The Magic Kingdom theme park at Walt Disney World in Florida, United States, reported over 17.7 million visitors in 2023. Despite welcoming more guests in 2023 than it did in 2022, the amusement park was not able to reach pre-pandemic levels of attendance that year. Theme parks - additional information The most visited theme park worldwide, Walt Disney World Magic Kingdom, located in Florida, reports increasing visitor numbers each year. However, this decreased slightly in 2016, during which attendance at the park was around 20.4 million. Disney's theme parks are not only ranked high in the United States. Disneyland Park in France received 9.93 million visitors in 2022 - almost twice that of its closest European competitor, De Efteling which counted 5.43 million attendees. SeaWorld In recent years, the controversial use of killer whales in shows and performances at SeaWorld parks has been the topic of public debate. In February 2010, a captive killer whale located at the SeaWorld park in Florida killed its trainer during a show. That year, the park reported a decline in visitor numbers. Declining visitor numbers at the SeaWorld theme park in California were also reported during the same year.

This dataset provides a log of recorded incidents that occurred on Walt Disney World and Universal Orlando properties [3]. It has been meticulously created from unstructured PDF files available on the Florida government website [4]. The raw ride names have been cleaned and standardised, and the associated theme park for each incident has been added for clarity [4]. This resource is invaluable for analysts and data scientists looking to understand incident patterns and conduct further analysis [4].

Columns

• Company: Identifies the proprietor of the land where the incident took place, e.g., Disney or Universal [3, 4].
• Incident_date: The specific date when the incident occurred [3, 4].
• Ride_name_dirty: The original, raw name of the ride as it appeared in the source PDF file [3, 4].
• Ride_name: A manually cleaned version of the ride name, refined to remove duplicates and inconsistencies using domain knowledge [3, 4].
• Theme_Park: The specific theme park where the incident happened, determined through domain knowledge [3, 4].
• age_gender: Provides the age and gender of the guest affected by the incident. For instance, "43 yom" signifies a 43-year-old male, and "41 yof" represents a 41-year-old female [3, 4].
• description: A textual account detailing what transpired with the guest during the incident [4, 5].

Distribution

The dataset is provided as a CSV file, detailing individual incidents [2, 3]. While exact total row counts are not specified, the data spans incidents from 29th December 2001 to 7th December 2022 [5]. The distribution of incidents by company shows that 74% occurred at Disney World and 26% at Universal [5]. Notable ride names appearing in the data include Space Mountain and Expedition Everest [5, 6], while Magic Kingdom and Animal Kingdom are frequently listed theme parks [6]. Common incident descriptions involve issues like motion sickness and chest pain [6].

Usage

This dataset is ideal for various data science and analytics applications [4]. It can be utilised for: * Data Analytics: Understanding incident trends and frequencies across different parks and rides [4]. * Natural Language Processing (NLP): Analysing incident descriptions to extract key themes, common causes, or sentiment [4]. * Data Cleaning and Feature Engineering: Serving as a practical case study for cleaning unstructured text data and preparing features for machine learning models [4]. * Health and Safety Analysis: Identifying recurring health-related incidents or safety concerns within theme park environments [4].

Coverage

The dataset focuses on incidents occurring within Walt Disney World and Universal Orlando properties in Florida, USA [3]. The time coverage extends from 29th December 2001 to 7th December 2022 [5]. Demographic scope includes the age and gender of affected guests [3].

License

CC0

Who Can Use It

This dataset is suitable for: * Data Analysts: For exploratory data analysis and trend identification [4]. * Data Scientists: For building predictive models or applying NLP techniques [4]. * Researchers: Studying public safety and incident reporting in theme park environments. * Students: As a practical dataset for learning data cleaning, transformation, and analytical skills [4].

Dataset Name Suggestions

• Orlando Theme Park Incidents Log
• Universal/Disney World Incident Data (2001-2022)
• Florida Theme Park Safety Records
• Amusement Park Incident Tracker

Attributes

Original Data Source: Universal/Disney World Incident Data (2002-2022)

This dataset contains the digitized treatments in Plazi based on the original journal article Disney, R. Henry L., Durska, Ewa (2020): New Species And New Records Of Megaselia Rondani (Insecta: Diptera: Phoridae) From Wigry National Park (Poland). Annales Zoologici 70 (1): 97-108, DOI: 10.3161/00034541ANZ2020.70.1.004

Project goal: Students at MDES (Mount Desert Elementary School) continue their intertidal population study of the invasive green crab and other intertidal dwellers on Somes Sound. This project began in 2014 with data collected in the early fall and early spring each school year. About this project: Students at MDES (Mount Desert Elementary School) continue their intertidal population study of the invasive green crab and other intertidal dwellers on Somes Sound. This project began in 2014 with data collected in the early fall and early spring each school year. This study of green crab populations in the intertidal zone is done at Suminsby Park on Somes Sound, Maine. Students randomly sample 1/4 meter plots and extrapolate to get the meter square data. Data is collected on green crabs, blue mussels, periwinkles, dog whelks, and limpets populations. Data is collected in the upper, mid and low littoral zone.