Analysis of Uber's Ridership Data for NYC.

Early in 2017, the NYC Taxi and Limousine Commission (TLC) released a dataset about Uber's ridership between September 2014 and August 2015. The data contains features distinct from those in the set previously released and throughly explored by FiveThirtyEight and the Kaggle community. Check this repository to see the contents of the data.

This project aims to:

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 Attempt to predict the demand's growth beyond 2015 [IN PROGRESS] Publication The analysis produced in the Pycharm provide support for the story to be presented in the project's page.

Required Packages The code is written in a Pycharm 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)

lask==1.1.1

gunicorn==19.9.0

Jinja2==2.10.1

MarkupSafe==1.1.1

Werkzeug==0.15.5

numpy>=1.9.2

scipy>=0.15.1

scikit-learn>=0.18

pandas>=0.19