diff --git a/scripts/consolidated_data.py b/scripts/consolidated_data.py
index 0cd9c34..f24b551 100644
--- a/scripts/consolidated_data.py
+++ b/scripts/consolidated_data.py
@@ -9,7 +9,7 @@ import sys
 import platform
 from datetime import datetime, timedelta
 
-environment = "qa"
+environment = "af3cc"
 
 if __name__ == "__main__":
 
@@ -69,7 +69,7 @@ if __name__ == "__main__":
     # Convert the data to a DataFrame
     df = pd.DataFrame(data)
     print(df)
-    print(df.size)
+    print(df.columns)
 
 
     # Save the DataFrame to a CSV file
@@ -81,8 +81,11 @@ if __name__ == "__main__":
     writer = pd.ExcelWriter(output_path, engine = 'openpyxl')
     df = df[(df['testTime'] > start_date) & (df['testTime'] <= end_date)]
     df = df.sort_values(by=['testTime'], ascending=False)
-    
-    df = df[["_id", "errorMessages", "classificationResult",  "prdClassification", "predictedDenovixRatio", "calculatedRatio", "deviceRatio", "kitSerial", "abs1", "led1Average", "led1Buffer", "led1Sample", "abs2", "led2Average", "led2Buffer", "led2Sample", "hb3", "abs3", "led3Average", "led3Buffer", "led3Sample", "hb4", "abs4", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "deviceId", "deviceSerialNumber", "name", "testTime"]]
+
+    column_names = ["_id", "classificationResult", "deviceRatioClass",  "prdClassification", "slopeRatioClass", "predictedDenovixRatio", "slopeRatio", "calculatedRatio", "deviceRatio", "kitSerial", "led1Gain1", "led1Gain2", "led1Gain4", "abs1", "led1Average", "led1Buffer", "led1Sample", "led2Gain1", "led2Gain2", "led2Gain4", "abs2", "led2Average", "led2Buffer", "led2Sample", "led3Gain1", "led3Gain2", "led3Gain4", "hb3", "abs3", "led3Average", "led3Buffer", "led3Sample", "led4Gain1", "led4Gain2", "led4Gain4", "hb4", "abs4", "led4Average", "led4Average", "led4Buffer", "led4Sample", "batteryLevel", "batteryVoltage", "solution", "concentration", "volume", "errorMessages", "deviceId", "deviceSerialNumber", "appVersion", "name", "testTime"]
+    common_columns = [col for col in column_names if col in df.columns]
+    df = df[common_columns]
+
     # df.rename(columns={'deviceSerialNumber': "login_id", "calculatedRatio": "calibrated_ratio", "led1Buffer": "427_buffer_intensity", "led2Buffer": "555_buffer_intensity", "led1Sample": "427_sample_intensity", "led2Sample": "555_sample_intensity", "led1Average": "427_absorbance", "led2Average": "555_absorbance"}, inplace = True)
     # df = df.reindex(sorted(df.columns), axis=1)