This repository contains the data and R scripts used to analyze Toronto Island ferry ticket sales from 2016 to 2023. The analysis focuses on identifying temporal patterns, including daily, weekly, and seasonal trends. By highlighting peak usage periods and demand fluctuations, this study aims to provide actionable insights for optimizing ferry operations and enhancing visitor experiences during peak times.
The repository is structured as:
data/raw_data: Raw ferry ticket sales data obtained from Open Data Toronto at 15-minute intervals and simulated data.data/analysis_data: Contains the cleaned and validated dataset used for the analysis, focusing on complete yearly data from 2016 to 2023.other: Contains supporting material, such as notes on LLM chat interactions, and sketches.paper: Contains the Quarto document, the reference bibliography file, and the final PDF of the paper. This folder holds the paper that was generated based on the analysis.scripts: Contains R scripts used for data simulation, downloading from Open Data Toronto, cleaning, and performing the analysis.ChatGPT was used to assist in the drafting of the abstract, introduction, and some discussion sections. The full chat history of all LLM interactions is stored in the other/llm/usage.txt file.