diff --git a/02_activities/assignments/assignment_2.ipynb b/02_activities/assignments/assignment_2.ipynb
index fd02cc6cc..4b7769057 100644
--- a/02_activities/assignments/assignment_2.ipynb
+++ b/02_activities/assignments/assignment_2.ipynb
@@ -57,6 +57,15 @@
     "\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Module: Python\n",
+    "#### Assignment: 2\n",
+    "#### Name: Chun-Yuan Chen"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -72,31 +81,192 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import csv # CYC: I imported this module so I can read .csv files later on."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
    "metadata": {
     "id": "n0m48JsS-nMC"
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0,0,1,3,1,2,4,7,8,3,3,3,10,5,7,4,7,7,12,18,6,13,11,11,7,7,4,6,8,8,4,4,5,7,3,4,2,3,0,0\n",
+      "\n",
+      "0,1,2,1,2,1,3,2,2,6,10,11,5,9,4,4,7,16,8,6,18,4,12,5,12,7,11,5,11,3,3,5,4,4,5,5,1,1,0,1\n",
+      "\n",
+      "0,1,1,3,3,2,6,2,5,9,5,7,4,5,4,15,5,11,9,10,19,14,12,17,7,12,11,7,4,2,10,5,4,2,2,3,2,2,1,1\n",
+      "\n",
+      "0,0,2,0,4,2,2,1,6,7,10,7,9,13,8,8,15,10,10,7,17,4,4,7,6,15,6,4,9,11,3,5,6,3,3,4,2,3,2,1\n",
+      "\n",
+      "0,1,1,3,3,1,3,5,2,4,4,7,6,5,3,10,8,10,6,17,9,14,9,7,13,9,12,6,7,7,9,6,3,2,2,4,2,0,1,1\n",
+      "\n",
+      "0,0,1,2,2,4,2,1,6,4,7,6,6,9,9,15,4,16,18,12,12,5,18,9,5,3,10,3,12,7,8,4,7,3,5,4,4,3,2,1\n",
+      "\n",
+      "0,0,2,2,4,2,2,5,5,8,6,5,11,9,4,13,5,12,10,6,9,17,15,8,9,3,13,7,8,2,8,8,4,2,3,5,4,1,1,1\n",
+      "\n",
+      "0,0,1,2,3,1,2,3,5,3,7,8,8,5,10,9,15,11,18,19,20,8,5,13,15,10,6,10,6,7,4,9,3,5,2,5,3,2,2,1\n",
+      "\n",
+      "0,0,0,3,1,5,6,5,5,8,2,4,11,12,10,11,9,10,17,11,6,16,12,6,8,14,6,13,10,11,4,6,4,7,6,3,2,1,0,0\n",
+      "\n",
+      "0,1,1,2,1,3,5,3,5,8,6,8,12,5,13,6,13,8,16,8,18,15,16,14,12,7,3,8,9,11,2,5,4,5,1,4,1,2,0,0\n",
+      "\n",
+      "0,1,0,0,4,3,3,5,5,4,5,8,7,10,13,3,7,13,15,18,8,15,15,16,11,14,12,4,10,10,4,3,4,5,5,3,3,2,2,1\n",
+      "\n",
+      "0,1,0,0,3,4,2,7,8,5,2,8,11,5,5,8,14,11,6,11,9,16,18,6,12,5,4,3,5,7,8,3,5,4,5,5,4,0,1,1\n",
+      "\n",
+      "0,0,2,1,4,3,6,4,6,7,9,9,3,11,6,12,4,17,13,15,13,12,8,7,4,7,12,9,5,6,5,4,7,3,5,4,2,3,0,1\n",
+      "\n",
+      "0,0,0,0,1,3,1,6,6,5,5,6,3,6,13,3,10,13,9,16,15,9,11,4,6,4,11,11,12,3,5,8,7,4,6,4,1,3,0,0\n",
+      "\n",
+      "0,1,2,1,1,1,4,1,5,2,3,3,10,7,13,5,7,17,6,9,12,13,10,4,12,4,6,7,6,10,8,2,5,1,3,4,2,0,2,0\n",
+      "\n",
+      "0,1,1,0,1,2,4,3,6,4,7,5,5,7,5,10,7,8,18,17,9,8,12,11,11,11,14,6,11,2,10,9,5,6,5,3,4,2,2,0\n",
+      "\n",
+      "0,0,0,0,2,3,6,5,7,4,3,2,10,7,9,11,12,5,12,9,13,19,14,17,5,13,8,11,5,10,9,8,7,5,3,1,4,0,2,1\n",
+      "\n",
+      "0,0,0,1,2,1,4,3,6,7,4,2,12,6,12,4,14,7,8,14,13,19,6,9,12,6,4,13,6,7,2,3,6,5,4,2,3,0,1,0\n",
+      "\n",
+      "0,0,2,1,2,5,4,2,7,8,4,7,11,9,8,11,15,17,11,12,7,12,7,6,7,4,13,5,7,6,6,9,2,1,1,2,2,0,1,0\n",
+      "\n",
+      "0,1,2,0,1,4,3,2,2,7,3,3,12,13,11,13,6,5,9,16,9,19,16,11,8,9,14,12,11,9,6,6,6,1,1,2,4,3,1,1\n",
+      "\n",
+      "0,1,1,3,1,4,4,1,8,2,2,3,12,12,10,15,13,6,5,5,18,19,9,6,11,12,7,6,3,6,3,2,4,3,1,5,4,2,2,0\n",
+      "\n",
+      "0,0,2,3,2,3,2,6,3,8,7,4,6,6,9,5,12,12,8,5,12,10,16,7,14,12,5,4,6,9,8,5,6,6,1,4,3,0,2,0\n",
+      "\n",
+      "0,0,0,3,4,5,1,7,7,8,2,5,12,4,10,14,5,5,17,13,16,15,13,6,12,9,10,3,3,7,4,4,8,2,6,5,1,0,1,0\n",
+      "\n",
+      "0,1,1,1,1,3,3,2,6,3,9,7,8,8,4,13,7,14,11,15,14,13,5,13,7,14,9,10,5,11,5,3,5,1,1,4,4,1,2,0\n",
+      "\n",
+      "0,1,1,1,2,3,5,3,6,3,7,10,3,8,12,4,12,9,15,5,17,16,5,10,10,15,7,5,3,11,5,5,6,1,1,1,1,0,2,1\n",
+      "\n",
+      "0,0,2,1,3,3,2,7,4,4,3,8,12,9,12,9,5,16,8,17,7,11,14,7,13,11,7,12,12,7,8,5,7,2,2,4,1,1,1,0\n",
+      "\n",
+      "0,0,1,2,4,2,2,3,5,7,10,5,5,12,3,13,4,13,7,15,9,12,18,14,16,12,3,11,3,2,7,4,8,2,2,1,3,0,1,1\n",
+      "\n",
+      "0,0,1,1,1,5,1,5,2,2,4,10,4,8,14,6,15,6,12,15,15,13,7,17,4,5,11,4,8,7,9,4,5,3,2,5,4,3,2,1\n",
+      "\n",
+      "0,0,2,2,3,4,6,3,7,6,4,5,8,4,7,7,6,11,12,19,20,18,9,5,4,7,14,8,4,3,7,7,8,3,5,4,1,3,1,0\n",
+      "\n",
+      "0,0,0,1,4,4,6,3,8,6,4,10,12,3,3,6,8,7,17,16,14,15,17,4,14,13,4,4,12,11,6,9,5,5,2,5,2,1,0,1\n",
+      "\n",
+      "0,1,1,0,3,2,4,6,8,6,2,3,11,3,14,14,12,8,8,16,13,7,6,9,15,7,6,4,10,8,10,4,2,6,5,5,2,3,2,1\n",
+      "\n",
+      "0,0,2,3,3,4,5,3,6,7,10,5,10,13,14,3,8,10,9,9,19,15,15,6,8,8,11,5,5,7,3,6,6,4,5,2,2,3,0,0\n",
+      "\n",
+      "0,1,2,2,2,3,6,6,6,7,6,3,11,12,13,15,15,10,14,11,11,8,6,12,10,5,12,7,7,11,5,8,5,2,5,5,2,0,2,1\n",
+      "\n",
+      "0,0,2,1,3,5,6,7,5,8,9,3,12,10,12,4,12,9,13,10,10,6,10,11,4,15,13,7,3,4,2,9,7,2,4,2,1,2,1,1\n",
+      "\n",
+      "0,0,1,2,4,1,5,5,2,3,4,8,8,12,5,15,9,17,7,19,14,18,12,17,14,4,13,13,8,11,5,6,6,2,3,5,2,1,1,1\n",
+      "\n",
+      "0,0,0,3,1,3,6,4,3,4,8,3,4,8,3,11,5,7,10,5,15,9,16,17,16,3,8,9,8,3,3,9,5,1,6,5,4,2,2,0\n",
+      "\n",
+      "0,1,2,2,2,5,5,1,4,6,3,6,5,9,6,7,4,7,16,7,16,13,9,16,12,6,7,9,10,3,6,4,5,4,6,3,4,3,2,1\n",
+      "\n",
+      "0,1,1,2,3,1,5,1,2,2,5,7,6,6,5,10,6,7,17,13,15,16,17,14,4,4,10,10,10,11,9,9,5,4,4,2,1,0,1,0\n",
+      "\n",
+      "0,1,0,3,2,4,1,1,5,9,10,7,12,10,9,15,12,13,13,6,19,9,10,6,13,5,13,6,7,2,5,5,2,1,1,1,1,3,0,1\n",
+      "\n",
+      "0,1,1,3,1,1,5,5,3,7,2,2,3,12,4,6,8,15,16,16,15,4,14,5,13,10,7,10,6,3,2,3,6,3,3,5,4,3,2,1\n",
+      "\n",
+      "0,0,0,2,2,1,3,4,5,5,6,5,5,12,13,5,7,5,11,15,18,7,9,10,14,12,11,9,10,3,2,9,6,2,2,5,3,0,0,1\n",
+      "\n",
+      "0,0,1,3,3,1,2,1,8,9,2,8,10,3,8,6,10,13,11,17,19,6,4,11,6,12,7,5,5,4,4,8,2,6,6,4,2,2,0,0\n",
+      "\n",
+      "0,1,1,3,4,5,2,1,3,7,9,6,10,5,8,15,11,12,15,6,12,16,6,4,14,3,12,9,6,11,5,8,5,5,6,1,2,1,2,0\n",
+      "\n",
+      "0,0,1,3,1,4,3,6,7,8,5,7,11,3,6,11,6,10,6,19,18,14,6,10,7,9,8,5,8,3,10,2,5,1,5,4,2,1,0,1\n",
+      "\n",
+      "0,1,1,3,3,4,4,6,3,4,9,9,7,6,8,15,12,15,6,11,6,18,5,14,15,12,9,8,3,6,10,6,8,7,2,5,4,3,1,1\n",
+      "\n",
+      "0,1,2,2,4,3,1,4,8,9,5,10,10,3,4,6,7,11,16,6,14,9,11,10,10,7,10,8,8,4,5,8,4,4,5,2,4,1,1,0\n",
+      "\n",
+      "0,0,2,3,4,5,4,6,2,9,7,4,9,10,8,11,16,12,15,17,19,10,18,13,15,11,8,4,7,11,6,7,6,5,1,3,1,0,0,0\n",
+      "\n",
+      "0,1,1,3,1,4,6,2,8,2,10,3,11,9,13,15,5,15,6,10,10,5,14,15,12,7,4,5,11,4,6,9,5,6,1,1,2,1,2,1\n",
+      "\n",
+      "0,0,1,3,2,5,1,2,7,6,6,3,12,9,4,14,4,6,12,9,12,7,11,7,16,8,13,6,7,6,10,7,6,3,1,5,4,3,0,0\n",
+      "\n",
+      "0,0,1,2,3,4,5,7,5,4,10,5,12,12,5,4,7,9,18,16,16,10,15,15,10,4,3,7,5,9,4,6,2,4,1,4,2,2,2,1\n",
+      "\n",
+      "0,1,2,1,1,3,5,3,6,3,10,10,11,10,13,10,13,6,6,14,5,4,5,5,9,4,12,7,7,4,7,9,3,3,6,3,4,1,2,0\n",
+      "\n",
+      "0,1,2,2,3,5,2,4,5,6,8,3,5,4,3,15,15,12,16,7,20,15,12,8,9,6,12,5,8,3,8,5,4,1,3,2,1,3,1,0\n",
+      "\n",
+      "0,0,0,2,4,4,5,3,3,3,10,4,4,4,14,11,15,13,10,14,11,17,9,11,11,7,10,12,10,10,10,8,7,5,2,2,4,1,2,1\n",
+      "\n",
+      "0,0,2,1,1,4,4,7,2,9,4,10,12,7,6,6,11,12,9,15,15,6,6,13,5,12,9,6,4,7,7,6,5,4,1,4,2,2,2,1\n",
+      "\n",
+      "0,1,2,1,1,4,5,4,4,5,9,7,10,3,13,13,8,9,17,16,16,15,12,13,5,12,10,9,11,9,4,5,5,2,2,5,1,0,0,1\n",
+      "\n",
+      "0,0,1,3,2,3,6,4,5,7,2,4,11,11,3,8,8,16,5,13,16,5,8,8,6,9,10,10,9,3,3,5,3,5,4,5,3,3,0,1\n",
+      "\n",
+      "0,1,1,2,2,5,1,7,4,2,5,5,4,6,6,4,16,11,14,16,14,14,8,17,4,14,13,7,6,3,7,7,5,6,3,4,2,2,1,1\n",
+      "\n",
+      "0,1,1,1,4,1,6,4,6,3,6,5,6,4,14,13,13,9,12,19,9,10,15,10,9,10,10,7,5,6,8,6,6,4,3,5,2,1,1,1\n",
+      "\n",
+      "0,0,0,1,4,5,6,3,8,7,9,10,8,6,5,12,15,5,10,5,8,13,18,17,14,9,13,4,10,11,10,8,8,6,5,5,2,0,2,0\n",
+      "\n",
+      "0,0,1,0,3,2,5,4,8,2,9,3,3,10,12,9,14,11,13,8,6,18,11,9,13,11,8,5,5,2,8,5,3,5,4,1,3,1,1,0\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "all_paths = [\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_01.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_02.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_03.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_04.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_05.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_06.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_07.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_08.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_09.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_10.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_11.csv\",\n",
-    "  \"python/05_src/data/assignment_2_data/inflammation_12.csv\"\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_01.csv\", # CYC: I added r so these strings will not treat backslashes as escape characters.\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_02.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_03.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_04.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_05.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_06.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_07.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_08.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_09.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_10.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_11.csv\",\n",
+    "  r\"C:\\Users\\cyche\\OneDrive\\Desktop\\python\\inflammation_12.csv\"\n",
     "]\n",
     "\n",
     "with open(all_paths[0], 'r') as f:\n",
     "    # YOUR CODE HERE: Use the readline() or readlines() method to read the .csv file into a variable\n",
-    "    \n",
-    "    # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection"
+    "    all_rows = f.readlines()\n",
+    "\n",
+    "    # YOUR CODE HERE: Iterate through the variable using a for loop and print each row for inspection\n",
+    "    for indiv_row in all_rows:\n",
+    "       print(indiv_row)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "This file has 60 rows and 40 columns.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# CYC: I added this section of code just to check if it actually loaded correctly in terms of numbers of rows and columns on my end.\n",
+    "import numpy as np\n",
+    "data_load = np.loadtxt(all_paths[0], delimiter=',')\n",
+    "n_rows = data_load.shape[0]\n",
+    "n_cols = data_load.shape[1]\n",
+    "print(f\"This file has {n_rows} rows and {n_cols} columns.\")"
    ]
   },
   {
@@ -130,7 +300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "id": "82-bk4CBB1w4"
    },
@@ -145,12 +315,15 @@
     "    # 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=ax)\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=ax)\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=ax)\n",
     "\n",
     "    else:\n",
     "        # If the operation is not one of the expected values, raise an error\n",
@@ -161,11 +334,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "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",
@@ -173,6 +354,96 @@
     "print(len(data_min))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    id  min   mean   max\n",
+      "0    1  0.0  5.450  18.0\n",
+      "1    2  0.0  5.425  18.0\n",
+      "2    3  0.0  6.100  19.0\n",
+      "3    4  0.0  5.900  17.0\n",
+      "4    5  0.0  5.550  17.0\n",
+      "5    6  0.0  6.225  18.0\n",
+      "6    7  0.0  5.975  17.0\n",
+      "7    8  0.0  6.650  20.0\n",
+      "8    9  0.0  6.625  17.0\n",
+      "9   10  0.0  6.525  18.0\n",
+      "10  11  0.0  6.775  18.0\n",
+      "11  12  0.0  5.800  18.0\n",
+      "12  13  0.0  6.225  17.0\n",
+      "13  14  0.0  5.750  16.0\n",
+      "14  15  0.0  5.225  17.0\n",
+      "15  16  0.0  6.300  18.0\n",
+      "16  17  0.0  6.550  19.0\n",
+      "17  18  0.0  5.700  19.0\n",
+      "18  19  0.0  5.850  17.0\n",
+      "19  20  0.0  6.550  19.0\n",
+      "20  21  0.0  5.775  19.0\n",
+      "21  22  0.0  5.825  16.0\n",
+      "22  23  0.0  6.175  17.0\n",
+      "23  24  0.0  6.100  15.0\n",
+      "24  25  0.0  5.800  17.0\n",
+      "25  26  0.0  6.425  17.0\n",
+      "26  27  0.0  6.050  18.0\n",
+      "27  28  0.0  6.025  17.0\n",
+      "28  29  0.0  6.175  20.0\n",
+      "29  30  0.0  6.550  17.0\n",
+      "30  31  0.0  6.175  16.0\n",
+      "31  32  0.0  6.350  19.0\n",
+      "32  33  0.0  6.725  15.0\n",
+      "33  34  0.0  6.125  15.0\n",
+      "34  35  0.0  7.075  19.0\n",
+      "35  36  0.0  5.725  17.0\n",
+      "36  37  0.0  5.925  16.0\n",
+      "37  38  0.0  6.150  17.0\n",
+      "38  39  0.0  6.075  19.0\n",
+      "39  40  0.0  5.750  16.0\n",
+      "40  41  0.0  5.975  18.0\n",
+      "41  42  0.0  5.725  19.0\n",
+      "42  43  0.0  6.300  16.0\n",
+      "43  44  0.0  5.900  19.0\n",
+      "44  45  0.0  6.750  18.0\n",
+      "45  46  0.0  5.925  16.0\n",
+      "46  47  0.0  7.225  19.0\n",
+      "47  48  0.0  6.150  15.0\n",
+      "48  49  0.0  5.950  16.0\n",
+      "49  50  0.0  6.275  18.0\n",
+      "50  51  0.0  5.700  14.0\n",
+      "51  52  0.0  6.100  20.0\n",
+      "52  53  0.0  6.825  17.0\n",
+      "53  54  0.0  5.975  15.0\n",
+      "54  55  0.0  6.725  17.0\n",
+      "55  56  0.0  5.700  16.0\n",
+      "56  57  0.0  6.250  17.0\n",
+      "57  58  0.0  6.400  19.0\n",
+      "58  59  0.0  7.050  18.0\n",
+      "59  60  0.0  5.900  18.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "# CYC: I added this section of code just to get a quick look at each patient’s descriptive stats.\n",
+    "import pandas as pd # CYC: Not taught in the module, but a handy tool!\n",
+    " \n",
+    "data_mean = patient_summary(all_paths[0], 'mean')\n",
+    "data_max = patient_summary(all_paths[0], 'max')\n",
+    "\n",
+    "summary_table = pd.DataFrame({\n",
+    "    'id': range(1, len(data_mean)+1), # CYC: I applied +1 so ids start from 1 instead of 0.\n",
+    "    'min': data_min,\n",
+    "    'mean': data_mean,\n",
+    "    'max': data_max\n",
+    "})\n",
+    "\n",
+    "print(summary_table)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -228,7 +499,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {
     "id": "_svDiRkdIwiT"
    },
@@ -251,7 +522,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "metadata": {
     "id": "LEYPM5v4JT0i"
    },
@@ -261,21 +532,68 @@
     "\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",
-    "  return"
+    "    means = patient_summary(file_path, 'mean')\n",
+    "    return check_zeros(means)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "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",
     "print(detect_problems(all_paths[0]))"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "inflammation_01.csv is False\n",
+      "inflammation_02.csv is False\n",
+      "inflammation_03.csv is True\n",
+      "inflammation_04.csv is False\n",
+      "inflammation_05.csv is False\n",
+      "inflammation_06.csv is False\n",
+      "inflammation_07.csv is False\n",
+      "inflammation_08.csv is True\n",
+      "inflammation_09.csv is False\n",
+      "inflammation_10.csv is False\n",
+      "inflammation_11.csv is True\n",
+      "inflammation_12.csv is False\n"
+     ]
+    }
+   ],
+   "source": [
+    "# CYC: I added this section of code just to check all files.\n",
+    "import os\n",
+    "\n",
+    "for i, path in enumerate(all_paths, start=1):\n",
+    "    print(f\"{os.path.basename(path)} is {detect_problems(path)}\") # CYC: Interestingly, it looks like one patient with all 0s shows up in the last row of each of the three identified files."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Wishing a wonderful long weekend to the person reviewing my assignment!"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {
@@ -314,7 +632,8 @@
    "provenance": []
   },
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "dsi_participant",
+   "language": "python",
    "name": "python3"
   },
   "language_info": {
@@ -327,7 +646,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.9.19"
   }
  },
  "nbformat": 4,