Assessing Whether a Time-Series Follows a Random Walk

I demonstrate how to assess 3 characteristics of a random walk process on a set of time-series data. A random walk meanders, has differences that form a random process, and has a standard deviation larger than the standard deviation of the differences. To check the first characteristic, I merely make a time-series plot and look for a general pattern of "points close together in time that are also close together in value". To check if the differences are random, create a column of differences, and make a time-series plot of those differences, and look for randomness. Finally, to check the standard deviations merely find descriptive stats on the original series and the differences and compare standard deviations.