diff --git a/scripts/consolidated_data.py b/scripts/consolidated_data.py
index cfb2b29..11a9a9a 100644
--- a/scripts/consolidated_data.py
+++ b/scripts/consolidated_data.py
@@ -11,10 +11,10 @@ import platform
 if __name__ == "__main__":
 
     path_delim = ""
-    if platform.system() == 'Darwin':
-        path_delim = '/'
-    else:
+    if platform.system() == 'Windows':
         path_delim = '\\'
+    else:
+        path_delim = '/'
     
     key_file_path = os.getcwd() + path_delim + "keys" + path_delim + "hpos-af3cc-firebase-adminsdk-n261k-2bfd463ec0.json"
     cred = credentials.Certificate(key_file_path)  # Replace with your own service account key path
@@ -35,7 +35,7 @@ if __name__ == "__main__":
     # Prepare data to store in CSV
     data = []
     for patient_doc in patient_docs:
-        print(patient_doc)
+        # print(patient_doc)
         patient_data = patient_doc.to_dict()
         patient_id = patient_data["_id"]
 
@@ -43,7 +43,7 @@ if __name__ == "__main__":
         test_docs = test_collection.where("_id", "==", patient_id).stream()
 
         for test_doc in test_docs:
-            print(test_doc)
+            # print(test_doc)
             test_data = test_doc.to_dict()
 
             # Combine the data from both collections into a single dictionary
@@ -62,12 +62,17 @@ if __name__ == "__main__":
     print(df.size)
 
     # Save the DataFrame to a CSV file
-    output_filename = "data.csv"
+    output_filename = "data.xlsx"
     df.to_csv(output_filename, index=False)
 
     downloads_dir = os.path.join(os.path.expanduser("~"), "Downloads")
     output_path = os.path.join(downloads_dir, output_filename)
-    df.to_csv(output_path, index=False)
+    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.drop(['resultData', "reportUploadTime", "userImageURL", "testType", "birthYear", "testStatus", "reportPath", "createdBy", "csvPath", "result", "mobileId", "resultRatio", "localFlag", "led2", "led1"], axis=1)
+    df.to_excel(writer, sheet_name = 'data', index=False)
+    writer.close()
 
     print(f"Data saved to '{output_path}'")