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Transform XBRL core_ferc714__yearly_planning_area_demand_forecast table #3856
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…ferc714__yearly_planning_area_demand_forecast table
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Just a high-level comment, but I spent some time tackling the duplicate PK values in the XBRL data before I realized that they were getting handled in the FercXBRLSQLiteIOManager
class load_input
function. Specifically, I didn't realize that the older publication_date
values were getting dropped and the report_year
column was getting made there. It's a little confusing to have that happen in the IOManager vs. the transforms. I understand that it might be more efficient to do it that way though.
Out of scope to change for this PR, just a thought I had.
) -> pd.DataFrame: | ||
"""Transform the yearly planning area forecast data per Planning Area. | ||
class YearlyPlanningAreaDemandForecast: | ||
"""Class for building the :ref:`core_ferc714__yearly_planning_area_demand_forecast` asset. |
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The hourly table has an out
prefix. Which one should we have here?
Overview
Closes #3837 .
What problem does this address?
Adds XBRL data (2021 +) for the annual demand forecast table.
What did you change?
YearlyPlanningAreaDemandForecast
class and class functions.forecast
to the column names with forecasted values.Ideas
We could add some tests for the 714 data that made sure the mwh and mw values fell within a reasonable range. Might be something we put on the backburner for now.
Testing
How did you make sure this worked? How can a reviewer verify this?
Materialize the
core_ferc714__yearly_planning_area_demand_forecast
table in dagster.To-do list