353 create imputation markers

[Jday7879]

Summary

Added function which creates a logical column checking if the target variable is a return, or can be imputed by forward or backwards imputation or imputed by construction
Updated original unit tests ready to expand to create a single test dataset, but this should be added to the backlog and looked at further down the line

Checklists

This pull request meets the following requirements:

• installable with all dependencies recorded
• runs without error
• follows PEP8 and project specific conventions
• appropriate use of comments, for example no descriptive comments
• functions documented using Numpy style docstings
• assumptions and decisions log considered and updated if appropriate
• unit tests have been updated to cover essential functionality for a reasonable range of inputs and conditions
• other forms of testing such as end-to-end and user-interface testing have been considered and updated as required
• tests suite passes (locally as a minimum)
• peer reviewed with review recorded

If you feel some of these conditions do not apply for this pull request, please
add a comment to explain why.

[AntonZogk]

@Jday7879 lovely work for a complicated task love what you did with ffil and bffill smart solution :)

I have left some comments, happy to chat in more detail about them

[AntonZogk]

I updated the function .

Instead of calling flag_matched_pair_merge within the function to create the predictive_auxiliary, it is defined as function argument. Hence flag_matched_pair_merge must be called before create_impute_flags. This will convert flag_matched_pair_merge to a low level function and using only pandas framework.

I added the predictive_auxiliary to test_data csv file and I also updated the tests accordingly to match expected columns

Ticket needs new review from different developer

[robertswh]

Looks good to me, tests pass.