Includes recipes utilizing tabulations, g functions, selections, and performing sorts and various mathematical operations.

**Determining the most highly correlated pairs**

You can calculate the correlation coefficient of two items using`g_cor(G;S;X;Y)`, but sometimes it is necessary to compute the correlation coefficient for multiple pairs and determine which items are the most highly correlated.**Parameterizing column names**

Sometimes it is necessary to dynamically determine column names for computed columns based on the information contained in a variable.**Dividing data into buckets**

Dividing data into buckets can make it easier to perform analyses and gather information about the data, especially if the data set is large. If the location of the items are not important, you can randomly divide the data into a predefined number of equal groups.**Calculating unique counts with different criteria**

Calculating the unique count of a specific column can be accomplished with a tabulation. However, calculating that unique count for two different situations requires more manipulation.**Creating pairs without duplication**

You can create a list of every possible combination of two lists of items by performing a link and expand. However, with this method, you will get duplicate pairs, where the items are simply listed in a different order (i.e., reciprocals). Using computed columns and g_functions, you can create a list of pairs without any reciprocals.