Project Introduction

Now that we’ve covered all the basics when it comes to data science, it’s time to practice what you’ve learned by applying your knowledge to analyzing real world situations. In this practice project, you’ll analyze stock market data.

The datasets for this project are generated using pandas DataReader, which allows us to read stock information directly from the internet.

This project will focus on Exploratory Data Analysis (EDA) of stock prices. Although the stock price data can be read directly from API, for convenience’s sake, there are .csv files for each company in the course resources for you to use.

Please note that this project is only intended as practice of the data visualization and analysis skills you’ve learned and is in no way meant to provide financial advice.

Domain knowledge

Domain knowledge plays an important role when analyzing data and presenting solid conclusions. Whenever we have some data to analyze, we should try our best to get as much information as possible about the circumstances which generated it. A reliable domain knowledge allows us to present solid conclusions.

Overview of the practice exercise

It’s well known that the world oil market has significant effects on the global economy. In 2009, the world economy and GDP was affected by a chain of incidents that occured between 2007 and 2009, namely a significant change in the price of oil (from about 147 USD to about 32 US dollars a barrel) and global financial crises. These events caused several countries to fall into a recession.

With this context in mind, in this practice exercise you’ll explore how the stock price of some Canadian oil companies and banks varied from 2006 to 2017. You’ll also explore the ups and downs of the United States Oil Fund (USO).

The United States Oil Fund is an exchange-traded fund that attempts to track the price of West Texas Intermediate Light Sweet Crude Oil (WTI). WTI is a grade of crude oil that’s used as a benchmark in oil pricing.

Libraries to import

Let’s import some important libraries first.