Transposes attributes so that the values in any selected Column Attribute are transposed into their own individual columns. The corresponding selected Row Attribute(s) will also be transposed in accordance with the selected column and its attributes. Aggregation works by grouping the results into desired Group-By column categories. This transformer also allows you to add a suffix to the end of the newly transposed column names in order to maintain clarity and produce distinction between previously defined data columns.

(Example):

The table below shows the inputs offered by the transformer:

The data structure below shows the data before it is transposed.

The next image shows the state of data after it has gone through the transformer using the inputs specified in Image 1. This displays the tranposing + aggregation behavior of the transformer.

Notes

The transformer will not preserve geometry. It only works on tabular data.

New attributes are created dynamically and should be exposed using an AttributeExposer, for example.

All original attributes will still be exposed on the output feature, but will not have a value, except for the Column Attributes.

This transformer has been tested on Python 2.7 and 3.4.