Derive auxiliary for selective editing #139
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| dataframe[ | ||
| (dataframe[period] == previous_period) & (dataframe[question_no] == 49) | ||
| ][[imputation_class, construction_link, question_no]] | ||
| .drop_duplicates() |
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maybe we should look for duplicates in imputation_class and question_no as a quick check?
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Not sure if we have a generic validation, but something similar is done when producing SE outputs
robertswh
changed the title
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| standardising_factor["imputation_flags_adjustedresponse"] = standardising_factor[ | ||
| question_output = pd.merge(standardising_factor, auxiliary_value, on=["reference", "imputation_class", "questioncode"], how="left") |
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doesn't make sense to merge on reference and imputation_class, one or the other
| @@ -28,7 +30,7 @@ def calculate_predicted_value( | |||
| and imputed_value | |||
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| """ | |||
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| # TODO: This has already been combined somewhere updstream | |||
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Is this function still needed in the pipeline. From what I can see its only called in unit tests
| name of column in dataframe containing construction link variable | ||
| imputation_class : str | ||
| name of column in dataframe containing imputation class, where | ||
| there is one contruction link per imputation_class and period |
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| there is one contruction link per imputation_class and period | |
| there is one construction link per imputation_class and period |
| q40["auxiliary_value"] = q40[frozen_turnover] | ||
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| previous_period = period_selected - pd.DateOffset(months=1) | ||
| prev_const_link = ( |
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Nitpick: Could maybe refactor to use .loc not sure which one is better in the long term?
dataframe.loc[
(dataframe[period] == previous_period) & (dataframe[question_no] == 49),
[imputation_class, construction_link, question_no]
]
| dataframe[ | ||
| (dataframe[period] == previous_period) & (dataframe[question_no] == 49) | ||
| ][[imputation_class, construction_link, question_no]] | ||
| .drop_duplicates() |
There was a problem hiding this comment.
Not sure if we have a generic validation, but something similar is done when producing SE outputs
Jday7879
dismissed
their stale review
I am continuing this work. Removing this review so that others can approve without me changing the review
Pull Request Title
Derive auxiliary variable for the selective editing output.
The functionality has been written and added to the output but hasn't been tested yet.
Summary
Derive the required auxiliary variables for Q49 for the selective editing output for SPP
Type of Change
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