Work for Data Science classes from Federal University of Espirito Santo (UFES)
Explore the docs »
01/22 - 03/22
Report Bug
For this project, I used a range of tools and techniques from the Introduction to Data Science classes and self-research to analyze and classify stocks on the Brazilian stock exchange (Ibovespa). This involved data acquisition using web tools such as urllib and BeautifulSoup, data processing with pandas and scipy, data visualization with matplotlib and seaborn, and classification using sklearn and DecisionTreeClassifier.
My goal was to analyze and classify stocks based on their financial indicators. I divided the stocks by sector and compared the indicators with those of rival stocks to gain insights and make more informed investment decisions. I also used graphical analysis to make the comparison easier.
Overall, this project helped me gain a better understanding of the Brazilian stock exchange and develop practical data science skills. By using a range of tools and techniques, I was able to perform in-depth analysis of stocks based on their financial indicators.
