Lauren To's Projects
Big Data ETL using AWS RDS and PostgreSQL, and used PySpark to investigate whether Amazon Vine reviews are free of bias.
Neural network / deep learning model.
Using SQLAlchemy ORM queries, Pandas and Matplotlib to analyze a climate database. A Flask API was then created to store the analysis.
Cryptocurrency classification system using dimensionality reduction with PCA & t-SNE and cluster analysis with K-Means
Created an interactive web dashboard where multiple charts update from data that is stored in PostgreSQL. The project is powered by a Python Flask API.
Created a table schema and ERD for employee data using PostgreSQL database. Used SQL to analyze data.
Analyzed 45,000+ films to explore the relationship between book adaptations and movies using Python, Pandas, Matplotlib, Numpy and Scipy. Visualizations: linear regressions, T-tests, ANOVA, Word Clouds (text analysis).
This project uses Python to analyze financial records in PyBank and to analyze votes in PyPoll. Results are exported to a text file.
Analyzed the weather of 500+ cities using the OpenWeatherMap API. Displayed results using pandas, linear regressions via matplotlib, and a heatmap using Google Places API.
This project uses pivot tables and statistical analysis to analyze the success of Kickstarter campaigns.
Personal README
Portfolio site
D3, Leaflet, Mapbox and HTML are used to create an interactive map that plots earthquake data from the United States Geological Survey (USGS).
This project builds a web application that scrapes various websites for data related to the Mission to Mars and displays the information in a single HTML page. MongoDB is used with Flask to deploy results to an HTML page.
Extracted global pharmaceutical spending data to determine how much countries spend on off the shelf pharmaceutical medicines. Data was extracted from CSV and JSON sources, transformed using Python, Pandas and SQL. Data was then loaded into PostgreSQL. SQLAlchemy was used with Flask to deploy results to a pharmaceutical web app.
Using JS & Plotly to design an interactive dashboard that analyzes biodiversity within the human belly button.
Machine learning model that attempts to predict whether a loan from LendingClub will become high risk using Logistic Regression and Random Forest classifiers.
Machine Learning model that predicts the risk of early readmission to the hospital for diabetic patients (within 30 days).
In progress. Analyzing food deserts in Savannah to determine where affordable, fresh food and community gardens are needed.
This project uses Pandas to analyze district-wide standardized test results to show trends in school performance.
Using VBA scripting to analyze stock market data
Analyzing the effects of Covid-19 on NYC's Citi Bike program using stories and dashboards in Tableau.
Analyzed anti-cancer pharmaceutical study results in 249 mice across various drug regiments, using pandas and matplotlib.
This project uses HTML, CSS, Bootstrap and Pandas to create a website displaying climate and weather data and visualizations.