Analysis of reported car accidents across the United States between 2016 and 2019.
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Using Python: Pandas, Matplotlib, and Plotly.
Interactive dashboard to explore Belly Button Biodiversity dataset, which catalogs the microbes that colonize human navels.
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Using HTML; CSS; JavaScript: Plotly, D3.
Visualizing Citi Bike data finds those born in the 1960's were a significant part of the 2019 growth in summer ridership.
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Using Tableau.
Machine learning models to classify exoplanets from the raw dataset.
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Using Python: Sklearn, Joblib, NumPy, Pandas, Matplotlib.
Lessons from San Jose, Cincinnati, and Kansas City on ways governments can be successful in their data efforts.
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Cited Resource at Johns Hopkins University University - GovEx Academy.
Explore relationships between health risks and particular demographics.
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Using HTML; CSS; JavaScript: Plotly, D3.
Mapping of United States Geological Survey APIs.
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Using Javascript: Leaflet, D3; HTML, CSS.
Dynamic dashboard to review the relevance of population & GDP to countries' performances at the Olympics.
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Using Python: Pandas, Flask, SQLite; JavaScript: Leaflet, Highcharts, D3; HTML. Deployed using Heroku.
Machine learning with three different types of models to predict NBA play-off teams based on season statistics.
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Using Python: Sklearn, Joblib, NumPy, Pandas; HTML, CSS, Javascript.