Jupyter_extension_rmagic_rpy2_tutorial.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Display R Plots in Python: the rmagic Method \n",
    "\n",
    "In this Jupyter Notebook you will find an rpy2 code example in which we use the Python package rpy2 to create R plots. We use the r-packages 'graphics' and 'ggplot2' and display them here in this Jupyter Notebook.\n",
    "\n",
    "This is an alternative method, compared to the one used in the [YouTube Video about using Rpy2 and plotting in Jupyter notebooks](https://youtu.be/RK-n78ZOXUg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "%Rdevice png"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "barplot(c(1,3,2,5,4), ylab=\"value\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeAAAAHgCAMAAABKCk6nAAAA51BMVEUAAAAAADoAAGYAOmYAOpAAZrYzMzM6AAA6ADo6AGY6Ojo6OmY6OpA6ZmY6kLY6kNtNTU1NTW5NTY5NbqtNjshmAABmADpmAGZmOgBmOjpmOpBmZjpmtv9uTU1uTY5ubqtuq6tuq+SOTU2OTY6ObquOjsiOq+SOyP+QOgCQOjqQ29uQ2/+rbk2rbo6r5P+2ZgC2Zjq2kDq2/7a2///Ijk3Ijm7IyP/I///bkDrbtmbb25Db2//b/9vb///kq27kq47k/8jk///r6+v4dm3/tmb/yI7/25D/5Kv//7b//8j//9v//+T///+8MUTPAAAMs0lEQVR4nO2dDVvb1hmGnZZk68pmJZB13Ug6kw9DIdANUrxsmFKwjbH+/++ZZDshFvqyrdfn6NH9XL1MSd8e3de5c14d2UK0QiKdlmsAYhsEiwfB4kkTPDkOduOX5ycbxyFVJ03woBN+PBm/+/ztM+IkdoKjNfzhYvQq2Lme2f2dOIil4PH+bryMR++n3yWP9Hv50ZcotaqtLYLpCo71zl8Q7AjBUHC/G7mNX7qpR2rC7HqAYCg42kDvXE+30qlHasLseoBg26K/DoKdICBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkfwU/DNTenSZLyaXQ8QvBR8c7NouLaz6wECgp0O21DBtOjqhvVT8Oqlfs2uBwgIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxhA0KrvD5fDc3FQ6mnVqu4OSN8SsOywouHwT7ilBLwcmffFhxWASXD5ssXxEQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCO4Ef/kR0JyfBZ2ntrPrAYIzwV9+iDvvp7nnqe3seoCAYKfDCgumRW8GgU2WOAKCxREMBU+Og93ZS+qRmjC7HiAYCh50wo8n0ct5N/VITZhdDxBMW/Tkw8XVSSw6fBbF9TPfmhlLweP93WgNTwWHrGBHCLabrEHnCsFuEQwF97uRW87BjhFsd9E71+yiHSNwHSyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkfYoGDXD/VrZjxfwbOHhdd2+XiA4Lfg+eP+azu7HiAg2OmwTRdMi157WM8FL13q1+x6gIBgcQQEiyMgWBwBweIICBZHQLA4AoLFERAsjoBgcQQEiyMgWBwBweIICBZHQLA4AoLFERAsjoBgcQQEiyPUTfDsJq1ytcuMW2GpXwg1Ezy/zbJU7TLjVlnqFwKCKy/1C6FmgmnRy9bWTbCr2toiIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOIKh4PF+8OJichw8P0k9UhNm1wMEQ8H9btjvjN9lHakJs+sBgm2LHnRHr4Kd6+gwUVw/1K+ZMRU8fns96ISj99NvWMFOECwFj99cxF8ix2lHasLseoBgKHj0+mJ6Ih50U4/UhNn1AMFQ8HkQBJ1oF72bfqQmzK4HCFwHiyMgWBwBweIICH5I3j3XCC6M94Jzf2oCwYVB8Jq1CF63lhadHQnBkggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgGBxBASLI+QKHm5flhzQmeBH9zKvOrsFvysAwYUxEfz4pxFWnN2i3/YhJHj4h9Y3Z2Gv1WrHgj9/vT88Gn7/t+g/pAfB9rUVCb7761HYezr87iz6l+H2p/nXqeA/HmUOSIu2r61I8Kwt3z4Nw9O94fZ/5l+ngnMa9hfBdy9bcZ48/rvAJssJQlnBs3WcOeDDCj7di//vlFoEO0FIbdG3W58WW/R3Z1F/LreCfziLX/79w6OzNYKdIORssvbmm6xoSZ62vv2xnOD7g3gFb31KWcGun/nWzFT+Rkd8Et7630H7UQkr2AkC72SJI9is4LRejmAnCFULnp+DUwwj2AlC1YLnu+iUd7wQ7ASh8hZ92p5dRT8Kgp0gVL6CZ+9ktR6/a41gJwjsosURECyOUP05OL1BI9gRgskuOjUIdoJQ+Qr+JetDYwQ7QcgSXPD5dzIPgnu0aK8QMgQX3cGSDC3aV4Sygu9ePvnHXnSR+81Z9LJ1eX+wuEr9aNExs1ez6wFC2Rbd27s/2Ovthff/jV5u27ftxberEm90uGnR07+VXs2uBwhlN1nRwuzFK/jJUXwd9DSyvBAvroPzBKeecR7VZp+X5AVHRuO7raLF25t9Wbxp2gvBOS06fU+RrM3ZecgLjk66f9rrtWbn4FY7PF28cdIPwdm1CC6RZFv+Or4LpkWXSK0Fr1tbWwQ+bBBHQLA4gq7gjPPp13+M4NLxT3DGjnjhjxFcOgi2r0XwYi0tehpdwdXW1hYBweIICBZHQLA4AoLFERAsjoBgcQQEiyMgWBwBweIICBZHQLA4AoLFEQwFj/eDFxeT42A3/UhNmF0PEAwF97thvzPohOfd1CM1YXY9QLBt0YPu1UkYOQ6fRXH6RL/GxlTw+O31x5ngkBXsCMFS8PjNRXiFYLcIhoJHry/C0JNzcPr9OwgunTTB50EQdPzYRWfcgYfg0vH8OhjB68ZzwbTodeO74LVra4uAYHEEBIsjIFgcAcFFme3PcksTWzgEJxgK41Lw/AorrzR5EYbgBENhELz6sAguCi06jrDgmiMgWBwBweIICBZHQLA4AoKLUmIXbY2wzrAILkiJ62BrhLWGRXBBEDyNrmBa9DTCgmuOgGBxBASLIyBYHAHB4ggIFkdAcHEMf6EagpctNai1/IVqCF62FMGJWgQXhxYtLrjWCAguCu9Fx9EVzKdJ0yDYEGGtYRFcFFp0HGHBNUdAsDgCgsURNijY9TPfmhlWsDgCglcuzfx98AhOMBTGS8EZz97aJEKZWgSvWorgRNQE06ITkRNcDwQEiyMgWBwBweIICBZHQLA4AoLFERAsjoBgcQQEiyMgWBwBwUbDZr5TvTmEaRBsM2z2Z00bQ5gFwTbDIlhcMC1aXbAvCAgWR0CwOAKCxREQLI6AYHEEBH9O/nUNggvjueCCdyYQXBgEr1mL4PVqadF5ERAsioDgkqUl31u2RFhpWASXS9lPhwwREGxZi+DC1FswLbowNRdcVwQEiyMguCj5T7pL69wITjAUxqXg/GdVpu69EJxgKAyCVx/WVHC/G06Og+cnqUeqieCvW3SKzEa36POgG47fZR2pLoIfSg1uha214PGv0QoevQp2rqPDRHH9UL+1Ewt2zbB0rFv0oBOO3k+/qf8KNrjXudYreCo4SuQ47Ug1FFxHBGvB8SLuph6pCbO7OYREc9noLno3/UhCs+seIbn/4zpYDAHB69b6juCmRS8EwU4QECyOgGBxBAQvUcobHXmpv2Dei84NgitAWL4WwUuU0qLzIiC4jggIFkdAsDgCgsURECyOgGBxBASLIyBYHAHB4ggIFkdAsDgCgsURECyOgOAKSjPveNscQmYtgtcvzb5ndWMI2bUIXr8UwalH0hFMi049kpBgnxEQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjbFCw64f6NTOsYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6AYHEEBIsjIFgcAcHiCAgWR0CwOAKCxREQLI6A4HojJB50+/lbBIsgJB5V/eVbBIsgILiqWl8RaNEV1dYWAcHiCAgWRzAV3O+Gk+NgN/1ITZhdDxAsBZ8H3XDQCc+7qUdqwux6gGAoePxrtIKvTmLH4bMorp/51sxYt+iPM8EhK9gRgrXgKwS7RbAWzDnYMQK7aHEEroPFERAsjoBgcQQEiyMgWBwBweIICBZHQLA4wgYFEyfZmOA1UhHkpsat17DlguDaDlsutoKJ8yBYPAgWD4LFYyh4vB+8uDAY9+GT6ooz+um6+kEj2ucn1Q9bOoaC+92w3zEYd9CJbxirPpPjHQPB43fVj7lMbFv0oGsy7OSDRWfo//OtgeDRq8Di703pmAoeW8xY3PstWvTop98scKN+M3pf/bClYyl4/MZiocUZGLT+fhAEFmcUG9rSMRQ8em3jd3bLp0FMGk5Ma3OiKhdDwedGSyLal9qc1UwEm+35S4brYPEgWDwIFg+CxYNg8SBYPPKC7/5+6RrBaeQFD7cRLJhY6+nT8P7w54PWVqMNiwq+Pzy6+3H7cjj9xzWM04gKDnvt2/YvR702Ldo1gFGG2//au/3L4RGCXQMY5f7w+7Phn6MdNIJF09u6vD9oR5dJL9lkEeEgWDwIFg+CxYNg8SBYPAgWz/8BzBzHM/nRJm0AAAAASUVORK5CYII=\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R\n",
    "require(ggplot2)\n",
    "gg <- ggplot(mtcars, aes(x=wt, y=mpg)) + geom_point(aes(colour='qsec')) + theme_bw()\n",
    "\n",
    "gg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}