Final Project

What I did

I chose to use the NYC_Bicycle_Counts_2016_Corrected.csv dataset, which gives information on bike traffic across a number of bridges in New York City to answer the following questions:

1. You want to install sensors on the bridges to estimate overall traffic across all the bridges. But you only have enough budget to install sensors on three of the four bridges. Which bridges should you install the sensors on to get the best prediction of overall traffic? (code used to solve in problem1.py)
2. The city administration is cracking down on helmet laws, and wants to deploy police officers on days with high traffic to hand out citations. Can they use the next day's weather forecast to predict the number of bicyclists that day? (code used to solve in problem2.py)
3. Can you use this data to predict whether it is raining based on the number of bicyclists on the bridges? (code used to solve in problem3.1.py and problem3.2.py)

Write up of methods used is in report.pdf

Given prompts (from instructor)

Objectives

There are two possible paths through this project.

1. You may use data set #1, which captures information about bike usage in New York City. See below for the analysis questions we want you to answer.
2. You may use data set #2, which captures information about student behavior and performance in an online course. See below for the analysis questions we want you to answer.

Path 1: Bike traffic

The NYC_Bicycle_Counts_2016_Corrected.csv gives information on bike traffic across a number of bridges in New York City. In this path, the analysis questions we would like you to answer are as follows:

1. You want to install sensors on the bridges to estimate overall traffic across all the bridges. But you only have enough budget to install sensors on three of the four bridges. Which bridges should you install the sensors on to get the best prediction of overall traffic?
2. The city administration is cracking down on helmet laws, and wants to deploy police officers on days with high traffic to hand out citations. Can they use the next day's weather forecast to predict the number of bicyclists that day?
3. Can you use this data to predict whether it is raining based on the number of bicyclists on the bridges?

What to turn in

You must turn in two sets of files, by pushing them to your leader's Github repository:

• report.pdf: A project report, which should consist of:

  • A section with the names of the team members (maximum of two), your Purdue username(s), your GitHub usernames, and the path (1 or 2) you have taken.
  • A section describing the dataset you are working with.
  • A section describing the analyses you chose to use for each analysis question (with a paragraph or two justifying why you chose that analysis and what you expect the analysis to tell you).
  • A section (or more) describing the results of each analysis, and what your answers to the questions are based on your results. Visual aids are helpful here, if necessary to back up your conclusions. Note that it is OK if you do not get "positive" answers from your analysis, but you must explain why that might be.

• All Python .py code files you wrote to complete the analysis steps.

Partners

On this project you may work with one partner (except for Honors contracting students who must work individually). Working with a partner is optional, and working with a partner will not impact how the project is graded.