`quarterly_average` – Aggregate to quarterly via mean of the three monthly observations.#

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Operational op under axis monthly_to_quarterly_rule, sub-layer l2_a, layer l2. Standalone callable: mf.functions.freq_align_monthly_to_quarterly_clean.

Function signature#

mf.functions.freq_align_monthly_to_quarterly_clean(
    panel: pd.DataFrame,
) -> pd.DataFrame

Parameters#

name	type	default	constraint	description
`panel`	`pd.DataFrame`	—	—	Input panel. Each column is a variable; rows are time periods. Series is promoted to a single-column DataFrame internally.

Returns#

pd.DataFrame — scalar result.

Behavior#

Standard NIPA aggregation for stocks / averages.

Configures the monthly_to_quarterly_rule axis on l2_a (layer l2); the quarterly_average value is materialised in the recipe’s fixed_axes block under that sub-layer.

When to use

Default. Stock variables (interest rates, prices, employment levels).

In recipe context#

Set params.monthly_to_quarterly_rule = "quarterly_average" in the relevant layer to activate this op within a recipe:

# Layer L2 recipe fragment
params:
  monthly_to_quarterly_rule: quarterly_average

References#

macroforecast design Part 2, L2: ‘preprocessing is the only layer with a strict A→B→C→D→E execution order; every cell follows the same pipeline.’

quarterly_average – Aggregate to quarterly via mean of the three monthly observations.#