New York Taxi Trends Analysis

• Tech Stack: Sodapy, Bokeh, plotly, folium, matplotlib, seaborn, HTML, JS, CSS, Pandas
• Webpage: Link
• Github URL: Project Link
• Contributors: Peter Anthony Wright and Carlos Marcos Torrejon

Taxi trips analysis in New York City from 2009 to 2020. Our initial study is centred on Taxi trends throughout the years and the day, but we will utilise the information obtained to make a comparison with new transport providers like Uber and to visually see the impact of the recent Covid-Pandemic on life in big cities. We believe this data-set provides endless opportunities and that we have only scratched the surface with our studies. However some our visualisations show how fascinating the data-set is and how with data we comprehend the world’s dynamics. Our Analysis is guided by a Consistent Visual Platform which we use to direct the path of interest of the User, providing multiple articles as well as summaries and annotations. We also decided to realise many of our graphs interactive using several libraries form in order to deliver a more stimulating experience for the whomever is interested in visualising our work, even if it is not their area of expertise.

Possible Optimisation

• Use Spark for data processing
• Write python code in OOP style instead of in Notebooks. Improve in organization, reutilization and flexibility, and scalability.
• Introduce new contrast analysis for example: pollution, weather, events, economical issues, or other cities/countries.