Summary

In this chapter, we set up our working environment with Python 3.7 and used the virtual environment package to manage separate package installations. The pip command is a handy Python package manager that easily downloads and installs Python modules, including Jupyter, Quandl, and pandas. Jupyter is a browser-based interactive computational environment for executing Python code and visualizing data. With a Quandl account, we can easily obtain high-quality time series datasets. These sources of data are contributed by various data publishers. Datasets directly download into a pandas DataFrame object that allows us to perform financial analytics, such as plotting daily percentage returns, histograms, Q-Q plots, correlations, simple moving averages, and exponential moving averages.