I created a website to analyze climate metrics over time. This is Plotly Dash application that displays climate data over the past 60 years anywhere in the world. I was inspired to create this project as mean global temperatures have increased nearly 2 degrees Fahrenheit in recent history, but it was hard to connect that to the changes in my local climate. The application highlights the change in mean temperature, snowfall, and days of frost year by year, which allows you to see the climate change in your area.

While going through a period of high inflation in 2022 I started to wonder if there were trends in the inflation of certain good by regions. This could prove useful when looking looking to make major purchases for items like homes and automobiles. I created a script that would allow a user to explore different ways of visualizing the inflationary data of housing, renting a house, and the overall CPI by region.

It was getting late in the winter, spring was just around the corner, but I wasn’t sure if now was the right time to sow some seeds for the garden. I looked for resources online for when to sow different seeds and the Farmer’s Almanac has a plant date for every seed and region imaginable. This let me know that a good time to sow most seeds, ie last frost date, was late April in Northern Virginia.

Let’s say you have $1,000 and you’d like to invest in the stock market but you’d like to balance the risk and rewards between stocks and bonds in your portfolio. This Tableau visualization will allow you to evaluate the potential return on investment with a variable ratio of stock to bonds. The visualization shows the growth of your $1,000 in the 2008 recession or over the past two years (2018-2020) which is characterized as a growth period.

Urban soundscapes are hectic places where the sounds of people and machinery are always a commotion. In order to make sense of the busy noises of a city, we developed a data science algorithm to classify these sounds. The classifier is able to distinguish between 10 different urban sounds. I did this project as part of a collaborative masters project at Virginia Tech with Brannon King. We digested the 10,000+ sound files with the librosa python package and extracted features such as RMS Frequency, Amplitude, and Length.