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Data Cleaning & Type Conversion #4

Description

@carlboy2002
  • Convert the value column from string to numeric (float), handling nulls with errors='coerce'.

  • Convert the period column to a standardized UTC Datetime objects.

  • Pivot the data so that "Demand" and "Day-ahead forecast" are individual columns for analysis.

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