Clarify/simplify data retrieval for Tileset/Mozaic objects
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 30/100
Research direction
Start by tracing the Mozaic, TileSet, and Tile objects and the existing to_df() path shown for country_mozaics_d[FORECAST_START_DATE]['DAU']['IN']. Clarify the desired default access pattern and DataFrame columns before changing model generation or retrieval. Done means the supported top-level data view and its default schema are agreed and available.
Written by the indexing model from the issue text.
Description
When running a model across multiple countries and populations, the current data structure makes it somewhat difficult to access the actual data outputs directly. There are a number of different objects that are generated and attached to the Mozaic, TileSet, and/or Tile objects, sometimes in different formats (such as unlabelled matrices with simulation run outputs).
What would be especially helpful is to have a more general top-level way of viewing all model data in a top-level pandas DataFrame object. There is already an option to get this for a specific sub-model --- if I'm understanding the nomenclature correctly, this would be a single country Mozaic? E.g.:
my_df = country_mozaics_d[FORECAST_START_DATE]['DAU']['IN'].to_df()
I think what would help would be to have one default way of getting this across these objects. Maybe this means changing the default usage for generating models, or maybe it just means incorporating FORECAST_START_DATE, 'DAU', and 'IN' as columns within one overarching DataFrame.
Exactly which columns should be included in this DataFrame by default is worth discussing -- especially if there is concern that it may be overwhelming or confusing to include too many.
- Dominant language
- Python
- Stars
- 3
- Forks
- 3
- PR merge metrics
- No merged PRs in 30d
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