Assignment_Basics_of_Python.ipynb

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      "collapsed_sections": [
        "O1qaR1xhSmzD",
        "zVe_Aho3cN0B",
        "m1Kc07GieFzL"
      ],
      "authorship_tag": "ABX9TyMUUyWAx/TTn7rR58jEY1Su",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/arwoooooosh/Assignment---Basics-of-Python/blob/main/Assignment_Basics_of_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q1. L is a list defined as L= [11, 12, 13, 14].\n",
        "---"
      ],
      "metadata": {
        "id": "O1qaR1xhSmzD"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 54,
      "metadata": {
        "id": "NAgPspcnRrZb"
      },
      "outputs": [],
      "source": [
        "L = [11, 12, 13, 14]"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(i) WAP to add 50 and 60 to L.\n",
        "---"
      ],
      "metadata": {
        "id": "A_sRtLQaSWYU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L.extend([50,60])\n",
        "print(L)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ne57niBEVcTr",
        "outputId": "caeb11fb-ac16-4b11-9a9d-39a39e88665a"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[11, 12, 13, 14, 50, 60]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ii) WAP to remove 11 and 13 from L.\n",
        "---"
      ],
      "metadata": {
        "id": "0qhM9L3yW2Hx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L.remove(11)\n",
        "L.remove(13)\n",
        "print(L)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lvqoDj7DW8CS",
        "outputId": "c54b3a80-1250-44c9-c35d-682cd8b3d514"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[12, 14, 50, 60]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iii) WAP to sort L in ascending order.\n",
        "---"
      ],
      "metadata": {
        "id": "HI_aSZTsXJLK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L.sort()\n",
        "print(L)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T4CrFSalXNci",
        "outputId": "07fafa8a-d198-4a71-a611-1acc3fe70ec1"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[12, 14, 50, 60]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iv) WAP to sort L in descending order.\n",
        "---"
      ],
      "metadata": {
        "id": "jfg0TeIHXlQq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L.sort(reverse=True)\n",
        "print(L)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UoIi9XZiXtXp",
        "outputId": "0dd750cb-ddac-49b0-fb45-5a87b1b5169e"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[60, 50, 14, 12]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(v) WAP to search for 13 in L.\n",
        "---"
      ],
      "metadata": {
        "id": "7pZApivLXmpz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L.index(13)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 165
        },
        "id": "AibtVyAjX0vy",
        "outputId": "4446e809-acf4-4432-a04c-ee0fdb6416ca"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ValueError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-59-106875d11a64>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mL\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m13\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mValueError\u001b[0m: 13 is not in list"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(vi) WAP to count the number of elements present in L\n",
        "---"
      ],
      "metadata": {
        "id": "unSqQrcpYw3C"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(L)"
      ],
      "metadata": {
        "id": "zd7Nf4jNYx9p"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(vii) WAP to sum all the elements in L.\n",
        "---\n"
      ],
      "metadata": {
        "id": "uYRqO7DaZH2T"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sum(L)"
      ],
      "metadata": {
        "id": "qHVa8ZneZV2b"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(viii) WAP to sum all ODD numbers in L.\n",
        "---"
      ],
      "metadata": {
        "id": "QAsLKBCMZWUb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sum(num for num in L if num % 2 != 0)"
      ],
      "metadata": {
        "id": "aTw4NSPRZZOq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ix) WAP to sum all EVEN numbers in L.\n",
        "---"
      ],
      "metadata": {
        "id": "WkYJ5eCSZYQK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sum(num for num in L if num % 2 == 0)"
      ],
      "metadata": {
        "id": "DGegkJw_Zb7C"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(x) WAP to sum all PRIME numbers in L.\n",
        "---"
      ],
      "metadata": {
        "id": "UP0OY-h-ZcXq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def is_prime(num):\n",
        "    if num < 2:\n",
        "        return False\n",
        "    for i in range(2, int(num ** 0.5) + 1):\n",
        "        if num % i == 0:\n",
        "            return False\n",
        "    return True\n",
        "\n",
        "sum(num for num in L if is_prime(num))"
      ],
      "metadata": {
        "id": "pXEcM2u9ZdxS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(xi) WAP to clear all the elements in L.\n",
        "---"
      ],
      "metadata": {
        "id": "UqqFsZ9rZeGS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L.clear()\n",
        "L"
      ],
      "metadata": {
        "id": "FWk9EsfRZf6C"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(xii) WAP to delete L.\n",
        "---"
      ],
      "metadata": {
        "id": "mn_oiAoQZgTC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "del L"
      ],
      "metadata": {
        "id": "1M2mgZdoZg_K"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q2. D is a dictionary defined as D= {1:5.6, 2:7.8, 3:6.6, 4:8.7, 5:7.7}.\n",
        "---"
      ],
      "metadata": {
        "id": "zVe_Aho3cN0B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "D = {1: 5.6, 2: 7.8, 3: 6.6, 4: 8.7, 5: 7.7}"
      ],
      "metadata": {
        "id": "rdo-pvUTcUTi"
      },
      "execution_count": 68,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(i) WAP to add new entry in D; key=8 and value is 8.8\n",
        "---"
      ],
      "metadata": {
        "id": "_t2BntKhcgpy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "D[8] = 8.8\n",
        "D"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "puUiJu1gckwa",
        "outputId": "8f6de78d-844e-462c-9467-0647558474c5"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: 5.6, 2: 7.8, 3: 6.6, 4: 8.7, 5: 7.7, 8: 8.8}"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ii) WAP to remove key=2.\n",
        "---"
      ],
      "metadata": {
        "id": "3CVLjDeIclIq"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "del D[2]\n",
        "D"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7-AcHa5JcpgE",
        "outputId": "dcfdaeb4-72cb-41cd-e4c9-51cf79682e9d"
      },
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: 5.6, 3: 6.6, 4: 8.7, 5: 7.7}"
            ]
          },
          "metadata": {},
          "execution_count": 64
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iii) WAP to check whether 6 key is present in D.\n",
        "---"
      ],
      "metadata": {
        "id": "CR0KMm0dcqfr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "if 6 in D:\n",
        "    print(\"Key 6 is present in the dictionary.\")\n",
        "else:\n",
        "    print(\"Key 6 is not present in the dictionary.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wgvs510nctq0",
        "outputId": "83e7d323-0904-4172-ec53-df7f0559124f"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Key 6 is not present in the dictionary.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iv) WAP to count the number of elements present in D.\n",
        "---"
      ],
      "metadata": {
        "id": "15HBZf0scuir"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "len(D)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a_3s3yC5cuyT",
        "outputId": "b352b418-e5c9-4ea7-df73-a8df85a33c9a"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(v) WAP to add all the values present D.\n",
        "---"
      ],
      "metadata": {
        "id": "zvR2l0H2cvFb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sum(D.values())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jY3uuIWRcvR1",
        "outputId": "fe107f97-b364-4954-dcf1-a159a61835d7"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "36.4"
            ]
          },
          "metadata": {},
          "execution_count": 69
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(vi) WAP to update the value of 3 to 7.1.\n",
        "---"
      ],
      "metadata": {
        "id": "KauDwZ5qcvh8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "D[3] = 7.1\n",
        "D"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9KTxFQsecvtL",
        "outputId": "5dbde323-5c69-40e6-a9a0-99082edd363c"
      },
      "execution_count": 70,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1: 5.6, 2: 7.8, 3: 7.1, 4: 8.7, 5: 7.7}"
            ]
          },
          "metadata": {},
          "execution_count": 70
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(vii) WAP to clear the dictionary\n",
        "---"
      ],
      "metadata": {
        "id": "ZI_okK5Icv70"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "D.clear()\n",
        "D"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V39M7D42cwGT",
        "outputId": "6e3bb915-a45f-4880-df01-0326703306e6"
      },
      "execution_count": 71,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{}"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q3. S1 is a set defined as S1= [10, 20, 30, 40, 50, 60], S2 is a set defined as\n",
        "# S2= [40, 50, 60, 70, 80, 90].\n",
        "---\n"
      ],
      "metadata": {
        "id": "m1Kc07GieFzL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "S1 = {10, 20, 30, 40, 50, 60}\n",
        "S2 = {40, 50, 60, 70, 80, 90}"
      ],
      "metadata": {
        "id": "yLTym-fEn8VB"
      },
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(i) WAP to add 55 and 66 in Set S1.\n",
        "---\n"
      ],
      "metadata": {
        "id": "aXwZ0bvXn8fw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "S1.add(55)\n",
        "S1.add(66)\n",
        "S1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LRdnvdaFn8og",
        "outputId": "3a9739f8-1b5b-496e-e5ae-74765b8d3ca7"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{10, 20, 30, 40, 50, 55, 60, 66}"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ii) WAP to remove 10 and 30 from Set S1.\n",
        "---"
      ],
      "metadata": {
        "id": "7z-vSQj5n8xo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "S1.remove(10)\n",
        "S1.remove(30)\n",
        "S1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r4DGqJiOn84Y",
        "outputId": "9a780d60-8f3f-46e5-b335-8b67e1fae252"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{20, 40, 50, 55, 60, 66}"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iii) WAP to check whether 40 is present in S1.\n",
        "---"
      ],
      "metadata": {
        "id": "Z_9E8DqDn8_4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "if 40 in S1:\n",
        "    print(\"40 is present in Set S1.\")\n",
        "else:\n",
        "    print(\"40 is not present in Set S1.\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "tvfjFggmn9Fx",
        "outputId": "08985c59-32e7-416d-d6d7-ddc7ee553458"
      },
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40 is present in Set S1.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iv) WAP to find the union between S1 and S2.\n",
        "---"
      ],
      "metadata": {
        "id": "5tMEXW9En9NQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "S1.union(S2)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SFfpFzwTpllA",
        "outputId": "8d1edc19-86af-41b5-cff4-4d765c70f726"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{20, 40, 50, 55, 60, 66, 70, 80, 90}"
            ]
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(v) WAP to find the intersection between S1 and S2.\n",
        "---"
      ],
      "metadata": {
        "id": "yFeXM1_vpjjp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "S1.intersection(S2)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pViaNVb_pjuh",
        "outputId": "5ecedd77-f669-4a4f-9d7e-103754dd3005"
      },
      "execution_count": 87,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{40, 50, 60}"
            ]
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "--\n",
        "(vi) WAP to find the S1 - S2.\n",
        "---"
      ],
      "metadata": {
        "id": "627rMnmNpj3R"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "S1-S2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3e-ghFw2pkAx",
        "outputId": "7862f979-1534-43f9-f9e0-7059aabcb0fe"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{20, 55, 66}"
            ]
          },
          "metadata": {},
          "execution_count": 88
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q4. Write the following program\n",
        "---"
      ],
      "metadata": {
        "id": "A8qPwe8UporX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(i) WAP to print 100 random strings whose length between 6 and 8.\n",
        "---"
      ],
      "metadata": {
        "id": "Q5-5SjEGtR-4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "import string\n",
        "\n",
        "# Generate and print 100 random strings\n",
        "for _ in range(100):\n",
        "    length = random.randint(6, 8)\n",
        "    random_string = ''.join(random.choices(string.ascii_letters + string.digits, k=length))\n",
        "    print(random_string)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5Qn-IX4Cvc4A",
        "outputId": "caadca62-49af-474c-9929-81e23d8fa80e"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "pUthtTf\n",
            "AZ7FRO\n",
            "eb57VBDc\n",
            "ui0kBCwT\n",
            "PgAUOHh\n",
            "bUVYDYI\n",
            "zi2RNm\n",
            "ZLOdKBH\n",
            "bIWRtApb\n",
            "vn8Jrt\n",
            "EAioIH2x\n",
            "aIplAXTU\n",
            "zUjptkd\n",
            "fq30oG\n",
            "Y6hzE4\n",
            "xkEMup\n",
            "NOWJLa\n",
            "nrVaBlgX\n",
            "uzd7vFh\n",
            "uh0Mj3Kp\n",
            "2MDnnUu\n",
            "14qpb0k\n",
            "rE5zrBM\n",
            "WvSr7qE\n",
            "ez8Jabz3\n",
            "cBTZQ1o\n",
            "pD3F1Mo3\n",
            "Bl8R9ahV\n",
            "nD0Zqlw\n",
            "ljNiyr\n",
            "Xjia4ujK\n",
            "0SaEWO\n",
            "49mvFnG\n",
            "D1mZgb\n",
            "Nh9jQs2\n",
            "RaB3j87G\n",
            "2Cqs2fL\n",
            "eyABVARb\n",
            "tjTCr3\n",
            "aTC8zrL\n",
            "Zyb2Cbc\n",
            "6wofmS\n",
            "05ccTrrw\n",
            "MDz3e5QY\n",
            "Oz1i2K\n",
            "ozSa1Om\n",
            "RrRyCW\n",
            "01WsMx7\n",
            "MfhAPI\n",
            "0rTMDF\n",
            "0cDOO6\n",
            "kHxMLLFV\n",
            "dBNfPrvs\n",
            "byoVA5C2\n",
            "JWQF8xt\n",
            "aFrQtf\n",
            "fwMii7\n",
            "HWFvmVO\n",
            "7yuMW7PN\n",
            "HfHNJl8\n",
            "mK2GGD\n",
            "mA3q7pZr\n",
            "Mjx8uLQ\n",
            "6yKHmnfO\n",
            "W5wIckP\n",
            "KnobHL\n",
            "uQz152\n",
            "k0NWi3PI\n",
            "UE4Bde0k\n",
            "vJwybeJ\n",
            "lx2hYxl2\n",
            "UQ7OnJjO\n",
            "OYL6OA\n",
            "YMuaMI0V\n",
            "doQECD\n",
            "1mCXOnh\n",
            "Jo2M1B\n",
            "8QQz2C2\n",
            "9rjQg3SL\n",
            "4x1csnh\n",
            "w2pzuHu\n",
            "kHzvYx\n",
            "oXI08My\n",
            "qpYBVO7\n",
            "5fCA2mS\n",
            "AjmZvk\n",
            "sUkuLz\n",
            "WW2FkP\n",
            "RJqOKTBz\n",
            "1gCOGOXq\n",
            "XOrndGc\n",
            "R7V3uiL\n",
            "qVAXsvNq\n",
            "8ZJos8wW\n",
            "Bd9hFwfI\n",
            "IDCrFE\n",
            "5dfqf7\n",
            "5i6GHDr\n",
            "FtL6y34s\n",
            "f41nlp2s\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ii) WAP to print all prime numbers between 600 and 800\n",
        "---"
      ],
      "metadata": {
        "id": "VPxAT9-0vpdw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lower_limit = 600\n",
        "upper_limit = 800\n",
        "\n",
        "print(\"Prime numbers between\", lower_limit, \"and\", upper_limit, \"are:\")\n",
        "\n",
        "for num in range(lower_limit, upper_limit + 1):\n",
        "    if num > 1:\n",
        "        for i in range(2, int(num ** 0.5) + 1):\n",
        "            if (num % i) == 0:\n",
        "                break\n",
        "        else:\n",
        "            print(num)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vW0tl3-nvp4h",
        "outputId": "5d38b8af-e866-42da-9309-06516739f0a7"
      },
      "execution_count": 90,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Prime numbers between 600 and 800 are:\n",
            "601\n",
            "607\n",
            "613\n",
            "617\n",
            "619\n",
            "631\n",
            "641\n",
            "643\n",
            "647\n",
            "653\n",
            "659\n",
            "661\n",
            "673\n",
            "677\n",
            "683\n",
            "691\n",
            "701\n",
            "709\n",
            "719\n",
            "727\n",
            "733\n",
            "739\n",
            "743\n",
            "751\n",
            "757\n",
            "761\n",
            "769\n",
            "773\n",
            "787\n",
            "797\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iii) WAP to print all numbers between 100 and 1000 that are divisible by 7 and 9.\n",
        "---"
      ],
      "metadata": {
        "id": "5S_7RuGwvqNJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "lower_limit = 100\n",
        "upper_limit = 1000\n",
        "\n",
        "print(\"Numbers between\", lower_limit, \"and\", upper_limit, \"that are divisible by 7 and 9:\")\n",
        "\n",
        "for num in range(lower_limit, upper_limit + 1):\n",
        "    if num % 7 == 0 and num % 9 == 0:\n",
        "        print(num)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UWSoh0R_vqYg",
        "outputId": "0b2f9059-a058-42b3-d21d-1075d95a350a"
      },
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Numbers between 100 and 1000 that are divisible by 7 and 9:\n",
            "126\n",
            "189\n",
            "252\n",
            "315\n",
            "378\n",
            "441\n",
            "504\n",
            "567\n",
            "630\n",
            "693\n",
            "756\n",
            "819\n",
            "882\n",
            "945\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q5. WAP to create two lists of 10 random numbers between 10 and 30; Find\n",
        "---"
      ],
      "metadata": {
        "id": "tuGEDgNPytcA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "list1 = [random.randint(10, 30) for _ in range(10)]\n",
        "list2 = [random.randint(10, 30) for _ in range(10)]\n",
        "print(list1)\n",
        "print(list2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TD7m3CCcy4k4",
        "outputId": "1590f2b2-0f13-4bab-fe5c-08f3eebc26cd"
      },
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[24, 15, 19, 19, 24, 20, 21, 13, 29, 15]\n",
            "[15, 25, 26, 24, 13, 13, 19, 15, 28, 29]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(i) Common numbers in the two lists\n",
        "---"
      ],
      "metadata": {
        "id": "pXAWWfUjy-lp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "list(set(list1) & set(list2))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pqLWJeRSy-yJ",
        "outputId": "48ea98e9-75f3-4b5a-dee8-e3b0bba31e7f"
      },
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[17, 21, 23]"
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ii) Unique numbers in both the list\n",
        "---"
      ],
      "metadata": {
        "id": "AmM2RDALy_Fx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "list(set(list1) | set(list2))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I5wMC9k_y_Pp",
        "outputId": "f3056bd5-2e18-42e3-9361-416cbd19901b"
      },
      "execution_count": 100,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[12, 13, 16, 17, 18, 21, 22, 28, 29]"
            ]
          },
          "metadata": {},
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iii) Minimum in both the list\n",
        "---"
      ],
      "metadata": {
        "id": "xaZuuLExy_YB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "minimum_list1 = min(list1)\n",
        "minimum_list2 = min(list2)\n",
        "print(minimum_list1)\n",
        "print(minimum_list2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m93hWMVvy_ga",
        "outputId": "3ad9ab98-8075-43c2-c04c-32c3a05f59b6"
      },
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "12\n",
            "12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iv) Maximum in both the list\n",
        "---"
      ],
      "metadata": {
        "id": "_VyaVlhZy_pa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "maximum_list1 = max(list1)\n",
        "maximum_list2 = max(list2)\n",
        "print(maximum_list1)\n",
        "print(maximum_list2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xfkMx2jgy_x5",
        "outputId": "265543c5-e436-4528-dce8-0b4035d2e069"
      },
      "execution_count": 104,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "29\n",
            "30\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(v) Sum of both the lists\n",
        "---"
      ],
      "metadata": {
        "id": "AHgTs2u1y_5R"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sum(list1) + sum(list2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GhugWgIizAEp",
        "outputId": "e5717d45-e8c5-4b12-fec9-d21a02bfe372"
      },
      "execution_count": 106,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "406"
            ]
          },
          "metadata": {},
          "execution_count": 106
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q6. WAP to create a list of 100 random numbers between 100 and 900. Count and print the: \n",
        "---"
      ],
      "metadata": {
        "id": "Kqt3VlP839lC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "number_list = [random.randint(100, 900) for _ in range(100)]\n",
        "number_list"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gywfvbXw4rEQ",
        "outputId": "798be2ba-1f1b-4b73-c5f6-44ff3bda1b17"
      },
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[641,\n",
              " 310,\n",
              " 866,\n",
              " 537,\n",
              " 496,\n",
              " 524,\n",
              " 385,\n",
              " 881,\n",
              " 343,\n",
              " 211,\n",
              " 454,\n",
              " 385,\n",
              " 134,\n",
              " 141,\n",
              " 639,\n",
              " 209,\n",
              " 592,\n",
              " 552,\n",
              " 546,\n",
              " 843,\n",
              " 386,\n",
              " 686,\n",
              " 439,\n",
              " 430,\n",
              " 482,\n",
              " 448,\n",
              " 706,\n",
              " 169,\n",
              " 823,\n",
              " 155,\n",
              " 713,\n",
              " 899,\n",
              " 892,\n",
              " 140,\n",
              " 374,\n",
              " 638,\n",
              " 827,\n",
              " 535,\n",
              " 480,\n",
              " 817,\n",
              " 420,\n",
              " 311,\n",
              " 681,\n",
              " 763,\n",
              " 327,\n",
              " 574,\n",
              " 467,\n",
              " 355,\n",
              " 761,\n",
              " 291,\n",
              " 179,\n",
              " 618,\n",
              " 613,\n",
              " 349,\n",
              " 609,\n",
              " 428,\n",
              " 193,\n",
              " 570,\n",
              " 335,\n",
              " 314,\n",
              " 143,\n",
              " 732,\n",
              " 292,\n",
              " 820,\n",
              " 215,\n",
              " 562,\n",
              " 692,\n",
              " 890,\n",
              " 122,\n",
              " 451,\n",
              " 390,\n",
              " 159,\n",
              " 207,\n",
              " 830,\n",
              " 386,\n",
              " 398,\n",
              " 776,\n",
              " 513,\n",
              " 167,\n",
              " 454,\n",
              " 351,\n",
              " 325,\n",
              " 851,\n",
              " 830,\n",
              " 597,\n",
              " 702,\n",
              " 461,\n",
              " 706,\n",
              " 791,\n",
              " 214,\n",
              " 607,\n",
              " 319,\n",
              " 167,\n",
              " 299,\n",
              " 319,\n",
              " 278,\n",
              " 309,\n",
              " 485,\n",
              " 287,\n",
              " 491]"
            ]
          },
          "metadata": {},
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(i) All odd numbers\n",
        "---"
      ],
      "metadata": {
        "id": "ZCYcCymi4vSh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "odd_numbers = [num for num in number_list if num % 2 != 0]\n",
        "print(odd_numbers)\n",
        "print(len(odd_numbers))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "t-zLpg6I6CxJ",
        "outputId": "02000cc1-433d-4ef3-cba4-1c6bae381249"
      },
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[321, 113, 445, 309, 219, 415, 275, 847, 665, 685, 299, 227, 627, 571, 883, 827, 291, 721, 883, 863, 647, 103, 621, 543, 711, 133, 433, 867, 603, 633, 561, 251, 881, 531, 527, 455, 597, 425, 271, 499, 533, 143, 803, 575]\n",
            "44\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(ii) All even numbers\n",
        "---"
      ],
      "metadata": {
        "id": "hER59BRG6ZtB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "even_numbers = [num for num in number_list if num % 2 == 0]\n",
        "print(even_numbers)\n",
        "print(len(even_numbers))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JkgtjFKo6DZR",
        "outputId": "7ef28cf5-e780-48a3-9429-1e7b55845b68"
      },
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[310, 866, 496, 524, 454, 134, 592, 552, 546, 386, 686, 430, 482, 448, 706, 892, 140, 374, 638, 480, 420, 574, 618, 428, 570, 314, 732, 292, 820, 562, 692, 890, 122, 390, 830, 386, 398, 776, 454, 830, 702, 706, 214, 278]\n",
            "44\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "(iii) All prime numbers\n",
        "---"
      ],
      "metadata": {
        "id": "o92v_QYs6Dlh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def is_prime(num):\n",
        "    if num < 2:\n",
        "        return False\n",
        "    for i in range(2, int(num ** 0.5) + 1):\n",
        "        if num % i == 0:\n",
        "            return False\n",
        "    return True\n",
        "\n",
        "prime_numbers = [num for num in number_list if is_prime(num)]\n",
        "print(prime_numbers)\n",
        "print(len(prime_numbers))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K0AffmH-6DvJ",
        "outputId": "ed511e23-6677-433a-92b2-8179e092dabf"
      },
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[641, 881, 211, 439, 823, 827, 311, 467, 761, 179, 613, 349, 193, 167, 461, 607, 167, 491]\n",
            "18\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q7. D is a dictionary defined as D={1:\"One\",2:\"Two\",3:\"Three\",4:\"Four\", 5:\"Five\"}.\n",
        "# WAP to read all the keys and values from dictionary and write to the file in the given below format.\n",
        "Key1, Value1\n",
        "\n",
        "Key2, Value2 \n",
        "\n",
        "Key3, Value3\n",
        "\n",
        "---"
      ],
      "metadata": {
        "id": "acTjlUaO8mFR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "D = {1: \"One\", 2: \"Two\", 3: \"Three\", 4: \"Four\", 5: \"Five\"}\n",
        "\n",
        "\n",
        "with open(\"output.txt\", \"w\") as file:\n",
        "    for key, value in D.items():\n",
        "        file.write(f\"{key}, {value}\\n\")\n"
      ],
      "metadata": {
        "id": "DJhe9Gp09PR4"
      },
      "execution_count": 116,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q8. L is a list defined as L={\"One\",\"Two\",\"Three\",\"Four\",\"Five\"}.\n",
        "# WAP to count the length of reach element from a list and write to the file in the given below format:\n",
        "\n",
        "One, 3\n",
        "\n",
        "Two, 3\n",
        "\n",
        "Four, 4\n",
        "\n",
        "---"
      ],
      "metadata": {
        "id": "4EzNei8A9zkP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "L = [\"One\", \"Two\", \"Three\", \"Four\", \"Five\"]\n",
        "\n",
        "with open(\"output.txt\", \"w\") as file:\n",
        "    for element in L:\n",
        "        length = len(element)\n",
        "        file.write(f\"{element}, {length}\\n\")\n"
      ],
      "metadata": {
        "id": "Vi7qBYFw-HQY"
      },
      "execution_count": 117,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q9. Write to the file 100 random strings whose length between 10 and 15.\n",
        "---"
      ],
      "metadata": {
        "id": "Co11r_b9-cyJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import random\n",
        "import string\n",
        "\n",
        "def generate_random_string():\n",
        "    length = random.randint(10, 15)\n",
        "    letters = string.ascii_letters + string.digits + string.punctuation\n",
        "    return ''.join(random.choice(letters) for _ in range(length))\n",
        "\n",
        "with open(\"output.txt\", \"w\") as file:\n",
        "    for _ in range(100):\n",
        "        random_string = generate_random_string()\n",
        "        file.write(random_string + \"\\n\")\n"
      ],
      "metadata": {
        "id": "qOZHZ0Yu-wSS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q10. Write to the file all prime numbers between 600 and 800.\n",
        "---"
      ],
      "metadata": {
        "id": "KvoEt9Aq-6kY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def is_prime(num):\n",
        "    if num < 2:\n",
        "        return False\n",
        "    for i in range(2, int(num ** 0.5) + 1):\n",
        "        if num % i == 0:\n",
        "            return False\n",
        "    return True\n",
        "\n",
        "with open(\"output.txt\", \"w\") as file:\n",
        "    for num in range(600, 801):\n",
        "        if is_prime(num):\n",
        "            file.write(str(num) + \"\\n\")\n"
      ],
      "metadata": {
        "id": "xkyNeeo5-66h"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q11. WAP to calculate the time taken by a program.\n",
        "---"
      ],
      "metadata": {
        "id": "YqgKN2Zb_Sqp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import time\n",
        "\n",
        "start_time = time.time()\n",
        "\n",
        "end_time = time.time()\n",
        "\n",
        "elapsed_time = end_time - start_time\n",
        "\n",
        "print(\"Time taken:\", elapsed_time, \"seconds\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "923P-Q3U_WuB",
        "outputId": "192d092b-e929-4ff6-bdcf-c3d5c7716778"
      },
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Time taken: 4.458427429199219e-05 seconds\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q12. WAP to sort following number of elements in a list, calculate time taken and plot the graph.\n",
        "Number of elements in list, Time Taken\n",
        "\n",
        "5k, T1\n",
        "\n",
        "10k, T2\n",
        "\n",
        "15k, T3\n",
        "\n",
        "20k, T4\n",
        "\n",
        "25k, T5\n",
        "\n",
        "---"
      ],
      "metadata": {
        "id": "tsufveNf_27h"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import time\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def sort_list(num_elements):\n",
        "    # Generate a list of random numbers\n",
        "    my_list = [random.randint(1, 100) for _ in range(num_elements)]\n",
        "    \n",
        "    # Start the timer\n",
        "    start_time = time.time()\n",
        "    \n",
        "    # Sort the list\n",
        "    my_list.sort()\n",
        "    \n",
        "    # End the timer\n",
        "    end_time = time.time()\n",
        "    \n",
        "    # Calculate the time taken\n",
        "    elapsed_time = end_time - start_time\n",
        "    \n",
        "    return elapsed_time\n",
        "\n",
        "# Define the number of elements and corresponding labels\n",
        "num_elements = [5000, 10000, 15000, 20000, 25000]\n",
        "time_taken = [0, 0, 0, 0, 0]  # Placeholder list to store the time taken\n",
        "\n",
        "# Iterate over the number of elements and corresponding time labels\n",
        "for i in range(len(num_elements)):\n",
        "    # Sort the list and measure the time taken\n",
        "    time_taken[i] = sort_list(num_elements[i])\n",
        "\n",
        "# Plot the graph\n",
        "plt.plot(num_elements, time_taken, marker=\"o\")\n",
        "plt.xlabel(\"Number of Elements\")\n",
        "plt.ylabel(\"Time Taken (seconds)\")\n",
        "plt.title(\"Sorting Time\")\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 472
        },
        "id": "_ypjrrMwAln4",
        "outputId": "a3a0a0b7-9451-4dfa-827a-fb58136b87af"
      },
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "---\n",
        "# Q13. WAP to create a dictionary of student marks in five subjects and you have to find the student having maximum and minimum average marks.\n",
        "---"
      ],
      "metadata": {
        "id": "2fjgSGxfGEW6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Dictionary of student marks\n",
        "student_marks = {\n",
        "    \"Alice\": [85, 90, 92, 88, 87],\n",
        "    \"Bob\": [92, 87, 85, 90, 89],\n",
        "    \"Charlie\": [78, 82, 80, 85, 88],\n",
        "    \"David\": [90, 85, 92, 86, 88],\n",
        "    \"Eve\": [88, 86, 90, 92, 85]\n",
        "}\n",
        "\n",
        "# Calculate the average marks for each student\n",
        "average_marks = {}\n",
        "for student, marks in student_marks.items():\n",
        "    average_marks[student] = sum(marks) / len(marks)\n",
        "\n",
        "# Find the student with maximum and minimum average marks\n",
        "max_student = max(average_marks, key=average_marks.get)\n",
        "min_student = min(average_marks, key=average_marks.get)\n",
        "\n",
        "# Print the results\n",
        "print(\"Student with Maximum Average Marks:\")\n",
        "print(f\"Student: {max_student}\")\n",
        "print(f\"Average Marks: {average_marks[max_student]}\")\n",
        "\n",
        "print(\"\\nStudent with Minimum Average Marks:\")\n",
        "print(f\"Student: {min_student}\")\n",
        "print(f\"Average Marks: {average_marks[min_student]}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jmFmujsPGOjQ",
        "outputId": "84eebc11-6fb2-48f2-bb1c-3b4a0b715289"
      },
      "execution_count": 126,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Student with Maximum Average Marks:\n",
            "Student: Bob\n",
            "Average Marks: 88.6\n",
            "\n",
            "Student with Minimum Average Marks:\n",
            "Student: Charlie\n",
            "Average Marks: 82.6\n"
          ]
        }
      ]
    }
  ]
}