Select Series

Reduce a dataset to specific series — a variable combined with one set of entity values — and flatten them into named columns.

The Select Series step reduces a dataset down to the individual series you want. A series here is one variable paired with one combination of entity values — “Argentina + Consumer Price Index”, for example.

How series are enumerated

The step scans the dataset and builds the list of available series by crossing every non-entity variable with every distinct combination of entity values. Combinations with no data for that variable are left out, so the picker only shows series that actually exist.

Configuration

Field	Description
Series	The series to keep. Tick them individually, or use Select all / Clear all.
Series name mask	A template for naming the resulting columns.

Each entity column and the variable become filterable columns in the picker, so you can narrow a long list before selecting.

Naming with a mask

The series name mask names every resulting column from a template, using the entity and variable names as placeholders. The default is:

{country} - {Variable}

which produces Argentina - EMBI Global Diversified Subindices. Edit the mask and press Apply to all to rename every selected series at once.

Trim the mask to just {country} when every series is the same variable — the variable name in each column then becomes noise rather than information.

The output is flattened: entity columns disappear and each selected series becomes its own column keyed on date. This is close to what Unstack does, but driven by an explicit selection rather than by pivoting a whole column.

Leaving the selection empty passes the data through untouched, so you can add the step early and fill it in once you can see the available series.

Next steps

Filter Entity

Keep entity structure and filter by value instead.

Create a Chart

Chart the selected series.