Hello! 👋 This is just a repo I've put together that I hope will serve as a portfolio for some of the work I've done in the field of data analysis. Listed below is a description of the files included and what their purpose is.
Contains some of the code I wrote for our teams entry into the 2017 Teradata University Data Challenge.
Goal: Analyze Rise Hunger's annual donation dataset to gain insights into any trends, or patterns that would help predict the amount of meals and/or money donated in any single year.
Result: We earned a spot as a runner up and I was awarded a Teradata University Network scholarship and invited to attend the conference in Anaheim, California. More importantly though this was my first real experience collaborating with a group on a coding project. For many of us, myself included, it was our first experience using a programming language to analyze data. Everything previously had been done mainly using Excel, and while it was a very steep learning curve at first it really opened my eyes to the advantages these languages possess over more casual spreadsheet programs. All in all, it was a great experience and I believe everyone in my group was proud of the work we put together and submitted.
Conatins the code, visualizations and report of the final project I completed for a Quantitative Analysis course in my last semster of college.
Goal: Find a dataset, analyze it using any kind of programming language and just write a report about our findings.
Result: Being a realtor allowed me access to our Multiple Listing Service and I thought it would be interesting to conduct some research on a real-world dataset that was so pertininent to the community I was living in and the line of work I was doing. It was definietly a learning experience, and looking back on the code I wrote I definitely had some learning to do but I have to say it was a project I truly worked hard on and was very proud of at the time! The timeline for this project was about a week, so I was able to do some basic exploratory analysis along with visualizations and tried my hand at the best model I could come up with.
Just some various code files I've written using the R programming language. Most exapmles use MASS & ISLR datasets and their results could be replicated for anyone who is interested. Everything in here for the most part is pretty basic data wrangling, visualization and modeling. Some of it was written for academic purposes, other stuff was written just to help myself learn.
Same purpose as the R folder except for the python programming language. As far as data analysis goes, I prefer R and R Studio. However, Im aware that python does possess some advantages and I would really be restricting myself by not utilizing it at all. I'm going to search through my files to find some more code I have written but as of now the only thing in there is a geolocator script I wrote as part of a project for a job. I downloaded some of our Multiple Listing Service data and wanted to visualize the change in sales volume for geographic areas in Starkville, Mississippi over the course of about 5 years. However, the data I was able to obtain did not have longitude and latitude features so I decided to use Googles Map API to return these coordinates given each address in the dataset. Also, this script could join any new data I used and join in with an existing master database if I needed to update it.
I do love Python for other purposes though and have used it with the Django Rest Framework extensively in developing a proprietary web application for our business.