Analyzing Historical Stock and Revenue Data and Building Dashboard with Python
Project Overview In this project, I will assume the role of a Data Scientist / Data Analyst working for a new startup investment firm that helps customers invest their money in stocks. My job is to extract financial data like historical share price and quarterly revenue reportings from various sources using Python Libraries and Webscraping on popular stocks. After collecting this data I will visualize it in a dashboard to identify patterns or trends. The stocks I will work with are Tesla and GameStop.
Dashboard Analytics Displayed A dashboard often provides a view of key performance indicators in a clear way. Analyzing a data set and extracting key performance indicators will be practiced. Prompts will be used to support learning in accessing and displaying data in dashboards. Learning how to display key performance indicators on a dashboard will be included in this project. I will be using Plotly in this project for data visualization and is not a requirement to take this project.
Watson Studio For this project I will use Skills Network Labs and Watson Studio. Skills Network Labs is a sandbox environment for learning and completing labs in courses. Whereas Watson Studio, a component of IBM Cloud Pak for Data, is a suite of tools and a collaborative environment for data scientists, data analysts, AI and machine learning engineers and domain experts to develop and deploy your projects.
Question 1 - Extracting Tesla Stock Data Using yfinance. Question 2 - Extracting Tesla Revenue Data Using Webscraping. Question 3 - Extracting GameStop Stock Data Using yfinance. Question 4 - Extracting GameStop Revenue Data Using Webscraping. Question 5 - Tesla Stock and Revenue Dashboard. Question 6 - GameStop Stock and Revenue Dashboard.