Python.ipynb

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      "authorship_tag": "ABX9TyO/xhLfmDtdvgtrD19UTvvB",
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
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      "source": [
        "<a href=\"https://colab.research.google.com/github/Konikakonika/AI-ML-Month/blob/main/Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!python3 --version"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/"
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        "id": "952gJeosVT6b",
        "outputId": "aeb35a1a-f18f-42f8-cc50-3bc16fb0ed0b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python 3.10.11\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!sudo update-alteratives --config python3"
      ],
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          "base_uri": "https://localhost:8080/"
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sudo: update-alteratives: command not found\n"
          ]
        }
      ]
    },
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      "execution_count": null,
      "metadata": {
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "hello world!\n"
          ]
        }
      ],
      "source": [
        "print(\"hello world!\")"
      ]
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      "cell_type": "code",
      "source": [
        "x=12\n",
        "y=12"
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      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "z=x+y"
      ],
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        "id": "kYOCsnUEnwUd"
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      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(z)"
      ],
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      "outputs": [
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          "name": "stdout",
          "text": [
            "24\n"
          ]
        }
      ]
    },
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      "source": [
        "type(z)"
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      "cell_type": "code",
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        "x='hello'\n",
        "type(x)"
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        "x,y=10,20"
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      "outputs": []
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        "x,y=y,x"
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      "execution_count": null,
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    {
      "cell_type": "code",
      "source": [
        "x+y"
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        "x-y"
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      "source": [
        "8%4"
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          "metadata": {},
          "execution_count": 193
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    },
    {
      "cell_type": "code",
      "source": [
        "a=7\n",
        "b=8\n",
        "c=a+b\n",
        "print(c)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FHYMynLppwfP",
        "outputId": "08daf37c-5c67-463e-e7f7-5cfdb0ccb53b"
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"Sum is\", c)"
      ],
      "metadata": {
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          "base_uri": "https://localhost:8080/"
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        "id": "oYqZDG5FqBn5",
        "outputId": "1e92da86-53bb-4cad-a554-5c6b25add872"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Sum is 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"sum of\",a,\"and\",b,\"is\",c)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LdapGIMqqI5s",
        "outputId": "74342bc7-9d90-4cda-da43-94533466a1e5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 7 and 8 is 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"sum of %d\"%c)\n",
        "print(\"sum of %d and %d os %d\"%(a,b,c))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wdH-XGmFqw4q",
        "outputId": "bed61fbc-b430-4de1-df33-2b59ca68dc99"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 15\n",
            "sum of 7 and 8 os 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"sum of {}\".format(c))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xjIw2qMFrgbe",
        "outputId": "f9fed79d-1bb0-4f63-cf18-06774efc133a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"sum of {} and {} is {}\".format(a,b,c))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "44rn4yDVsRRK",
        "outputId": "b5c11325-e501-45b4-98fb-3a176ca37a8b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 7 and 8 is 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "d=a/b\n",
        "d"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iPXx-XGxtPRB",
        "outputId": "73d84b6b-0852-486e-ffa7-986a3f5c7362"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.875"
            ]
          },
          "metadata": {},
          "execution_count": 200
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"div of {} and {} is {}\".format(a,b,d))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bU737CeytVpQ",
        "outputId": "eeb99e7c-ce0b-4aa4-b7c7-124f769f59ff"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "div of 7 and 8 is 0.875\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"div of {} and {} is {:.2f}\".format(a,b,d))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6E0rKKtQtfge",
        "outputId": "e2edd182-8c3e-4c49-8f01-f02694458ee6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "div of 7 and 8 is 0.88\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"sum of {} and {} is {}\".format(c,a,b))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lfFHjMrlt3fa",
        "outputId": "af25a1ca-c57b-4e33-f34a-41043a422f82"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 15 and 7 is 8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"sum of {1} and {2} is {0}\".format(c,a,b))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "05MOU1DPub-U",
        "outputId": "e7c00667-c907-4f37-efa2-0957d8d76d10"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 7 and 8 is 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#f-strings=format string lierals\n",
        "print(f\"sum of {a} and {b} is {c}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PgdEuWIGuiZ6",
        "outputId": "42bc68a7-6caa-428f-cdda-9a2030f058eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum of 7 and 8 is 15\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "c=a+b\n",
        "d=a-b\n",
        "e=a/b\n",
        "f=a*b\n",
        "print(f\"1. add is{c}\")\n",
        "print(f\"2. add is{d}\")\n",
        "print(f\"3. add is{e}\")\n",
        "print(f\"4. add is{f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TuXWnr3Fvd2h",
        "outputId": "1f1e27f5-bafb-4f42-db7d-a8c939aa3640"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1. add is15\n",
            "2. add is-1\n",
            "3. add is0.875\n",
            "4. add is56\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(f\"\"\"\n",
        "1. add is {c}\n",
        "2. sub is {d}\n",
        "3. mul is {f}\n",
        "\"\"\")#multiline print statement"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HFwn1nbHTPn9",
        "outputId": "b2ed93ae-567d-4360-f035-f93cbd1c4bd7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "1. add is 15\n",
            "2. sub is -1\n",
            "3. mul is 56\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "a=10\n",
        "b=10\n",
        "c=a+b\n",
        "print(\"sum is \",c)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Eb81pD96UGAw",
        "outputId": "c06e4fb2-7dd5-497e-ceb2-c5a8def9dd65"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum is  20\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#a=10\n",
        "#b=10\n",
        "#c=a+b\n",
        "#print(\"sum is \",c=a+b)#print m c naam ka operator nhi hoti chlega nhi code"
      ],
      "metadata": {
        "id": "jHp2QJWqUl_L"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "a=6\n",
        "b=8\n",
        "#walrus operator :=\n",
        "print(\"sum is\", c:=a+b)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Emd3Ijq6U425",
        "outputId": "3d3c3ff7-cc81-4a29-e683-45158c87e723"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sum is 14\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x=input(\"enter first no :\")\n",
        "y=input(\"enter sec no :\")\n",
        "z=x+y\n",
        "print(\"sum is\",z) # wrong ans becz input funct string hi written krta h"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6o22URSeVF9S",
        "outputId": "18691ff3-9391-440e-f3fa-2f41a3695035"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "enter first no :5\n",
            "enter sec no :6\n",
            "sum is 56\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x=int(input(\"enter first no :\"))\n",
        "y=int(input(\"enter sec no :\"))\n",
        "z=x+y\n",
        "print(\"sum is\",z)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D-HfB6-hXRrE",
        "outputId": "8cbbec71-34fc-4f42-ab60-77fafd6ccf7f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "enter first no :5\n",
            "enter sec no :7\n",
            "sum is 12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#control flow statement\n",
        "#loops\n",
        "#-for\n",
        "#-while"
      ],
      "metadata": {
        "id": "WWGgfV90XdQG"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(5): #indentatation error\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vLKKHJNKYAK-",
        "outputId": "2b1d8497-835b-495b-ee80-a1606010cdfb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n",
            "3\n",
            "4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(3):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GyBCW3BrYhez",
        "outputId": "8299ea82-ecc7-47b0-d7b5-5b2ef5c9aae3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0\n",
            "1\n",
            "2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(1,11):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OF3FiF2AYxfk",
        "outputId": "dcac9f22-b086-471f-b053-f26c0ec7c384"
      },
      "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": [
        "for i in range(1,21,2):\n",
        "  print(i,end=\",\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Exei6F63ZJph",
        "outputId": "0b4ac2dc-d419-4778-a437-67597d0a183c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1,3,5,7,9,11,13,15,17,19,"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(2,21,2):\n",
        "  print(i,end=\" \")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FZnO9bhyZWo8",
        "outputId": "bfe142f7-eba9-4339-8dd6-13d70ae3ac41"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2 4 6 8 10 12 14 16 18 20 "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(2,21,2):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OGJzXXolZpMg",
        "outputId": "ccf84f11-6af0-41d5-ca82-bb6207a0de1a"
      },
      "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",
            "20\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(3):\n",
        "  for j in range(3):\n",
        "    print(i,j)\n",
        "    print(\"*\" * 10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YDx6r0wmZxU0",
        "outputId": "330f347e-8bdd-484c-de21-8207ffd06aa8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0 0\n",
            "**********\n",
            "0 1\n",
            "**********\n",
            "0 2\n",
            "**********\n",
            "1 0\n",
            "**********\n",
            "1 1\n",
            "**********\n",
            "1 2\n",
            "**********\n",
            "2 0\n",
            "**********\n",
            "2 1\n",
            "**********\n",
            "2 2\n",
            "**********\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(10,1,-1):\n",
        "  print(i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kYKBsIhvaSFV",
        "outputId": "23d51310-0c95-47c1-82b2-64ce09511d64"
      },
      "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"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(1,6):\n",
        "  print(\"*\"*i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ncPW4BUZa3DW",
        "outputId": "162d0544-a3d4-45f6-9391-39f746f71afa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "*\n",
            "**\n",
            "***\n",
            "****\n",
            "*****\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(6,0,-1):\n",
        "  print(\"*\"*i)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CAHYnUPwbJH7",
        "outputId": "1d08fd30-cb15-4668-b064-e3ede92d7e23"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "******\n",
            "*****\n",
            "****\n",
            "***\n",
            "**\n",
            "*\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in range(10):\n",
        "  print(\" \"*(10-i)+\"*\"*(2*i+1))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5C2sOAGMbl3u",
        "outputId": "312c6cec-beb7-46dc-fdd4-4347ad11223d"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "          *\n",
            "         ***\n",
            "        *****\n",
            "       *******\n",
            "      *********\n",
            "     ***********\n",
            "    *************\n",
            "   ***************\n",
            "  *****************\n",
            " *******************\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x=10\n",
        "while x>0:\n",
        "  print(x)\n",
        "  x-=1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X4mmIp1ccZ4M",
        "outputId": "c8349132-8025-4ad5-a527-6506fb6b6122"
      },
      "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": [
        "x=10\n",
        "while True:\n",
        "  print(x)\n",
        "  x -=1\n",
        "  if x==1:\n",
        "    break\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GFb8dGJ4cvTo",
        "outputId": "3d60ff70-e59f-4273-cfd8-3fd11b4618fa"
      },
      "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"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "num=6\n",
        "if num%2==0:\n",
        "  print(\"no is even\")\n",
        "else:\n",
        "    print(\"no id odd\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jWH6sPzidKu3",
        "outputId": "61032d66-55d4-476b-e39f-59182f1880f2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "no is even\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "if num%2==0: print(\"no is even\")\n",
        "else:\n",
        "  print(\"no id odd\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HQqPnFvQdnUv",
        "outputId": "4473562e-5e62-4a93-c525-a0c0c290806b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "no is even\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(\"even\") if num%2==0 else print(\"odd\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6XCun0uadxjV",
        "outputId": "4c4bd45a-f066-4748-c655-5d3af88f2e11"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "even\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x,y,z=10,20,30\n",
        "if x>y and x>z:\n",
        "  print(\"x is greatest\")\n",
        "elif y>z and y>x:\n",
        "    print(\"y is greatest\")\n",
        "else:\n",
        "      print(\"z is greatest\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CctHSYg1eGsO",
        "outputId": "34f15093-f7f3-4383-8a1c-a4b5bdb1fb83"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "z is greatest\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\"x\" if x>y and x>z else \"y\" if y>x and y>z else \"z\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "m7E2Tcd-pLnX",
        "outputId": "353171d7-c542-458f-f946-15295e20aecc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'z'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 231
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#mini game -guess the no\n",
        "import random\n",
        "\n",
        "cpu= random.randint(1,100)\n",
        "counter=5\n",
        "while True:\n",
        "  guess=int(input(\"guess the number:\"))\n",
        "\n",
        "  if cpu==guess:\n",
        "    print(\"congrats, you guessed the correct no...\")\n",
        "\n",
        "    break\n",
        "  elif guess>cpu:\n",
        "    print(\"you guess is a greater number...\")\n",
        "\n",
        "  elif guess<cpu:\n",
        "    print(\"you guess is a smaller number...\")\n",
        "  counter-=1\n",
        "  print(\"chances left ::\",counter)\n",
        "\n",
        "  if counter==0:\n",
        "    print(\"you lose the game..number was\",cpu)\n",
        "    break"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7K18LboZpjbL",
        "outputId": "34827f9c-b73b-4c1e-9c03-3b2fcef70152"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "guess the number:67\n",
            "you guess is a greater number...\n",
            "chances left :: 4\n",
            "guess the number:78\n",
            "you guess is a greater number...\n",
            "chances left :: 3\n",
            "guess the number:45\n",
            "you guess is a greater number...\n",
            "chances left :: 2\n",
            "guess the number:34\n",
            "you guess is a greater number...\n",
            "chances left :: 1\n",
            "guess the number:33\n",
            "you guess is a greater number...\n",
            "chances left :: 0\n",
            "you lose the game..number was 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "end of python from ravi sir video"
      ],
      "metadata": {
        "id": "ywjI_MO9vb-M"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**DATA SCIENCE**"
      ],
      "metadata": {
        "id": "MjpDfK5bvpJ2"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "JmZabTbXuMqI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.array([3,4,5,6,7,8])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6m3JCPo_OgM0",
        "outputId": "b92844a6-41e4-461c-f0aa-8bea69d6df68"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([3, 4, 5, 6, 7, 8])"
            ]
          },
          "metadata": {},
          "execution_count": 234
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.array([3,4,56,56.78,24.4])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "r7KUoSD3OodT",
        "outputId": "85fe2469-3f33-426e-cf9b-dc56ecde78a4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 3.  ,  4.  , 56.  , 56.78, 24.4 ])"
            ]
          },
          "metadata": {},
          "execution_count": 235
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.arange(1,11)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mrf3VSSkO23X",
        "outputId": "38ffedde-7420-41fd-b7e9-97b292c1ccf6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1,  2,  3,  4,  5,  6,  7,  8,  9, 10])"
            ]
          },
          "metadata": {},
          "execution_count": 236
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.arange(2,21,2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jx_22GZ6Pl3D",
        "outputId": "f6d42059-9014-4881-fa6d-660879afcf10"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 2,  4,  6,  8, 10, 12, 14, 16, 18, 20])"
            ]
          },
          "metadata": {},
          "execution_count": 237
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.linspace(2,50)#linearspace"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wry8ymQoPrA_",
        "outputId": "ebbf441c-b101-4c42-c3d3-f16df606bfb8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 2.        ,  2.97959184,  3.95918367,  4.93877551,  5.91836735,\n",
              "        6.89795918,  7.87755102,  8.85714286,  9.83673469, 10.81632653,\n",
              "       11.79591837, 12.7755102 , 13.75510204, 14.73469388, 15.71428571,\n",
              "       16.69387755, 17.67346939, 18.65306122, 19.63265306, 20.6122449 ,\n",
              "       21.59183673, 22.57142857, 23.55102041, 24.53061224, 25.51020408,\n",
              "       26.48979592, 27.46938776, 28.44897959, 29.42857143, 30.40816327,\n",
              "       31.3877551 , 32.36734694, 33.34693878, 34.32653061, 35.30612245,\n",
              "       36.28571429, 37.26530612, 38.24489796, 39.2244898 , 40.20408163,\n",
              "       41.18367347, 42.16326531, 43.14285714, 44.12244898, 45.10204082,\n",
              "       46.08163265, 47.06122449, 48.04081633, 49.02040816, 50.        ])"
            ]
          },
          "metadata": {},
          "execution_count": 238
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.linspace(2,25)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Q6JciF_4QB4b",
        "outputId": "3b5c7cd3-5758-498e-c1b4-4a439e2b56b4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 2.        ,  2.46938776,  2.93877551,  3.40816327,  3.87755102,\n",
              "        4.34693878,  4.81632653,  5.28571429,  5.75510204,  6.2244898 ,\n",
              "        6.69387755,  7.16326531,  7.63265306,  8.10204082,  8.57142857,\n",
              "        9.04081633,  9.51020408,  9.97959184, 10.44897959, 10.91836735,\n",
              "       11.3877551 , 11.85714286, 12.32653061, 12.79591837, 13.26530612,\n",
              "       13.73469388, 14.20408163, 14.67346939, 15.14285714, 15.6122449 ,\n",
              "       16.08163265, 16.55102041, 17.02040816, 17.48979592, 17.95918367,\n",
              "       18.42857143, 18.89795918, 19.36734694, 19.83673469, 20.30612245,\n",
              "       20.7755102 , 21.24489796, 21.71428571, 22.18367347, 22.65306122,\n",
              "       23.12244898, 23.59183673, 24.06122449, 24.53061224, 25.        ])"
            ]
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          "metadata": {},
          "execution_count": 239
        }
      ]
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          "output_type": "execute_result",
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            "text/plain": [
              "(array([ 2.        ,  4.55555556,  7.11111111,  9.66666667, 12.22222222,\n",
              "        14.77777778, 17.33333333, 19.88888889, 22.44444444, 25.        ]),\n",
              " 2.5555555555555554)"
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          "execution_count": 240
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              "       [0., 0., 0., 0., 1.]])"
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            "<ipython-input-245-8516034fbf9d>:1: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.\n",
            "Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n",
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              "array([[0.74228019, 0.11940332, 0.76262331, 0.80280027],\n",
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              "       [0.54928517, 0.38897319, 0.74712523, 0.07658137]])"
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              "       [ 1, 37, 54,  3, 67]])"
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XD6LQbmPVUnC",
        "outputId": "c0034a1e-8e8d-42de-b384-5029c6d87dd1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 276
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=y.flatten()"
      ],
      "metadata": {
        "id": "ls8ZN1GhVYnU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jsk-a36-VfmD",
        "outputId": "3f332cea-9254-4a6f-8d87-a77468109b1a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([40, 23, 63, 29,  8, 43, 53, 65, 36, 91, 72, 86, 51, 40, 30, 45,  2,\n",
              "        1,  4, 25, 30, 47, 78, 38])"
            ]
          },
          "metadata": {},
          "execution_count": 278
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.min(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E2_RCh20VhNr",
        "outputId": "fbdd19e0-e65c-4573-9e4b-cbfab107749e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 279
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.max(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "75WIIFE0VtTF",
        "outputId": "4fd8041c-3871-4dc7-dcdd-17d6a37df1fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "91"
            ]
          },
          "metadata": {},
          "execution_count": 280
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.sort(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "L5FlClnKVv9L",
        "outputId": "2356149c-c8d1-4750-eeca-b5d44d209372"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1,  2,  4,  8, 23, 25, 29, 30, 30, 36, 38, 40, 40, 43, 45, 47, 51,\n",
              "       53, 63, 65, 72, 78, 86, 91])"
            ]
          },
          "metadata": {},
          "execution_count": 281
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.argmax(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ufMcv7i4V1QH",
        "outputId": "cb98d28a-b928-4afe-f481-2f56d511cd70"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "9"
            ]
          },
          "metadata": {},
          "execution_count": 282
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.argmin(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ARSauDRqV5jb",
        "outputId": "d6b4bd32-f51a-420b-9007-40e01f10a724"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "17"
            ]
          },
          "metadata": {},
          "execution_count": 283
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=np.sort(y)"
      ],
      "metadata": {
        "id": "f97YQVOhV-UC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4xqHiTKgWHQg",
        "outputId": "eabb08fc-8b00-460d-8b0b-b18803d24b1f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1,  2,  4,  8, 23, 25, 29, 30, 30, 36, 38, 40, 40, 43, 45, 47, 51,\n",
              "       53, 63, 65, 72, 78, 86, 91])"
            ]
          },
          "metadata": {},
          "execution_count": 285
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#mutable h\n",
        "y[0]\n",
        "y[0]=100\n",
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RWV4z6RZWJo9",
        "outputId": "4d87788a-a213-46d9-bdcd-67021107a7c3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([100,   2,   4,   8,  23,  25,  29,  30,  30,  36,  38,  40,  40,\n",
              "        43,  45,  47,  51,  53,  63,  65,  72,  78,  86,  91])"
            ]
          },
          "metadata": {},
          "execution_count": 286
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.sort(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Sac3L3DiWV4O",
        "outputId": "91ce48d5-c57e-4cca-8e98-a497f9e91f73"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([  2,   4,   8,  23,  25,  29,  30,  30,  36,  38,  40,  40,  43,\n",
              "        45,  47,  51,  53,  63,  65,  72,  78,  86,  91, 100])"
            ]
          },
          "metadata": {},
          "execution_count": 287
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.sum(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T-twS_6jWe_d",
        "outputId": "ae1cd7fc-5eb5-4839-e1ad-3255951f4ab9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1099"
            ]
          },
          "metadata": {},
          "execution_count": 288
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.mean(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D06PVAzQWmiX",
        "outputId": "c9e98430-c7bf-44ec-c2b1-ce072ca516dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "45.791666666666664"
            ]
          },
          "metadata": {},
          "execution_count": 289
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.median(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "w2GXQT_YWpIW",
        "outputId": "b76f6145-243a-4b3c-8def-a439d2e28a09"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "41.5"
            ]
          },
          "metadata": {},
          "execution_count": 290
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.std(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cU8MoPtNW2Gt",
        "outputId": "a9579197-ecb4-4257-e6f8-0251367c1993"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "25.921321929167803"
            ]
          },
          "metadata": {},
          "execution_count": 291
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.var(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_mtjP5FWW5MA",
        "outputId": "df9a2160-a759-4ebe-88cc-a0adba2f7b37"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "671.9149305555555"
            ]
          },
          "metadata": {},
          "execution_count": 292
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=np.reshape(y,(6,4))"
      ],
      "metadata": {
        "id": "x7R5bUA6W78J"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f-Hu6SHHXhTD",
        "outputId": "9881bd0c-4e0f-4ac4-9845-904b55f80d1a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[100,   2,   4,   8],\n",
              "       [ 23,  25,  29,  30],\n",
              "       [ 30,  36,  38,  40],\n",
              "       [ 40,  43,  45,  47],\n",
              "       [ 51,  53,  63,  65],\n",
              "       [ 72,  78,  86,  91]])"
            ]
          },
          "metadata": {},
          "execution_count": 294
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y=np.reshape(y,(4,-1))"
      ],
      "metadata": {
        "id": "A5zDtEf3Xk92"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "guITw_0RXyB6",
        "outputId": "bd867e25-6b42-4d86-e0e4-522b63707c63"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[100,   2,   4,   8,  23,  25],\n",
              "       [ 29,  30,  30,  36,  38,  40],\n",
              "       [ 40,  43,  45,  47,  51,  53],\n",
              "       [ 63,  65,  72,  78,  86,  91]])"
            ]
          },
          "metadata": {},
          "execution_count": 296
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.max(y)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H2jWWDuOXznt",
        "outputId": "24ce875a-fa14-4019-824f-ef07f9c24c98"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "100"
            ]
          },
          "metadata": {},
          "execution_count": 297
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.max(y,axis=0)#column ka max"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WglsPGo7X5mW",
        "outputId": "653bbaa5-0abf-49a3-9dcd-f7cb3f14330f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([100,  65,  72,  78,  86,  91])"
            ]
          },
          "metadata": {},
          "execution_count": 298
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.max(y,axis=1)#row ka max deta h)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cGuxcvczX-0F",
        "outputId": "3b1f5e2c-0b25-4401-8133-06da6f770bc5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([100,  40,  53,  91])"
            ]
          },
          "metadata": {},
          "execution_count": 299
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z=np.array([[2,4,5,2,55,2]])\n",
        "np.vstack((y,z))#vertically data stack ho rha h"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B2zJIefTYYWS",
        "outputId": "13e4c1df-9714-4a93-fd12-47ecbea3896b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[100,   2,   4,   8,  23,  25],\n",
              "       [ 29,  30,  30,  36,  38,  40],\n",
              "       [ 40,  43,  45,  47,  51,  53],\n",
              "       [ 63,  65,  72,  78,  86,  91],\n",
              "       [  2,   4,   5,   2,  55,   2]])"
            ]
          },
          "metadata": {},
          "execution_count": 300
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#z=np.array([[2],[4],[5],[55],[2]])\n",
        "#np.hstack((y,z))"
      ],
      "metadata": {
        "id": "svryTAO6ZXwb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "np.vstack((y,[2,3,4,5,66,5]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gYH61WYFaCZa",
        "outputId": "b374817d-1b99-48d3-a86e-19d8dc152574"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[100,   2,   4,   8,  23,  25],\n",
              "       [ 29,  30,  30,  36,  38,  40],\n",
              "       [ 40,  43,  45,  47,  51,  53],\n",
              "       [ 63,  65,  72,  78,  86,  91],\n",
              "       [  2,   3,   4,   5,  66,   5]])"
            ]
          },
          "metadata": {},
          "execution_count": 302
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NFVwqczxav5j",
        "outputId": "abd73958-7ba4-4c73-da64-bca6a302b09f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[100,   2,   4,   8,  23,  25],\n",
              "       [ 29,  30,  30,  36,  38,  40],\n",
              "       [ 40,  43,  45,  47,  51,  53],\n",
              "       [ 63,  65,  72,  78,  86,  91]])"
            ]
          },
          "metadata": {},
          "execution_count": 303
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qadu_TJFaxwV",
        "outputId": "92a3b4cc-a6a9-4cf5-af47-6e1a7a605527"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([ 1, 47, 63, 70, 58, 39, 46, 66, 26, 89])"
            ]
          },
          "metadata": {},
          "execution_count": 304
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "z=np.random.randint(1,100,[5,6])"
      ],
      "metadata": {
        "id": "ZZQ4zjMCazS9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "z"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NE8ODXuGbseZ",
        "outputId": "18c5d222-2cf8-4ca5-e97a-14f0a8ec4152"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[54, 85, 19, 17, 76, 66],\n",
              "       [96, 77, 13, 71, 95,  1],\n",
              "       [24, 49,  9, 45, 64, 33],\n",
              "       [77, 47, 42, 85, 37, 45],\n",
              "       [60, 12, 93, 85, 19, 41]])"
            ]
          },
          "metadata": {},
          "execution_count": 306
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.vstack((z,[2,4,5,2,55,2]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EF3OgE04bzzM",
        "outputId": "25141476-a9d1-473b-c018-379e8ff4b43c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[54, 85, 19, 17, 76, 66],\n",
              "       [96, 77, 13, 71, 95,  1],\n",
              "       [24, 49,  9, 45, 64, 33],\n",
              "       [77, 47, 42, 85, 37, 45],\n",
              "       [60, 12, 93, 85, 19, 41],\n",
              "       [ 2,  4,  5,  2, 55,  2]])"
            ]
          },
          "metadata": {},
          "execution_count": 307
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#np.hstack((z,[5,8,56,3,9]))"
      ],
      "metadata": {
        "id": "_sMay4PfcDja"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "r=np.array([[2],[4],[6],[7],[3]])\n",
        "np.hstack((z,r))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aqgHkBhWcXGj",
        "outputId": "76a7bd2a-1d99-4526-c2b5-844a5bd0c01e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[54, 85, 19, 17, 76, 66,  2],\n",
              "       [96, 77, 13, 71, 95,  1,  4],\n",
              "       [24, 49,  9, 45, 64, 33,  6],\n",
              "       [77, 47, 42, 85, 37, 45,  7],\n",
              "       [60, 12, 93, 85, 19, 41,  3]])"
            ]
          },
          "metadata": {},
          "execution_count": 309
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "how to check time and space"
      ],
      "metadata": {
        "id": "KYLfP1Y_dNpw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import sys"
      ],
      "metadata": {
        "id": "BqpWJbc7c0k_"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sys.getsizeof([])#empty list kitna size le rhi h"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iXxiCD1GdYmC",
        "outputId": "fe6a5b47-51c3-4f4b-b16f-796f9fb0a531"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "56"
            ]
          },
          "metadata": {},
          "execution_count": 311
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sys.getsizeof(np.array([]))#np array kitna size le rha h"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2fhPmPx5ddv9",
        "outputId": "2a92ee15-86cf-4db4-b178-8133ec784bd3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "112"
            ]
          },
          "metadata": {},
          "execution_count": 312
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sys.getsizeof([5])#ek element se 8bite ka size bdhaya list m"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hIkbHzl8dwjU",
        "outputId": "18e429a8-383c-4524-c91d-915713596bb1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "64"
            ]
          },
          "metadata": {},
          "execution_count": 313
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sys.getsizeof(np.array([5]))#same 8bite bdhaya"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IrUm7VY6d-Ie",
        "outputId": "8641f342-da95-46de-ab7e-655635413f51"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "120"
            ]
          },
          "metadata": {},
          "execution_count": 314
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#size inc. krne k liy\n",
        "sys.getsizeof([i for i in range(100)])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vWsWraXzeHBq",
        "outputId": "5b493403-b7e3-4cdc-d40d-598a61abeb38"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "920"
            ]
          },
          "metadata": {},
          "execution_count": 315
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sys.getsizeof(np.array([i for i in range(100)]))#ab array size km le rha h it takes 4 bite"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KAcLKrJxeUss",
        "outputId": "410da654-f9f3-4d76-f6c6-06823fa233d4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "912"
            ]
          },
          "metadata": {},
          "execution_count": 316
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import time"
      ],
      "metadata": {
        "id": "zchCp_Spf_WA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x=list(range(1,4))\n",
        "y=list(range(1,4))\n",
        "z=[]\n",
        "start=time.time()\n",
        "for i in range(len(x)):\n",
        "  z.append(x[i]+y[i])\n",
        "  end=time.time()\n",
        "  total=end-start\n",
        "  print(\"total time taken is:\",total)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fU2Vzaoiekwl",
        "outputId": "b7d50aff-41fb-4e99-d274-8972964b88b9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total time taken is: 0.00010609626770019531\n",
            "total time taken is: 0.0018973350524902344\n",
            "total time taken is: 0.0019490718841552734\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#list n jyda time liya h nd array n km time leta h"
      ],
      "metadata": {
        "id": "RvaDtK7ggX7e"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "**PANDAS**"
      ],
      "metadata": {
        "id": "CJcePHzhhnRY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
      "metadata": {
        "id": "RsOdeYJlhebN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.Series([2,1,3,4,5,6,7,7,4])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FAC7EjjsnDa_",
        "outputId": "92b1cb22-3285-46df-cad9-ea61566fd0d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    2\n",
              "1    1\n",
              "2    3\n",
              "3    4\n",
              "4    5\n",
              "5    6\n",
              "6    7\n",
              "7    7\n",
              "8    4\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 321
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.Series([2,1,3,5],index=['A','B','C','D'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cFLWmSIBnMM6",
        "outputId": "11e85447-f966-488c-d5f2-e0a40f80daac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "A    2\n",
              "B    1\n",
              "C    3\n",
              "D    5\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 322
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np"
      ],
      "metadata": {
        "id": "nfdklUwOnZLH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "age=np.random.randint(18,50,70)\n",
        "Series=pd.Series(age)"
      ],
      "metadata": {
        "id": "mwEWaQ0qnlXa"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Series[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i9Q0WZ39nzRe",
        "outputId": "b55956ea-7888-4cd4-cb48-e6c802ffb232"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "28"
            ]
          },
          "metadata": {},
          "execution_count": 325
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Series[0:5]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gOk3B2VEn1cf",
        "outputId": "f8d03d9f-e5fa-4919-e7bf-bd91a6e666eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    28\n",
              "1    46\n",
              "2    24\n",
              "3    19\n",
              "4    35\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 326
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Series.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T8WiWjhgoTpA",
        "outputId": "06f6080a-5d52-4fc1-d871-1328ad9867fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    28\n",
              "1    46\n",
              "2    24\n",
              "3    19\n",
              "4    35\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 327
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Series.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3De_WBNiuxDX",
        "outputId": "600464ac-33a9-4827-9870-cfc267b160f1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "65    19\n",
              "66    29\n",
              "67    45\n",
              "68    41\n",
              "69    20\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 328
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Series.tail(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mIL3Vkz1u8p9",
        "outputId": "ab8fa14f-521d-4efa-c083-cbf8d8036056"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "68    41\n",
              "69    20\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 329
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Series.mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OYh5KWQcu_6y",
        "outputId": "bcbe1133-d6e2-498a-9845-5f21f49b3085"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "34.542857142857144"
            ]
          },
          "metadata": {},
          "execution_count": 330
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data={\n",
        "    \"names\":[\"john\",\"mac\",\"sam\",\"nick\",\"peter\",\"tim\"],\n",
        "    \"sal\":[4500,6500,8700,5500,3400,3200],\n",
        "    \"dept\":[\"it\",\"it\",\"hr\",\"hr\",\"it\",\"hr\"]\n",
        "}"
      ],
      "metadata": {
        "id": "MEwxOWq_vIdS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df=pd.DataFrame(data,index=['e1','e2','e3','e4','e5','e6'])"
      ],
      "metadata": {
        "id": "5ipYDrPowEgQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "G94SPYBowVDl",
        "outputId": "8bc1ac3a-0f68-4c9d-98f4-3f3c67792df5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    names   sal dept\n",
              "e1   john  4500   it\n",
              "e2    mac  6500   it\n",
              "e3    sam  8700   hr\n",
              "e4   nick  5500   hr\n",
              "e5  peter  3400   it\n",
              "e6    tim  3200   hr"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f323040c-921a-4de4-9c38-5d6375ee90a2\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>names</th>\n",
              "      <th>sal</th>\n",
              "      <th>dept</th>\n",
              "    </tr>\n",
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              "      <th>e1</th>\n",
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              "      <td>it</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>e6</th>\n",
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              "      <td>3200</td>\n",
              "      <td>hr</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f323040c-921a-4de4-9c38-5d6375ee90a2')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
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              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f323040c-921a-4de4-9c38-5d6375ee90a2 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f323040c-921a-4de4-9c38-5d6375ee90a2');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 333
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4-9txYCPwMO7",
        "outputId": "aea140d5-e6d5-4950-b4be-9999b673ddc6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(6, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 334
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1EIcx0GfwXas",
        "outputId": "95d2cfad-8c1b-41a3-f9bc-d6acfb9d35ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['names', 'sal', 'dept'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 335
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "I2Is_TFHwlWm",
        "outputId": "e7cac5ba-91bb-4fff-9075-c5d557731070"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    names   sal dept\n",
              "e1   john  4500   it\n",
              "e2    mac  6500   it\n",
              "e3    sam  8700   hr\n",
              "e4   nick  5500   hr\n",
              "e5  peter  3400   it"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-05b0281a-a1f1-4807-a02f-4f94227b4c04\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>names</th>\n",
              "      <th>sal</th>\n",
              "      <th>dept</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>e1</th>\n",
              "      <td>john</td>\n",
              "      <td>4500</td>\n",
              "      <td>it</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>e2</th>\n",
              "      <td>mac</td>\n",
              "      <td>6500</td>\n",
              "      <td>it</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>e3</th>\n",
              "      <td>sam</td>\n",
              "      <td>8700</td>\n",
              "      <td>hr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>e4</th>\n",
              "      <td>nick</td>\n",
              "      <td>5500</td>\n",
              "      <td>hr</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>e5</th>\n",
              "      <td>peter</td>\n",
              "      <td>3400</td>\n",
              "      <td>it</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-05b0281a-a1f1-4807-a02f-4f94227b4c04')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-05b0281a-a1f1-4807-a02f-4f94227b4c04 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-05b0281a-a1f1-4807-a02f-4f94227b4c04');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 336
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['names']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SNHeS0F4wpiw",
        "outputId": "f03266c0-bb3f-47ed-e71b-b86bd8ce49a9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "e1     john\n",
              "e2      mac\n",
              "e3      sam\n",
              "e4     nick\n",
              "e5    peter\n",
              "e6      tim\n",
              "Name: names, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 337
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#df.loc[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        },
        "id": "5joAu2nUwyfS",
        "outputId": "072f802e-e5f2-40a7-f807-b32e11d9647c"
      },
      "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/usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   3801\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3802\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\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   3803\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 0",
            "\nThe above exception was the direct cause of the following exception:\n",
            "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-338-7eaf75073732>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\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;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1071\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1072\u001b[0m             \u001b[0mmaybe_callable\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply_if_callable\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1073\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmaybe_callable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\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   1074\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1075\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1310\u001b[0m         \u001b[0;31m# fall thru to straight lookup\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1311\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_validate_key\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1312\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\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   1313\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1314\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_slice_axis\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mslice_obj\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mslice\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexing.py\u001b[0m in \u001b[0;36m_get_label\u001b[0;34m(self, label, axis)\u001b[0m\n\u001b[1;32m   1258\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_get_label\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mint\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1259\u001b[0m         \u001b[0;31m# GH#5567 this will fail if the label is not present in the axis.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1260\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\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   1261\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1262\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_handle_lowerdim_multi_index_axis0\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtup\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtuple\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mxs\u001b[0;34m(self, key, axis, level, drop_level)\u001b[0m\n\u001b[1;32m   4054\u001b[0m                     \u001b[0mnew_index\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4055\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 4056\u001b[0;31m             \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\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   4057\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4058\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mndarray\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m   3802\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3803\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3804\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3805\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3806\u001b[0m                 \u001b[0;31m# If we have a listlike key, _check_indexing_error will raise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyError\u001b[0m: 0"
          ]
        }
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    },
    {
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        "df.loc['e1']"
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      "execution_count": null,
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        {
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          "data": {
            "text/plain": [
              "names    john\n",
              "sal      4500\n",
              "dept       it\n",
              "Name: e1, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 339
        }
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      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   names   sal dept\n",
              "e1  john  4500   it\n",
              "e2   mac  6500   it\n",
              "e3   sam  8700   hr"
            ],
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              "e1     john\n",
              "e2      mac\n",
              "e3      sam\n",
              "e4     nick\n",
              "e5    peter\n",
              "e6      tim\n",
              "Name: names, dtype: object"
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              "e3    True\n",
              "e4    True\n",
              "e5    True\n",
              "e6    True\n",
              "Name: sal, dtype: bool"
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            "text/plain": [
              "   names   sal dept\n",
              "e2   mac  6500   it\n",
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              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 344
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df[df['dept']=='it']"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "6GyjTSoqyZlg",
        "outputId": "51de017a-155f-48a5-b820-4b25cca0d267"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    names   sal dept\n",
              "e1   john  4500   it\n",
              "e2    mac  6500   it\n",
              "e5  peter  3400   it"
            ],
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              "          document.querySelector('#df-7c6451b6-b23c-43ec-801a-5fe6f9b8cee6 button.colab-df-convert');\n",
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              "          const element = document.querySelector('#df-7c6451b6-b23c-43ec-801a-5fe6f9b8cee6');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "IuIJxUiTysNH"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}