{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using R in a Python notebook With rpy2\n",
    "The rpy2 package provides a way of using R components as python objects."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from rpy2.robjects import r, pandas2ri\n",
    "pandas2ri.activate()\n",
    "r.data('iris')\n",
    "r['iris'].head(2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using Native R Code Cells in a Python Notebook\n",
    "\n",
    "We can also use cell magic to allow us to cross back and forth between `python` and `R` code cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext rpy2.ipython\n",
    "import pandas as pd\n",
    "df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6], 'C':[7,8,9]})\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%R -i df -o rdf\n",
    "library(ggplot2)\n",
    "\n",
    "rdf='My R created variable'\n",
    "ggplot(df) + geom_point(aes(x=A,y=B,size=C)) + ggtitle(rdf)"
   ]
  }
 ],
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.1"
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