addressed sonarqube errors

Author: Andyg79

docs/utility-guides/FitKitLogged.md

@@ -26,20 +26,26 @@ The methods in this utility require specific arguments. Below is a summary of th
 
 The `fit_kit_logged` Utility includes methods for retrieving FIT test kits from the DB and splitting them into 'Normal' and 'Abnormal' results. Below are their key functions:
 
-1.  **`process_kit_data(smokescreen_properties: dict) -> list`**
-    Retrieves the test data needed for compartment 3 and then splits it into two data frames, using the `split_fit_kits` method.
-    - **Arguments**:
-     - `smokescreen_properties` (dict): A dictionary containing properties required to retrieve and process kit data.
-   - **Returns**: A list of tuples where each tuple contains a device ID (str) and a boolean flag (True for normal, False for abnormal).
-  
-2. **`split_fit_kits(kit_id_df: pd.DataFrame, smokescreen_properties: dict) -> pd.DataFrame`**
-    This method splits the `dataframe` into two dataframes, 1 normal and 1 abnormal.
-    - **Arguments**:
-     -  `kit_id_df` (pd.DataFrame): A `dataframe` containing fit kit IDs.
-     -  `smokescreen_properties` (dict): A dictionary containing the number of normal and abnormal fit kits to split.
-   - **Returns**: A tuple containing two dataframes:
-            - normal_fit_kit_df (pd.DataFrame): `dataframe` containing normal fit kits.
-            - abnormal_fit_kit_df (pd.DataFrame): `dataframe` containing abnormal fit kits.
+1. **`process_kit_data(smokescreen_properties: dict) -> list`**
+  Retrieves the test data needed for compartment 3 and then splits it into two data frames, using the `split_fit_kits` method.
+
+  - **Arguments**:
+    - `smokescreen_properties` (dict): A dictionary containing properties required to retrieve and process kit data.
+
+  - **Returns**:
+    A list of tuples where each tuple contains a device ID (str) and a `boolean` flag (True for normal, False for abnormal).
+
+2. **`split_fit_kits(kit_id_df: pd.DataFrame, smokescreen_properties: dict) -> tuple`**
+  This method splits the `dataframe` into two dataframes, one normal and one abnormal.
+
+  - **Arguments**:
+    - `kit_id_df` (pd.DataFrame): A `dataframe` containing fit kit IDs.
+    - `smokescreen_properties` (dict): A dictionary containing the number of normal and abnormal fit kits to split.
+
+  - **Returns**:
+    A tuple containing two dataframes:
+    - `normal_fit_kit_df` (pd.DataFrame): `dataframe` containing normal fit kits.
+    - `abnormal_fit_kit_df` (pd.DataFrame): `dataframe` containing abnormal fit kits.
 
 ## Example Usage