causalis.data_contracts.panel_data_scm

Module Contents

Classes

PanelDataSCM

Validated long-format panel contract for Synthetic Control estimators.

Data

TimeLike

API

causalis.data_contracts.panel_data_scm.TimeLike

None

class causalis.data_contracts.panel_data_scm.PanelDataSCM(/, **data: Any)

Bases: pydantic.BaseModel

Validated long-format panel contract for Synthetic Control estimators.

Required fields

df : pandas.DataFrame Long-format panel data. y : str Outcome column name in df. unit_col : str Unit identifier column name in df. time_col : str Calendar time column name in df. Preferred input format is pandas.Period values with a regular frequency (for example monthly Period['M']). Datetime/string values are accepted only when a regular frequency can be inferred. treated_time : str Binary treatment-assignment column in df (0/1 or False/True).

Notes

There are no optional contract fields. Extra keyword arguments are rejected. The contract derives treated_unit, treatment_start, and time_freq from the input data. The model stores a validated internal dataframe snapshot used by all contract methods; mutating the public df attribute after construction does not affect validated contract behavior. Outcome y must not contain null/NaN values. Represent missing panel periods by omitting unit-time rows, not by keeping rows with NaN outcome. For fiscal quarter/year semantics, pass time_col explicitly as pandas.Period with the desired fiscal frequency.

Initialization

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

model_config

‘ConfigDict(…)’

df: pandas.DataFrame

‘Field(…)’

y: str

‘Field(…)’

unit_col: str

‘Field(…)’

time_col: str

‘Field(…)’

treated_time: str

‘Field(…)’

property treated_unit: Hashable

property treatment_start: pandas.Period

property time_freq: str

property n_pre_periods: int

property n_post_periods: int

property last_post_period: pandas.Period

donor_pool() → Sequence[Hashable]

df_analysis() → pandas.DataFrame

pre_times() → Sequence[pandas.Period]

post_times() → Sequence[pandas.Period]

analysis_times() → Sequence[pandas.Period]

time_to_index() → dict[pandas.Period, int]

treatment_start_idx() → int

__repr__() → str