UK Train Rides Data Analysis using Python (EDA & Visualization)

I conducted a complete data analysis project on UK train rides data to explore passenger behavior, delays, and operational performance. The project included data cleaning and preprocessing using Python, where I handled missing values, removed duplicates, and prepared the dataset for analysis. I then performed exploratory data analysis (EDA) to identify patterns and trends in the data. Key analysis performed: Analysis of purchase types and customer behavior Identification of the most used payment methods Detection of stations with the highest delays and cancellations Investigation of reasons behind journey delays and cancellations Comparison between delayed and cancelled journeys I used Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn to perform the analysis and create clear visualizations. The goal of this project was to extract meaningful insights from raw data and present them in a clear and understandable way to support better decision-making.