Welcome to the Data Verification project for bus and tram passenger volumes in Dublin and Basel. This study focuses on checking and understanding the accuracy of data about the number of people using buses and trams in Dublin, Ireland, and Basel, Switzerland. The datasets sourced from the Central Statistics Office Ireland (CSO) and Basler Verkehrs-Betriebe (BVB) form the basis for the investigation. Employing techniques from Statistics, Machine Learning, Programming, and Data Preparation and Visualization, this research aims to ensure data accuracy and extract meaningful insights. Knowing how many people use buses and trams is crucial for managing public transportation effectively. Dublin and Basel are different cities with unique transportation challenges. The CSO in Ireland and BVB in Switzerland provide valuable data that can help us understand how people move around in these cities. Walkthrough: • Data Verification: Ensuring the precision of datasets to reflect real-world transit scenarios. • Programming Techniques: Streamlining data processing and model implementation using programming languages. • Data Preparation and Visualization: Cleaning and organizing data for effective analysis, complemented by visualization techniques. • Statistical Analysis: Unearthing patterns and trends in passenger volume data using statistical methods. • Machine Learning Modeling: Developing predictive models, including linear regression and random forest, to enhance accuracy. This research is important for a few reasons. It helps understand how people use public transport in cities. By combining different techniques, it is offered practical insights for improving transportation planning. The findings may help city planners and transport authorities make informed decisions to enhance bus and tram services in Dublin and Basel. This project uses the original datasets as below: Basel Bus/ Trams combined – JSON"https://data.bs.ch/api/explore/v2.1/catalog/datasets/100075/exports/json?lang=en&timezone=Europe%2FLondon" Dublin Luas (Trams) – “TII03.csv” Dublin Bus – “TOA14.csv”

A new grouped dataset has been created to apply Statistics and Machine Learning and models: ”dublin_dataset.csv” ”basel_dataset.csv” The project is divided into 4 phases: Phase I – Data Preparation and Visualization Phase II – Statistics Phase III - Machine Learning