TuplePython2.ipynb

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      "authorship_tag": "ABX9TyPbsgDs8GSwd+PqzO1eHhGx",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "language_info": {
      "name": "python"
    }
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  "cells": [
    {
      "cell_type": "markdown",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/gayatrriiii/Build-A-Quiz-App-With-HTML-CSS-and-JavaScript/blob/master/TuplePython2.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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        },
        "id": "uAGTn9K3_afs",
        "outputId": "19b288cf-9602-4404-d1ce-721e2f4816e9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(23, 34, 56, 4.5, 6.7)\n",
            "<class 'tuple'>\n"
          ]
        }
      ],
      "source": [
        "#tuple\n",
        "\n",
        "t1 = (23,34,56,4.5,6.7)\n",
        "print(t1)\n",
        "print(type(t1))"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t1[0]\n"
      ],
      "metadata": {
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        "id": "pWKRMN5dACva",
        "outputId": "6fd86b66-c616-4aa2-97d4-a1d691d62eeb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "23"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t1[-1]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9X6XPrO5AQG8",
        "outputId": "3417816e-fba1-480f-e772-a246f8219882"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6.7"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t1[2:4]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5CqE_sLGARbN",
        "outputId": "0cc5dfe0-3212-4ab4-87a2-43cad095e0d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(56, 4.5)"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t1[0]=100"
      ],
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        },
        "id": "YdEjdHlRAacm",
        "outputId": "7bdbf4e0-c397-4bf5-e24f-ae9b79ef54a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-9-7cb4489bea4f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mt1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m100\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m: 'tuple' object does not support item assignment"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#modifying/editing a tuple\n",
        "#create tuple\n",
        "t2 = tuple((34,56,78))\n",
        "t2"
      ],
      "metadata": {
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      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(34, 56, 78)"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "l1 = list(t2)"
      ],
      "metadata": {
        "id": "S2V679pvA-HR"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "l1"
      ],
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          "base_uri": "https://localhost:8080/"
        },
        "id": "aNQ48IXGBMd0",
        "outputId": "715b6703-ebc4-4cad-ee53-e1a5bda16fe9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[34, 56, 78]"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "l1.append(100)\n",
        "#convert back to tuple\n",
        "t2 = tuple(l1)\n",
        "t2"
      ],
      "metadata": {
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(34, 56, 78, 100)"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t1 = (1,2,3,[1,2],4)\n",
        "t1[3][0]=9  #modifying data\n",
        "print(t1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c5A0VeerBmtN",
        "outputId": "943162d7-6d42-40bf-82a8-c7e864d55c62"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(1, 2, 3, [9, 2], 4)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t2.count(100)\n",
        "            "
      ],
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      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t2.index(34)"
      ],
      "metadata": {
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        },
        "id": "zRine2xECE8N",
        "outputId": "9ed828ae-590e-44b8-b2ef-1902cf5d9add"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#unpacking the tuple\n",
        "fruits = (\"apple\", \"banana\", \"cherry\")\n",
        "fruits"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E3SJl4TsCHtv",
        "outputId": "7ce1d417-167e-481e-f33f-e4b01313e9f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "('apple', 'banana', 'cherry')"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "(a,b,c) = fruits\n",
        "print(a,b,c)"
      ],
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          "base_uri": "https://localhost:8080/"
        },
        "id": "acykN1pBCheo",
        "outputId": "ae55692a-81b2-4092-c920-e4ef4c172cf8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "apple banana cherry\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Sets\n",
        "set1 = {11,22,'apple','cherry'}\n",
        "print(set1)\n",
        "print(type(set1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RykqYOupCnkO",
        "outputId": "559a4c30-63c4-4f24-ed8e-4ecb7105f920"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'apple', 'cherry', 11, 22}\n",
            "<class 'set'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "set1[2]=55"
      ],
      "metadata": {
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        },
        "id": "-m6dX1PaEFnk",
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-22-966eebaa503a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mset1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m55\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m: 'set' object does not support item assignment"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "set1[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 166
        },
        "id": "IQrTaHwvEqic",
        "outputId": "f486e8fc-6e97-4eee-ad0c-66f627cc0095"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "TypeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-23-c38563f1af7a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mset1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;31mTypeError\u001b[0m: 'set' object is not subscriptable"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "set1 = {11,11,22,22,'apple','cherry'}"
      ],
      "metadata": {
        "id": "Gz2nAG4YEuCs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "set1 #no duplicates allowed"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7slpe2OSEzEO",
        "outputId": "b32a4ffa-d04b-4927-9383-fa9cc3557b69"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{11, 22, 'apple', 'cherry'}"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('apple' in set1)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BXZnX8uREzop",
        "outputId": "d66b0d54-0d4a-473d-9a11-62121aeb8e22"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#convert into set\n",
        "set2 = set(l1)\n",
        "set2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jQfSpXh7E9Nu",
        "outputId": "e86b0b19-bde0-4827-c555-51792a495670"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{34, 56, 78, 100}"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#set methods\n",
        "set2.add(\"hello\")\n",
        "set2\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a7vcXvPgFJg4",
        "outputId": "b300555d-125d-4df0-898f-db2e9b2406b9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{100, 34, 56, 78, 'hello'}"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "set2.update(set1)\n",
        "set2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H8TEYfOeFk7j",
        "outputId": "f0497400-e2a5-4932-d266-7166e1953e32"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{100, 11, 22, 34, 56, 78, 'apple', 'cherry', 'hello'}"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "set2.remove(55) #error\n",
        "set2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 183
        },
        "id": "U9dyUflHF-lA",
        "outputId": "218e1d88-5fc6-4ef7-d471-ea9c938e87f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "error",
          "ename": "KeyError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-31-20555bbcb8bb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mset2\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mremove\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m55\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mset2\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 55"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "set2.discard(55) #no error even when element not present in the set\n",
        "set2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8W_AyhgLGLL-",
        "outputId": "7b1886b9-df8b-484d-f29f-26d76ebd8313"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{100, 11, 22, 34, 56, 'apple', 'cherry', 'hello'}"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#set operations\n",
        "\n",
        "x = {1,2,3,4,5}\n",
        "y = {4,5,6,7,8}\n",
        "\n"
      ],
      "metadata": {
        "id": "gDU3IlvpGXvi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "A.union(B) #duplicates removed"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kisequQ8HZc0",
        "outputId": "a6be0a6c-830d-4d3a-889a-cd847b14ba9d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1, 2, 3, 4, 5, 6, 7, 8}"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "B.union(A)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bC5_3VroHbYy",
        "outputId": "0ab4cec0-45a0-4042-b981-839b5661eceb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1, 2, 3, 4, 5, 6, 7, 8}"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "A.intersection(B) #common elements\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kUT-yOnSHgVc",
        "outputId": "c273bf95-cfb4-40f9-8d41-8571b2d1e626"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{4, 5}"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x.intersection_update(y)\n",
        "x"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xMfnO2iWHnYU",
        "outputId": "d63783c9-b9b8-4030-ed63-043e70078d8f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{4, 5}"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#difference\n",
        "A.difference(B) #all elements in one which aint in other"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "j92bpkorIB7k",
        "outputId": "17ce652c-63fe-4baf-bd4e-8585bf7674b3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1, 2, 3}"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "B.difference(A)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IFz45cXQISf1",
        "outputId": "ccbc2649-ecca-424b-b54c-5f2af9d34727"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{6, 7, 8}"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "A.symmetric_difference(B)  #uncommon elements"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cIjp1Wk1Immb",
        "outputId": "b290192e-8220-48ca-ac4b-3163dd60d8fe"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{1, 2, 3, 6, 7, 8}"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "para1=\"\"\"Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data. These insights can be used to guide decision making and strategic planning.\n",
        "\n",
        "The accelerating volume of data sources, and subsequently data has made data science is one of the fastest growing field across every industry. As a result, it is no surprise that the role of the data scientist was dubbed the “sexiest job of the 21st century” by Harvard Business Review (link resides outside of IBM). Organizations are increasingly reliant on them to interpret data and provide actionable recommendations to improve business outcomes.\n",
        "The data science lifecycle involves various roles, tools, and processes, which enables analysts to glean actionable insights. Typically, a data science project undergoes the following stages\n",
        "\"\"\"\n"
      ],
      "metadata": {
        "id": "HpaJdy6dIwAG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "para2=\"\"\"Data analytics is the science of \n",
        "analyzing raw data to make conclusions about that information. Many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption.\n",
        "\"\"\""
      ],
      "metadata": {
        "id": "iw-f-l4aKNJk"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "para1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "J1E0X4LALUDb",
        "outputId": "52763fac-3802-420d-e338-afbc1f8d8cf2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data. These insights can be used to guide decision making and strategic planning.\\n\\nThe accelerating volume of data sources, and subsequently data has made data science is one of the fastest growing field across every industry. As a result, it is no surprise that the role of the data scientist was dubbed the “sexiest job of the 21st century” by Harvard Business Review (link resides outside of IBM). Organizations are increasingly reliant on them to interpret data and provide actionable recommendations to improve business outcomes.\\nThe data science lifecycle involves various roles, tools, and processes, which enables analysts to glean actionable insights. Typically, a data science project undergoes the following stages\\n'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#removing unwanted char from both para\n",
        "text1 = para1.lower()\n",
        "text1 = text1.replace('\\n','')\n",
        "text1 = text1.replace(',','')\n",
        "text1 = text1.replace(':','')\n",
        "text1 = text1.replace('.','')\n",
        "text1 = text1.replace('/','')\n",
        "text1 = text1.replace('\"','')\n",
        "\n",
        "text2= para2.lower()\n",
        "text2 = text2.replace('\\n','')\n",
        "text2 = text2.replace(',','')\n",
        "text2 = text2.replace(':','')\n",
        "text2 = text2.replace('.','')\n",
        "text2 = text2.replace('/','')\n",
        "text2 = text2.replace('\"','')\n",
        "\n"
      ],
      "metadata": {
        "id": "QCbJVK1MLVu9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(text1)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bxEpCaI8MGJ5",
        "outputId": "b339eed6-5011-4600-fac9-8616eb79e779"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data science combines math and statistics specialized programming advanced analytics artificial intelligence (ai) and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data these insights can be used to guide decision making and strategic planningthe accelerating volume of data sources and subsequently data has made data science is one of the fastest growing field across every industry as a result it is no surprise that the role of the data scientist was dubbed the “sexiest job of the 21st century” by harvard business review (link resides outside of ibm) organizations are increasingly reliant on them to interpret data and provide actionable recommendations to improve business outcomesthe data science lifecycle involves various roles tools and processes which enables analysts to glean actionable insights typically a data science project undergoes the following stages\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(text2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0ziKs6doNGZz",
        "outputId": "302fad59-b51a-446a-bc50-44f1f24a56ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data analytics is the science of analyzing raw data to make conclusions about that information many of the techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#find unique words in text1\n",
        "words1 = text1.split()\n",
        "words1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B8CYXMdgMIeT",
        "outputId": "6dca54be-e51f-433d-d64d-4932fc4d4f9e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['data',\n",
              " 'science',\n",
              " 'combines',\n",
              " 'math',\n",
              " 'and',\n",
              " 'statistics',\n",
              " 'specialized',\n",
              " 'programming',\n",
              " 'advanced',\n",
              " 'analytics',\n",
              " 'artificial',\n",
              " 'intelligence',\n",
              " '(ai)',\n",
              " 'and',\n",
              " 'machine',\n",
              " 'learning',\n",
              " 'with',\n",
              " 'specific',\n",
              " 'subject',\n",
              " 'matter',\n",
              " 'expertise',\n",
              " 'to',\n",
              " 'uncover',\n",
              " 'actionable',\n",
              " 'insights',\n",
              " 'hidden',\n",
              " 'in',\n",
              " 'an',\n",
              " 'organization’s',\n",
              " 'data',\n",
              " 'these',\n",
              " 'insights',\n",
              " 'can',\n",
              " 'be',\n",
              " 'used',\n",
              " 'to',\n",
              " 'guide',\n",
              " 'decision',\n",
              " 'making',\n",
              " 'and',\n",
              " 'strategic',\n",
              " 'planningthe',\n",
              " 'accelerating',\n",
              " 'volume',\n",
              " 'of',\n",
              " 'data',\n",
              " 'sources',\n",
              " 'and',\n",
              " 'subsequently',\n",
              " 'data',\n",
              " 'has',\n",
              " 'made',\n",
              " 'data',\n",
              " 'science',\n",
              " 'is',\n",
              " 'one',\n",
              " 'of',\n",
              " 'the',\n",
              " 'fastest',\n",
              " 'growing',\n",
              " 'field',\n",
              " 'across',\n",
              " 'every',\n",
              " 'industry',\n",
              " 'as',\n",
              " 'a',\n",
              " 'result',\n",
              " 'it',\n",
              " 'is',\n",
              " 'no',\n",
              " 'surprise',\n",
              " 'that',\n",
              " 'the',\n",
              " 'role',\n",
              " 'of',\n",
              " 'the',\n",
              " 'data',\n",
              " 'scientist',\n",
              " 'was',\n",
              " 'dubbed',\n",
              " 'the',\n",
              " '“sexiest',\n",
              " 'job',\n",
              " 'of',\n",
              " 'the',\n",
              " '21st',\n",
              " 'century”',\n",
              " 'by',\n",
              " 'harvard',\n",
              " 'business',\n",
              " 'review',\n",
              " '(link',\n",
              " 'resides',\n",
              " 'outside',\n",
              " 'of',\n",
              " 'ibm)',\n",
              " 'organizations',\n",
              " 'are',\n",
              " 'increasingly',\n",
              " 'reliant',\n",
              " 'on',\n",
              " 'them',\n",
              " 'to',\n",
              " 'interpret',\n",
              " 'data',\n",
              " 'and',\n",
              " 'provide',\n",
              " 'actionable',\n",
              " 'recommendations',\n",
              " 'to',\n",
              " 'improve',\n",
              " 'business',\n",
              " 'outcomesthe',\n",
              " 'data',\n",
              " 'science',\n",
              " 'lifecycle',\n",
              " 'involves',\n",
              " 'various',\n",
              " 'roles',\n",
              " 'tools',\n",
              " 'and',\n",
              " 'processes',\n",
              " 'which',\n",
              " 'enables',\n",
              " 'analysts',\n",
              " 'to',\n",
              " 'glean',\n",
              " 'actionable',\n",
              " 'insights',\n",
              " 'typically',\n",
              " 'a',\n",
              " 'data',\n",
              " 'science',\n",
              " 'project',\n",
              " 'undergoes',\n",
              " 'the',\n",
              " 'following',\n",
              " 'stages']"
            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(words1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "skKB8kGEM3M7",
        "outputId": "a0904718-3469-4bae-c935-e28a2dbe9fa8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(words1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SEHBlXMxNLMj",
        "outputId": "8bc438b0-ab74-41c6-94c3-21ac782329fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "138"
            ]
          },
          "metadata": {},
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# to set\n",
        "unq_words1 = set(words1)\n",
        "print(unq_words1)\n",
        "print(len(unq_words1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5PdjAY6pNMil",
        "outputId": "2743aca5-7d60-4fa1-8d0c-61a02dcb3d64"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'no', 'advanced', 'scientist', 'of', 'science', 'accelerating', 'increasingly', 'job', '(link', 'the', 'matter', 'century”', 'combines', 'growing', 'hidden', 'dubbed', 'enables', 'outside', 'can', 'used', 'it', 'intelligence', 'to', 'which', 'an', 'fastest', 'subsequently', 'undergoes', 'analytics', 'made', 'was', 'these', 'them', 'roles', 'learning', 'strategic', 'with', 'as', 'in', 'making', 'uncover', 'planningthe', 'various', 'guide', 'role', 'processes', 'decision', 'insights', 'improve', 'industry', 'lifecycle', 'across', 'glean', 'be', 'typically', 'are', 'a', 'math', 'programming', '21st', 'subject', 'is', 'and', 'actionable', 'result', 'resides', 'data', 'specialized', 'specific', 'by', '(ai)', 'involves', 'provide', 'machine', 'that', 'artificial', 'organizations', '“sexiest', 'interpret', 'surprise', 'organization’s', 'ibm)', 'one', 'following', 'stages', 'review', 'tools', 'has', 'project', 'outcomesthe', 'statistics', 'expertise', 'analysts', 'every', 'reliant', 'harvard', 'field', 'business', 'sources', 'on', 'volume', 'recommendations'}\n",
            "102\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "words2= text2.split()\n",
        "words2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nQY7B3YoNWE0",
        "outputId": "ac6ab8f3-53b0-4dc5-8c5e-e5f0957e8c02"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['data',\n",
              " 'analytics',\n",
              " 'is',\n",
              " 'the',\n",
              " 'science',\n",
              " 'of',\n",
              " 'analyzing',\n",
              " 'raw',\n",
              " 'data',\n",
              " 'to',\n",
              " 'make',\n",
              " 'conclusions',\n",
              " 'about',\n",
              " 'that',\n",
              " 'information',\n",
              " 'many',\n",
              " 'of',\n",
              " 'the',\n",
              " 'techniques',\n",
              " 'and',\n",
              " 'processes',\n",
              " 'of',\n",
              " 'data',\n",
              " 'analytics',\n",
              " 'have',\n",
              " 'been',\n",
              " 'automated',\n",
              " 'into',\n",
              " 'mechanical',\n",
              " 'processes',\n",
              " 'and',\n",
              " 'algorithms',\n",
              " 'that',\n",
              " 'work',\n",
              " 'over',\n",
              " 'raw',\n",
              " 'data',\n",
              " 'for',\n",
              " 'human',\n",
              " 'consumption']"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "type(words2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SXKFBvOQNn_X",
        "outputId": "9b7bb283-ab40-4236-a2de-6d3d43d42c02"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {},
          "execution_count": 67
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(words2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s515VDxqNqgE",
        "outputId": "d052cdea-0b74-4776-9b14-e58638d5560e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "40"
            ]
          },
          "metadata": {},
          "execution_count": 68
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "unq_words2 = set(words2)\n",
        "print(unq_words2)\n",
        "print(len(unq_words2))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O5OYUORHNr1y",
        "outputId": "37501303-1be8-4d01-a20e-5d56b5773354"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'about', 'mechanical', 'make', 'many', 'and', 'consumption', 'of', 'science', 'automated', 'techniques', 'been', 'into', 'have', 'data', 'the', 'processes', 'conclusions', 'work', 'algorithms', 'that', 'to', 'for', 'analytics', 'information', 'analyzing', 'human', 'over', 'is', 'raw'}\n",
            "29\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#lexical diversity = No of words/No of unique words\n",
        "\n",
        "ld1 = len(words1)/len(unq_words1)\n",
        "\n",
        "ld1\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ew3D8u3ONzt0",
        "outputId": "6b1fb5a4-2961-42a4-882b-42dc3c91d938"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.3529411764705883"
            ]
          },
          "metadata": {},
          "execution_count": 71
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ld2 = len(words2)/len(unq_words2)\n",
        "ld2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YcjUsoENONMe",
        "outputId": "204bcb04-3817-4672-9318-86c4bc2ef4e7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1.3793103448275863"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#print common words in para1 and para2\n",
        "print(unq_words1.intersection(unq_words2))\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "syfMNRrkOVMH",
        "outputId": "d760a442-29b0-4cbb-e4bb-6d758c501299"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'data', 'the', 'analytics', 'that', 'processes', 'and', 'of', 'science', 'to', 'is'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(unq_words1.intersection(unq_words2)))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k1QztHbMOvwO",
        "outputId": "510e686f-6c2a-4b77-87ff-350fe8d159b0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(unq_words1.difference(unq_words2)) #words in para1 not in para 2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bPDp-hSFO2Lu",
        "outputId": "1ad05569-6b51-495e-e4fe-ed187a970535"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'no', 'advanced', 'scientist', 'accelerating', 'increasingly', 'job', '(link', 'matter', 'century”', 'combines', 'growing', 'hidden', 'dubbed', 'enables', 'outside', 'can', 'used', 'it', 'intelligence', 'which', 'an', 'fastest', 'subsequently', 'undergoes', 'made', 'was', 'these', 'them', 'roles', 'learning', 'strategic', 'with', 'as', 'in', 'making', 'uncover', 'planningthe', 'various', 'guide', 'role', 'decision', 'insights', 'improve', 'industry', 'lifecycle', 'across', 'glean', 'be', 'typically', 'are', 'a', 'math', 'programming', '21st', 'subject', 'actionable', 'result', 'resides', 'specialized', 'specific', 'by', '(ai)', 'involves', 'provide', 'machine', 'artificial', 'organizations', '“sexiest', 'interpret', 'surprise', 'organization’s', 'ibm)', 'one', 'following', 'stages', 'review', 'tools', 'has', 'project', 'outcomesthe', 'statistics', 'expertise', 'analysts', 'every', 'reliant', 'harvard', 'field', 'business', 'sources', 'on', 'volume', 'recommendations'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#list of uncommon words in both\n",
        "print(unq_words1.symmetric_difference(unq_words2))\n",
        "print(len((unq_words1.symmetric_difference(unq_words2))))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-clc_IisPC1P",
        "outputId": "771ef6e7-f408-481f-e18a-c299348e8402"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'no', 'about', 'make', 'many', 'advanced', 'actionable', 'consumption', 'scientist', 'accelerating', 'increasingly', 'techniques', 'job', 'result', '(link', 'resides', 'have', 'matter', 'specialized', 'century”', 'combines', 'growing', 'hidden', 'dubbed', 'specific', 'by', 'enables', 'work', 'outside', '(ai)', 'involves', 'provide', 'can', 'machine', 'algorithms', 'artificial', 'used', 'it', 'intelligence', 'organizations', 'which', 'an', 'fastest', 'subsequently', '“sexiest', 'undergoes', 'on', 'human', 'volume', 'made', 'was', 'raw', 'these', 'them', 'roles', 'learning', 'mechanical', 'interpret', 'strategic', 'with', 'as', 'in', 'making', 'uncover', 'planningthe', 'automated', 'surprise', 'various', 'been', 'into', 'guide', 'organization’s', 'role', 'ibm)', 'conclusions', 'decision', 'one', 'insights', 'following', 'stages', 'review', 'improve', 'industry', 'lifecycle', 'across', 'tools', 'glean', 'be', 'typically', 'has', 'project', 'outcomesthe', 'statistics', 'expertise', 'analysts', 'are', 'every', 'a', 'for', 'math', 'reliant', 'programming', 'information', 'harvard', 'field', 'business', '21st', 'analyzing', 'sources', 'subject', 'recommendations', 'over'}\n",
            "111\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#dictionary\n",
        "\n",
        "student = {'id': 12, 'Name':'John', 'Branch':'IT'}\n",
        "print(student)\n",
        "print(type(student))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EmvxHAgTPoF6",
        "outputId": "398102f3-7ccd-4d6d-a013-e245d5c4a651"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'id': 12, 'Name': 'John', 'Branch': 'IT'}\n",
            "<class 'dict'>\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "student.items()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rROtyf9GWue1",
        "outputId": "9679cf31-8732-487f-c3e5-139828e21102"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_items([('id', 12), ('Name', 'John'), ('Branch', 'IT')])"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "student.keys()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ws7SnxdrXLwT",
        "outputId": "c4789472-6375-4983-aae4-91d760bb019c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_keys(['id', 'Name', 'Branch'])"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "student.values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yXHswK8aXZrj",
        "outputId": "a779ffc7-e968-412c-bcb0-7c6378a6183c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_values([12, 'John', 'IT'])"
            ]
          },
          "metadata": {},
          "execution_count": 84
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#access a key value pair\n",
        "student['Name']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "aOLhoeLzXdIJ",
        "outputId": "56a5731c-cd68-461c-912c-5193701fea49"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'John'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 85
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "student['Branch']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "61Clg_caXghP",
        "outputId": "f9de45e3-7f66-454d-a692-40220449abec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'IT'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 86
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "student.get('Name')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "Q-SVEBkKXioQ",
        "outputId": "e095acd9-74ed-43aa-ce59-e710a87c1208"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'John'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 87
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#change the key value\n",
        "student['Name'] = 'Harry'"
      ],
      "metadata": {
        "id": "sn-CLWNqXvSg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "student.items()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Wb4tOVVfX-8w",
        "outputId": "5383d1c4-6d5a-4098-ae6c-171cac205040"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_items([('id', 12), ('Name', 'Harry'), ('Branch', 'IT')])"
            ]
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "student['Branch'] = 'Mechanical'\n",
        "student.items()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "12sSN47yYARA",
        "outputId": "7a51f2a0-2ac1-43c5-c651-d992ea843312"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_items([('id', 12), ('Name', 'Harry'), ('Branch', 'Mechanical')])"
            ]
          },
          "metadata": {},
          "execution_count": 90
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#add new key value pair\n",
        "student['Age'] = 22\n",
        "student"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MVNqgfEfYEcA",
        "outputId": "8e691b91-2c19-4ac7-9b93-5c62bff97477"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'id': 12, 'Name': 'Harry', 'Branch': 'Mechanical', 'Age': 22}"
            ]
          },
          "metadata": {},
          "execution_count": 91
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#membership operation\n",
        "print('Branch' in student)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8IYYXoUPYZt-",
        "outputId": "05363052-875b-4f84-ed54-f53e2ea7b003"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "True\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#pop methhod\n",
        "student.pop('Age')\n",
        "student"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0tvrIlbMY23Q",
        "outputId": "c7013b16-3541-477a-d248-967ceba4814a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'id': 12, 'Name': 'Harry', 'Branch': 'Mechanical'}"
            ]
          },
          "metadata": {},
          "execution_count": 95
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#multiple values in dictionary\n",
        "\n",
        "players={'Name':['Virat', 'Rohit', 'Dhoni'], \n",
        "         'Age':[31,32,33],\n",
        "         'Designation':['Captain','VC','WK'], \n",
        "         'Role': \"Cricketers\"}"
      ],
      "metadata": {
        "id": "2QIU_IgdY9wg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "players"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WRccExLEZomf",
        "outputId": "1f6b969d-77fd-43e4-e914-d4047e3afb87"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Name': ['Virat', 'Rohit', 'Dhoni'],\n",
              " 'Age': [31, 32, 33],\n",
              " 'Designation': ['Captain', 'VC', 'WK'],\n",
              " 'Role': 'Cricketers'}"
            ]
          },
          "metadata": {},
          "execution_count": 97
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(players)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G_HbI9yDZp8X",
        "outputId": "bb743a52-c03f-47cd-ff68-4064fa2678be"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4"
            ]
          },
          "metadata": {},
          "execution_count": 98
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "players['Name']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i9TPd13RZtJF",
        "outputId": "537dffff-9b31-498b-902b-a53db74c7b22"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Virat', 'Rohit', 'Dhoni']"
            ]
          },
          "metadata": {},
          "execution_count": 99
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#access particular element by their index\n",
        "players['Name'][0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "WBrs1pjKZ0xn",
        "outputId": "c6b43d34-29d5-4edd-85ae-cc8cfdb3017a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Virat'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 100
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "players['Age'][1] = 55\n",
        "players"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Z4TT92LaAN4",
        "outputId": "3e629002-52a5-4d4d-c130-7eac263bd389"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Name': ['Virat', 'Rohit', 'Dhoni'],\n",
              " 'Age': [31, 55, 33],\n",
              " 'Designation': ['Captain', 'VC', 'WK'],\n",
              " 'Role': 'play'}"
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "players.update({'Role': 'play'})"
      ],
      "metadata": {
        "id": "bJM4U_xhaRBr"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "players"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2c4Fjpdtafrv",
        "outputId": "883679c2-fe58-43ee-d833-6c8014442e84"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Name': ['Virat', 'Rohit', 'Dhoni'],\n",
              " 'Age': [31, 32, 33],\n",
              " 'Designation': ['Captain', 'VC', 'WK'],\n",
              " 'Role': 'play'}"
            ]
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#conditional statements\n",
        "#if-else\n",
        "a = 10\n",
        "b = 5\n",
        "if a > 5:\n",
        "  print('a is greater')\n",
        "else:\n",
        "  print('b is greater')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7p5jfdNEagvm",
        "outputId": "d9b5ddea-dede-443e-da38-d0b732cae938"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "a is greater\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = input('Enter first number')\n",
        "b = input('Enter second number')\n",
        "print(a + b)\n",
        "if a > b:\n",
        "  print('a is greater')\n",
        "else:\n",
        "  print('b is greateR')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7lB-zRtjbkvk",
        "outputId": "c708e205-4cf6-48b7-e45c-683f9514c832"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter first number10\n",
            "Enter second number20\n",
            "1020\n",
            "b is greateR\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = int(input('Enter first number'))\n",
        "b = int(input('Enter second number'))\n",
        "print(a + b)\n",
        "if a > b:\n",
        "  print('a is greater')\n",
        "else:\n",
        "  print('b is greateR')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RMNeVNofcPKk",
        "outputId": "ec30d501-79b8-4c65-ba31-0409009d7d6d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter first number10\n",
            "Enter second number10\n",
            "20\n",
            "b is greateR\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#check if one can vote or not\n",
        "\n",
        "age = int(input('Please enter your age: '))\n",
        "if age >= 18:\n",
        "  print('Yes, you can vote!')\n",
        "else:\n",
        "  print(\"Sorry, you can't vote!\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PVBGIoj6ch65",
        "outputId": "67b61dea-baa8-45c7-9c76-04f542824e5d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Please enter your age: 18\n",
            "Yes, you can vote!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#print student marksheet\n",
        "#checking  multiple conditions\n",
        "marks = int(input('Enter Marks'))\n",
        "if marks >= 90:\n",
        "  print('A Grade')\n",
        "elif marks < 90 and marks >= 80:\n",
        "  print('B Grade')\n",
        "elif marks < 80 and marks >= 70:\n",
        "  print('C Grade')\n",
        "else:\n",
        "  print('Try Next Time')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e7zOB3zPc8Vw",
        "outputId": "33bb55d5-0cd4-419c-acf3-a3c3bdbacfb6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter Marks30\n",
            "Try Next Time\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#employee salary\n",
        "\n",
        "salary = int(input('Enter your salary:'))\n",
        "if salary<20000 and salary >= 10000:\n",
        "  salary = salary + salary * 0.20 + 10000\n",
        "elif salary < 10000 and salary >= 5000:\n",
        "  salary = salary+salary*0.30+5000\n",
        "  \n",
        "\n",
        "else:\n",
        "  salary = salary+salary*0.40+2500\n",
        "print(salary)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8PU582p1ehpk",
        "outputId": "945f7ee3-3bd5-4302-9eb9-a015aa9edaf6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter your salary:10000\n",
            "22000.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#Project - store username and pass\n",
        "#ask user to enter his username and pass - if credential matches, welcome\n",
        "#else if wrong then ask user for signup, update that data in my storage\n",
        "\n",
        "cred={'Rohit': 'rohit01',\n",
        "      'Virat': 'virat02',\n",
        "      'Kapil': 'sharma23',}\n",
        "cred.keys()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XMrqDFumfcuY",
        "outputId": "ebf257ab-32bd-4217-f5d5-2ddf67a5ed08"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_keys(['Rohit', 'Virat', 'Kapil'])"
            ]
          },
          "metadata": {},
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cred.values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yacYvhtxhywR",
        "outputId": "daf707dd-5f5c-449b-aba5-2fd7c1293ace"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dict_values(['rohit01', 'virat02', 'sharma23'])"
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "username = input('Please enter your username:')\n",
        "password = input('Please enter your password:')\n",
        "\n",
        "if username not in cred.keys():\n",
        "  print('Username is not in the database!')\n",
        "  ask = input('Would you like to signup? y/n:')\n",
        "  if ask.lower() == 'y':\n",
        "    username = input('Please enter your username:')\n",
        "    password = input('Please enter your password:')\n",
        "\n",
        "    cred.update({username:password})\n",
        "    print('Account added successfully!')\n",
        "    print(cred)\n",
        "  else:\n",
        "    print('Thankyou!!')\n",
        "elif cred[username] == password:\n",
        "  print('Hello {} welcome'.format(username) )\n",
        "else:\n",
        "  print('username or password is incorrect')\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q7sdJ91ah4SA",
        "outputId": "548db22e-5c4d-403b-c764-00053471d715"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Please enter your username:gayatri\n",
            "Please enter your password:gayatri\n",
            "Username is not in the database!\n",
            "Would you like to signup? y/n:y\n",
            "Please enter your username:gayatri\n",
            "Please enter your password:bhosale\n",
            "Account added successfully!\n",
            "{'Rohit': 'rohit01', 'Virat': 'virat02', 'Kapil': 'sharma23', 'gayatri': 'bhosale'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cred\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pSb2-T5EjvwR",
        "outputId": "ec73ae4b-e591-4061-b3bf-01cff7f491a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'Rohit': 'rohit01',\n",
              " 'Virat': 'virat02',\n",
              " 'Kapil': 'sharma23',\n",
              " 'gayatri': 'bhosale'}"
            ]
          },
          "metadata": {},
          "execution_count": 127
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#loops\n",
        "list1 = [23,45,67,89]\n",
        "for i in list1:\n",
        "  print(i)\n",
        "  "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RLzn_Y-Hk8Fd",
        "outputId": "0c87a793-8e70-473f-ccee-a7bf89da7d2f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "23\n",
            "45\n",
            "67\n",
            "89\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "t1 = (23,45,67,67)\n",
        "for i in t1:\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lPs1DcPLlSfD",
        "outputId": "0d04b134-c183-4a24-a78c-bf46e70794a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "23\n",
            "45\n",
            "67\n",
            "67\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#break keyword\n",
        "list1 = [23,45,67,-1,89]\n",
        "for i in list1:\n",
        "  if i < 0:\n",
        "    break #breaks current execution\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wPsLxLI4lcr0",
        "outputId": "e1614ff9-1b7f-49d1-e6f6-066e2adbad78"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "23\n",
            "45\n",
            "67\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#continue keyword\n",
        "\n",
        "list1 = [23,45,-2, -22, 67,-1,89, -99]\n",
        "for i in list1:\n",
        "  if i < 0:\n",
        "    continue #breaks current execution\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pcVr5FNxl1B5",
        "outputId": "b79fa112-6d08-49b6-bac1-f2ad94c09d0b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "23\n",
            "45\n",
            "67\n",
            "89\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "list2 = [10,10,10]\n",
        "sum = 0\n",
        "for i in list2:\n",
        "  sum += i\n",
        "print(sum)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "J3cDJxSNmJsN",
        "outputId": "d083fb81-0727-4dc0-c1bf-96df57b4b6ef"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "30\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(10):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Kqih_h5_mkBx",
        "outputId": "5d89bad7-27fc-451c-d181-57d5c2f7da08"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "5\n",
            "6\n",
            "7\n",
            "8\n",
            "9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(20,31):\n",
        "    print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aXk5p0evnViW",
        "outputId": "aae04bbb-7a22-4e29-d7ce-75d9c8c6457e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "20\n",
            "21\n",
            "22\n",
            "23\n",
            "24\n",
            "25\n",
            "26\n",
            "27\n",
            "28\n",
            "29\n",
            "30\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "vQXluINzn7CQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(2,20,2):\n",
        "  print(i)\n",
        "  "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E6yDSnSEna-S",
        "outputId": "7ea6bf73-0b60-4198-81d1-18371aa360fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2\n",
            "4\n",
            "6\n",
            "8\n",
            "10\n",
            "12\n",
            "14\n",
            "16\n",
            "18\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "number = int(input('Enter number'))\n",
        "for i in range(1,11):\n",
        "  print(f'{number} * {i} = {number*i}')\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4gSQy_VInlSB",
        "outputId": "5d8322ca-1768-4961-d52f-f13ffd4385ec"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter number5\n",
            "5 * 1 = 5\n",
            "5 * 2 = 10\n",
            "5 * 3 = 15\n",
            "5 * 4 = 20\n",
            "5 * 5 = 25\n",
            "5 * 6 = 30\n",
            "5 * 7 = 35\n",
            "5 * 8 = 40\n",
            "5 * 9 = 45\n",
            "5 * 10 = 50\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#for loop w else\n",
        "cars = ['tata','bmw','honda']\n",
        "for i in range(len(cars)):\n",
        "  print(\"I like\", cars[i])\n",
        "else:\n",
        "  print('No items left in list')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mP9JUHoDojD_",
        "outputId": "dc65f021-842c-4825-a6de-9e91744b4814"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "I like tata\n",
            "I like bmw\n",
            "I like honda\n",
            "No items left in list\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "i = 1\n",
        "while i <= 10:\n",
        "  print(i)\n",
        "  i += 1\n",
        "  "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ydWb3rcGpEN3",
        "outputId": "963e8ef9-87f0-4af2-d5db-ec187331882b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1\n",
            "2\n",
            "3\n",
            "4\n",
            "5\n",
            "6\n",
            "7\n",
            "8\n",
            "9\n",
            "10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "i = 10\n",
        "while i >= 1:\n",
        "  print(i)\n",
        "  i -= 1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aYBqKFNCp-o9",
        "outputId": "cf0141a6-d736-462c-f4d8-58d0c3b3750b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10\n",
            "9\n",
            "8\n",
            "7\n",
            "6\n",
            "5\n",
            "4\n",
            "3\n",
            "2\n",
            "1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#python session 3\n",
        "#program to enter list elements through user\n",
        "\n",
        "list1 = []\n",
        "#input from user \n",
        "n = int(input('Enter number of elements in the list:'))\n",
        "for i in range(0, n):\n",
        "  print('Enter the elements no {}'.format(i+1))\n",
        "  element = int(input())\n",
        "  list1.append(element)\n",
        "print('The entered list is \\n', list1)\n",
        "4"
      ],
      "metadata": {
        "id": "wmM3icNaqN4L",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "49122aea-ba51-44c5-90dd-2b1fdef7e27f"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter number of elements in the list:5\n",
            "Enter the elements no 1\n",
            "2\n",
            "Enter the elements no 2\n",
            "3\n",
            "Enter the elements no 3\n",
            "4\n",
            "Enter the elements no 4\n",
            "5\n",
            "Enter the elements no 5\n",
            "6\n",
            "The entered list is \n",
            " [2, 3, 4, 5, 6]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#create random numbers  #pip install random\n",
        "\n",
        "import random\n",
        "rand = []\n",
        "for i in range(100):\n",
        "  num = random.randint(0,100) #creates random integers numbers list \n",
        "  rand.append(num)\n",
        "print(rand)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JNnDoi5RCMAy",
        "outputId": "6d339056-e979-4852-a93f-b62336d1c877"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4, 57, 6, 99, 12, 14, 100, 88, 77, 39, 94, 57, 74, 82, 12, 45, 62, 23, 48, 22, 14, 46, 68, 0, 34, 86, 50, 43, 34, 36, 12, 10, 5, 48, 58, 76, 12, 74, 65, 33, 75, 66, 73, 98, 23, 12, 85, 79, 68, 50, 16, 47, 15, 34, 83, 90, 96, 98, 21, 87, 72, 31, 44, 16, 4, 85, 77, 66, 63, 95, 15, 91, 87, 38, 46, 11, 35, 73, 70, 84, 5, 17, 1, 100, 8, 0, 71, 11, 46, 100, 90, 61, 30, 38, 59, 99, 53, 97, 97, 79]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#find and create a list of even numbers in this rand list\n",
        "\n",
        "rand2 = []\n",
        "for i in rand:\n",
        "  if i != 0:\n",
        "    if i%2 == 0:\n",
        "      rand2.append(i)\n",
        "print(rand2)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "06N0DN3-DcyS",
        "outputId": "b9be99ef-970d-4043-9178-268a3202dec0"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[4, 6, 12, 14, 100, 88, 94, 74, 82, 12, 62, 48, 22, 14, 46, 68, 34, 86, 50, 34, 36, 12, 10, 48, 58, 76, 12, 74, 66, 98, 12, 68, 50, 16, 34, 90, 96, 98, 72, 44, 16, 4, 66, 38, 46, 70, 84, 100, 8, 46, 100, 90, 30, 38]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#create a list of numbers divisible by 5\n",
        "\n",
        "rand3 = []\n",
        "for i in rand:\n",
        "  if i%5 == 0:\n",
        "    rand3.append(i)\n",
        "print(rand3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Owu6gVQZFHkG",
        "outputId": "c3944c72-eaaf-4a72-dd6d-be0e24961746"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[100, 45, 0, 50, 10, 5, 65, 75, 85, 50, 15, 90, 85, 95, 15, 35, 70, 5, 100, 0, 100, 90, 30]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#use for loop with dictionary\n",
        "emp = {'empid':1, 'name':'Rohit','Dept':'HR','Address': 'Mumbai'}\n",
        "\n",
        "for key in emp.keys():  #iterating over loop \n",
        "  print('key is',key,'maps to',emp[key])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8vlkU3slGFHN",
        "outputId": "678f4d62-f384-4b73-95ee-b70985c1a583"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "key is empid maps to 1\n",
            "key is name maps to Rohit\n",
            "key is Dept maps to HR\n",
            "key is Address maps to Mumbai\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#else with while loop\n",
        "\n",
        "numbers=[10,20,30,40,50]\n",
        "\n",
        "index = 0\n",
        "while index < len(numbers):\n",
        "  print(numbers[index])\n",
        "  index += 1\n",
        "  print('current index', index)\n",
        "else:\n",
        "  print('\\n empty now')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cdC3aaf4Hb1x",
        "outputId": "5e39431b-7c4e-4cc1-ea5b-27b27eda3a56"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10\n",
            "current index 1\n",
            "20\n",
            "current index 2\n",
            "30\n",
            "current index 3\n",
            "40\n",
            "current index 4\n",
            "50\n",
            "current index 5\n",
            "\n",
            " empty now\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "text=\"\"\"Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data. This analysis helps data scientists to ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results.\n",
        "\"\"\"\n"
      ],
      "metadata": {
        "id": "uc5nVS1qIIP5"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "text\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "id": "JkAKFvKUIzmp",
        "outputId": "1699e16f-6728-4ccb-b84c-2a49b80ca458"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data. This analysis helps data scientists to ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results.\\n'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#list of words from text that starts with 'e'\n",
        "#list of words from text that ends with 's'\n",
        "#print words till word 'analysis'\n",
        "\n",
        "text1 = text.split()\n",
        "text1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lw8XVyajI1bT",
        "outputId": "5bc2d8a4-311a-44b5-e851-6b9068de38b1"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Data',\n",
              " 'science',\n",
              " 'is',\n",
              " 'the',\n",
              " 'study',\n",
              " 'of',\n",
              " 'data',\n",
              " 'to',\n",
              " 'extract',\n",
              " 'meaningful',\n",
              " 'insights',\n",
              " 'for',\n",
              " 'business.',\n",
              " 'It',\n",
              " 'is',\n",
              " 'a',\n",
              " 'multidisciplinary',\n",
              " 'approach',\n",
              " 'that',\n",
              " 'combines',\n",
              " 'principles',\n",
              " 'and',\n",
              " 'practices',\n",
              " 'from',\n",
              " 'the',\n",
              " 'fields',\n",
              " 'of',\n",
              " 'mathematics,',\n",
              " 'statistics,',\n",
              " 'artificial',\n",
              " 'intelligence,',\n",
              " 'and',\n",
              " 'computer',\n",
              " 'engineering',\n",
              " 'to',\n",
              " 'analyze',\n",
              " 'large',\n",
              " 'amounts',\n",
              " 'of',\n",
              " 'data.',\n",
              " 'This',\n",
              " 'analysis',\n",
              " 'helps',\n",
              " 'data',\n",
              " 'scientists',\n",
              " 'to',\n",
              " 'ask',\n",
              " 'and',\n",
              " 'answer',\n",
              " 'questions',\n",
              " 'like',\n",
              " 'what',\n",
              " 'happened,',\n",
              " 'why',\n",
              " 'it',\n",
              " 'happened,',\n",
              " 'what',\n",
              " 'will',\n",
              " 'happen,',\n",
              " 'and',\n",
              " 'what',\n",
              " 'can',\n",
              " 'be',\n",
              " 'done',\n",
              " 'with',\n",
              " 'the',\n",
              " 'results.']"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in text1:\n",
        "  if i[0] == 'e':\n",
        "    print(i)\n",
        "  "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IUXJhCDaJpV7",
        "outputId": "6e96dc85-01c2-4c24-b1de-074233bde446"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "extract\n",
            "engineering\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "end_e = []\n",
        "for words in text1:\n",
        "  if words.endswith('e'):\n",
        "    end_e.append(words)\n",
        "end_e"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kwJw0lAgJ5c_",
        "outputId": "5f00ec1a-e6bd-4b82-824f-bc267ffc6f2e"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['science', 'the', 'the', 'analyze', 'large', 'like', 'be', 'done', 'the']"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in text1:\n",
        "  if i == \"analysis\":\n",
        "      break\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mbsf5GMKLuAT",
        "outputId": "e8f02689-d22c-44a2-f231-894e181f4be4"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Data\n",
            "science\n",
            "is\n",
            "the\n",
            "study\n",
            "of\n",
            "data\n",
            "to\n",
            "extract\n",
            "meaningful\n",
            "insights\n",
            "for\n",
            "business.\n",
            "It\n",
            "is\n",
            "a\n",
            "multidisciplinary\n",
            "approach\n",
            "that\n",
            "combines\n",
            "principles\n",
            "and\n",
            "practices\n",
            "from\n",
            "the\n",
            "fields\n",
            "of\n",
            "mathematics,\n",
            "statistics,\n",
            "artificial\n",
            "intelligence,\n",
            "and\n",
            "computer\n",
            "engineering\n",
            "to\n",
            "analyze\n",
            "large\n",
            "amounts\n",
            "of\n",
            "data.\n",
            "This\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#funtions\n",
        "\n",
        "def display():\n",
        "  ''' It prints hello world'''\n",
        "  print('hello world')\n",
        "#calling the function\n",
        "\n",
        "display()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8u8mPLawMXZK",
        "outputId": "b6f56264-1546-40ac-b8e1-6106345bf953"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "hello world\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#add two numbers\n",
        "def add(x,y):\n",
        "  return x + y"
      ],
      "metadata": {
        "id": "piZA_HtCOV32"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "add(123,566)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p2OZ2nfgPs3F",
        "outputId": "6be94dd1-c711-4bf8-e804-595c76781e72"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "689"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "add(1,78987)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u5e-JBSFPxVZ",
        "outputId": "ac8a752a-a3da-4569-c53a-923b35e16507"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "78988"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#create a function to do square of a number\n",
        "def square(a):\n",
        "  return a*a\n",
        "  "
      ],
      "metadata": {
        "id": "1qxC2E85P1Dv"
      },
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "square(4)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Oi6KKdzRQVoS",
        "outputId": "45ddc5a4-34b8-4786-f6f9-b0fa8c7d4aae"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#create sum of elements of a given range(1,25)\n",
        "\n",
        "def sum(a,b):\n",
        "  result = 0\n",
        "  for i in range(a,b+1):\n",
        "    result += i\n",
        "  \n",
        "  print('sum of numbers from {} to {} is {}'.format(a,b,result)) "
      ],
      "metadata": {
        "id": "YIgdGXqMQW5w"
      },
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sum(100,300)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "n5-ek_DhRFP5",
        "outputId": "27a812bc-7e08-4b8f-8761-e13cbb33015d"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of numbers from 100 to 300 is 40200\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#return multiple value to variables\n",
        "def square_cube(num):\n",
        "  print(num)\n",
        "  return num*num, num**3\n"
      ],
      "metadata": {
        "id": "siB54wruRKN6"
      },
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "square,cube = square_cube(4)\n",
        "print(square,cube)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "o7oN7ayNSZ3a",
        "outputId": "5aab1e18-3942-4259-9ca1-96c75d3d306e"
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4\n",
            "16 64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#example1 - passing a mutable object(list), func will change the list\n",
        "\n",
        "\n",
        "def changelist(list1):\n",
        "  list1.append(20)\n",
        "  list1.append(30)\n",
        "  print('list inside the function', list1)"
      ],
      "metadata": {
        "id": "1ev-BfEwSfuv"
      },
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "list1 = [12,13,34,45]\n",
        "changelist(list1)\n",
        "print('list outside the function', list1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NREQsAskTUw0",
        "outputId": "54e826b5-7951-4420-f951-d63531686051"
      },
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "list inside the function [12, 13, 34, 45, 20, 30]\n",
            "list outside the function [12, 13, 34, 45, 20, 30]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def change_str(str1):\n",
        "  str1 = str1 + 'python'\n",
        "  print('string inside the function', str1)\n"
      ],
      "metadata": {
        "id": "yEICF498TbjJ"
      },
      "execution_count": 67,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "str1 = 'hello this is'\n"
      ],
      "metadata": {
        "id": "1SUigejiUgJY"
      },
      "execution_count": 68,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "change_str(str1)\n",
        "print('string outside the function',str1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jsEVkxPmUiKf",
        "outputId": "40dcde1d-4ab2-4cdc-e207-870abb8c49d6"
      },
      "execution_count": 69,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "string inside the function hello this ispython\n",
            "string outside the function hello this is\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.core.completer import position_to_cursor\n",
        "#types of arguments\n",
        "\n",
        "#required arguments - exact match of argument with their position in the function call and func definition\n",
        "#keyword arguments -\n",
        "#default arguments\n",
        "#variable length arguments\n"
      ],
      "metadata": {
        "id": "pzR_FeudUp1B"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#program to calculate simple interest\n",
        "\n",
        "def simple(p,t,r):\n",
        "  return (p*t*r)/100"
      ],
      "metadata": {
        "id": "Y2kQeZ9iVMwR"
      },
      "execution_count": 71,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "simple(100,2,3) #should be in order always"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z_ZV2519VKGX",
        "outputId": "92f7dbab-6489-4e1f-f30c-494df38d7606"
      },
      "execution_count": 72,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "6.0"
            ]
          },
          "metadata": {},
          "execution_count": 72
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def details(place,pincode):\n",
        "  print(\"place={}' and pincode={}\".format(place,pincode))\n"
      ],
      "metadata": {
        "id": "O1wyqjAuWBRt"
      },
      "execution_count": 73,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "details('Hyderabad',500082)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ID1XCA0IW8Op",
        "outputId": "a7474029-8fe7-44bc-804e-090b8e4b7312"
      },
      "execution_count": 74,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "place=Hyderabad' and pincode=500082\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "details(12344,'Delhi')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WxjIxOR0W_PD",
        "outputId": "78266685-0c03-4e37-a0ce-723d20e11c28"
      },
      "execution_count": 75,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "place=12344' and pincode=Delhi\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#keyword arguments\n",
        "\n",
        "details(pincode=12345, place='Delhi') #very useful"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NIRUPGJ_XDJf",
        "outputId": "1eae6e71-413e-4629-f146-8c74843d1ed4"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "place=Delhi' and pincode=12345\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#default arguments\n",
        "\n",
        "def AOC(r, pi=3.14):\n",
        "  return pi*r*r\n"
      ],
      "metadata": {
        "id": "LGmTqwMbXiZc"
      },
      "execution_count": 80,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "AOC(5) #only one parameter can be passed as one is by default"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oLyBQYZCYBgd",
        "outputId": "285d180d-c5cf-432d-9f64-03e3da6e6009"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "78.5"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "AOC(5,3.144) #overridden"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hj9LuqD8YGxK",
        "outputId": "1f83636b-9cd3-4182-8f34-ab55632cbf8c"
      },
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "78.60000000000001"
            ]
          },
          "metadata": {},
          "execution_count": 82
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#variable length argument\n",
        "#when we dont know how many arguments should we pass in advance\n",
        "#by tuples\n",
        "\n",
        "def display(*names):\n",
        "  print('data structure is', type(names))\n",
        "  print('printing the names')\n",
        "  for name in names:\n",
        "    print(name)"
      ],
      "metadata": {
        "id": "5Z7zRnuKYX6y"
      },
      "execution_count": 86,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "display('aby','john','sej','gayu','minku','kash','harry')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6YC2Th52ZG9I",
        "outputId": "2911953f-2222-4347-fa2c-8c9d1e0d2795"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "data structure is <class 'tuple'>\n",
            "printing the names\n",
            "aby\n",
            "john\n",
            "sej\n",
            "gayu\n",
            "minku\n",
            "kash\n",
            "harry\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#multiple keyword arguments\n",
        "\n",
        "def food(**kw):\n",
        "  print(kw)"
      ],
      "metadata": {
        "id": "japDce_vZKsm"
      },
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "food(fruits='apple', vege='carot', fastfood='burger')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XNGO4208aJAD",
        "outputId": "8bda8dd0-4fa9-4ee1-9cf0-3f73cfe49940"
      },
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "{'fruits': 'apple', 'vege': 'carot', 'fastfood': 'burger'}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#scope of variable\n",
        "a = 10\n",
        "def print_a():\n",
        "  a = 20\n",
        "  print(a)\n"
      ],
      "metadata": {
        "id": "NlWVK1TBaZij"
      },
      "execution_count": 110,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print_a()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sx07gD-8ax0e",
        "outputId": "55a73a35-04c9-4aee-fa4d-b755437c1fde"
      },
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "20\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(a) #local scope"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5TYQkSdOay-r",
        "outputId": "d2645388-e109-41bf-ab2c-3963ead901ea"
      },
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#can function change value of a global variable?\n",
        "\n",
        "b = 20\n",
        "def printb():\n",
        "  global b \n",
        "  print(\"global var is\", b)\n",
        "  b = 30\n",
        "  print('value inside the function', b)\n",
        "  "
      ],
      "metadata": {
        "id": "3sZsbXBca6I7"
      },
      "execution_count": 114,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "printb()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YmZ5ae5Pb_N4",
        "outputId": "c835e2f6-59a6-4ac3-c650-994fa2944ae8"
      },
      "execution_count": 115,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "global var is 20\n",
            "value inside the function 30\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(b) #global changes the value!"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ohV4jMFjcJSL",
        "outputId": "211f3737-ecb3-4872-c204-3a5751f2859d"
      },
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "30\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#modify each element of list by 3\n",
        "\n",
        "def modify(l):\n",
        "  return [i*3 for i in l]\n",
        "modify([1,2,3,4])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kyqMLdLxcXQR",
        "outputId": "4bc98126-bf86-48f7-f9ee-a9d3d1b9f35e"
      },
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[3, 6, 9, 12]"
            ]
          },
          "metadata": {},
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#lambda function \n",
        "#small anonymous function\n",
        "#function which doesn't have any name and can be written inside any code\n",
        "#can take any number of arguments\n",
        "#but can have only one expression\n",
        "\n",
        "\n",
        "#syntax:   lambda arguments:expression\n",
        "\n",
        "def add(a,b):\n",
        "  return a+b\n",
        "\n",
        "  #more simple way\n",
        "add_lam = lambda a,b:a+b\n",
        "add_lam(5,6)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_sAULgrNiLQq",
        "outputId": "271d13f6-f37a-4bfb-a372-0675e7a039fd"
      },
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "11"
            ]
          },
          "metadata": {},
          "execution_count": 121
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#find a number if even or odd\n",
        "find_even = lambda x:x%2==0\n",
        "find_even(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0O2_8YhJjS8V",
        "outputId": "1c589a73-5055-4022-f317-36313133d232"
      },
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "metadata": {},
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#if-else w lambda\n",
        "\n",
        "Max = lambda a,b:a if (a > b) else b\n"
      ],
      "metadata": {
        "id": "oFgnr4svkDP6"
      },
      "execution_count": 123,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Max(34,67)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lll8P0jGkPUT",
        "outputId": "86903310-a486-433f-de66-6adcb8a1231f"
      },
      "execution_count": 124,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "67"
            ]
          },
          "metadata": {},
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#example of lambda inside code\n",
        "#take one argument from user and that number will be multiplied w some unknown number\n",
        "def myfunc(n):\n",
        "  return lambda a:a*n"
      ],
      "metadata": {
        "id": "QjjIcBUXkQwH"
      },
      "execution_count": 125,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "double = myfunc(3)\n"
      ],
      "metadata": {
        "id": "5_t54Gklkw3p"
      },
      "execution_count": 130,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "double(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TsiCnbF0k7i9",
        "outputId": "3c0de36b-c90b-4375-faf7-17d39b347bfc"
      },
      "execution_count": 131,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "30"
            ]
          },
          "metadata": {},
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a = myfunc(3)"
      ],
      "metadata": {
        "id": "vF0jYpV6k83D"
      },
      "execution_count": 132,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yDcVbLIEmK7t",
        "outputId": "dbcd92e7-1359-4f77-b64d-067466988fe7"
      },
      "execution_count": 133,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "30"
            ]
          },
          "metadata": {},
          "execution_count": 133
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#sort list of tuples using lambda\n",
        "\n",
        "subject_marks=[('english', 88),('science', 90), ('physics', 70),('social science', 75)]\n",
        "print(subject_marks)\n",
        "#sort the list\n",
        "\n",
        "subject_marks.sort(key = lambda x:x[1])\n",
        "print(subject_marks)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ei9YQ1hRmLmx",
        "outputId": "db401a65-18c6-424b-a918-27dfc65d25af"
      },
      "execution_count": 135,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[('english', 88), ('science', 90), ('physics', 70), ('social science', 75)]\n",
            "[('physics', 70), ('social science', 75), ('english', 88), ('science', 90)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        " #map, filter, reduce\n",
        "\n",
        "#list of numbers from 300 to 700 with a step of 3\n",
        "list1 = list(range(300,700,3))"
      ],
      "metadata": {
        "id": "s4J7dkNvnNJ7"
      },
      "execution_count": 136,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "list1\n"
      ],
      "metadata": {
        "id": "toRjnGvypUtv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#filter the list with the help of function that check element is even or not\n",
        "\n",
        "list2 = list(filter(lambda x:x%2==0, list1))"
      ],
      "metadata": {
        "id": "kr-NE5BupWQm"
      },
      "execution_count": 138,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "list2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "m-XYEWdCqNKN",
        "outputId": "c554ac21-cbc4-4fe0-d96b-8b2a21e58a46"
      },
      "execution_count": 139,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[300,\n",
              " 306,\n",
              " 312,\n",
              " 318,\n",
              " 324,\n",
              " 330,\n",
              " 336,\n",
              " 342,\n",
              " 348,\n",
              " 354,\n",
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              " 444,\n",
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              " 558,\n",
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              " 582,\n",
              " 588,\n",
              " 594,\n",
              " 600,\n",
              " 606,\n",
              " 612,\n",
              " 618,\n",
              " 624,\n",
              " 630,\n",
              " 636,\n",
              " 642,\n",
              " 648,\n",
              " 654,\n",
              " 660,\n",
              " 666,\n",
              " 672,\n",
              " 678,\n",
              " 684,\n",
              " 690,\n",
              " 696]"
            ]
          },
          "metadata": {},
          "execution_count": 139
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "list2 = list(filter(lambda x:x<10, list1))"
      ],
      "metadata": {
        "id": "YjWsGYPVqN1O"
      },
      "execution_count": 142,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "list2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Im19tlFq0RG",
        "outputId": "a7a74b43-80b0-45e2-be2c-d01b2465dbab"
      },
      "execution_count": 143,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {},
          "execution_count": 143
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#create a string filter all numbers from string using filter fun\n",
        "\n",
        "str1 = \"Hello123\"\n",
        "num = list(filter(lambda x: True if x in \"1234567890\" else False,str1))\n",
        "print(num)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OUrQbMyZq1qF",
        "outputId": "6ec93d7e-a596-4f82-a9e4-0fd06d80f2b8"
      },
      "execution_count": 144,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['1', '2', '3']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "#MAP\n",
        "#map() function returns a map object(which is an iterator of the results after applying function to each item) \n",
        "\n",
        "list1\n",
        "len(list1)\n",
        "#subtract all value of list w 300\n",
        "list2=list(map(lambda x:x-300,list1))\n"
      ],
      "metadata": {
        "id": "zkjrsPIwshj3"
      },
      "execution_count": 151,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "list2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iA6v-a2_tvg6",
        "outputId": "37bf1bec-6f6a-453d-a755-ac5cc24efbb4"
      },
      "execution_count": 152,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0,\n",
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              " 390,\n",
              " 393,\n",
              " 396,\n",
              " 399]"
            ]
          },
          "metadata": {},
          "execution_count": 152
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(list1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hOZyhclDt0uN",
        "outputId": "a6570279-2811-400d-ff96-54c295e0f7cb"
      },
      "execution_count": 153,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "134"
            ]
          },
          "metadata": {},
          "execution_count": 153
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(list2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GVUQt-BwuESh",
        "outputId": "1a67b181-6554-4795-8e87-877bc80cbcad"
      },
      "execution_count": 154,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "134"
            ]
          },
          "metadata": {},
          "execution_count": 154
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#square all elements of list using map function\n",
        "\n",
        "listsquare = list(map(lambda x:x*x, list1))"
      ],
      "metadata": {
        "id": "tDTQJUKduFvS"
      },
      "execution_count": 157,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "listsquare"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gn9hVnHrunqF",
        "outputId": "1d6c8c03-7443-4ca8-b90d-7e46cfe47547"
      },
      "execution_count": 158,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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            ]
          },
          "metadata": {},
          "execution_count": 158
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#add 2 lists using map function\n",
        "\n",
        "l1 = [1,2,3]\n",
        "l2 = [2,3,4]\n",
        "l3 = list(map(lambda x,y:x+y, l1,l2))\n",
        "l3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9TKV2Ug0uoao",
        "outputId": "1f3dc839-0a9b-4d5a-efb7-d287182b1ef2"
      },
      "execution_count": 160,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[3, 5, 7]"
            ]
          },
          "metadata": {},
          "execution_count": 160
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fruit = ['Apple','banana','pear','orange','Apricot']\n",
        "#filter list which words start with A\n",
        "\n",
        "l1 = list(filter(lambda x:x[0]=='A', fruit))\n",
        "l1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bP-1bQp7viqg",
        "outputId": "0f09d5fa-d355-4946-c2c4-64654df02c83"
      },
      "execution_count": 163,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Apple', 'Apricot']"
            ]
          },
          "metadata": {},
          "execution_count": 163
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#reduce\n",
        "#aggregation of tasks\n",
        "\n",
        "import functools\n",
        "from functools import reduce\n",
        "\n",
        "list1\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KtI6XG4Qv9Qm",
        "outputId": "32bbc24b-fa7c-44fa-aaea-379367add664"
      },
      "execution_count": 167,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              " 696,\n",
              " 699]"
            ]
          },
          "metadata": {},
          "execution_count": 167
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "reduce(lambda x,y:x+y,list1 )\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rX4_7Nc-xI5p",
        "outputId": "9d4d0052-8756-46a9-c0be-b1b9b0c46e0f"
      },
      "execution_count": 166,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "66933"
            ]
          },
          "metadata": {},
          "execution_count": 166
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#find greatest number in a list\n",
        "\n",
        "list1 = [70,110,200,400,34]\n",
        "reduce(lambda x,y:x if x>y else y, list1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "smxY8dvDxsVp",
        "outputId": "4ab6b01a-7cf1-4a20-8502-cff24256874b"
      },
      "execution_count": 168,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "400"
            ]
          },
          "metadata": {},
          "execution_count": 168
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "red = lambda x,y:x if x>y  else y\n",
        "reduce(red,list1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TLzxRyL9yVIm",
        "outputId": "5bca4ebb-b9aa-4280-df81-4434f419ae3a"
      },
      "execution_count": 169,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "400"
            ]
          },
          "metadata": {},
          "execution_count": 169
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "help(reduce)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KlA39LL1ywEa",
        "outputId": "67f3ff07-8e80-42f5-9aee-ce13d5ad5a74"
      },
      "execution_count": 170,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Help on built-in function reduce in module _functools:\n",
            "\n",
            "reduce(...)\n",
            "    reduce(function, sequence[, initial]) -> value\n",
            "    \n",
            "    Apply a function of two arguments cumulatively to the items of a sequence,\n",
            "    from left to right, so as to reduce the sequence to a single value.\n",
            "    For example, reduce(lambda x, y: x+y, [1, 2, 3, 4, 5]) calculates\n",
            "    ((((1+2)+3)+4)+5).  If initial is present, it is placed before the items\n",
            "    of the sequence in the calculation, and serves as a default when the\n",
            "    sequence is empty.\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "O9ltR8yyzYXf"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}