Full analysis of store sales from January 2019 to December 2019. Leveraged Python (Pandas & Matplotlib) for reading data, merging data files, data cleaning, data visualization, and analyzing data to find patterns.
Manipulated data to answer questions such as:
What was the best month for sales? How much money was made in that month? Which U.S. city had the highest number of sales? What time should advertisements be displayed to maximize likelihood of customer's buying products? What products are most often sold together? Which product sold the most, and why did you think it did?