olympics

Introduction

This is the historical olympic data analysis project for MSDS 7331. The dataset was taken from kaggle. The dataset consists of 271k rows and 15 columns full of olympic data which span the years 1896 to 2016.

Windows Anaconda Setup

The environment.yml file holds all the dependencies for this particular project. In order to have the project working on your machine you will need to perform the following setup of anaconda as conda is used to manage the python environment for this project.

If Anaconda is not setup on your machine you can follow the directions here

Mac Anaconda setup

If you are using a mac the following directions for set up can be found here.

Starting the project for first time

Creating the olympics environment

# cd into the olympics directory
cd <your_local_path>/olympics/
#in the terminal run

conda env create -f environment.yml

This creates the olympic conda environment with all the dependencies listed in environment.yml. You can now switch to the environment by running the following..

source activate olympics

Making updates to environment

If you add a new dependency to the project make sure you update the environment.yml file so in order to have those new updates reflect locally for you.

conda env update -f environment.yml

This olympics environment includes jupyter notebook as well as many of the other packages we need in order to run the analysis on this project.

Using The Application

Our group has developed a proof of concept which includes an Olympic sport recommendation engine. Our system takes in a few factors from the user and gives the user an olympic sport that might be best suitable for them. Our models prediction is based on over 200 years worth of olympic athletic data. See which sport best fits you!

Olympic Sport Recommender POC

Group Members

| Brian Coari | Stephen Merritt | Cory Thigpen | Quentin Thomas |