GitHub | Portfolio
GitHub | Portfolio
The aim of this project is to examine the safety, reliability, and accessibility of the Transport for London (TfL) network. As one of the world's largest transit systems, TfL bears a great responsibility to connect Londoners and visitors alike to the UK's capital. While safety, reliability, and accessibility can be analysed through a variety of measures, this project presents a view on crime, affordability, transit delays, network coverage, and passenger perceptions and experiences.
Chart 1 is a point map of crime at TfL stations in 2023-2024 as reported by the British Transport Police. This visualisation was created by scraping the British Transport Police's list of UK stations to parse out TfL stations. These were then matched with TfL's available station data.
British Transport Police's list did not have all TfL stations*, so some are left out of the map. Because the list included UK-wide stations and used a certain naming convention for each type, I used Python code to clean and process the data. The TfL station data csv was last updated in 2018, meaning certain stations which opened after this date needed to be added for proper matching. My Jupyter notebook explains in-depth the process I took to correct errors in matching.
*British Transport Police did not have crime info for the following TfL stations: Stratford High Street (DLR), Mile End (LU), Rickmansworth (LU), Stockwell (LU), South Wimbledon (LU). We cannot assume their exclusion is due to station crime being 0, as British Transport Police includes data for other stations with 0 crime.
Chart 2 presents TfL's data on "lost customer hours," capturing the impact of service disruptions on the underground lines.
Note: This visualisation is interactive. Click on the legend to highlight the underground line you are interested in viewing.
Since 2016, lost customer hours increased to a peak in 2019, with the Central line consistently hosting the most hours lost. However, the Covid-19 pandemic made it difficult for TfL to capture this data past 2020, as demand assumptions no longer held up.
TfL's lost customer hours data only show lost customer hours for underground lines – and not all underground lines are included. As TfL works toward recovering passenger demand post-Covid, TfL should begin collecting and publishing this data again, particularly after the opening of new lines and extensions.
This analytic chart presents a comparison of the affordability of the maximum price of single journey fares in major transit cities as of December 2024 (analysing the fare as a percentage of the minimum hourly wage). Maximum prices include the furthest possible journey in the case of distance-based systems (not including special fares such as airport journeys).
Note: Cities directly on the x-axis have no legal minimum wage.
London has quite an unaffordable maximum underground fare, representing more than half of the London hourly minimum wage. In contrast, TfL's bus network – which is not distance-based – is relatively affordable.
The data presented is self-compiled from the various transit agencies, as no one data source provided this information. Due to frequent changes in transit pricing, data may become outdated soon. The conversion of fares to GBP was done using exchange rates of late-December 2024. To compare network sizes, I looked to system length of metros. However, bus networks were more difficult to compare, as some agencies provide square-mileage covered, while others provide data on length of routes. To standardise bus network size, I turned to fleet numbers, though this may not provide an accurate view of how comprehensive the operations are.
This heat map compiles demographic survey data on Londoners' travel behaviours and experiences related to safety, reliability, and accessibility.
Note: This visualisation is interactive. Use the dropdown boxes to explore different parts of the survey data. BAME refers to "Black, Asian, and minority ethnic" communities. LGB refers to "lesbian, gay, and bisexual" people.
Source is TfL's Travel in London: Understanding our diverse communities 2019 report. The report misses some data points for certain groups – represented by greyed-out boxes.
TfL's network is not limited to buses and trains; Santander bikes offer Londoners a cost-effective and more autonomous mode of travel. This choropleth displays the percentage of households within each borough without access to a car or van and is overlayed with a point map of Santander bike dock points.
Note: This visualisation is interactive. Use the checkboxes to see the extent of TfL's network, where bike docks don't reach.
This chart is fed by TfL's REST API, which produces near-real time data of Santander bikes docked throughout London. Bus stop locations are provided by the Department for Transport (DfT). Station locations could not be extracted from DfT, as their dataset included non-London stations and was missing the NaPTAN codes necessary to isolate TfL stations specifically. Therefore, station data was again retrieved from TfL.
Transport for London offers a comprehensive and multi-modal network covering the nation’s capital, though cost and overcrowding pose barriers to higher usage of TfL services. Though the underground fare can be a costly barrier for many, TfL’s expansive bus network can be accessed through a relatively low fare, making passengers appreciate its value for money. Central London – with its high traffic and tourist vulnerability – unsurprisingly hosts the largest number of station crimes with some high-crime stations scattered throughout the outskirts. However, safety on the network itself varies, with groups like women, BAME passengers, and disabled people much more vulnerable to crime and worried about their safety on public transport. Nonetheless, the collection and publication of this data may point to TfL's willingness to constantly improve passenger experiences and can help explain just how safe, reliable, and accessible TfL's services truly are.