Portfolio
San Francisco Fire Department Assessment
Link to Dashboard on Tableau Public
Link to Presentation on Tableau Public
Link to Non-interactive PDF Version of Presentation (better for smaller screens)
- Evaluated the efficiency of each fire station in the San Francisco Fire Department.
- Created a visually compelling Tableau story and dashboard by assessing response times of each station from original dataset of over 550k records.
Tableau Public
Link to Tableau Public
- Participate in the Makeover Monday community project to create more effective visualizations using public data.
- Other projects of interest also captured.
Identifying Electric Vehicle Charging on Residential Power Grid
Link to Jupyter Notebook in Jupyter NBViewer
- Analyzed and visualized individual and aggregated customer consumption data to identify grid inefficiencies such as charging electric vehicles during periods of peak demand.
- Data was extracted from individual files and loaded into a Pandas DataFrame. Statistics for three criteria were collected to determine how likely each residence had an electric vehicle.
- Goal of identifying and changing behavior through the use of future power company incentives.
- Machine Learning Addendum: Exploring classifying meters through grouping with K-means Clustering and K-nearest Neighbor Classification.
NOAA Tidal Prediction Shift Based on Wind Speed and Direction
Link to Jupyter Notebook in Jupyter NBViewer
- Assessed if wind direction and velocity caused a correlated shift to predicted tide levels in Wells, ME using Pandas and Jupyter Notebook.
- Extracted data using API and by segmenting requests to avoid limitations.
- Plotted data with Seaborn and Matplotlib.
- Determined east-northeast and east wind directions have a positive correlation with respect to predicted height. A 20 mph sustained wind from the ENE or E will cause about a 2 ft increase in sea level.
Housing Search in Massachusetts Supplemented by Foursquare Venue Data
Link to PDF of Report
Link to Jupyter Notebook in Jupyter NBViewer
- Leveraged Redfin and Foursquare APIs to create a method of recommending homes which fit both client house and neighborhood amenity criteria.
- Project returns a list of suitable homes as well as a Folium map of each suitable neighborhood with nearest required amenities shown.