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More consistent handling of .csv data when manually duplicating/creating scenarios
Problem statement/pain points: When creating a new scenario via duplicating an existing one manually (not using Python code), there appear to be currently two ways to make a change to input data in a table of the new scenario: 1) change data directly in the corresponding table of “Input Data” under “Select Data”. However, these changes are limited to editing existing rows and columns, i.e. columns/rows can't be added/deleted 2) delete the corresponding “Input Data” table (under “Select Data”), and import a new one using an updated .csv file
#2 is not transparent to the user. Given that it is possible to do a lazy copy of the original scenario data by making changes using #1, it is natural for a user to assume that they can upload a new version of the same .csv file to the data panel, import it in the new scenario and NOT have the original scenario data changed.
- Download mytable.csv data (used in the original scenario) - Make updates to mytable.csv - Rename mytable.csv to mytable1.csv - Upload mytable1.csv in the data panel - “Import to Scenario” from the Data Panel using mytable1.csv - Rename “mytable1” table to “mytable” in “Input Data” of the new scenario - Repeat the process for each table that needs to be changed
Proposed solution - Once data is imported into a scenario, do not keep a reference to the original .csv. - If a table needs to be updated from .csv, require another “Import to Scenario” from the new updated .csv (At the very least there needs to be a warning to the user when they upload a .csv with an existing name to the Data Panel, that a number of existing scenarios are being automatically updated)
Benefits/value - Avoid confusion and possible loss of data due to user misunderstanding of where scenario data is copied by reference to a .csv and where it is a lazy copy (changing values directly in “Input Data” tables)
# of users impacted/ how often impacted - All users who wish to manually change/duplicate/create new scenarios using the Data Panel instead of Python
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