Advanced convert to Pandas for hierarchcial DynamicTables #13
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…e to evaluate query
This was referenced Nov 14, 2019
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Problem "For storage and queries on specific tables it is useful to represent data in a normalized fashion in a hierarchy of tables define by the extension. This avoids repeating data values (which can easily lead to errors and data inconsistencies) and allows us to interact with the data at the appropriate level. For visualization and queries across tables, however, it can be useful to represent the data in a single table (i.e., Pandas DataFrame).
Approach This PR adds a new class
HierarchicalDynamicTableMixinwhich serves a mixin class for DynamicTables that reference other tables in a hierarchical fashion (like is done in this extension). TheHierarchicalDynamicTableMixinclass provides functions to convert all data from the hierarchical DynamicTables into a single hierarchical (or flat) Pandas DataFrame. This allows us to represent (and accordingly query) all data via a single table. This PR also adds an example illustrating the result of this conversion process.