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* Normalize universe data frames
Universe and (generically BaseDataCollection) data frames are not normalize and unpacked into a data frame, instead of just creating data frames with the universe lists within it
* Fix unit tests and algorithms to expecte new universe dataframe format
* Fixes
* Add PandasConverter.DataFrameGenerator class
* Pandas data frame generator class fixes
* Add comments
* Housekeeping
* Add attributes to mark classes and properties for pandas processing
* Improve pandas properties expanding
Allow and handle duplicate names
* Use PandasData generalization for Lean common data types
* Add points time as column when converting base data collections to data frames
* Cleanup and minor changes
* Minor change
* Pandas data to get type members on demand
* Move Pandas helper classes to their own files
* Minor changes
* Add flatten argument to python history api
This allows users to decide whether they want fully expanded dataframes for universe and other collection data types. Else, master behavior is kept
* Adding missing changes to last commit
* Update Pythonnet version to 2.0.40
* Add flattent argument to algorithm's OptionChain api
* Minor changes
* Housekeeping
* Minor changes
* Bug fix skipping data collection data points
* Add comment
* Set correct exchange time to OptionUniverse instances
* Address peer review and cleanup
* Cleanup
* Minor changes
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* Adds ETF(...) to UniverseDefinitions
* Adds ETF constituents universe framework regression algorithm
for C#/Python
* Address review: adds test cases for ticker/Symbol ETF universe additions
* Fixes bug where null Market would result in null dereference exception
* Address review: add missing Index tests
* Address review: don't hardcode market when creating constituent universe
* Uses Brokerage Model's default markets collection to determine
the market for the given security type
* Address review: restore QC500 and DollarVolume.Top(...)
* Restores algorithms related to both helper universe
definition methods
* Address review: remove copy to output directory for python algos
* Add example algorithms for ETF constituent universes using custom RSI alpha model
* Address review: adjust algorithm to use cache + algo RSI & clean up code
* Address review: make ETF Constituent RSI Alpha Model algo a regression test
* Address review: increase trade count and remove single trade logic