{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": [
     "hide-input"
    ],
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] \"Hello, Jupyter!\"\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 x 2</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>x</th><th scope=col>y</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td> 1.55175375</td><td>-1.1073710</td></tr>\n",
       "\t<tr><th scope=row>2</th><td> 2.28273416</td><td>-1.0857253</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>-1.06807222</td><td> 1.3690179</td></tr>\n",
       "\t<tr><th scope=row>4</th><td> 0.41424787</td><td> 0.4336028</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>-0.02718582</td><td> 1.6366157</td></tr>\n",
       "\t<tr><th scope=row>6</th><td> 1.12756405</td><td>-0.2097676</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 x 2\n",
       "\\begin{tabular}{r|ll}\n",
       "  & x & y\\\\\n",
       "  & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\t1 &  1.55175375 & -1.1073710\\\\\n",
       "\t2 &  2.28273416 & -1.0857253\\\\\n",
       "\t3 & -1.06807222 &  1.3690179\\\\\n",
       "\t4 &  0.41424787 &  0.4336028\\\\\n",
       "\t5 & -0.02718582 &  1.6366157\\\\\n",
       "\t6 &  1.12756405 & -0.2097676\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 x 2\n",
       "\n",
       "| <!--/--> | x &lt;dbl&gt; | y &lt;dbl&gt; |\n",
       "|---|---|---|\n",
       "| 1 |  1.55175375 | -1.1073710 |\n",
       "| 2 |  2.28273416 | -1.0857253 |\n",
       "| 3 | -1.06807222 |  1.3690179 |\n",
       "| 4 |  0.41424787 |  0.4336028 |\n",
       "| 5 | -0.02718582 |  1.6366157 |\n",
       "| 6 |  1.12756405 | -0.2097676 |\n",
       "\n"
      ],
      "text/plain": [
       "  x           y         \n",
       "1  1.55175375 -1.1073710\n",
       "2  2.28273416 -1.0857253\n",
       "3 -1.06807222  1.3690179\n",
       "4  0.41424787  0.4336028\n",
       "5 -0.02718582  1.6366157\n",
       "6  1.12756405 -0.2097676"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean of x: 0.1496077 \n",
      "Mean of y: -0.03976437 \n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Install necessary packages if not already installed\n",
    "if (!requireNamespace(\"IRkernel\", quietly = TRUE)) {\n",
    "  install.packages(\"IRkernel\", repos = \"http://cran.us.r-project.org\")\n",
    "  IRkernel::installspec()\n",
    "}\n",
    "\n",
    "if (!requireNamespace(\"ggplot2\", quietly = TRUE)) {\n",
    "  install.packages(\"ggplot2\", repos = \"http://cran.us.r-project.org\")\n",
    "}\n",
    "\n",
    "if (!requireNamespace(\"dplyr\", quietly = TRUE)) {\n",
    "  install.packages(\"dplyr\", repos = \"http://cran.us.r-project.org\")\n",
    "}\n",
    "\n",
    "# Load libraries with suppressed messages\n",
    "suppressPackageStartupMessages(library(ggplot2))\n",
    "suppressPackageStartupMessages(library(dplyr))\n",
    "\n",
    "# Print a simple message\n",
    "print(\"Hello, Jupyter!\")\n",
    "\n",
    "# Create a simple data frame\n",
    "data <- data.frame(\n",
    "  x = rnorm(100),\n",
    "  y = rnorm(100)\n",
    ")\n",
    "\n",
    "# Display the first few rows of the data frame\n",
    "head(data)\n",
    "\n",
    "# Create a simple plot\n",
    "ggplot(data, aes(x = x, y = y)) +\n",
    "  geom_point() +\n",
    "  ggtitle(\"Scatter Plot of Random Data\")\n",
    "\n",
    "# Perform a simple calculation\n",
    "mean_x <- mean(data$x)\n",
    "mean_y <- mean(data$y)\n",
    "\n",
    "# Print the results\n",
    "cat(\"Mean of x:\", mean_x, \"\\n\")\n",
    "cat(\"Mean of y:\", mean_y, \"\\n\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "R",
   "language": "R",
   "name": "ir"
  },
  "language_info": {
   "codemirror_mode": "r",
   "file_extension": ".r",
   "mimetype": "text/x-r-source",
   "name": "R",
   "pygments_lexer": "r",
   "version": "4.4.0"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {},
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}