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Pizza Sales Transaction Data
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About
This synthetic dataset captures a year of pizza sales from a pizza establishment located in the US. While the underlying data is artificial, the ingredients listed for the pizzas are realistic. The dataset features 32 distinct pizzas, categorised into four main types: classic, chicken, supreme, and veggie. The classic pizzas are described as familiar yet uniquely prepared, chicken pizzas highlight chicken as a primary ingredient, supreme pizzas are presented as premium options with select ingredients, and veggie pizzas contain no meat, with some available only in larger sizes.
Columns
- id: A unique identifier for each order, which may consist of one or multiple pizzas placed at a specific date and time.
- date: The order date, formatted as YYYY-MM-DD (ISO 8601).
- time: The order time, expressed in 24-hour format as hh:mm:ss (ISO 8601 extended).
- name: The short name of the pizza, corresponding to a full name and its main ingredients, such as 'classic_dlx' for The Classic Deluxe Pizza.
- size: The size of the pizza, which can be Small (S), Medium (M), Large (L), Extra Large (XL, rare), or Extra Extra Large (XXL, even rarer). Not all pizzas are available in all sizes.
- type: The category of pizza, which includes 'classic', 'chicken', 'supreme', or 'veggie'.
- price: The selling price of the pizza in USD.
Distribution
The dataset is structured as a tibble, containing 49,574 rows and 7 variables. It is typically provided in CSV format. All records are valid, with no mismatched or missing data identified. There are 21,350 unique order IDs. The dates span from 1st January 2015 to 31st December 2015, representing a full year of sales. The 'name' column contains 32 unique pizza varieties, with 'classic_dlx' being the most common, accounting for 5% of entries. Pizza sizes include S, M, L, XL, and XXL, with 'L' being the most frequent at 38%. The four pizza types are 'classic', 'chicken', 'supreme', and 'veggie', with 'classic' being the most frequent, making up 30% of the dataset. Pizza prices range from 9.75 USD to 36 USD, with a mean price of 16.5 USD and a standard deviation of 3.62 USD.
Usage
This dataset is ideal for:
- Conducting data analytics to identify sales trends and popular pizza choices.
- Performing exploratory data analysis to uncover insights into customer ordering patterns.
- Executing statistical analysis for business forecasting or menu optimisation.
- Developing pricing strategies based on pizza type, size, and ingredient costs.
- Analysing peak ordering times and days.
Coverage
The dataset covers pizza sales from a single pizza establishment located somewhere within the United States. The temporal scope spans an entire year, specifically from 1st January 2015 to 31st December 2015. No demographic information about customers is included.
License
CC0: Public Domain
Who Can Use It
- Data Analysts: To explore sales performance, identify best-selling items, and understand seasonal trends.
- Business Owners/Managers: To inform menu development, refine pricing, and optimise inventory management.
- Students: For learning purposes in data analysis, statistics, and business intelligence projects.
- Researchers: Studying consumer preferences in the food service industry or market dynamics.
Dataset Name Suggestions
- Pizza Sales Records 2015
- US Pizza Shop Sales Data
- Annual Pizza Order Log
- Synthetic Pizza Sales Analytics
- Pizza Sales Transaction Data
Attributes
Original Data Source: Pizza Sales Transaction Data
QUALITY