Skills used: matplotlib, pandas, numpy, seaborn, webscraping, API data retrieval.
I used libraries like Seaborn and Matplotlib to showcase the relationship between sales, profit, and discount. By analyzing this plot, we can see whether discounts positively or negatively impact the company's profitability, and we can identify any trends or patterns that may exist in the data.
Overall, this project provides valuable insights into the correlation between discounts, sales, and profit, which can help inform the company's sales and pricing strategies in the future.
I used BeautifulSoup and requests to webscrape the 4th table from this wikipedia page that compares operating systems.
This can be a useful way to extract and analyze large amounts of structured data for research projects.
For this project, I used Python to pull data on various cryptocurrencies from CoinMarketCap's public API.
This can be useful for investors and traders looking to make informed decisions about buying, selling, or holding cryptocurrency assets.