diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb
index 36a3e2bb7..e81e1a297 100644
--- a/02_activities/assignments/assignment_2.ipynb
+++ b/02_activities/assignments/assignment_2.ipynb
@@ -79,24 +79,33 @@
    "outputs": [],
    "source": [
     "all_paths = [\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_01.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_02.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_03.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_04.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_05.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_06.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_07.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_08.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_09.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_10.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_11.csv\",\n",
-    "  \"../../05_src/data/assignment_2_data/inflammation_12.csv\"\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_01.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_02.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_03.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_04.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_05.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_06.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_07.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_08.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_09.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_10.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_11.csv\",\n",
+    "  \"C:/Users/lungy/Desktop/python/05_src/data/assignment_2_data/inflammation_12.csv\"\n",
     "]\n",
     "\n",
     "with open(all_paths[0], 'r') as f:\n",
+    "\n",
     "    # YOUR CODE HERE: Use the readline() or readlines() method to read the .csv file into a variable\n",
+    "    # READ THE .CSV FILES USING READLINES()\n",
+    "\n",
+    "    #Read the first data filel and assigne a name called 'patients'\n",
+    "    patients = f.readlines()\n",
     "    \n",
-    "    # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection"
+    "    # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n",
+    "\n",
+    "    # Print out the first data file by rows \n",
+    "for patient in patients:\n",
+    "    print (patient.strip())\n"
    ]
   },
   {
@@ -142,15 +151,20 @@
     "    data = np.loadtxt(fname=file_path, delimiter=',') # Load the data from the file\n",
     "    ax = 1  # This specifies that the operation should be done for each row (patient)\n",
     "\n",
+    "# Define each operational function: mean, max, min\n",
     "    # Implement the specific operation based on the 'operation' argument\n",
     "    if operation == 'mean':\n",
     "        # YOUR CODE HERE: Calculate the mean (average) number of flare-ups for each patient\n",
+    "        summary_values = np.mean(data, axis =1)\n",
     "\n",
     "    elif operation == 'max':\n",
     "        # YOUR CODE HERE: Calculate the maximum number of flare-ups experienced by each patient\n",
+    "        summary_values = np.max(data, axis =1)\n",
+    "\n",
     "\n",
     "    elif operation == 'min':\n",
     "        # YOUR CODE HERE: Calculate the minimum number of flare-ups experienced by each patient\n",
+    "        summary_values = np.min(data, axis = 1)\n",
     "\n",
     "    else:\n",
     "        # If the operation is not one of the expected values, raise an error\n",
@@ -161,11 +175,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {
     "id": "3TYo0-1SDLrd"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "60\n"
+     ]
+    }
+   ],
    "source": [
     "# Test it out on the data file we read in and make sure the size is what we expect i.e., 60\n",
     "# Your output for the first file should be 60\n",
@@ -228,7 +250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 24,
    "metadata": {
     "id": "_svDiRkdIwiT"
    },
@@ -261,18 +283,31 @@
     "\n",
     "def detect_problems(file_path):\n",
     "  #YOUR CODE HERE: Use patient_summary() to get the means and check_zeros() to check for zeros in the means\n",
+    "  \n",
+    "  # Integrate patient_summary function into the check_zeros function\n",
+    "  result=check_zeros(patient_summary(file_path, 'mean'))\n",
     "\n",
-    "  return"
+    "  return result"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "False\n"
+     ]
+    }
+   ],
    "source": [
     "# Test out your code here\n",
     "# Your output for the first file should be False\n",
+    "\n",
+    "# Print out the results from the detect_problem\n",
     "print(detect_problems(all_paths[0]))"
    ]
   },
@@ -314,7 +349,8 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "python-env",
+   "language": "python",
    "name": "python3"
   },
   "language_info": {
@@ -327,7 +363,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.11.13"
   }
  },
  "nbformat": 4,