src.postprocess package

Submodules

src.postprocess.CDC_ITF module

src.postprocess.CDC_ITF.postprocess(data: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5c803c3be0>)

Apply dataset-level transformations to CDC_ITF data.

Parameters:data (pd.DataFrame) – Input CDC_ITF data. Returns:CDC_ITF data with transformations appied. Return type:pd.DataFrame

src.postprocess.CDC_ITF.remove_id_duplicates(data: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5c803c37f0>)

Remove duplicate records with identical measure_stage values

Removes duplicate records with identical values in ref_cols.

Parameters:data (pd.DataFrame) – Input CDC_ITF data. Returns:Data with duplicates removed. Return type:pd.DataFrame

src.postprocess.JH_HIT module

src.postprocess.JH_HIT.combine_measures(data: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5c803de6a0>, who_code: str, id_stub: str)

Combine groups of records with an arbitrary who_code.

Example:

Groups are defined by records with identical numeric prop_id values:

333_school_secondary, 333_school_nursery, 333_school_primary etc. -> 333_school_closure

or

234_border_in, 234_border_out -> 234_border_closure

Parameters:

• data (pd.DataFrame) – Input data.
• who_code (str) – who_code to combine.
• id_stub (str) – Stub name to add to combined ID numbers.

Returns:

Data with combination applied.

Return type:

pd.DataFrame

src.postprocess.JH_HIT.postprocess(data: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5c803de630>)

Apply dataset-level transformations to JH_HIT data.

Parameters:data (pd.DataFrame) – Input JH_HIT data. Returns:JH_HIT data with transformations appied. Return type:pd.DataFrame

src.postprocess.main module

src.postprocess.main.postprocess(data: <sphinx.ext.autodoc.importer._MockObject object at 0x7f5c803ebef0>)

Unify manual changes applied to specific datasets.

Parameters:data (pd.DataFrame) – Input dataset. Returns:Dataset with postprocessing changes applied. Return type:pd.DataFrame

Module contents