A basic Indicator dataclass should deal with individual indicator data. Essentially a wrapper around a Pandas DataFrame which takes care of a few basic operations that we may need to do on each dataset (like rescaling/normalising, getting a few descriptive stats)
A Dimension dataclass which should store data for two+ indicators. It should also take care of things like assessing the similarity/correlation between the loaded indicators, checking for data completeness, dealing with imputations (at dimension level) etc.
An Index dataclass which should store one or more dimensions. It should also take care of things like producing the actual index, imputing data using the full range of indicators, assessing similarities across the whole range of loaded indicators and/or dimensions.
A basic
Indicatordataclass should deal with individual indicator data. Essentially a wrapper around a Pandas DataFrame which takes care of a few basic operations that we may need to do on each dataset (like rescaling/normalising, getting a few descriptive stats)A
Dimensiondataclass which should store data for two+ indicators. It should also take care of things like assessing the similarity/correlation between the loaded indicators, checking for data completeness, dealing with imputations (at dimension level) etc.An
Indexdataclass which should store one or more dimensions. It should also take care of things like producing the actual index, imputing data using the full range of indicators, assessing similarities across the whole range of loaded indicators and/or dimensions.