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Update app.py
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app.py
CHANGED
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@@ -140,7 +140,7 @@ Now, provide your response in the following format:
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3. **Analysis Step A:** [e.g., "Calculate average wait times per hospital by grouping `dfs[0]` by 'Facility' and averaging 'Surgery_Median'."]
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4. **Analysis Step B:** [e.g., "Identify top 5 specialties by grouping `dfs[0]` by the 'Specialty' column and calculating the mean of 'Surgery_Median'."]
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5. **Analysis Step C:** [e.g., "Determine zone-level performance by grouping by 'Zone' and comparing to the overall provincial average."]
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6. **JSON Output Structure:** [Describe the keys and values of the final JSON object]
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# Your complete Python script starts here
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import pandas as pd
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@@ -150,7 +150,8 @@ import re
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# Main analysis logic...
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# ...
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# Final print statement
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print(json.dumps(final_data_structure, indent=4))
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generated_text = cohere_chat(prompt_for_coder)
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# This regex is more robust for extracting the final code block
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match = re2.search(r"PYTHON SCRIPT:\s*```python\n(.*?)```", generated_text, re2.DOTALL)
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3. **Analysis Step A:** [e.g., "Calculate average wait times per hospital by grouping `dfs[0]` by 'Facility' and averaging 'Surgery_Median'."]
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4. **Analysis Step B:** [e.g., "Identify top 5 specialties by grouping `dfs[0]` by the 'Specialty' column and calculating the mean of 'Surgery_Median'."]
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5. **Analysis Step C:** [e.g., "Determine zone-level performance by grouping by 'Zone' and comparing to the overall provincial average."]
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6. **JSON Output Structure:** [Describe the keys and values of the final JSON object]
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# Your complete Python script starts here
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import pandas as pd
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# Main analysis logic...
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# ...
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# Final print statement
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print(json.dumps(final_data_structure, indent=4))"""
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generated_text = cohere_chat(prompt_for_coder)
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# This regex is more robust for extracting the final code block
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match = re2.search(r"PYTHON SCRIPT:\s*```python\n(.*?)```", generated_text, re2.DOTALL)
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