Yuanhong(Claire) Zhang

Yuanhong(Claire) Zhang

Claire’s way: explore the unknonws in data, try(make) a new cuisine, go visit a new place, and always keep smiling.

NYC Taxi Fare Analysis and Prediction

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NYC Taxi Fare Analysis and Prediction

Come see what I discovered in NYC…Taxi Fare dataset!

This project focuses on identifying any trends and patterns in New York City taxi fares. If we are able to discover any insights from the data, we can make recommendations to taxi drivers on how to boost their daily earnings.

Secondly, I built linear regression and random forest regression models to predict taxi fares. We all know that taxi fares is calculated using trip distance (the longer the trip, the higher the taxi fares). What I am interested in is to see how other factors such time in a day, day in a week, pickup and dropoff locations and etc, affect taxi fares. Then we could answer questions like, the best time to work (mid-day, early monring or late night), the best day in a week to work, the best neighborhood to pickup passengers, to NYC taxi drivers.

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