Aluwani877/transport_equity_analysis

Data analysis exploring differences in commuting costs, travel time and satisfaction between car owners and people using alternative transportation in South Africa # transport_equity_analysis All rights reserved. This project is available for viewing as part of my portfolio. Please ask for permission before copying or reusing any part of the project. Contact: Aluwani Abigail Sibanda - GitHub: Aluwani877 ## About this project This project looks at the differences between people who own private cars and those who use other forms of transport, such as taxis, buses, trains, and walking in South Africa. The analysis focuses on the three main areas: 1. Monthly transport costs 2. One-way commuting time 3. Transport satisfaction The goal is to better understand how different transport options compare in terms of cost, time, and overall satisfaction. ## About the Data The dataset used in this project is synthetic data, meaning it was generated using a computer program rather than collected directly from survey participants. It was designed to reflect patterns from published South African statistics, including Stats SA's General Household Survey 2024 and National Household Travel Survey 2020. Synthetic data was used because access to the original survey datasets requires registration and permission. The raw dataset also includes some intentionally introduced data-quality issues, such as duplicate records, missing values, inconsistent text formatting, and unrealistic values. These issues were included to demonstrate and practice the data-cleaning process. ## Project Steps 1. Created the data 2. Cleaned the data (removed duplicates, fixed missing values, fixed incorrect text, removed impossible values) 3. Analyzed the data and created graphs comparing the two groups ## Project Structure transport-equity-analysis/ ├── transport_equity_analysis.ipynb # Main notebook with the analysis ├── data/ │ ├── raw/ # Original uncleaned dataset │ └── processed/ # Cleaned data and summaries ├── visuals/ # Generated graphs ├── requirements.txt # Required Python libraries ├── LICENSE # Project usage rights └── README.md # Project documentation ## …