diff --git a/ersilia/core/tracking.py b/ersilia/core/tracking.py
index 9013d0eb..9f77f219 100644
--- a/ersilia/core/tracking.py
+++ b/ersilia/core/tracking.py
@@ -16,12 +16,6 @@ class RunTracker:
     NOTE: Currently, the Splunk connection is not set up. For now, we will print tracking results to the console.
     """
 
-    def sample_df(self, df, num_rows, num_cols):
-        """
-        Returns a sample of the dataframe, with the specified number of rows and columns.
-        """
-        return df.sample(num_rows, axis=0).sample(num_cols, axis=1)
-
     def __init__(self):
         self.time_start = None
 
@@ -29,8 +23,14 @@ def __init__(self):
     def start_tracking(self):
         self.time_start = datetime.now()
 
+    def sample_df(self, df, num_rows, num_cols):
+        """
+        Returns a sample of the dataframe, with the specified number of rows and columns.
+        """
+        return df.sample(num_rows, axis=0).sample(num_cols, axis=1)
+
     def stats(self, result):
-        dat = self.read_csv(result)
+        dat = read_csv(result)
 
         # drop first two columns (key, input)
         dat = dat.drop(["key", "input"], axis=1)
@@ -46,15 +46,28 @@ def stats(self, result):
             print("Max %s: %s" % (column, dat[column].max()))
             print("Standard deviation %s: %s" % (column, dat[column].std()))
 
+    def get_file_sizes(self, input_df, output_df):
+        input_size = input_df.memory_usage(deep=True).sum() / 1024
+        output_size = output_df.memory_usage(deep=True).sum() / 1024
+
+        input_avg_row_size = input_size / len(input_df)
+        output_avg_row_size = output_size / len(output_df)
+
+        print("Average Input Row Size (KB):", input_avg_row_size)
+        print("Average Output Row Size (KB):", output_avg_row_size)
+
     def track(self, input, result, meta):
         """
         Tracks the results after a model run.
         """
+        input_dataframe = read_csv(input)
+        result_dataframe = read_csv(result)
+
         print("Run input file:", input)
-        print(read_csv(input))
+        print(input_dataframe)
 
         print("Run output file:", result)
-        print(read_csv(result))
+        print(result_dataframe)
 
         print("Model metadata:", meta)
 
@@ -66,17 +79,7 @@ def track(self, input, result, meta):
 
         self.stats(result)
 
-        input_dataframe = self.read_csv(input)
-        result_dataframe = self.read_csv(result)
-
-        input_size = input_dataframe.memory_usage(deep=True).sum() / 1024
-        output_size = result_dataframe.memory_usage(deep=True).sum() / 1024
-
-        input_avg_row_size = input_size / len(input_dataframe)
-        output_avg_row_size = output_size / len(result_dataframe)
-
-        print("Average Input Row Size (KB):", input_avg_row_size)
-        print("Average Output Row Size (KB):", output_avg_row_size)
+        self.get_file_sizes(input_dataframe, result_dataframe)
 
     def log_to_console(self, data):
         print(f"\n{json.dumps(data)}\n")