diff --git a/Day-16/Indhu Subash.ipynb b/Day-16/Indhu Subash.ipynb
deleted file mode 100644
index cec8d76..0000000
--- a/Day-16/Indhu Subash.ipynb	
+++ /dev/null
@@ -1,98 +0,0 @@
-{
- "cells": [
-  {
-   "metadata": {},
-   "cell_type": "markdown",
-   "source": [
-    "# This is a sample Jupyter Notebook\n",
-    "\n",
-    "Below is an example of a code cell. \n",
-    "Put your cursor into the cell and press Shift+Enter to execute it and select the next one, or click 'Run Cell' button.\n",
-    "\n",
-    "Press Double Shift to search everywhere for classes, files, tool windows, actions, and settings.\n",
-    "\n",
-    "To learn more about Jupyter Notebooks in PyCharm, see [help](https://www.jetbrains.com/help/pycharm/ipython-notebook-support.html).\n",
-    "For an overview of PyCharm, go to Help -> Learn IDE features or refer to [our documentation](https://www.jetbrains.com/help/pycharm/getting-started.html)."
-   ],
-   "id": "8a77807f92f26ee"
-  },
-  {
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2024-12-20T12:21:53.769586Z",
-     "start_time": "2024-12-20T12:21:53.744373Z"
-    }
-   },
-   "cell_type": "code",
-   "source": [
-    "\"\"\"\n",
-    "AUTHOR : INDHU SUBASH\n",
-    "DATE : 20-12-2024\n",
-    "\"\"\"\n",
-    "student_ids = [102, 101, 105, 102, 101, 103, 104, 105]\n",
-    "unique_sorted_ids = sorted(set(student_ids))\n",
-    "unique_sorted_ids=set(unique_sorted_ids)\n",
-    "print(\"Unique and Sorted Student IDs:\", unique_sorted_ids)\n",
-    "\n",
-    "grades = (100,98,95,87,93)\n",
-    "average_grade = sum(grades) / len(grades)\n",
-    "print(f\"Grades : {grades}\")\n",
-    "print(\"Average Grade:\", average_grade)\n",
-    "\n",
-    "python_students = {\"Appu\", \"Abhijith\", \"Unni\", \"Abhishek\"}\n",
-    "machine_learning_students = {\"Unni\", \"Eve\", \"Abhishek\", \"Alice\"}\n",
-    "\n",
-    "common_students = python_students & machine_learning_students\n",
-    "print(\"Students attending both workshops:\", common_students)\n",
-    "\n",
-    "student_grades = {\n",
-    "    \"Appu\": (85, 90, 78),\n",
-    "    \"Abhijith\": (88, 76, 92),\n",
-    "    \"Unni\": (80, 85, 88),\n",
-    "}\n",
-    "\n",
-    "for student, grades in student_grades.items():\n",
-    "    average = sum(grades) / len(grades)\n",
-    "    print(f\"{student}'s Average Grade: {average:.2f}\")\n"
-   ],
-   "id": "fbc121e30a2defb3",
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Unique and Sorted Student IDs: {101, 102, 103, 104, 105}\n",
-      "Grades : (100, 98, 95, 87, 93)\n",
-      "Average Grade: 94.6\n",
-      "Students attending both workshops: {'Abhishek', 'Unni'}\n",
-      "Appu's Average Grade: 84.33\n",
-      "Abhijith's Average Grade: 85.33\n",
-      "Unni's Average Grade: 84.33\n"
-     ]
-    }
-   ],
-   "execution_count": 1
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 2
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython2",
-   "version": "2.7.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}