Portfolio
Curiosity meets clarity
Assorted data musings from a curious person. Exploring housing, behavior, and systems through code, charts, and context.
Python, Pandas, Seaborn
A dive into Zillow's rental affordability data. Is Seattle really cheaper than SF? What happened to Oakland? And what's changed pre-and post-pandemic, especially when you account for inflation?
Python, Pandas, Plotly Express
When trying to explain to my parents just how bad the air quality got during the fires around the Bay Area in 2020, I formed a data visualization in my mind that I wanted to see realized in real life.
Tableau
Taking the data extract from part 1, I built a story in Tableau Public to explore how much worse the air quality in my hometown of Oakland, and other major West Coast Cities, has been getting.
Tableau
Remember back when Bay Wheels was Ford GoBike? (OK, it wasn't that long ago.) For my first ever exploratory data analysis I dug into publicly available Ford GoBike data, with a focus on attempting to determine the tourist/local breakdown as well as ridership by age cohorts.
Salesforce, Python, Pandas, Pandaforce
Tracking a client's MQLs (marketing qualified leads) across the lifecycle from start to end. I've seen many expensive custom Salesforce solutions but found that a Python script delivers 80% of the value in 10% of the time.
Salesforce, Python, Pandas, Pandaforce
A Python script for a client that I open sourced. First and last touch attribution plus all campaign memberships across leads, contacts, and opportunities, without expensive custom architecture or 3rd party tools. Also includes some conversion rate reporting and a few other custom KPIs.
BigQuery, Python, Pandas, Matplotlib
I decided to explore the ACS data to see what I could find about how Oakland is changing, and whether its findings matched my predictions.
