Bikeshare services are being introduced around the worlds' major cities with privately owned companies gaining traction in the last couple years. In this challenge you will have to aid such a business with their expansion strategy.
This dataset contains data about bikes of a bikeshare business operation in and around Manhattan, New York and was obtained from Kaggle
The dataset is provided in a simple .csv file. It is recommended to use the Python packages numpy and pandas to read and manipulate the data. Choice of programming language is not restricted, however Imperial Strategics & Data Science Society projects/workshops are in Python.
The maps are rendered with the aid of Basemap, a package extending matplotlib whose installation instructions can be found here.
The map that is used for visualization was downloaded from the NYC OpenData site.
This challenge is about visualizing and exploring data as opposed to modeling relations an equally important part of data science.
This is not an exhaustive list of tasks, the points are provided in order to guide you:
One visualization is provided in the example code but it might be useful to do exploratory analysis to understand the data better.
This company is looking to expand its fleet by 200 bikes. Suggest where they should install their stations and what size these stations should be(number of bikes). Back up your reasoning with the available data. Support your arguments with visualizations and exploratory analysis.