Correlation

Correlation is one of the most common statistics and is directly built into the pandas DataFrame. A correlation is a single number that describes the degree of relationship between two variables, and specifically between two sequences of observations of those variables.

A common example of using a correlation is to determine how closely the prices of two stocks follows each other as time progresses. If the changes move closely, the two stocks have a high correlation, and if there is no discernible pattern they are uncorrelated. This is valuable information that can be used in a number of investment strategies.

The level of correlation of two stocks can also vary slightly with the time frame of the entire dataset, as well as the interval. Fortunately, pandas has powerful capabilities for us to easily change these parameters and rerun correlations. We will look at correlations in several places later in the book.