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app.py
CHANGED
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@@ -153,14 +153,14 @@ def batch_predict():
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# Create DataFrame for prediction
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input_data = pd.DataFrame([{
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'Product_Id': f'FD{i+1:03d}', # Unique product ID for batch
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'Product_Weight': float(item['Product_Weight']),
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'Product_Sugar_Content': str(item['Product_Sugar_Content']),
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'Product_Allocated_Area': float(item['Product_Allocated_Area']),
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'Product_Type': str(item['Product_Type']),
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'Product_MRP': float(item['Product_MRP']),
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'Store_Id': f'OUT{i+1:03d}', # Unique store ID for batch
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'Store_Establishment_Year': int(item['Store_Establishment_Year']),
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'Store_Size': str(item['Store_Size']),
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'Store_Location_City_Type': str(item['Store_Location_City_Type']),
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'Store_Type': str(item['Store_Type']),
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| 153 |
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# Create DataFrame for prediction
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input_data = pd.DataFrame([{
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+
#'Product_Id': f'FD{i+1:03d}', # Unique product ID for batch
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'Product_Weight': float(item['Product_Weight']),
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'Product_Sugar_Content': str(item['Product_Sugar_Content']),
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'Product_Allocated_Area': float(item['Product_Allocated_Area']),
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'Product_Type': str(item['Product_Type']),
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'Product_MRP': float(item['Product_MRP']),
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'Store_Id': f'OUT{i+1:03d}', # Unique store ID for batch
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#'Store_Establishment_Year': int(item['Store_Establishment_Year']),
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'Store_Size': str(item['Store_Size']),
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'Store_Location_City_Type': str(item['Store_Location_City_Type']),
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'Store_Type': str(item['Store_Type']),
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