diff --git a/.ipynb_checkpoints/argument-checkpoint.ipynb b/.ipynb_checkpoints/argument-checkpoint.ipynb
index 23ebdd8..8a134f1 100644
--- a/.ipynb_checkpoints/argument-checkpoint.ipynb
+++ b/.ipynb_checkpoints/argument-checkpoint.ipynb
@@ -96,7 +96,7 @@
     "\n",
     "# Load the dataset\n",
     "def pandas(pd):\n",
-    "    file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\")  \n",
+    "     df = pd.read_csv('Fast_Food_Dataset/nutrition.csv')\n",
     "\n",
     "   \n",
     "\n",
@@ -106,14 +106,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "id": "heated-blade",
    "metadata": {},
    "outputs": [],
    "source": [
     "#check first 15 rows\n",
     "def data (read_csv):\n",
-    "    data.head(15)"
+    "    data.head(15)\n",
+    "\n",
+    "\n",
+    "\n"
    ]
   },
   {
@@ -195,14 +198,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 8,
    "id": "negative-highlight",
    "metadata": {},
    "outputs": [],
    "source": [
     "#######################################################################\n",
-    "def file_path():\n",
-    "    file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\") \n",
+    "\n",
+    "# Calculate calories from fat (assuming fat column is in grams)\n",
+    "# Formula: fat_grams * 9 calories per gram\n",
+    "def first_15():\n",
+    "    first_15['fat_calories']= first_15['fat'] * 9\n",
+    "\n",
     "### \n",
     "### Your data analysis may include a statistic and/or a data visualization\n",
     "#######################################################################"
@@ -210,24 +217,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "id": "victorian-burning",
    "metadata": {},
    "outputs": [
     {
-     "ename": "NameError",
-     "evalue": "name 'pd' is not defined",
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (2142274504.py, line 2)",
      "output_type": "error",
      "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m file_path \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFast_Food_Dataset/nutrition.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
+      "\u001b[0;36m  Cell \u001b[0;32mIn[16], line 2\u001b[0;36m\u001b[0m\n\u001b[0;31m    def first_15('item', 'fat', 'fat_calories', 'calories'):\u001b[0m\n\u001b[0m                 ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
      ]
     }
    ],
    "source": [
-    "file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\")"
+    "# Display relevant columns\n",
+    "def first_15('item', 'fat', 'fat_calories', 'calories'):\n",
+    "    return first_15"
    ]
   },
   {
diff --git a/argument.ipynb b/argument.ipynb
index 23ebdd8..8a134f1 100644
--- a/argument.ipynb
+++ b/argument.ipynb
@@ -96,7 +96,7 @@
     "\n",
     "# Load the dataset\n",
     "def pandas(pd):\n",
-    "    file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\")  \n",
+    "     df = pd.read_csv('Fast_Food_Dataset/nutrition.csv')\n",
     "\n",
     "   \n",
     "\n",
@@ -106,14 +106,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "id": "heated-blade",
    "metadata": {},
    "outputs": [],
    "source": [
     "#check first 15 rows\n",
     "def data (read_csv):\n",
-    "    data.head(15)"
+    "    data.head(15)\n",
+    "\n",
+    "\n",
+    "\n"
    ]
   },
   {
@@ -195,14 +198,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 8,
    "id": "negative-highlight",
    "metadata": {},
    "outputs": [],
    "source": [
     "#######################################################################\n",
-    "def file_path():\n",
-    "    file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\") \n",
+    "\n",
+    "# Calculate calories from fat (assuming fat column is in grams)\n",
+    "# Formula: fat_grams * 9 calories per gram\n",
+    "def first_15():\n",
+    "    first_15['fat_calories']= first_15['fat'] * 9\n",
+    "\n",
     "### \n",
     "### Your data analysis may include a statistic and/or a data visualization\n",
     "#######################################################################"
@@ -210,24 +217,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "id": "victorian-burning",
    "metadata": {},
    "outputs": [
     {
-     "ename": "NameError",
-     "evalue": "name 'pd' is not defined",
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (2142274504.py, line 2)",
      "output_type": "error",
      "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m file_path \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241m.\u001b[39mread_csv(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFast_Food_Dataset/nutrition.csv\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'pd' is not defined"
+      "\u001b[0;36m  Cell \u001b[0;32mIn[16], line 2\u001b[0;36m\u001b[0m\n\u001b[0;31m    def first_15('item', 'fat', 'fat_calories', 'calories'):\u001b[0m\n\u001b[0m                 ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"
      ]
     }
    ],
    "source": [
-    "file_path = pd.read_csv(\"Fast_Food_Dataset/nutrition.csv\")"
+    "# Display relevant columns\n",
+    "def first_15('item', 'fat', 'fat_calories', 'calories'):\n",
+    "    return first_15"
    ]
   },
   {