diff --git a/scripts/coefficients.py b/scripts/coefficients.py
new file mode 100644
index 0000000..34dd083
--- /dev/null
+++ b/scripts/coefficients.py
@@ -0,0 +1,76 @@
+import os
+import firebase_admin
+from firebase_admin import credentials
+from firebase_admin import firestore
+from google.cloud.firestore_v1.base_query import FieldFilter
+import pandas as pd
+from datetime import datetime
+import sys
+
+# Initialize Firebase Admin SDK
+cred = credentials.Certificate(os.getcwd() + '/' + 'keys/hpos-preprod-firebase-adminsdk.json')  # Replace with your own service account key path
+firebase_admin.initialize_app(cred)
+
+# Get a reference to the Firestore database
+db = firestore.client()
+
+# Specify the collections
+patient_collection = db.collection("devices")
+# test_collection = db.collection("testData")
+# start_date = sys.argv[1] # '2023-09-12' #input("Please enter the start date (yyyy-mm-dd): ")
+# end_date = sys.argv[2] #'2023-07-16' #input("Please enter the end date (yyyy-mm-dd): ")
+
+# query = test_collection.where(filter=FieldFilter("testTime", ">=", start_date)).where(filter=FieldFilter("testTime", "<", end_date))
+docs = patient_collection.stream()
+
+# Prepare data to store in CSV
+data = []
+for doc in docs:
+    doc_data = doc.to_dict()
+    # patient_id = patient_data["_id"]
+
+    # # Query the document from testData collection based on the common _id
+    # test_docs = test_collection.where("_id", "==", patient_id).stream()
+
+    # for test_doc in test_docs:
+    #     print(test_doc)
+    #     test_data = test_doc.to_dict()
+
+    #     # Combine the data from both collections into a single dictionary
+    #     combined_data = {**patient_data, **test_data}
+
+    #     # Fill empty fields in test_data with corresponding values from patient_data
+    #     for key, value in combined_data.items():
+    #         if value == "" and key in patient_data:
+    #             combined_data[key] = patient_data[key]
+
+    #     data.append(combined_data)
+    data.append(doc_data)
+
+# Convert the data to a DataFrame
+df = pd.DataFrame(data)
+print(df)
+print(df.size)
+
+# df = df[["_id", "classificationResult", "calculatedRatio", "deviceId", "deviceRatio", "kitSerial", "led1Average", "led1Buffer", "led1Sample", "led2Average", "led2Buffer", "led2Sample", "deviceSerialNumber", "name", "testTime", "resultData"]]
+# # df = df.groupby(["classificationResult"]).describe()
+# df_count = df.groupby(["classificationResult"]).describe()["calculatedRatio"]["count"]
+# print(df.groupby(["classificationResult"]).describe()["calculatedRatio"]["count"])
+
+# print("duplicates", len(df['_id']) - len(df['_id'].drop_duplicates()))
+
+# Save the DataFrame to a CSV file
+output_filename = f'devices_{datetime.today().strftime("%d_%m_%Y_%H_%M")}.xlsx'
+
+downloads_dir = os.path.join(os.path.expanduser("~"), "Downloads")
+output_path = os.path.join(downloads_dir, output_filename)
+writer = pd.ExcelWriter(output_path, engine = 'openpyxl')
+df.to_excel(writer, sheet_name = 'data', index=False)
+# df_count.to_excel(writer, sheet_name = "count")
+writer.close()
+
+print(f"Data saved to '{output_path}'")
+
+# Close the Firebase Admin SDK
+firebase_admin.delete_app(firebase_admin.get_app())
+