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01783ce
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Update src/ProcessOneSingleCampaign.py

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  1. src/ProcessOneSingleCampaign.py +14 -18
src/ProcessOneSingleCampaign.py CHANGED
@@ -553,21 +553,19 @@ class CampaignProcessor:
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  float: The transformed previous funding goal
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  """
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  try:
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- # Check if value is already provided in the expected field
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- if 'previous_funding_goal' in campaign:
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- previous_goal = float(campaign.get('previous_funding_goal', 0))
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- print(f"Using provided previous_funding_goal directly: {previous_goal}")
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- else:
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- print(f"No previous_funding_goal in input data, looking for alternative field names")
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- previous_goal = 0.0
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- # Apply logarithmic transformation
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  if previous_goal > 0:
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- # Log1p transformation, good for general compression while preserving relative differences
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  transformed_goal = np.log1p(previous_goal)/np.log(10)
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  print(f"Applied log transformation to previous_funding_goal: {previous_goal} β†’ {transformed_goal}")
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  return transformed_goal
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  else:
 
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  return 0.0
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  except Exception as e:
@@ -589,21 +587,19 @@ class CampaignProcessor:
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  float: The transformed previous pledged amount
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  """
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  try:
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- # Check if value is already provided in the expected field
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- if 'previous_pledged' in campaign:
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- pledged = float(campaign.get('previous_pledged', 0))
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- print(f"Using provided previous_pledged directly: {pledged}")
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- else:
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- print(f"No previous_pledged in input data, looking for alternative field names")
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- pledged = 0.0
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- # Apply logarithmic transformation
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  if pledged > 0:
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- # Log1p transformation, good for general compression while preserving relative differences
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  transformed_pledge = np.log1p(pledged)/np.log(10)
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  print(f"Applied log transformation to previous_pledged: {pledged} β†’ {transformed_pledge}")
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  return transformed_pledge
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  else:
 
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  return 0.0
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  except Exception as e:
 
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  float: The transformed previous funding goal
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  """
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  try:
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+ # Get the raw value
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+ previous_goal = float(campaign.get('previous_funding_goal', 0))
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+
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+ # Log the source value
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+ print(f"Previous funding goal raw value: {previous_goal}")
 
 
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+ # Apply logarithmic transformation if value is positive
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  if previous_goal > 0:
 
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  transformed_goal = np.log1p(previous_goal)/np.log(10)
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  print(f"Applied log transformation to previous_funding_goal: {previous_goal} β†’ {transformed_goal}")
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  return transformed_goal
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  else:
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+ print(f"No transformation applied to previous_funding_goal: value is {previous_goal}")
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  return 0.0
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  except Exception as e:
 
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  float: The transformed previous pledged amount
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  """
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  try:
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+ # Get the raw value
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+ pledged = float(campaign.get('previous_pledged', 0))
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+
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+ # Log the source value
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+ print(f"Previous pledged raw value: {pledged}")
 
 
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+ # Apply logarithmic transformation if value is positive
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  if pledged > 0:
 
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  transformed_pledge = np.log1p(pledged)/np.log(10)
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  print(f"Applied log transformation to previous_pledged: {pledged} β†’ {transformed_pledge}")
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  return transformed_pledge
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  else:
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+ print(f"No transformation applied to previous_pledged: value is {pledged}")
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  return 0.0
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  except Exception as e: