"The project aimed to compare yellow taxis and Citi Bikes in New York City, focusing on how weather conditions influenced transportation choices throughout 2019."
"Finding a suitable weather dataset was challenging, but ultimately a dataset with hourly temperature, precipitation, wind speed, cloud cover, and wind direction was secured."
"The cleaning process involved converting temperatures from Celsius to Fahrenheit, adding derived columns, and validating ranges to ensure data accuracy."
The project focused on analyzing transportation methods in New York City, specifically yellow taxis and Citi Bikes, while incorporating weather data for 2019. Initially, the team considered including green taxis but opted out due to operational limitations. Finding a comprehensive weather dataset proved challenging, but a suitable one was eventually located, covering hourly weather details. The dataset was cleaned and transformed using Scala, which was a new programming language for the team member. This analysis aimed to understand how weather influences transportation choices in the city.
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