The NYC Taxi and Limousine Commission (TLC) had released a dataset about Uber's ridership. The data contains features distinct from those in the set previously released and throughly explored by FiveThirtyEight. Check the Jupyter Notebook in this repository to see the contents of the data.
This project aims to:
- visualize Uber's ridership growth in NYC during the period
- characterize the demand based on identified patterns in the time series
- estimate the value of the NYC market for Uber, and its revenue growth
- other insights about the usage of the service
This project aims to: Design an algorithm which will tell the fare to be charged for a passenger.
A fare calculator helps a customer in identifying the fare valid for the trip. They are often used by passengers who are new to a city or tourists to get an estimate of travel costs.
The code is written in a Jupyter Notebook with a Python 2.7 kernel, and in addition it requires the following packages:
- Numpy (version: 1.11.2)
- Pandas (version: 0.19.2)
- Matplotlib (version: 1.5.3)
- Seaborn (version: 0.6.0)