This is a realistic and structured pizza sales dataset covering the time span from **2024 to 2025. ** Whether you're a beginner in data science, a student working on a machine learning project, or an experienced analyst looking to test out time series forecasting and dashboard building, this dataset is for you.

📁 What’s Inside? The dataset contains rich details from a pizza business including:

✅ Order Dates & Times ✅ Pizza Names & Categories (Veg, Non-Veg, Classic, Gourmet, etc.) ✅ Sizes (Small, Medium, Large, XL) ✅ Prices ✅ Order Quantities ✅ Customer Preferences & Trends

It is neatly organized in Excel format and easy to use with tools like Python (Pandas), Power BI, Excel, or Tableau.

💡** Why Use This Dataset?** This dataset is ideal for:

📈 Sales Analysis & Reporting 🧠 Machine Learning Models (demand forecasting, recommendations) 📅 Time Series Forecasting 📊 Data Visualization Projects 🍽️ Customer Behavior Analysis 🛒 Market Basket Analysis 📦 Inventory Management Simulations

🧠 Perfect For: Data Science Beginners & Learners BI Developers & Dashboard Designers MBA Students (Marketing, Retail, Operations) Hackathons & Case Study Competitions

pizza, sales data, excel dataset, retail analysis, data visualization, business intelligence, forecasting, time series, customer insights, machine learning, pandas, beginner friendly

Contents

This pizza sales dataset make up 12 relevant features: - order_id: Unique identifier for each order placed by a table - order_details_id: Unique identifier for each pizza placed within each order (pizzas of the same type and size are kept in the same row, and the quantity increases) - pizza_id: Unique key identifier that ties the pizza ordered to its details, like size and price - quantity: Quantity ordered for each pizza of the same type and size - order_date: Date the order was placed (entered into the system prior to cooking & serving) - order_time: Time the order was placed (entered into the system prior to cooking & serving) - unit_price: Price of the pizza in USD - total_price: unit_price * quantity - pizza_size: Size of the pizza (Small, Medium, Large, X Large, or XX Large) - pizza_type: Unique key identifier that ties the pizza ordered to its details, like size and price - pizza_ingredients: ingredients used in the pizza as shown in the menu (they all include Mozzarella Cheese, even if not specified; and they all include Tomato Sauce, unless another sauce is specified) - pizza_name: Name of the pizza as shown in the menu

🍕The Pizza Challenge

For the Maven Pizza Challenge, you’ll be playing the role of a BI Consultant hired by Plato's Pizza, a Greek-inspired pizza place in New Jersey. You've been hired to help the restaurant use data to improve operations, and just received the following note:

Welcome aboard, we're glad you're here to help!

Things are going OK here at Plato's, but there's room for improvement. We've been collecting transactional data for the past year, but really haven't been able to put it to good use. Hoping you can analyze the data and put together a report to help us find opportunities to drive more sales and work more efficiently.

Here are some questions that we'd like to be able to answer:

1. What days and times do we tend to be busiest?
2. How many pizzas are we making during peak periods?
3. What are our best and worst-selling pizzas?
4. What's our average order value?
5. How well are we utilizing our seating capacity? (we have 15 tables and 60 seats)

That's all I can think of for now, but if you have any other ideas I'd love to hear them – you're the expert!

Thanks in advance,

Mario Maven (Manager, Plato's Pizza)

Colllection Methodology

The public dataset is completely available on the Maven Analytics website platform where it stores and consolidates all available datasets for analysis in the Data Playground. The specific individual datasets at hand can be obtained at this link below: https://www.mavenanalytics.io/blog/maven-pizza-challenge

📌I set up the data model to include all the related instances in one single table so obtaining data for analysis is made easier.

My Inspiration

Complete details were also provided about the challenge in the link if you are interested. The purpose of uploading here is to conduct exploratory data analysis about the dataset beforehand with the use of Pandas and data visualization libraries in order to have a comprehensive review of the data and translate my findings and insights in the form of a single page visualization.

Pizza Or Not Pizza

## Overview

Pizza Or Not Pizza is a dataset for classification tasks - it contains Pizza Not_pizza annotations for 1,966 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).

Dataset

This dataset was created by Riya Raizada

Contents

Description

A synthetic dataset that describes pizza sales for a pizza place somewhere in the US. While the contents are artificial, the ingredients used to make the pizzas are far from it. There are 32 different pizzas that fall into 4 different categories: classic (classic pizzas: 'You probably had one like it before, but never like this!'), chicken (pizzas with chicken as a major ingredient: 'Try the Southwest Chicken Pizza! You'll love it!'), supreme (pizzas that try a little harder: 'My Soppressata pizza uses only the finest salami from my personal salumist!'), and, veggie (pizzas without any meats whatsoever: 'My Five Cheese pizza has so many cheeses, I can only offer it in Large Size!').

Variables

A tibble with 49574 rows and 7 variables:

• id: The ID for the order, which consists of one or more pizzas at a give date and time

• date: A character representation of the order date, expressed in the ISO 8601 date format (YYYY-MM-DD)

• time: A character representation of the order time, expressed as a 24-hour time the ISO 8601 extended time format (hh:mm:ss)

• name: The short name for the pizza

• size: The size of the pizza, which can either be S, M, L, XL (rare!), or XXL (even rarer!); most pizzas are available in the S, M, and L sizes but exceptions apply

• type: The category or type of pizza, which can either be classic, chicken, supreme, or veggie

• price: The price of the pizza and the amount that it sold for (in USD)

• Details: Each pizza in the dataset is identified by a short name. The following listings provide the full names of each pizza and their main ingredients.

Classic Pizzas:

• classic_dlx: The Classic Deluxe Pizza (Pepperoni, Mushrooms, Red Onions, Red Peppers, Bacon)

• big_meat: The Big Meat Pizza (Bacon, Pepperoni, Italian Sausage, Chorizo Sausage)

• pepperoni: The Pepperoni Pizza (Mozzarella Cheese, Pepperoni)

• hawaiian: The Hawaiian Pizza (Sliced Ham, Pineapple, Mozzarella Cheese)

• pep_msh_pep: The Pepperoni, Mushroom, and Peppers Pizza (Pepperoni, Mushrooms, and Green Peppers)

• ital_cpcllo: The Italian Capocollo Pizza (Capocollo, Red Peppers, Tomatoes, Goat Cheese, Garlic, Oregano)

• napolitana: The Napolitana Pizza (Tomatoes, Anchovies, Green Olives, Red Onions, Garlic)

• the_greek: The Greek Pizza (Kalamata Olives, Feta Cheese, Tomatoes, Garlic, Beef Chuck Roast, Red Onions)

Chicken Pizzas:

• thai_ckn: The Thai Chicken Pizza (Chicken, Pineapple, Tomatoes, Red Peppers, Thai Sweet Chilli Sauce)

• bbq_ckn: The Barbecue Chicken Pizza (Barbecued Chicken, Red Peppers, Green Peppers, Tomatoes, Red Onions, Barbecue Sauce)

• southw_ckn: The Southwest Chicken Pizza (Chicken, Tomatoes, Red Peppers, Red Onions, Jalapeno Peppers, Corn, Cilantro, Chipotle Sauce)

• cali_ckn: The California Chicken Pizza (Chicken, Artichoke, Spinach, Garlic, Jalapeno Peppers, Fontina Cheese, Gouda Cheese)

• ckn_pesto: The Chicken Pesto Pizza (Chicken, Tomatoes, Red Peppers, Spinach, Garlic, Pesto Sauce)

• ckn_alfredo: The Chicken Alfredo Pizza (Chicken, Red Onions, Red Peppers, Mushrooms, Asiago Cheese, Alfredo Sauce)

Supreme Pizzas:

• brie_carre: The Brie Carre Pizza (Brie Carre Cheese, Prosciutto, Caramelized Onions, Pears, Thyme, Garlic)

• calabrese: The Calabrese Pizza (‘Nduja Salami, Pancetta, Tomatoes, Red Onions, Friggitello Peppers, Garlic)

• soppressata: The Soppressata Pizza (Soppressata Salami, Fontina Cheese, Mozzarella Cheese, Mushrooms, Garlic)

• sicilian: The Sicilian Pizza (Coarse Sicilian Salami, Tomatoes, Green Olives, Luganega Sausage, Onions, Garlic)

• ital_supr: The Italian Supreme Pizza (Calabrese Salami, Capocollo, Tomatoes, Red Onions, Green Olives, Garlic)

• peppr_salami: The Pepper Salami Pizza (Genoa Salami, Capocollo, Pepperoni, Tomatoes, Asiago Cheese, Garlic)

• prsc_argla: The Prosciutto and Arugula Pizza (Prosciutto di San Daniele, Arugula, Mozzarella Cheese)

• spinach_supr: The Spinach Supreme Pizza (Spinach, Red Onions, Pepperoni, Tomatoes, Artichokes, Kalamata Olives, Garlic, Asiago Cheese)

• spicy_ital: The Spicy Italian Pizza (Capocollo, Tomatoes, Goat Cheese, Artichokes, Peperoncini verdi, Garlic)

Vegetable Pizzas

• mexicana: The Mexicana Pizza (Tomatoes, Red Peppers, Jalapeno Peppers, Red Onions, Cilantro, Corn, Chipotle Sauce, Garlic)

• four_cheese: The Four Cheese Pizza (Ricotta Cheese, Gorgonzola Piccante Cheese, Mozzarella Cheese, Parmigiano Reggiano Cheese, Garlic)

• five_cheese: The Five Cheese Pizza (Mozzarella Cheese, Provolone Cheese, Smoked Gouda Cheese, Romano Cheese, Blue Cheese, Garlic)

• spin_pesto: The Spinach Pesto Pizza (Spinach, Artichokes, Tomatoes, Sun-dried Tomatoes, Garlic, Pesto Sauce)

• veggie_veg: The Vegetables + Vegetables Pizza (Mushrooms, Tomatoes, Red Peppers, Green Peppers, Red Onions, Zucchini, Spinach, Garlic)

• green_garden: The Green Garden Pizza (Spinach, Mushroom...

According to the data, for the 12 weeks ending July 14, 2024, Uno was the leading refrigerated pizza and pizza kit brand of the United States, after private labels, with sales amounting to over 340,000 units. Panera Bread followed, with sales reaching close to 289,000 units.

Pizza Detection

## 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).

Pizza Classification

## Overview

Pizza Classification is a dataset for classification tasks - it contains Pizzas annotations for 470 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).

Pizza Ou Não Pizza?

## Overview

Pizza Ou Não Pizza? is a dataset for classification tasks - it contains Pizza annotations for 1,966 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).

Pizza is one of the most popular foods worldwide, with millions of pizzas being sold every day. As a result, understanding the pizza industry and its trends can provide valuable insights for businesses and researchers alike. This dataset on pizza sales offers a comprehensive look at pizza sales trends, including information on sales volume, revenue, and customer preferences. The dataset includes data from various pizza restaurants and chains, both large and small, across different regions and time periods.

Extreme Pizza location dataset — 22 locations in 7 states. 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.

In the United States between 2022 and 2024, frozen pizza was a very popular meal and its consumer share remained stable throughout the years. In 2024, as much as 87 percent of respondents indicated that they had frozen pizza.

Exlines' Best Pizza location dataset — 4 locations in 1 states. 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.

Pizza

## Overview

Pizza is a dataset for object detection tasks - it contains Pizza annotations for 893 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 [MIT license](https://creativecommons.org/licenses/MIT).

Domino's Pizza, Inc. operates as a leading international and domestic purveyor of pizza, managing its extensive operations through three distinct segments: U.S. Stores, International Franchise, and Supply Chain. The company is primarily recognized for its Domino's-branded pizzas, which are distributed via a vast network of both corporate-owned and independently franchised outlets. Beyond its flagship product, the menu also encompasses a variety of other offerings, including oven-baked sandwiches, pasta dishes, boneless and winged chicken, various bread and dip accompaniments, desserts, and soft drink beverages. As of January 2, 2022, the enterprise boasted approximately 18,800 locations spanning 90 global markets. Established in 1960, Domino's Pizza, Inc. is headquartered in Ann Arbor, Michigan.

In the first quarter of 2023, around ** percent of respondents in the United States said that they ordered from quick service pizza restaurants more than once a week. Comparatively, ** percent said that they ordered from pizza QSRs once every couple of weeks and once a month, respectively.

Tastewise US demand signals for cheese pizza and pepperoni pizza over the past year. Cheese pizza: 13.53% social share, down 11.1%, 1.10% menu share. Pepperoni pizza: 10.21% social share, down 2.1%, 1.10% menu share. Pepperoni as a topping: 30.86% share, up 6.1%.

Premium Frozen Pizza Market Outlook

According to our latest research, the global premium frozen pizza market size reached USD 8.7 billion in 2024, reflecting robust consumer demand for high-quality, convenient meal options. The market is projected to register a CAGR of 7.1% from 2025 to 2033, with the market size forecasted to reach USD 16.3 billion by 2033. This growth is underpinned by evolving consumer preferences towards gourmet, healthier, and specialty pizzas, as well as the ongoing expansion of retail and digital distribution channels worldwide.

One of the primary growth factors propelling the premium frozen pizza market is the increasing consumer inclination toward gourmet and artisanal food experiences at home. As urban lifestyles become more fast-paced, consumers are seeking convenient yet high-quality meal solutions that do not compromise on taste or nutritional value. Premium frozen pizzas, with their superior ingredients, innovative flavors, and chef-inspired recipes, address this demand efficiently. The proliferation of social media and food-centric digital content has also played a pivotal role in shaping consumer perceptions, with many individuals aspiring to replicate restaurant-style dining in the comfort of their homes. This shift in consumer behavior is further amplified by the rising disposable incomes and willingness to pay a premium for differentiated and healthier food products, thereby fueling the sustained growth of the premium frozen pizza market.

Another significant driver for the premium frozen pizza market is the increasing prevalence of dietary preferences and restrictions. The demand for gluten-free, vegan, and organic food products has been on a steady rise, compelling manufacturers to innovate and diversify their product offerings. Premium frozen pizzas now cater to a broad spectrum of dietary needs, including plant-based, low-carb, and allergen-free options, making them accessible to a wider consumer base. This trend is particularly pronounced among millennials and Gen Z consumers, who are more health-conscious and environmentally aware. The ability of premium frozen pizza brands to align with these shifting dietary trends through transparent labeling, sustainable sourcing, and clean ingredient lists has significantly contributed to market expansion.

Technological advancements in food processing and preservation have also played a crucial role in the premium frozen pizza marketÂ’s growth trajectory. Enhanced freezing techniques, improved packaging solutions, and advanced logistics have resulted in better product quality, longer shelf life, and reduced food wastage. These innovations ensure that premium frozen pizzas maintain their taste, texture, and nutritional integrity from production to consumption. Furthermore, the integration of digital technologies in supply chain management and inventory tracking has enabled manufacturers and retailers to optimize distribution and minimize stockouts, thereby ensuring product availability across diverse retail formats. The synergy between product innovation and supply chain efficiency continues to be a cornerstone for the marketÂ’s sustained growth.

The popularity of Frozen Margherita Pizza has surged as consumers seek classic flavors with a gourmet twist. Known for its simple yet delicious combination of tomato, mozzarella, and basil, this pizza variant appeals to those who appreciate traditional Italian cuisine. The premium frozen pizza market has capitalized on this trend by offering high-quality Margherita pizzas that boast fresh ingredients and authentic taste profiles. This aligns perfectly with the market's emphasis on artisanal and gourmet experiences, allowing consumers to enjoy a slice of Italy from the comfort of their homes. The convenience of having a restaurant-quality Margherita pizza readily available in the freezer has made it a staple in many households, further driving its demand.

From a regional perspective, North America and Europe dominate the premium frozen pizza market, accounting for a combined market share of over 60% in 2024. These regions have a well-established culture of pizza consumption, high consumer awareness, and a mature retail infrastructure. However, the Asia Pacific region is emerging as a lucrative market, driven by rapid urbanization, rising middle-class incomes, and the west

Global Pizza Cheese Market Analysis size 2021 was recorded $5211.24 Million whereas by the end of 2025 it will reach $6848 Million. According to the author, by 2033 Pizza Cheese market size will become $11825.2. Pizza Cheese market will be growing at a CAGR of 7.067% during 2025 to 2033.

In the 12 weeks ending July 14, 2024, the dollar sales of frozen pizza in the United States amounted to 1.5 billion U.S. dollars. Refrigerated pizza and pizza kits followed, with a sales value of close to 123 million dollars.