ENTITY Data Science Virtual Academy Final Project

This repository contains the files relating to my final project for the ENTITY Data Science Virtual Academy.

Evaluation Question

Can we predict hourly bike sharing rental counts, given weather, season, and date information?

Final Project Files

• Final Presentation Slides
• Final Python Jupyter Notebook - main work product
• Final R Jupyter Notebook - supplementary analyses only
• Final Tableau Vizzes

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What follows below are the sign-post products created on the way to the final presentation above. It is not necessary to delve into them unless desired. The files above contain the entire final work product.

Week 1 Deliverables

During Week 1 of the project, we were asked to complete several pre-planning documents, including choosing our dataset, identifying the variables, and writing a project proposal. Below are links to each of those expected deliverables.

1. Week 1 - Getting to Know Your Team (DOCX)
2. Week 1 - Submit Your Dataset (CSV) - This dataset was assigned to our group to all complete individual projects using the same set. The data will be used to predict hourly bike rentals based on seasonal and weather conditions.
3. Week 1 - Analysis Planning Worksheet (DOCX)
4. Week 1 - Project Proposal (DOCX)

Week 2 Deliverables

During Week 2 of the project, we started with our initial coding to perform Data Wrangling as we could foresee for our intended analyses. We were also asked to complete a Progress Update document.

1. Week 2 - Data Wrangling (Python Jupyter Notebook) - This version of the code is a copy of my living code document that is intended to mark the progress in time. For the most up-to-date version of code as my work progresses, see below.
2. Week 2 - Progress Update (DOCX) - This document seeks to answer the required question prompts for each week of the project progression.

Week 3 Deliverables

During Week 3 of the project, we were assigned to complete initial data exploration. I used Tableau to create a number of visualizations that show some aspects of bike rentals over different factors. As this is a preliminary step, a full explanation and presentation of the data has not yet been completed. Additional visualizations may be created in later phases as the project coalesces towards completion.

1. Week 3 - Data Exploration (Tableau)
2. Week 3 - Progress Update (DOCX)

Week 4 Deliverables

Week 4 was all about Data Analysis. Although I completed initial analyses to the best of my ability, I have reached out to Devin Moya for support in "putting all the pieces together" toward a complete Data Science project.

1. Week 4 - Data Analysis (R)
2. Week 4 - Data Analysis (Python)
3. Week 4 - Progress Update (DOCX)

Week 5 Deliverables

Week 5 was the week to assemble your presentation - in other words, make your data visual! Unfortnately, with the focus on creating a machine learning model, we don't have a whole lot of exciting work to show from the analysis. However, I did include several interesting visuals from the Data Exploration side.

1. Week 5 - Data Visualization (PPTX)
2. Week 5 - Progress Update (DOCX)

Week 6 Deliverables

The main goal of Week 6 was to actually present my final project. I presented my work to Jilian Dickson at 2:30pm ET on Sunday, September 4, 2022. Once I have the recording of my presentation, I will update it here.

1. Week 6 - Final Presentation Slides (PPTX)
2. Week 6 - Progress Update (DOCX)