Combining signals

This section contains functions which combine multiple signals into a new signal. They can be used when you have different signals which work for different entities, and you want to create a single signal which works for all the relevant entities.

signal.combine_first(other, extend_only=False)

Update null elements with value from the same location in other. This is a wrapper around the pandas combine_first() method.

Parameters:

  • other – Signal to use for filling null values.

  • extend_only – If True, null values are only replaced after the last non-null value.

Example:

Combine FactSet actual sales with FactSet consensus sales (note though that fs_metric() achieves the same thing and is recommended):

fs_actual('sales').combine_first(fs_consensus('sales'))
fallback(signals, pre_extend, post_extend)

For each entity, use the first signal which has values.

The signals given to the fallback function are evaluated in order, and for each entity, the first signal that has a non-NaN value for the entity is selected.

To determine if a signal has values for an entity, the evaluation period is extended in both directions.

Parameters:

  • signals (List[Signal]) – A list of signals. The signals are evaluated in order, and for each entity, the first signal that has a non-NaN value for the entity is selected.

  • pre_extend (int) – Number of days to pre-extend the evaluation period with, to determine if an entity has a value for a signal. Default value is 10*365.

  • post_extend (int) – Number of days to post-extend the evaluation period with, to determine if an entity has a value for a signal. Default value is 10*365.

Example:

To retrieve FactSet Estimates sales, and fallback to FactSet Fundamentals if the company is not covered by the former:

fallback([fs_actual('sales'), fs_fundamental('sales')])
entity_type_switch(mapping)

Evaluate different sub-signals based on the type of the evaluation entities.

This can be useful when you have different signals for different entity types, but you need to express them as a single signal, such as in dashboards with multiple entity types.

Parameters:

mapping (Mapping[str,Signal]) – A map of entity type to signal. The entity type should be specified with the format namespace.entity_type unless the entity type is in the global namespace, in which case only entity_type is needed.

Example:

Signal that when evaluated for a company returns FactSet company sales and when evaluated for a brand returns brand_sales (assuming this signal exists):

entity_type_switch({'company': fs_actual('sales'), 'ns.brand': brand_sales})