Python Projects#
See the Portfolio for detailed project pages with figures and interactive visualizations.
AQI Visualization for Oregon
01/2023 – current
Analyzed satellite data on carbon dioxide levels and air quality index, visualizing spatial distribution and time-series trends using Python.
Mapped CO2 values to counties throughout Oregon and acquired data through data hosting websites.
Utilized Python libraries (NumPy, Pandas, Seaborn, Matplotlib, and Scikit-learn) for data manipulation, visualization, and analysis.
Cleaned and integrated air quality and temperature data from multiple sources to provide a comprehensive view of environmental conditions in Oregon.
Developed custom functions for plotting geospatial data and created interactive visualizations with Jupyter Widget.
Economic Data Visualization
Data Analysis and Visualization of Economic Indicators and Legislation (Python, Pandas, Selenium, Plotly) 02/2023
Acquired economic indicator data through multiple sources by developing a web scraper that utilized Python and Selenium.
Cleaned, processed, and analyzed data using Pandas and other Python libraries.
Visualized data using Plotly to create interactive charts and graphs.
Plan to analyze the impact of specific legislation on economic indicators.
Data Analysis on Tips Dataset
02/2023
Conducted exploratory data analysis on tips dataset to compare tips received by male and female servers.
Utilized Python libraries (NumPy, Pandas, Seaborn, Matplotlib, and Scikit-learn) for data manipulation, visualization, and analysis.
Employed bootstrap resampling techniques to generate confidence intervals for mean tips of male and female servers.
Applied smoothed bootstrap and kernel density estimation methods for accurate representation of tips data distribution.