diff_diff.PanelProfile#

class diff_diff.PanelProfile[source]#

Bases: object

Structural facts about a DiD panel.

Returned by profile_panel(). Mirrors the BusinessContext frozen-dataclass pattern. Consume .to_dict() for a JSON-serializable representation and reason against the bundled llms-autonomous.txt guide.

Methods

`__init__`(n_units, n_periods, n_obs, ...[, ...])
`to_dict`()	Return a JSON-serializable dict representation of the profile.

Attributes

`outcome_shape`
`treatment_dose`
`n_units`
`n_periods`
`n_obs`
`is_balanced`
`observation_coverage`
`treatment_type`
`is_staggered`
`n_cohorts`
`cohort_sizes`
`has_never_treated`
`has_always_treated`
`treatment_varies_within_unit`
`first_treatment_period`
`last_treatment_period`
`min_pre_periods`
`min_post_periods`
`outcome_dtype`
`outcome_is_binary`
`outcome_has_zeros`
`outcome_has_negatives`
`outcome_missing_fraction`
`outcome_summary`
`alerts`

__init__(n_units, n_periods, n_obs, is_balanced, observation_coverage, treatment_type, is_staggered, n_cohorts, cohort_sizes, has_never_treated, has_always_treated, treatment_varies_within_unit, first_treatment_period, last_treatment_period, min_pre_periods, min_post_periods, outcome_dtype, outcome_is_binary, outcome_has_zeros, outcome_has_negatives, outcome_missing_fraction, outcome_summary, alerts, outcome_shape=None, treatment_dose=None)#

Parameters:

n_units (int)
n_periods (int)
n_obs (int)
is_balanced (bool)
observation_coverage (float)
treatment_type (str)
is_staggered (bool)
n_cohorts (int)
cohort_sizes (Mapping[Any, int])
has_never_treated (bool)
has_always_treated (bool)
treatment_varies_within_unit (bool)
first_treatment_period (Any | None)
last_treatment_period (Any | None)
min_pre_periods (int | None)
min_post_periods (int | None)
outcome_dtype (str)
outcome_is_binary (bool)
outcome_has_zeros (bool)
outcome_has_negatives (bool)
outcome_missing_fraction (float)
outcome_summary (Mapping[str, float])
alerts (Tuple[Alert, ...])
outcome_shape (OutcomeShape | None)
treatment_dose (TreatmentDoseShape | None)

Return type:

None

classmethod __new__(*args, **kwargs)#