Python_Video39.ipynb

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  "metadata": {
    "colab": {
      "name": "Python_Video39.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install parsivar"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "46xzirNrg822",
        "outputId": "7a1327b0-1b91-45c4-e1a9-97d5d1d309a0"
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      "execution_count": 2,
      "outputs": [
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting parsivar\n",
            "  Downloading parsivar-0.2.3.tar.gz (36.2 MB)\n",
            "\u001b[K     |████████████████████████████████| 36.2 MB 339 kB/s \n",
            "\u001b[?25hCollecting nltk==3.4.5\n",
            "  Downloading nltk-3.4.5.zip (1.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.5 MB 45.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from nltk==3.4.5->parsivar) (1.15.0)\n",
            "Building wheels for collected packages: parsivar, nltk\n",
            "  Building wheel for parsivar (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for parsivar: filename=parsivar-0.2.3-py3-none-any.whl size=36492972 sha256=2da83ad22a2503323f3eae613cf2c03e1fcea93d221b7f44701d841a5cbf5394\n",
            "  Stored in directory: /root/.cache/pip/wheels/ae/67/7a/49cbf08f64d3f76a26eceaf0e481a40e233f05d4356875cbed\n",
            "  Building wheel for nltk (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for nltk: filename=nltk-3.4.5-py3-none-any.whl size=1449925 sha256=55c57e42896acda4b96f981f2f8bd1982f6c256a1f1faa2905a755e028ac8266\n",
            "  Stored in directory: /root/.cache/pip/wheels/48/8b/7f/473521e0c731c6566d631b281f323842bbda9bd819eb9a3ead\n",
            "Successfully built parsivar nltk\n",
            "Installing collected packages: nltk, parsivar\n",
            "  Attempting uninstall: nltk\n",
            "    Found existing installation: nltk 3.2.5\n",
            "    Uninstalling nltk-3.2.5:\n",
            "      Successfully uninstalled nltk-3.2.5\n",
            "Successfully installed nltk-3.4.5 parsivar-0.2.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "FHI4GHiQf9Ri"
      },
      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.power(2,3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hxLxU42Dg59U",
        "outputId": "f2cda25c-7b5c-4ce7-dcb4-40377815c318"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.power(542,22)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FiBFc5vYhQp5",
        "outputId": "33391b38-85dc-4840-91af-eb6a266d55a7"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4414533532945219584"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.power(-32,3)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pU7xDHXPhTUq",
        "outputId": "6e4d24c9-b805-4a1d-f2f8-e2019742e6b8"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "-32768"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.power(0.25,0.1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YbuEwnVChfe-",
        "outputId": "c54cd051-00b0-4ae0-f041-508ca10be418"
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      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.8705505632961241"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = int(input(\"adad ra vared konid: \"))\n",
        "if x > 0:\n",
        "  print(np.power(x,2))\n",
        "elif x==0:\n",
        "  print(np.power(x,3))\n",
        "else:\n",
        "  print(np.power(x,4))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pSdk9C3ThjE4",
        "outputId": "d2d6deca-5708-402b-8c88-adc493c30ced"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "adad ra vared konid: 0\n",
            "0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "np.power(20,0)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WMwnxLvQiKlT",
        "outputId": "77c24ca2-e181-4665-af6a-b28650703e7a"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = int(input(\"adad ra vared konid: \"))\n",
        "while(x>-6):\n",
        "  print(x)\n",
        "  x = x-1"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Duo2hrv0inw3",
        "outputId": "34753e82-869c-4b7e-ccbb-4694ec166302"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "adad ra vared konid: 10\n",
            "10\n",
            "9\n",
            "8\n",
            "7\n",
            "6\n",
            "5\n",
            "4\n",
            "3\n",
            "2\n",
            "1\n",
            "0\n",
            "-1\n",
            "-2\n",
            "-3\n",
            "-4\n",
            "-5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x = int(input(\"adad1 ra vared konid: \"))\n",
        "y = int(input(\"adad2 ra vared konid: \"))\n",
        "if x%2 == 1:\n",
        "  x = x+1\n",
        "for i in range(x,y,2):\n",
        "  print(i, end=\" \")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ray7TqDDi7--",
        "outputId": "7366ab27-1c08-4808-be89-4652ff857a83"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "adad1 ra vared konid: 21\n",
            "adad2 ra vared konid: 30\n",
            "21 23 25 27 29 "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "uAdSeBp4jMWZ"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}