"When making important decisions, it's ok to trust your instincts but always verify with data"
– David Taieb
The study of time series is a very important field of data science with multiple applications in industry, including the weather, medicine, sales, and, of course, finance. It is a broad and complex subject and covering it in detail would be outside the scope of this book, but we'll try to touch upon a few of the important concepts in this chapter, staying sufficiently high level as not to require any particular specific knowledge from the reader. We also show how Python is particularly well adapted to time series analysis from data manipulation with libraries like pandas (https://pandas.pydata.org) for data analysis and NumPy (http://www.numpy.org) for scientific computation, to visualization with Matplotlib...