Terrorism Trends
Data on the rise of national political parties in Europe was cross referenced with data on the occurrence of terrorism in Europe to see if there was a correlation between the two. Co-Coded the python, and research terrorism counts for country by using international terrorism guidelines. Used NYTimes and BBC API to search count of terrorism activities/trends in Europe by keyword. Analyzed vote outcomes by country to determine the percent increase of the populist party. Python, API, Jupyter Notebook, PowerPoint
Beatport Webscraping
The EDM top 100 chart was web-scraped from beatport.com and the data was visualized using line graphs. Wrote the HTML, CSS, Co-Coded python, Flask, and Javascript. We used Python with BeautifulSoup, HTML, CSS, Flask, Plotly.js, Jupyter Notebook, Visual Studio Code, Power Point
Senator Tweet
For this project we grabbed over 290,000 tweets from US senators to see the rate of positive, negative and neutral tweets (using machine learning). We also had the machine learning program predict which political party the senator belongs to based off the tweet alone. Co-Coded python for API, visualization using Tableau Python, Tableau, Jupyter Notebook
