EXAMPLE - Flatten and Valuestocols Transforms
This example shows how you can break out a column of nested values into separate rows and columns of data.
Source:
The following data covers magazine subscriptions for individual customers. Their subscriptions are stored in an array of values. You are interested in who is subscribing to each magazine.
CustId | Subscriptions |
|---|---|
Anne Aimes | ["Little House and Garden","Sporty Pants","Life on the Range"] |
Barry Barnes | ["Sporty Pants","Investing Smart"] |
Cindy Compton | ["Cakes n Pies","Powerlifting Plus","Running Days"] |
Darryl Diaz | ["Investing Smart","Cakes n Pies"] |
Transformation:
When this data is loaded into the Transformer, you might need to apply a header to it. If it is in CSV format, you might need to apply some replace transformations to clean up the Subscriptions column so it looks like the above.
When the Subscriptions column contains cleanly formatted arrays, the column is re-typed as Array type. You can then apply the following transformation:
Transformation Name | |
|---|---|
Parameter: Column | Subscriptions |
Each CustId/Subscription combination is now written to a separate row. You can use this new data structure to break out instances of magazine subscriptions. Using the following transformation, you can add the corresponding CustId value to the column:
Transformation Name | |
|---|---|
Parameter: Column | Subscriptions |
Parameter: Fill when present | CustId |
Delete the two source columns:
Transformation Name | |
|---|---|
Parameter: Columns | CustId,Subscriptions |
Parameter: Action | Delete selected columns |
Results:
Little_House_and_Garden | Sporty_Pants | Life_on_the_Range | Investing_Smart | Cakes_n_Pies | Powerlifting_Plus | Running_Days |
|---|---|---|---|---|---|---|
Anne Aimes | ||||||
Anne Aimes | ||||||
Anne Aimes | ||||||
Barry Barnes | ||||||
Barry Barnes | ||||||
Cindy Compton | ||||||
Cindy Compton | ||||||
Cindy Compton | ||||||
Darryl Diaz | ||||||
Darry Diaz |