causalis.data_contracts.causaldata_instrumental

Module Contents

Classes

CausalDataInstrumental

Container for causal inference datasets with causaldata_instrumental variables.

API

class causalis.data_contracts.causaldata_instrumental.CausalDataInstrumental(/, **data: Any)

Bases: causalis.data_contracts.causaldata.CausalData

Container for causal inference datasets with causaldata_instrumental variables.

Attributes

instrument_name : str Column name representing the causaldata_instrumental variable.

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.

instrument_name: str

‘Field(…)’

classmethod from_df(df: pandas.DataFrame, treatment: str, outcome: str, confounders: Optional[Union[str, List[str]]] = None, user_id: Optional[str] = None, instrument: str = None, **kwargs: Any) → causalis.data_contracts.causaldata_instrumental.CausalDataInstrumental

Friendly constructor for CausalDataInstrumental.

Parameters

df : pd.DataFrame The DataFrame containing the data_contracts. treatment : str Column name representing the treatment variable. outcome : str Column name representing the outcome variable. confounders : Union[str, List[str]], optional Column name(s) representing the confounders/covariates. user_id : str, optional Column name representing the unique identifier for each observation/user. instrument : str, optional Column name representing the causaldata_instrumental variable. **kwargs : Any Additional arguments passed to the Pydantic model constructor.

Returns

CausalDataInstrumental A validated CausalDataInstrumental instance.

property instrument: pandas.Series

instrument column as a Series.

Returns

pd.Series The instrument column.

get_df(columns: Optional[List[str]] = None, include_treatment: bool = True, include_outcome: bool = True, include_confounders: bool = True, include_user_id: bool = False, include_instrument: bool = False) → pandas.DataFrame

Get a DataFrame with specified columns including instrument.

Parameters

columns : List[str], optional Specific column names to include. include_treatment : bool, default True Whether to include the treatment column. include_outcome : bool, default True Whether to include the outcome column. include_confounders : bool, default True Whether to include confounder columns. include_user_id : bool, default False Whether to include the user_id column. include_instrument : bool, default False Whether to include the instrument column.

Returns

pd.DataFrame A copy of the internal DataFrame with selected columns.

Raises

ValueError If any specified columns do not exist.

__repr__() → str