## Mathematica's information depository

We have considered an elementary example of time series with abstract values; however, in practice, we have to analyze large arrays in order to find patterns and dependencies and to make conclusions from these. In this section, we will review what data has been already collected by Mathematica for our use.

We can take demographic data and use any statistics of the country: GDP, unemployment rate, population, and so on:

Using the
`FinancialData`

function, you can access the values of various financial instruments such as share prices and exchange rates.

For example, you can determine the periods of the highest index volatility of Standards & Poor's 500 using the following functions:

In this case, we also got familiar with the `MovingMap`

function that built the time series with the standard deviations of S&P500 index based on the previous 3-year daily data. As you can see, the greatest jump falls during the 2009 crisis.

Using the `WeatherData`

function,...