Covid-19 brought cities all around the world to a virtual standstill, and Singapore was no exception. In this article, I use publicly available bus ridership data to try and understand how urban mobility has been affected since the start of the Covid-19 pandemic.

Tableau Prep 2019.3 allows users to run custom Python scripts in its workflows, opening up a wide range of possibilities for a more seamless integration of Tableau and Python. Here, I provide a step-by-step walkthrough on implementing named entity recognition (NER) and sentiment analysis on the BBC News article dataset, using Spacy, TabPy, and Tableau Prep.

I take a look at HDB’s resale flat transactions dataset to explore interesting patterns in our public housing market from 1990 till today. I also dive deeper into the housing bubble which emerged in the mid-1990s, incorporating data from various sources in an effort to better understand what happened.

Lyft recently announced an ambitious plan to double Citi Bike’s service area and triple its number of bicycles in New York City. What challenges will Citi Bike face in its planned expansion? In this post, I look at how Citi Bike has been performing thus far and identify some potential challenges.

By looking at how residents of Astoria and East Harlem use the Citi Bike network alongside the subway system, I find surprising patterns of intermodal commutes that may inform our approach to developing an integrated network of public transportation.

ltaer is an R package that serves as a convenient wrapper for LTA’s numerous transportation APIs. It simplifies the API request process and provides some useful additions which enables a quick analysis of the data obtained from the API.