How many seasons does a tropical country like Singapore have? Is global warming real, and is rainfall getting heavier? To answer these questions, I will show how we could use Requests and Pandas to build a data pipeline that extracts Singapore weather station data for a user-defined time period and explore the weather trends and seasons over the past few years. Most of the world experience the four seasons, but how many seasons does a tropical country like Singapore have? Is rainfall getting heavier? We can get such insights from publicly-available weather data; however, we need to write scripts to make API requests to retrieve the data. In this talk, I will be sharing about my approach in building a data pipeline that extracts Singapore weather station data from Data.gov.sg APIs for a user-defined time period using pandas. Based on the extracted data, I will also be using a data-driven approach to gain a better understanding on the weather trends and seasons over the past few years, and explore different approaches in forecasting future weather trends based on these insights.