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Also maybe not specific to this PR but how does a user find out what format dataframes (like `fertility_rates` need to be in? Or rather, what they can/can't put in their CSVs. It's difficult to tell by looking through the code. I guess it's in `Pregnancy.metadata`? Maybe we should have a data container class that centralises these operations e.g., have the module contain a data object that has a specification of the columns/types etc. and also handles standardization/parsing - then the module's constructor could pass whatever representation of the data the user provided to a `load` method or similar on that class, and subsequently access the sanitised data via that class too (e.g.,`Pregnancy.fertility_rates.df`)
In the Save phase, can we consider saving common or targeted data in data frames (maybe using polar vs. pandas to for 20x speed and 25% less memory usage advantage) and printing with the results (or exporting to a JSON file)? The next logical question would be: 'what (a) basic, (b) advanced, and/or (c) custom data would users want to see?'
Originally posted by @RomeshA in #235 (comment)
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