Validate scheme

validate

Validation utilities for weighting schemes.

This module provides functions to validate survey dataframes against weighting schemes before applying weights. Validation checks include column existence, missing values, and category mismatches between the data and scheme definitions.

validate_scheme_dict(df, scheme, raise_error=True)

Validate a dataframe against a scheme dictionary.

Checks if Data matches the Scheme (Columns, Categories, NaNs).

Parameters:

Name	Type	Description	Default
df	DataFrame	The survey dataframe to check	required
scheme	SchemeDict	The dictionary defining the weighting scheme	required
raise_error	bool	If True, raises a ValueError on the first Critical issue found. If False, returns a DataFrame report of all issues	True

Returns:

Type	Description
DataFrame or None	DataFrame report of all issues if raise_error=False, None otherwise

validate_scheme(df, scheme, raise_error=True)

Validate a dataframe against a Rim scheme object.

Checks for Columns, NaNs, and Category mismatches.

Parameters:

Name	Type	Description	Default
df	DataFrame	The survey dataframe to check	required
scheme	Rim	The Rim scheme object defining the weighting scheme	required
raise_error	bool	If True, raises a ValueError on the first Critical issue found. If False, returns a DataFrame report of all issues	True

Returns:

Type	Description
DataFrame or None	DataFrame report of all issues if raise_error=False, None otherwise