#BUG_FIX

Prompt Category:
Bug Fixing

Prompt:
Fix the error in this code. The target Google sheet is not being filled

User Observation:
Still the Taget google sheet is empty

Response ID:
b917bd10-659c-4e49-a6c0-078d872b3cf3

Author: suryasandeepboda

app.log

@@ -153,3 +153,16 @@ Exception: API Error
                     ^">
 2025-03-13 19:00:05,884 - ERROR - Failed to write to target sheet
 2025-03-13 19:00:05,885 - ERROR - Failed to process and transfer data
+2025-03-13 19:04:15,526 - INFO - Successfully loaded credentials
+2025-03-13 19:04:15,528 - INFO - file_cache is only supported with oauth2client<4.0.0
+2025-03-13 19:04:15,529 - INFO - Successfully created Google Sheets service
+2025-03-13 19:04:17,814 - INFO - Retrieved 144 rows of data
+2025-03-13 19:04:17,815 - INFO - Available columns in sheet: ['Timestamp', 'Email Address', 'Tool being used', 'Feature used', 'Task Objective', 'Repository Link', 'Repository: Public/Private', 'Repository: Lines of Code', '[Turn 1]: Prompt Category', '[Turn 1]: Prompt', '[Turn 1]: Model Response', '[Turn 1]: Model Response - File [Use only when response is too long]', '[Turn 1]: Observations', '[Turn 1]: Screenshots', '[Turn 2]: Prompt Category', '[Turn 2]: Prompt', '[Turn 2]: Model Response', '[Turn 2]: Model Response - File [Use only when response is too long]', '[Turn 2]: Observations', '[Turn 2]: Screenshot', '[Turn 3]: Prompt Category', '[Turn 3]: Prompt', '[Turn 3]: Model Response', '[Turn 3]: Model Response - File [Use only when response is too long]', '[Turn 3]: Observations', '[Turn 3]: Screenshot', '[Turn 4]: Prompt Category', '[Turn 4]: Prompt', '[Turn 4]: Model Response', '[Turn 4]: Model Response - File [Use only when response is too long]', '[Turn 4]: Observations', '[Turn 4]: Screenshot', '[Turn 5]: Prompt Category', '[Turn 5]: Prompt', '[Turn 5]: Model Response', '[Turn 5]: Model Response - File [Use only when response is too long]', '[Turn 5]: Observations', '[Turn 5]: Screenshot', '[Turn 6]: Prompt Category', '[Turn 6]: Prompt', '[Turn 6]: Model Response', '[Turn 6]: Model Response - File [Use only when response is too long]', '[Turn 6]: Observations', '[Turn 6]: Screenshot', '[Turn 7]: Prompt Category', '[Turn 7]: Prompt', '[Turn 7]: Model Response', '[Turn 7]: Model Response - File [Use only when response is too long]', '[Turn 7]: Observations', '[Turn 7]: Screenshot', 'Context Awareness', 'Context Awareness: Errors', 'Rationale for Context Awareness', 'Output Quality', 'Output Quality: Errors', 'Rationale for Output Quality', 'Autonomy', 'Autonomy: Errors', 'Rationale for Autonomy', 'Iteration Size and Speed', 'Iteration Size and Speed: Errors', 'Rationale for Iteration Size and Speed', 'Experience', 'Experience - Flexibility, Ease of Use and Reliability: Errors', 'Rationale for Experience', 'Loom Recording Link', 'Overall Rating', 'Rationale behind the overall rating', '[Turn 1]: Final Turn?', '[Turn 2]: Final Turn?', '[Turn 3]: Final Turn?', '[Turn 4]: Final Turn?', '[Turn 5]: Final Turn?', '[Turn 6]: Final Turn?', '[Turn 7]: Final Turn?', '[Turn 1]: Turn ID', '[Turn 2]: Turn ID', '[Turn 3]: Turn ID', '[Turn 4]: Turn ID', '[Turn 5]: Turn ID', '[Turn 6]: Turn ID', '[Turn 7]: Turn ID', 'Unique ID']
+2025-03-13 19:04:17,820 - INFO - Successfully filtered required columns
+2025-03-13 19:04:17,823 - INFO - Calculated mean ratings
+2025-03-13 19:04:17,824 - INFO - Calculated results and color mapping
+2025-03-13 19:04:17,825 - INFO - file_cache is only supported with oauth2client<4.0.0
+2025-03-13 19:04:19,170 - INFO - Target sheet cleared successfully
+2025-03-13 19:04:20,344 - INFO - Data written to target sheet successfully
+2025-03-13 19:04:20,345 - INFO - Data successfully written to target sheet
+2025-03-13 19:04:20,347 - INFO - Data processing and transfer successful

extract_data.py

@@ -45,9 +45,18 @@ def write_to_target_sheet(df, service):
     try:
         target_spreadsheet_id = '1FEqiDqqPfb9YHAWBiqVepmmXj22zNqXNNI7NLGCDVak'
 
+        # Clean the DataFrame by replacing NaN with empty strings
+        df_clean = df.fillna('')
+        
+        # Convert numeric columns to rounded strings
+        numeric_columns = ['Context Awareness', 'Autonomy', 'Experience', 
+                         'Output Quality', 'Overall Rating', 'Mean Rating', 'Difference']
+        for col in numeric_columns:
+            df_clean[col] = df_clean[col].apply(lambda x: f"{x:.2f}" if x != '' else '')
+        
         # Prepare data for writing
-        headers = df.columns.tolist()
-        values = [headers] + df.values.tolist()
+        headers = df_clean.columns.tolist()
+        values = [headers] + df_clean.values.tolist()
 
         # Write data
         body = {