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This dataset contain detailed information about pizza orders, including specifics about the pizza variants, quantities, pricing, dates, times, and categorization details.
pizza_id: A unique identifier assigned to each distinct pizza variant available for ordering. order_id: A unique identifier for each order made, which links to multiple pizzas. pizza_name_id: An identifier linking to a specific name of the pizza. quantity: The number of units of a specific pizza variant ordered within an order. order_date: The date when the order was placed. order_time: The time when the order was placed. unit_price: The cost of a single unit of the specific pizza variant. total_price: The aggregated cost of all units of a specific pizza variant in an order. pizza_size: Represents the size of the pizza (e.g., small, medium, large). pizza_category: Indicates the category of the pizza, such as vegetarian, non-vegetarian, etc. pizza_ingredients: Provides a list or description of the ingredients used in the pizza. pizza_name: Specifies the name of the specific pizza variant ordered.
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Basic: Retrieve the total number of orders placed. Calculate the total revenue generated from pizza sales. Identify the highest-priced pizza. Identify the most common pizza size ordered. List the top 5 most ordered pizza types along with their quantities.
Intermediate: Join the necessary tables to find the total quantity of each pizza category ordered. Determine the distribution of orders by hour of the day. Join relevant tables to find the category-wise distribution of pizzas. Group the orders by date and calculate the average number of pizzas ordered per day. Determine the top 3 most ordered pizza types based on revenue.
Advanced: Calculate the percentage contribution of each pizza type to total revenue. Analyze the cumulative revenue generated over time. Determine the top 3 most ordered pizza types based on revenue for each pizza category.
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This dataset contains thoroughly cleaned and transformed data of pizza sales, making it ideal for in-depth analysis and visualization. The data includes key information such as sales dates, pizza types, order quantities, prices, and more. It has been carefully structured to facilitate a wide range of analyses, including sales performance, customer preferences, and seasonal trends.
The dataset allows analysts to explore sales patterns over time, identify best-selling pizza types, and evaluate revenue trends across various periods. Additionally, it can be used to gain insights into customer ordering behavior, peak sales times, and regional preferences.
Pizza Types: Various types of pizzas sold, including detailed breakdowns of sizes, ingredients, and categories. Sales Data: Information on the number of pizzas sold, revenue generated, and sales by specific periods (days, months, etc.). Order Information: Data on order quantities and combinations, useful for identifying customer preferences and popular menu items. Price Data: Pricing details to evaluate revenue and profit margins. Use Cases:
Performing time-series analysis to discover trends in pizza sales across different seasons and days of the week. Visualizing the distribution of sales across different pizza types and identifying the most and least popular items. Analyzing sales performance to optimize inventory management, marketing strategies, and pricing models. Comparing sales across multiple outlets or regions to identify top-performing locations and customer segments. Whether you're looking to conduct exploratory data analysis, create interactive visualizations, or apply predictive models, this dataset offers a solid foundation for understanding pizza sales dynamics and enhancing business strategies.
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TwitterCalifornia had the most pizza restaurants in 2019 with 7,281 units. The state with the lowest number of pizza restaurants was Wyoming, with a total of 138 in the same year.
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TwitterSales of frozen pizza in the United States amounted to approximately 7.5 billion U.S. dollars in 2024, up from seven billion U.S. dollars the previous year. Frozen pizza - additional information Pizza is an Italian flatbread made with tomato sauce, cheese and an assortment of toppings such as meats, seafood and vegetables. Frozen pizzas, as well as other convenience foods, have become kitchen staples in many households in the United States. DiGiorno, Red Baron, and Totino's were the leading frozen pizza vendors in the U.S. in 2024, with DiGiorno, a subsidiary of Nestlé, reaching a market share of 16 percent. Private labels were also very popular among U.S. consumers, accounting for an 11 percent share of the frozen pizza market. DiGiorno frozen pizza was first introduced into the U.S. market in 1995. All DiGiorno pizza products are manufactured in the Midwest. The company sources all of its ingredients in the United States and its pizza bakeries employ more than 1,550 people. Apart from DiGiorno, Nestlé owns top frozen pizza brands Tombstone, Jack’s and California Pizza Kitchen.
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Pizza restaurants have suffered revenue declines due to growing competition and some economic volatility over the past five years. Still, demand for pizza restaurants has persisted, despite and somewhat because of the high inflation and economic uncertainty. Pizza is a mainstay in many US households, but other restaurants have begun selling it and various at-home options are available (such as frozen pizza). Further, rising health consciousness among Americans has lowered demand for pizzas. Pizza restaurant revenue has been falling at a CAGR of 1.7% over the past five years and is expected to reach $50.4 billion in 2026, when revenue will rise an estimated 2.0%. Pizza is generally viewed as a fast-casual option, with most consumers ordering it for takeout at home. Moreover, it is considered a good lunch option for time-crunched families, especially when sold by the slice and as a dinner option. As a result, when economic conditions improve or deteriorate, demand for pizza remains steady. The greatest threat to pizza restaurants is consumers' penchant for healthier options. But many owners have combated this by offering health-conscious items like low-fat pizza, salads and others. Other restaurants have opted to boost profit by offering a range of gourmet and non-pizza options, with varying degrees of success. Growth will return over the next five years, with revenue rising at an annualized rate of 0.6% to $52.0 billion. However, saturation will lead to greater internal competition as the number of pizza restaurants rises. Depending on the area of operation, some restaurants will endure a slight slowdown in growth, while others will have to increase marketing campaigns and fight to maintain their customer base. As during previous periods, a rise in health-conscious consumers will continue to threaten potential growth, but restaurants that are able and willing to provide a range of healthier options should fare well.
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## Overview
Pizza Detection is a dataset for object detection tasks - it contains Pizza annotations for 704 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [Public Domain license](https://creativecommons.org/licenses/Public Domain).
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Complete dataset included in the full report. Detailed tables, regional splits, forecasts, and methodologies are available with purchase.
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TwitterThe total assets of Domino’s Pizza decreased from 1.73 billion U.S. dollars in 2024 to 1.71 billion U.S. dollars in 2025. As recently as 2013, the total assets of the company were valued at under 500 million U.S. dollars. Domino’s total assets peaked in 2024.
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Market size, estimate, forecast and CAGR for the Frozen Pizza Market Size, Share & Trends Report 2026-2033.
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TwitterFor the 12 weeks ending July 14, 2024, the sales of frozen pizza in the United States amounted to some 299 million units. Refrigerated pizza and pizza kits sales amounted to approximately 17 million units.
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TwitterAccording to a survey carried out in April 2023, the favorite regional style of pizza among consumers in the United States was New York style, chosen by 27 percent of respondents. Chicago style pizza was the favorite type for 19 percent of respondents.
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This dataset contains transaction-level sales records from a fictional pizza restaurant. Each row represents a single order item and includes information about the order date and time, pizza name, category, size, quantity, unit price, and total price.
The dataset was created as a practice dataset for learning and experimenting with data analysis. It is suitable for exploratory data analysis (EDA), sales reporting, dashboard development, SQL queries, and introductory machine learning projects.
| Column | Description |
|---|---|
| order_id | Unique order identifier |
| order_date | Date of the order |
| order_time | Time of the order |
| day_of_week | Day when the order was placed |
| pizza_name | Name of the pizza |
| category | Pizza category |
| size | Pizza size |
| quantity | Number of pizzas ordered |
| unit_price | Price per pizza |
| total_price | Total amount of the order |
This is a synthetic dataset created for educational and portfolio purposes. It does not contain real customer information.
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Complete dataset included in the full report. Detailed tables, regional splits, forecasts, and methodologies are available with purchase.
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TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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## Overview
Pizza is a dataset for object detection tasks - it contains Pizza annotations for 500 images.
## Getting Started
You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.
## License
This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).
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According to our latest research, the global Sicilian Pizza Restaurant market size reached USD 10.9 billion in 2025, reflecting the growing global appetite for regional Italian cuisine and the enduring, distinctive appeal of Sicilian-style pizza. The market is projected to expand at a robust CAGR of 7.1% from 2026 to 2034, with the market size forecasted to reach USD 20.6 billion by 2034. This consistent growth is driven by a surge in consumer demand for authentic culinary experiences, the proliferation of food delivery platforms, and the increasing popularity of premium and artisanal pizza offerings across both established and emerging markets.
One of the primary growth factors for the Sicilian Pizza Restaurant market is the rising global interest in authentic regional cuisines. As consumers become more adventurous and discerning about their food choices, there is a marked shift toward traditional and artisanal offerings, with Sicilian pizza standing out for its distinctive thick, airy crust and rich, bold flavors. This trend is further propelled by the increasing number of food enthusiasts seeking unique dining experiences, prompting restaurants worldwide to incorporate Sicilian pizza into their menus. The influence of food tourism and social media has amplified this demand, as travelers and local diners share their experiences and recommendations, creating a viral effect that boosts the visibility and desirability of Sicilian pizza restaurants globally in 2025 and beyond. Operators looking to benchmark against adjacent Italian dining segments can reference the growing Neapolitan pizza restaurant sector, which shares many of the same premiumization and authenticity trends.
Another significant growth driver is the rapid expansion of food delivery and takeaway services. The post-pandemic era has seen a fundamental transformation in how consumers access restaurant-quality food, and by 2025 this behavioral shift has become fully entrenched. Sicilian pizza, with its robust structure and ability to retain quality during transport, is particularly well-suited for delivery and takeaway formats. This has encouraged both established restaurant chains and independent operators to invest in digital ordering platforms, optimize their menus for off-premise consumption, and expand their reach beyond traditional dine-in customers. The market has seen a proliferation of virtual brands and ghost kitchens specializing in Sicilian pizza, further accelerating growth and opening new revenue channels. Similarly, the rise of the sourdough pizza restaurant concept illustrates how fermentation-forward, artisanal crust styles are capturing growing consumer segments that overlap with Sicilian pizza enthusiasts.
The market is also benefiting from a wave of innovation in menu offerings and restaurant concepts. Operators are experimenting with contemporary and fusion variations of Sicilian pizza, catering to evolving tastes and dietary preferences, including vegetarian, vegan, and gluten-free options. This diversification is attracting a broader customer base, including younger consumers and health-conscious diners, while premiumization strategies (such as the use of high-quality imported Italian ingredients, artisanal preparation methods, and sophisticated branding) enable restaurants to command higher price points and improve profitability. The rise of experiential dining, featuring open kitchens, pizza-making workshops, and regionally themed interiors, is enhancing customer engagement and long-term loyalty.
In the realm of pizza-making, the Pizza Peel is an essential tool that plays a pivotal role in the preparation and serving of Sicilian pizza. This flat, shovel-like instrument is used to slide pizzas in and out of the oven, ensuring the crust is perfectly cooked while maintaining the integrity of the topping
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Domino's Pizza location dataset: 275 locations in Pennsylvania. Part of CREHQ's multi-unit intelligence platform covering retail, restaurant, financial services, and healthcare brands. Licensed access via enterprise API or dataset purchase. Training on CREHQ data is not permitted.
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TwitterDomino's Pizza was the pizza chain with the most units in the United States in 2024. The company had 7,014 restaurants across the country that year, which was 457 more than Pizza Hut and well over 2,729 more than Little Caesars. Which chain sells the most pizzas in the U.S.? Annual pizza restaurant sales in the United States surpassed 46 billion U.S. dollars, a figure which has steadily increased year.by-year. In terms of sales, Domino’s Pizza was the leading pizza chain in the United States in 2024. Pizza Hut and Little Caesars ranked second and third, respectively. Independent stores hope to break the chains The total number of pizza restaurants in the United States increased to 80,175 in 2022. That same year, there were 44,644 independent pizza restaurants in the U.S., which was roughly five thousand more than the previous year. Meanwhile, the number of U.S.-based pizza chain restaurants in 2022 was 35,531.
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The global pizza market size reached US$ 148.6 Billion in 2023. Looking forward, IMARC Group expects the market to reach US$ 222.5 Billion by 2032, exhibiting a growth rate (CAGR) of 4.45% during 2024-2032. The shifting consumer dietary patterns due to rapid westernization, the introduction of healthier product variants, such as low-calorie, vegan, and gluten-free pizzas, and the rising popularity of online pizza ordering through web portals and mobile apps are some of the major factors propelling the market.
|
Report Attribute
|
Key Statistics
|
|---|---|
|
Base Year
| 2023 |
|
Forecast Years
|
2024-2032
|
|
Historical Years
|
2018-2023
|
| Market Size in 2023 | US$ 148.6 Billion |
| Market Forecast in 2032 | US$ 222.5 Billion |
| Market Growth Rate 2024-2032 | 4.45% |
IMARC Group provides an analysis of the key trends in each segment of the global pizza market report, along with forecasts at the global, regional, and country levels from 2024-2032. Our report has categorized the market based on type, crust type and distribution channel.
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Marco's Pizza location dataset — 8 locations in Louisiana. Part of CREHQ's multi-unit intelligence platform covering retail, restaurant, financial services, and healthcare brands. Licensed access via enterprise API or dataset purchase. Training on CREHQ data is not permitted.
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TwitterApache License, v2.0https://www.apache.org/licenses/LICENSE-2.0
License information was derived automatically
This dataset contain detailed information about pizza orders, including specifics about the pizza variants, quantities, pricing, dates, times, and categorization details.
pizza_id: A unique identifier assigned to each distinct pizza variant available for ordering. order_id: A unique identifier for each order made, which links to multiple pizzas. pizza_name_id: An identifier linking to a specific name of the pizza. quantity: The number of units of a specific pizza variant ordered within an order. order_date: The date when the order was placed. order_time: The time when the order was placed. unit_price: The cost of a single unit of the specific pizza variant. total_price: The aggregated cost of all units of a specific pizza variant in an order. pizza_size: Represents the size of the pizza (e.g., small, medium, large). pizza_category: Indicates the category of the pizza, such as vegetarian, non-vegetarian, etc. pizza_ingredients: Provides a list or description of the ingredients used in the pizza. pizza_name: Specifies the name of the specific pizza variant ordered.