Analyze A/B Test Results: Should an e-commerce company use their new webpage or keep their old one? I will be working to understand the results of an A/B test run by an e-commerce website. My goal is to work through to help the company understand if they should implement the new page design (March 2, 2019).
Flights: Exploratory and Explanatory Analysis.The dataset I will be analyzing reports flights in the United States, including carriers, arrival and departure delays, and reasons for delays, for 2008 (April 30, 2019).
IMDb Movie Data: What contributes to making a genre popular? This study uses the data set containing information from about 10,000 movies collected from The Movie Database (TMDb). This data set contains information on a list of movies including its popularity, adjusted budget, adjusted revenue, run time, release year, vote average and so on. This study evaluates how each of the factors listed in the previous sentence impacts the popularity of a movie’s genre. Is there a correlation between each of these factors and the genre of the movie? (February 3, 2019).
Homelessness in the U.S.: How has Homelessness Changed in the U.S. from 2010 to 2016? This study reports trends in homelessness by state from 2007 – 2018. Estimates of homeless veterans are included from the beginning of 2011. This dataset was obtained from HUD EXCHANGE (June 25, 2019).
Wrangle and Analyze Data: Twitter Archive, “WeRateDogs”. Using Python and its libraries, I gathered data from a variety of sources and in a variety of formats, assessed its quality and tidiness, then cleaned it(March, 26, 2019).