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advdatastorageretrievalhawaiiweather

In this exercise I used SQLAlchemy, SQLite, and Flask to retrieve data from different datasets, to query, to analyze, and to make the data readily available as browsable api.

artic-ncov2019

ARTIC nanopore protocol for nCoV2019 novel coronavirus

challenge

citibiketripsny_tableau

In this project I used Python to merge multiple .csv files containing Citi Bike Trip History logs. After a quick exploration of the data, I imported the merged file into Tableau and analyzed the use of Citi bikes in New York City from April 2017 through May 2018. I created a workbook, which includes visualizations and a short summary of my findings.

cityschoolanalysis_pandas

In this exercise I utilized Pandas and Jupyter Notebook to analyze district-wide school's standardized test results

climatewebvisualizationdashboard

In this project I utilized Python libraries (requests, citipy, pandas, numpy, matplotlib.pyplot, datetime), JSON traversals and the OpenWeatherMap API to collect and analyze weather data from over nine hundred randomly selected cities worldwide (each point in the longitude vs. latitude scatterplot above represents a city analyzed). For all weather parameters analyzed (temperature, wind, humidity, and wind speed) temperature was the most strongly correlated to latitude. The webpage created contains source data as well as visualizations showing the correlation (or lack of correlation) between latitude and four different weather parameters.

craigslist-for-sale-alerts

A Slack/Email bot that helps you find for sale items on Craigslist.

earthquakemapping_leaflet

In this project I utilized leaflet.js to create a map to visualize earthquake locations and magnitudes around the world over a period of 24 hours. The data was pulled from the USGS GeoJSON Feed page.

electionandfinancialanalysis_python

In this exercise I utilized Python to analyze financial and election datasets.

excelpivottables

For this exercise I reformatted thousands of records in an Excel spreadsheet, utilized conditional formatting, and pivot tables to analyze a subset of Kickstarter campaigns to evaluate which projects are most likely to succeed.

exploringsakilamysql

In this exercise I loaded the database 'sakila' into MySQL and ran queries using joins and subqueries when necessary to answer questions about the dataset. See SQL code below for each problem.

improving_yelp_ratings_with_ml

Our goal in this group project is to apply NLP and other features from Yelp reviews into a model that outputs a new 5-star-rating, so that there is less discrepancy between reviews and star ratings. In order to make our model more robust, we will also incorporate new user star-ratings based on reviews read (meaning that someone who did not write the review gives a star-rating based on the review text alone) into our model so that it better reflects the review sentiment. We used multiple ML models, including: Naive Bayes, k-NN, K-Means, LSTM, N-Gram, TD-IDF and Linear Regression

javascriptdom_ufotable

In this project I created an HTML web page that contains a table with UFO sightings information that can be dynamically searched through by entering a specific date/time of interest.

newssentimentanalysis

In this exercise I utilized Python libraries - pandas, numpy, matplotlib.pyplot, tweepy, seaborn, datetime, VADER - JSON traversals, and Twitter's API to perform a sentiment analysis on the news mood based on tweets from five different news organizations - BBC, CBS, CNN, Fox News, and New York times.

openweathermapapi

In this exercise I utilized Python libraries (requests, citipy, pandas, numpy, matplotlib.pyplot, datetime), JSON traversals, and the OpenWeatherMap API to answer a fundamental question: "What's the weather like as we approach the equator?" Weather data were collected for over nine hundred randomly selected cities across the world.

pharmaceuticalstudy_matplotlib

In this study, 250 mice were treated through a variety of drug regimes over the course of 45 days. Their physiological responses were then monitored over the course of that time. I utilized matplotlib, numpy and pandas to analyze the physiological response of mice, under four different treatments (Capomulin, Infubinol, Ketapril, and Placebo).

stockmarket_vba

In this exercise I utilized VBA scripting to analyze stock market data.

uscensusdata_d3

In this exercise I used data from the U.S. Census Bureau and the CDC Behavioral Risk Factor Surveillance System Prevalence Data to see if there was a correlation between people that work from home (non-commuters) and the frequency of their physical activity. A scatterplot created using D3.js shows the correlation between these two datasets with each circle representing the population from each state in the United States.

webscrapingmarsinfo

In this project I utilized Jupyter Notebook, BeautifulSoup, Pandas, and Requests/Splinter to scrape information about Mars from several different websites, and utilized MongoDB with Flask templating to create an HTML page with all the information that was scraped.