a fictional Chinese restaurant. It was meticulously generated for academic purposes. The data is designed to be realistic and contains a mix of numeric and categorical fields, perfect for learning and practicing data analysis, pivot tables, dashboard creation, and business intelligence reporting.

The dataset includes typical Point-of-Sale (POS) information such as transaction details, server performance, menu item sales, and calculated financial metrics like profit. It is intentionally "clean" but contains a few minor inconsistencies to simulate real-world data, making it ideal for teaching data cleansing and preparation techniques.

Acknowledgements: This dataset was generated by an AI assistant. It is intended for educational use only.

Purpose: The primary purpose of this dataset is to serve as a practical tool for students to demonstrate their mastery of advanced Excel functions, including:

Usage: This dataset is perfect for:

Students learning data analytics with spreadsheets.

Educators teaching business intelligence, Excel, or data visualization.

Beginners in data analysis looking for a clean, understandable dataset to practice on.

Creating interactive dashboards, sales performance reports, and inventory analyses.

This statistic shows the projected sales of the restaurant industry in the United States in 2017, by state. In that year, restaurant sales in California amounted to approximately ***** billion U.S. dollars.

Restaurant Sales - Historical chart and current data through 2025.

This statistic shows the restaurant industry food and drink sales in the United States from 1970 to 2017. In 2016, food and drink sales of the U.S. restaurant industry amounted to approximately *** billion U.S. dollars.

More statistics and facts on fast food, the U.S. restaurant industry and the pizza (delivery) market.

U.S. restaurant industry - additional information

In 2016, food and drink sales in the United States restaurant industry amounted to *** billion U.S. dollars, up from ***** billion U.S. dollars in the previous year. Restaurants in the United States have created a booming industry that employed more than ** million people nationwide in 2015.

Unsurprisingly, the majority of food and drink sales in the U.S. restaurant industry take place in commercial restaurants. In 2016, full-service restaurant sales amounted to *** billion U.S. dollars and limited-service sales were *** U.S. dollars. The second largest contributor in 2015 was retail, vending, recreation and mobile vendors with sales of ***** billion U.S. dollars. The smallest proportion came from came from bars and taverns.

As of December 2016, things were still looking up for the U.S. restaurant industry: the monthly Restaurant Industry Tracking Survey, conducted by the National Restaurant Association, recorded a performance index score of ***** – any score over 100 indicates a period of expansion. The lowest performance index score between 2011 and 2017, ****, was recorded in August 2011. In November 2016, ** percent of U.S. consumers reported that cheaper restaurants would make them dine out more often.

United States - Retail Sales: Full Service Restaurants was -9.40000 % Chg. from Preceding Period in January of 2020, according to the United States Federal Reserve. Historically, United States - Retail Sales: Full Service Restaurants reached a record high of 16.80000 in December of 2017 and a record low of -13.10000 in January of 2018. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Retail Sales: Full Service Restaurants - last updated from the United States Federal Reserve on December of 2025.

Dataset

This dataset was created by Ashok Adupa

Released under CC0: Public Domain

Contents

Graph and download economic data for Advance Retail Sales: Food Services and Drinking Places (RSFSDP) from Jan 1992 to Sep 2025 about beverages, retail trade, food, sales, retail, services, and USA.

Canada Food Services Sales: Receipts: Full-Service Restaurants data was reported at 3,017,385.000 CAD mn in Feb 2025. This records a decrease from the previous number of 3,151,187.000 CAD mn for Jan 2025. Canada Food Services Sales: Receipts: Full-Service Restaurants data is updated monthly, averaging 1,844,030.500 CAD mn from Jan 1998 (Median) to Feb 2025, with 326 observations. The data reached an all-time high of 3,851,653.000 CAD mn in Aug 2024 and a record low of 664,031.000 CAD mn in Apr 2020. Canada Food Services Sales: Receipts: Full-Service Restaurants data remains active status in CEIC and is reported by Statistics Canada. The data is categorized under Global Database’s Canada – Table CA.H022: Food Services Sales. [COVID-19-IMPACT]

In 2022, sales generated at U.S. independent pizza restaurants amounted to ***** billion U.S. dollars, up from ***** billion U.S. dollars the previous year. Sales generated at chain pizza restaurants in the U.S. reached ***** billion U.S. dollars in the same year, slightly less than the previous year's total sales.

Restaurant sales by county and quarter for some counties in Colorado since 2009 from the Colorado Department of Revenue (DOR).

Comprehensive restaurant performance data including sales, inventory, staff, and customer metrics for business intelligence.

Each record is a date with attached features. The target variable is the amount of sales in the period of 2:00 - 5:59 PM each day.

Dummy Variable features included: - Day of week - Month of Year - Holidays

Historical data features: - Daily Avg (over past N days) - Weekly Avg (over past N days) - MinSales (over past N days) - MaxSales (over past N days)

The full research article can be found here: https://www.mdpi.com/2504-4990/4/1/6

Publicly available code and data are available here: https://github.com/austinschmidt/MLRestaurantSalesForecasting

Germany HRI: FB: Restaurants & Mobile Food Service data was reported at 97.800 2010=100 in Feb 2018. This records a decrease from the previous number of 100.600 2010=100 for Jan 2018. Germany HRI: FB: Restaurants & Mobile Food Service data is updated monthly, averaging 115.950 2010=100 from Jan 1994 (Median) to Feb 2018, with 290 observations. The data reached an all-time high of 153.400 2010=100 in Jul 1995 and a record low of 81.300 2010=100 in Feb 2010. Germany HRI: FB: Restaurants & Mobile Food Service data remains active status in CEIC and is reported by Statistisches Bundesamt. The data is categorized under Global Database’s Germany – Table DE.H019: Hotel and Restaurant Sales Index: 2010=100. Rebased from 2010=100 to 2015=100 Replacement series ID: 403747747