R_in_Colab.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "R_in_Colab.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "R",
      "language": "R",
      "name": "ir"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AtharKharal/Data_science_with_python/blob/master/R_in_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "metadata": {
        "id": "mejRe4gPz-yE",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Code without visible output:"
      ]
    },
    {
      "metadata": {
        "id": "iY7d5FiRz-yH",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "a <- 22"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "EmaiygFHz-yO",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "b <- 4:59"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "Ys35G_AUz-yT",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "With visible output:"
      ]
    },
    {
      "metadata": {
        "id": "0xIhFP0tz-yU",
        "colab_type": "code",
        "outputId": "b46f805b-eee9-46f1-b5c4-ee3e90582572",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 79
        }
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "[1] \"a\" \"b\""
            ],
            "text/latex": "\\begin{enumerate*}\n\\item 'a'\n\\item 'b'\n\\end{enumerate*}\n",
            "text/markdown": "1. 'a'\n2. 'b'\n\n\n",
            "text/html": [
              "<ol class=list-inline>\n",
              "\t<li>'a'</li>\n",
              "\t<li>'b'</li>\n",
              "</ol>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "OyBiyRhDz-yf",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Printing is captured and sent to the frontend:"
      ]
    },
    {
      "metadata": {
        "id": "Qdp13IhWz-yg",
        "colab_type": "code",
        "outputId": "c19f2b03-53d3-4140-89cc-5d20947f8aea",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "print('Hello world! Love, R in Jupyter.')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[1] \"Hello world! Love, R in Jupyter.\"\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "VoQCRfViz-yl",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "So are errors:"
      ]
    },
    {
      "metadata": {
        "id": "i4_toplfz-ym",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "f2 <- function() stop('deep error')\n",
        "throw <- function() f2()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "4x_9hNcnz-yp",
        "colab_type": "code",
        "outputId": "bbd71e59-9f08-4c17-99f8-02a68b8abfc8",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "'this line is run / displayed'\n",
        "throw()\n",
        "'this line is not run / displayed'"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "'this line is run / displayed'"
            ],
            "text/latex": "'this line is run / displayed'",
            "text/markdown": "'this line is run / displayed'",
            "text/plain": [
              "[1] \"this line is run / displayed\""
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "error",
          "ename": "ERROR",
          "evalue": "Error in f2(): deep error\n",
          "traceback": [
            "Error in f2(): deep error\nTraceback:\n",
            "1. throw()",
            "2. f2()   # at line 2 of file <text>",
            "3. stop(\"deep error\")   # at line 1 of file <text>"
          ]
        }
      ]
    },
    {
      "metadata": {
        "id": "QZ-bbYNzz-yt",
        "colab_type": "text"
      },
      "cell_type": "markdown",
      "source": [
        "Plotting works too:"
      ]
    },
    {
      "metadata": {
        "id": "2UETR4LOz-yu",
        "colab_type": "code",
        "outputId": "aeb25ee0-65d1-454a-806a-6a8337509028",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 857
        }
      },
      "cell_type": "code",
      "source": [
        "x <- seq(0, 2*pi, length.out=50)\n",
        "plot(x, sin(x))"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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xvsshTnRsVej/k6Ce57MW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\nA1b0tRxDYbkzAAAAAElFTkSuQmCC",
            "text/plain": [
              "plot without title"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "sImuhiU78fH-",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 164
        },
        "outputId": "9e200a90-ff88-48df-a6c7-55c67f872b6d"
      },
      "cell_type": "code",
      "source": [
        "(.packages())"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "[1] \"stats\"     \"graphics\"  \"grDevices\" \"utils\"     \"datasets\"  \"methods\"  \n",
              "[7] \"base\"     "
            ],
            "text/latex": "\\begin{enumerate*}\n\\item 'stats'\n\\item 'graphics'\n\\item 'grDevices'\n\\item 'utils'\n\\item 'datasets'\n\\item 'methods'\n\\item 'base'\n\\end{enumerate*}\n",
            "text/markdown": "1. 'stats'\n2. 'graphics'\n3. 'grDevices'\n4. 'utils'\n5. 'datasets'\n6. 'methods'\n7. 'base'\n\n\n",
            "text/html": [
              "<ol class=list-inline>\n",
              "\t<li>'stats'</li>\n",
              "\t<li>'graphics'</li>\n",
              "\t<li>'grDevices'</li>\n",
              "\t<li>'utils'</li>\n",
              "\t<li>'datasets'</li>\n",
              "\t<li>'methods'</li>\n",
              "\t<li>'base'</li>\n",
              "</ol>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "metadata": {
        "id": "5XEDx4yL8h4B",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "5bb5698d-da39-404c-b6a3-ffe86ac96dcd"
      },
      "cell_type": "code",
      "source": [
        "install.packages(\"data.table\")"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Installing package into ‘/usr/local/lib/R/site-library’\n",
            "(as ‘lib’ is unspecified)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "metadata": {
        "id": "TwBQNdBZ9LIa",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "library(data.table)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "i7lMCCBB9Qyi",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        "ls(\"package:data.table\")"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "metadata": {
        "id": "_j43t99U9UDm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        },
        "outputId": "c48df3c3-bfc8-4516-8dbe-8583d8c65992"
      },
      "cell_type": "code",
      "source": [
        "str(mtcars)"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "'data.frame':\t32 obs. of  11 variables:\n",
            " $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...\n",
            " $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...\n",
            " $ disp: num  160 160 108 258 360 ...\n",
            " $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...\n",
            " $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...\n",
            " $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...\n",
            " $ qsec: num  16.5 17 18.6 19.4 17 ...\n",
            " $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...\n",
            " $ am  : num  1 1 1 0 0 0 0 0 0 0 ...\n",
            " $ gear: num  4 4 4 3 3 3 3 4 4 4 ...\n",
            " $ carb: num  4 4 1 1 2 1 4 2 2 4 ...\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "metadata": {
        "id": "Pf42xXbQ9ZYX",
        "colab_type": "code",
        "colab": {}
      },
      "cell_type": "code",
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}