Running_R_on_Colab.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Running_R_on_Colab.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/kiat/R-Examples/blob/master/Running_R_on_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "seG5y0ZZ7acg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "outputId": "abd4a414-2212-4a6f-a4f3-2157fc0a07b4"
      },
      "source": [
        "%load_ext rpy2.ipython"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "The rpy2.ipython extension is already loaded. To reload it, use:\n",
            "  %reload_ext rpy2.ipython\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TkqA4mlK9bsx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "a932a6e1-cdf8-48dc-c32c-f88a36abd776"
      },
      "source": [
        "%%R\n",
        "install.packages(\"dplyr\", lib=\"/content/R\")"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Would you like to use a personal library instead? (yes/No/cancel) yes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CKJWCl-jDkHD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 215
        },
        "outputId": "fd742f24-1880-43c9-99a3-530ab0ae8976"
      },
      "source": [
        "%%R\n",
        "\n",
        "# First read the data as a dataframe into your R memory \n",
        "decay <- read.csv(\"https://raw.githubusercontent.com/kiat/R-Examples/master/Datasets/decay.csv\" )\n",
        "\n",
        "#print the dataframe to check the content\n",
        "# Note, this is only possible if your data is small \n",
        "decay\n"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   strength weeks\n",
              "1       118     2\n",
              "2       126     2\n",
              "3       126     2\n",
              "4       120     2\n",
              "5       129     2\n",
              "6       124    16\n",
              "7        98    16\n",
              "8       110    16\n",
              "9       140    16\n",
              "10      110    16\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2MzlwxWMixnh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "outputId": "10bc9c0f-8271-45e1-e14d-7903a70def56"
      },
      "source": [
        "%%R\n",
        "# Print out a summary of the data for the 2 weeks sample data \n",
        "summary(decay$strength[decay$weeks==2])"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
              "  118.0   120.0   126.0   123.8   126.0   129.0 \n"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zEx-yT85DpCd",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 53
        },
        "outputId": "1cd7d650-bc87-4c8f-eb9a-917a553e8173"
      },
      "source": [
        "%%R\n",
        "# Print out a summary of the data for the 16 weeks sample data \n",
        "summary(decay$strength[decay$weeks==16])"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. \n",
              "   98.0   110.0   110.0   116.4   124.0   140.0 \n"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "muUuiaMyisiz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 497
        },
        "outputId": "19570bbd-b4b2-4f29-9013-de4cd3bf5668"
      },
      "source": [
        "%%R \n",
        "boxplot(decay$strength ~ decay$weeks,  main=\"Polyester  Strenght after weeks under soil\", xlab=\"group\",  ylab=\"strength\")"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Ieogu9N+c7xFqRM9mfdOYZe6AYBkIEbwuJylFo9OkUCOGVOib8iJzBwTLQMwZ7Jvi/47v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\n"
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PdnNsERdF9PE",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 233
        },
        "outputId": "55d11e9d-cf55-4318-e934-54528032e704"
      },
      "source": [
        "%%R\n",
        "t.test(decay$strength[decay$weeks==2], decay$strength[decay$weeks==16], alternative=\"two.sided\", conf.level=0.95)\n"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "\n",
              "\tWelch Two Sample t-test\n",
              "\n",
              "data:  decay$strength[decay$weeks == 2] and decay$strength[decay$weeks == 16]\n",
              "t = 0.98887, df = 4.651, p-value = 0.3713\n",
              "alternative hypothesis: true difference in means is not equal to 0\n",
              "95 percent confidence interval:\n",
              " -12.2789  27.0789\n",
              "sample estimates:\n",
              "mean of x mean of y \n",
              "    123.8     116.4 \n",
              "\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}