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Rmd to IPython Notebook and HTML

I had blogged earlier about a proof-of-concept for how to convert an R Markdown Notebook into an IPython Notebook. The idea was to allow R users to author reproducible documents in R Markdown, but be able to seamlessly convert into HTML or an IPython Notebook, which allows greater interactivity.

This is an update to the same post that makes use of the native R kernel for the IPython Notebook, being developed by @takluyver.

As noted earlier, the bulk of the work here is done by notedown, a python module that helps create IPython notebooks from markdown. The approach I have taken here is to convert the RMarkdown file into a Markdown file using a custom knitr script, and then using notedown to render it as an IPython notebook.

If you want to test this out, you will first need to install notedown

$ pip install notedown

The next step is to convert the Rmd source into html and ipynb. For the sake of convenience, I have added a Makefile that will do it all. Just run make all and it will create example.html using knit2html and example.ipynb using knitr and notedown. So you get two birds with one stone!

Now, to open the ipython notebook, you will need to install the native R kernel. Installation instructions can be found here. Once you have installed all dependencies, you can open the notebook from the command line using:

ipython notebook --KernelManager.kernel_cmd="['R', '-e', 'IRkernel::main(\'{connection_file}\')']"

The notebook will not contain any output, since I set eval = F while converting it. You will need to select Cell > Run All from the toolbar to automatically execute all cells and embed output. I am presuming there might be a mechanism in the IPython Notebook architecture to trigger this execution from the command line.

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<h2>Introduction to ggplot2</h2>
<a href="example.Rmd">Download</a>
<p>This is a short demo on how to convert an R Markdown Notebook into an IPython Notebook using knitr and notedown.</p>
<p>This is an introduction to <a href="http://github.com/hadley/ggplot2">ggplot2</a>. You can view the source as an R Markdown document, if you are using an IDE like RStudio, or as an IPython notebook, thanks to <a href="https://github.com/aaren/notedown">notedown</a>.</p>
<p>We need to first make sure that we have <code>ggplot2</code> and its dependencies installed, using the <code>install.packages</code> function.</p>
<p>Now that we have it installed, we can get started by loading it into our workspace</p>
<pre><code class="r">library(ggplot2)
</code></pre>
<p>We are now fully set to try and create some amazing plots. </p>
<h4>Data</h4>
<p>We will use the ubiqutous <a href="http://stat.ethz.ch/R-manual/R-patched/library/datasets/html/iris.html">iris</a> dataset.</p>
<pre><code class="r">head(iris)
</code></pre>
<pre><code>## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
</code></pre>
<h4>Simple Plot</h4>
<p>Let us create a simple scatterplot of <code>Sepal.Length</code> with <code>Petal.Length</code>.</p>
<pre><code class="r">ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) + geom_point()
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-3"/> </p>
<p>The basic idea in <code>ggplot2</code> is to map different plot aesthetics to variables in the dataset. In this plot, we map the x-axis to the variable <code>Sepal.Length</code> and the y-axis to the variable <code>Petal.Length</code>.</p>
<h4>Add Color</h4>
<p>Now suppose, we want to color the points based on the <code>Species</code>. <code>ggplot2</code> makes it really easy, since all you need to do is map the aesthetic <code>color</code> to the variable <code>Species</code>.</p>
<pre><code class="r">ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) + geom_point(aes(color = Species))
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-4"/> </p>
<p>Note that I could have included the color mapping right inside the <code>ggplot</code> line, in which case this mapping would have been applicable globally through all layers. If that doesn&#39;t make any sense to you right now, don&#39;t worry, as we will get there by the end of this tutorial.</p>
<h4>Add Line</h4>
<p>We are interested in the relationship between <code>Petal.Length</code> and <code>Sepal.Length</code>. So, let us fit a regression line through the scatterplot. Now, before you start thinking you need to run a <code>lm</code> command and gather the predictions using <code>predict</code>, I will ask you to stop right there and read the next line of code.</p>
<pre><code class="r">ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) + geom_point() + geom_smooth(method = &quot;lm&quot;,
se = F)
</code></pre>
<p><img 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" alt="plot of chunk unnamed-chunk-5"/> </p>
<p>If you are like me when the first time I ran this, you might be thinking this is voodoo! I thought so too, but apparently it is not. It is the beauty of <code>ggplot2</code> and the underlying notion of grammar of graphics.</p>
<p>You can extend this idea further and have a regression line plotted for each <code>Species</code>.</p>
<pre><code class="r">ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color = Species)) + geom_point() +
geom_smooth(method = &quot;lm&quot;, se = F)
</code></pre>
<p><img 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" 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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Introduction to ggplot2\n",
"\n",
"This is a short demo on how to convert an R Markdown Notebook into an IPython Notebook using knitr and notedown.\n",
"\n",
"This is an introduction to [ggplot2](http://github.com/hadley/ggplot2). You can view the source as an R Markdown document, if you are using an IDE like RStudio, or as an IPython notebook, thanks to [notedown](https://github.com/aaren/notedown).\n",
"\n",
"We need to first make sure that we have `ggplot2` and its dependencies installed, using the `install.packages` function.\n",
"\n",
"Now that we have it installed, we can get started by loading it into our workspace"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"library(ggplot2)"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We are now fully set to try and create some amazing plots. \n",
"\n",
"#### Data\n",
"\n",
"We will use the ubiqutous [iris](http://stat.ethz.ch/R-manual/R-patched/library/datasets/html/iris.html) dataset."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"head(iris)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
" Sepal.Length Sepal.Width Petal.Length Petal.Width Species\n",
"1 5.1 3.5 1.4 0.2 setosa\n",
"2 4.9 3.0 1.4 0.2 setosa\n",
"3 4.7 3.2 1.3 0.2 setosa\n",
"4 4.6 3.1 1.5 0.2 setosa\n",
"5 5.0 3.6 1.4 0.2 setosa\n",
"6 5.4 3.9 1.7 0.4 setosa"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Simple Plot\n",
"\n",
"Let us create a simple scatterplot of `Sepal.Length` with `Petal.Length`."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +\n",
" geom_point()"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": []
},
{
"metadata": {},
"output_type": "display_data",
"png": 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kFwFX34Cxhgzj93gLxhg+3oKtCUMxeL03EoZAc+XKZex68hPDY16XMR5wmDvSgX88bfNrn6G/cubMqfotHi6JXPP444/LjBkzVBGLFy+W+fPny4UXXphIkea1uBcxBO3EfKZZqAc2cB9i3tap3w+s++3Zs6c5pL1y5UpZtmyZqiPZzfXrdwz3IDhH6jN8D+NNripgjJt/+eWXUq1aNXnttdeka9euUqZMGVPWTz75RGBibqTGjRvL1Vdfbex68hOwPTRt7hgj/DAg5c6d27EyvVKQn/sMc4qpSBs3bjSrxQ/Unj175KqrrjKPJbLh1/5Cu/CDjnWtTiTYa1jnk3fu3KkeyIoWLepE8bbK8Gufob/wm5gvX76wPDDKG29yVQHj6bxFixZSrlw51QA8nbVr186UtU+fPuY2NjCsZSz+DjjhoR2/GhvQCMtDN1mMosAI66+//goYRYrx0oSztWnTRjD8iVS6dGn19uvUdxdvUzTCiq2L8NIyb948lfnaa69VU35O9UNsEvw3l19/F2M1wrLDyprXVQUMxWtYj2GBODqJiQRIQH8CeHiuUaOGemBu1qyZFCpUSP9GadiCsWPHmnPw8ITFpBcBVxUw3Jl98cUX8v3336vlRTAUYCIBEvAHgWuuucYfDdG4FRhlvOGGGzRuQXqL7qoCxvzUrbfeKidPnow4iZ3eXcDWkwAJeIkAlk9u3bpV2atEMr5xU2aMGB45ciTAZsbN+lh2agi4ugzJaFKqbmKjfn6SAAmQQCwEYIcCuxXMrTZq1Eg2b94cy2WO5oFxat26daV+/foyaNAgR8tmYd4ikBQF7K0mUxoSIAESCE1g8uTJ8vvvv6uTsDB+4403Qmd08ejw4cNNw7qpU6fKunXrXKyNRaeSABVwKumzbhIgAU8RyJs3b4A8qTAcDZbBj0sDAyCn8Q4VcBp3PptOAiQQSKBLly7SsGFD5dykVq1acs899wRmSMIe4u8i9i2m7h588EGpmIJoREloJqvIIuCqERYJkwAJkIBOBOBw4a233hIYYmE9cioSrMvhMwHBKPzmDSwVPL1cJ9+Avdw7lI0ESCAlBFKlfK2NpfK10vDndmoe8fzJkq0iARJIkMDevXsFhlBQgLfddpsULFgwwRL/e/mqVauU7+pKlSqpqGxwneiHhOVK77zzjvIchsAY8GjHpA8BKmB9+oqSkoCvCcCnNPwGIAg70ty5c2XKlCkJtxlLiRAKFf4IkLZv3y59+/ZNuFwvFAD/+itWrFCiwOnR9OnTvSAWZYiRAIegYwTFbCRAAu4SQDABQ/miJsyDHj9+POFK4YnPUL4o7Ntvv024TC8UsH//flP5Qh5EQ8IIApM+BKiA9ekrSkoCviZQsmRJKV++vNnGSy+91BH/8ZdffnmAMRNCo/ohYbi5cuXKZlMQDjIVkZBMAbhhmwCHoG0j4wUkQAJuEIDR0bvvvisTJ05Uc8C9evVypBooKcyTfvrpp4I54DvuuMORcr1QyKRJk2TcuHFqDpi+9r3QI/ZkyJYV9ivT3iXu5YYbuEOHDrlXgQMl+zXsFsMROnBzJLkIhCPctWuX6TUpydW7Vh3DEbqG1rWC/fq7GGs4QqzbjidxCDoearyGBEiABEiABBIkQAWcIEBeTgIk4H0Cbdq0kQsuuEAwrwzjLicSDJ66desmNWvWlIceekg573CiXJaRPgSogNOnr9lSEkhLAmPGjBGsA8Zs2+HDh6Vfv36OcHj55ZeVRfXBgwflo48+Un+OFMxC0oYAFXDadDUbSgLpSQDz5NZ09OhR627c21gGZE379u2z7nKbBKISoAKOiogZSIAEdCbQv39/sUYUcspa+M477zQ9dZUtW1Y6duyoMybKngICXIaUAuiskgRIIHkESpQoIT/88IPMnj1batSoIVWqVHGkcswnL1iwQMUPrlatmiNrlh0RjIVoQ4AKWJuuoqAkQALxEihQoIDcdNNN8V4e9rrChQsLwhYykUA8BDgEHQ81XkMCGhHYsWOHzJw5U/lAdlLszz77TEaMGCG7d++OWixC/I0aNcoR15JRKwuRAYZSeANev359iLM8RAKpIcA34NRwZ60kkBQCq1evVm9+x44dU0OkCG6AodNE03333aeUOsoZP368LFq0SAWRD1XuDTfcoPwU49ybb74pP//8s2TPnrxnfxhHtW7dWvAggihIo0ePlrZt24YSlcdIIKkEkvctSGqzWBkJkAAIYHkMlC8SAhtg34k0Z84cs5hTp07J22+/be5bNxDhCEECjIQ30Xnz5hm7Sfn8+uuvlfJFZViKhHCHTCTgBQJUwF7oBcpAAi4RsAY3QBXB+/FWW6hQoYBLq1evHrBv7OBNN2fOnMau+nTKCCqg0Ag75cqVCzgbvB9wkjskkEQCVMBJhM2qSCDZBLp06SJYLnPRRRdJ9+7dBUHbnUgYdoZ1MXwAY/lN8+bNwxb74osvCoyV8ubNK1gSlGwFeOWVV8ojjzwisFSGR6yHH344rKw8QQLJJMBgDDZp+9XpOIMx2LwRPJCdwRg80Ak2RMBvxznnnGMOh9u41PNZ/fq7yGAMnr/1KCAJkAAJkAAJ2CfAIWj7zHgFCZCADQJbt26VAQMGyN13360soCNdCqtteKqClfXvv/8eKatr5yZMmKBiBsOH9OnTp12rhwWTAJch8R4gARJwlQCU6fLly1UdS5YsUUuW4BgjOMGaGtGF9uzZo07Benru3LnB2VzdnzFjhjz11FOqDni5gpw9evRwtU4Wnr4E+Aacvn3PlpOA6wSw7Gft2rVmPYcOHQrrEASK11C+uGDTpk1Jd9yxZs0aU1Zs4I2ciQTcIkAF7BZZlksCJKAcX8Dy2EgXX3yxistr7Fs/S5cuLXXq1DEPNWvWLOn+lVu2bGkum4LTDqvspmDcIAGHCHAI2iGQLIYESCA0AbirbNy4sYrFC69YOXKE/9mZNGmSfP7550oJXn/99aELdPEovISh/oULF0rt2rUd8RrmorgsWnMC4b8JmjeM4pMACXiDQEZGRsxvkljOcssttyiPVWfOnElJAypXriz4YyIBtwlwCNptwiyfBDQiAEOo7du3KwWokdgpExVW0tu2bSOvlPWA3hVTAevdf5SeBBwjAGOp+vXrq78OHTrI0aNHHSvbjwVt3LhRGjZsKNdcc416w4efayYSsEOACtgOLeYlAR8TeOWVV8zQgr/88otMmzbNx61NvGljx441vVrBWnrq1KmJF8oS0ooAFXBadTcbSwLhCQQHTciVK1f4zDxjWksbKIL5Gcf5SQLhCFABhyPD4ySQZgT69esnF154oWp1kyZNGDM3Sv/DwUjVqlVVrgYNGsjNN98c5QqeJoFAArSCDuTBPRJIWwIVKlQQxPk9ceKE5M6dO205xNrwMmXKyKxZs8grVmDM9w8CfAP+BxIeIIH0JkDla6//ycseL+b+HwEq4P+x4BYJkIALBGAd3Lt3b+natausX7/ehRpYJAnoSYBD0Hr2G6UmAW0ING3a1LSubt26tYqIFCoYgzYNoqAk4BABvgE7BJLFkAAJ/JPA2bNnTeWLs3BcATePTCRAAiJUwLwLSIAEXCOQPXt2KViwoFk+AhzUrVvX3OcGCaQzASrgdO59tp0EkkDg448/VkENLrjgAhk3bpwULVo0CbWyChLwPgHOAXu/jyghCWhNoFKlSvLZZ59p3QYKTwJuEOAbsBtUWSYJkAAJkAAJRCFABRwFEE+TAAkkj8Ds2bNVcAPED/7uu+8cq/i5555Tc89dunRR0Z4cK5gFkUACBKiAE4DHS0mABJwjgOhL/fv3lz/++EMQaej+++93JMzfN998I6+99prs2bNHFi9eLMOHD3dOaJZEAgkQoAJOAB4vJQEScI7AkSNHlFtHo0Q48Dh58qSxG/fn33//HXAtFDETCXiBABWwF3qBMpAACUiJEiUCAhrcddddjvikbt68ucAQDAkRnlAuEwl4gQCtoL3QC5SBBEhAEcBc7Z133ik5cuQwlWaiaOB1a8aMGbJixQopV66clCxZMtEieT0JOEKACtgRjCyEBEjAKQLVq1dXc79nzpxxqkj1Jl2nTh3HymNBJOAEAQ5BO0GRZZBAGALHjh2TIUOGyIgRI8Lk+N/h48ePy/z582Xt2rX/OxhmC/Ojn3/+uWzevDlMDvcPr1u3TubNmyeQ26mUmZmpXFUuXbrUqSJdLWfr1q0qhOO+fftcrYeF+5MA34D92a9slQcI4A2uZs2acurUKSXN1KlTZdmyZSElQwzeDh06yJo1a9T5J598UkUPCpV59+7d0qZNG/nrr7/UUO3YsWPluuuuC5XVtWOTJ0+WRx55RJVfpUoV+fTTTyVPnjwJ14cg94ixi4QlQ08//XTCZbpVwJIlS6Rbt27KUOycc85RzkbOO+88t6pjuT4kwDdgH3Yqm+QNAtOmTTOVLySC9W04q178mBvKF3nffPNNfIRMWCsL5YuE4AbvvPNOyHxuHnzrrbfM4hFicNGiReZ+vBtok6F8Ucb7778fYBUdb7luXffee++Z/Yk3YHr7cou0f8ulAvZv37JlKSaAuczgBCvcUKlMmTIBhyO9SZUtWzYgb/B+wEmXdoLrDJY/nmoLFSok1jCFxYsXV1bL8ZSVjGuCGQTvJ0MG1qE3gYzHs5JXmoD5snBvCF6REdaZeOvwW8LwISLVODmf5xVGqeozKJDffvtN/SEqEJxMXHnllSGxFCtWTM4991zZsmWLQHEPGzZMChcuHDLv+eefr47v379f6tWrp4aCnRj+DVlZmIO1a9eWTZs2Sc6cOWXAgAGODIGjn9B2OOHAAwgsop1Q7GGakPBhTC/s2rVLvaXffPPN0rNnT/UdClcw2pc3b145fPhwuCzaHk/Vd8xtYPny5ROE1MQUUbiEh2rkiydlyzJ6yIznQjeuwYL5Q4cOuVG0Y2Xih86PSqpIkSLqx8OPxiR+7TMoKSgAY47ZsZs8xQXhxxw/S05aQae4Sap63IeYK96xY4cXxHFUBr9+x/BgjO8XjB7DJYza4GE7nsQh6Hio8RoSIAESIAESSJAAFXCCAHl5+hHAMPFDDz0kffv2DTCcSiYJGHi1b99eLW+KNDzmlkx4I4Cl9t133y3wtez1NHPmTOUBC8PamOpiIgEvEOAyJC/0AmXQigBcGWINLBKslxcuXJhUYyEsZXrggQdMZrBJGDhwoLmfjI3HHntMLT1CXVgL/PXXX0v58uWTUbXtOlauXClY3oQ0Z84cNZ8H+ZlIINUEPKeAMZfg5YT5Ka/LGA8/tAtGWH5tm1PtgpGgoXzBGUuLDhw4oFwcxsM9nmuw7MeasHzJqfZZy420vXr1avM0HgBgkIX1wE4kGKxhDtgp85QNGzYEiAXZk80LAsBYB21LRd0BAFzY8evvYkZGhroP3eozzylgrxs4oSO8LmM83y+0y69W0E73WbNmzeSrr75SmGvUqKEMMJJ5T9SvX1/9iBt1tmjRIun3ZMuWLcVQbDBAgUWwIU8895/1GqeNsGB5DkMZw/o4FbyM9sGi1ilORple+HT6O+aFNkGG/Pnzq1UvkfrMunTOrty0grZJzK83Gq2gY78R8BYMpwuYe8U8LL6kyU544/zhhx/UsG+4pU1uy/Tll18KXDG2bt3a0QAHTitgcMC8PeRFVKRrr73WbTQhy8dvB62gQ6Lx7EG3raCpgG12PRWwTWAeyO7XPuMyJA/cXDZEoAK2AcsjWd1WwLSC9khHU4zUE8AbrR/XQWMuFf6jnZpTNXoKQ7pwmpHOCUPKYMtEAvEQoAKOhxqv8R0BRCGCd6fLL79cBg0a5Jv2QTlgzvOKK64QBKY3fEgn2sDx48fLpZdeKk2bNhXMSUMRpVtCJCoMZ4MtpiKMOeZ048D2xk+ACjh+drzSRwQQdefIkSOqRYha9PPPP/uidQiaYBhLwS3mxIkTHWnXCy+8YJazfft2mTBhgrmfLhuvvvqqmgNHe3/99VeZMmVKujSd7XSIABWwQyBZjN4EsNzAmoL3red02g5uB5bBOJFgMW9NTpVrLdPr226x9Xq7KZ9zBJz5NjonD0sigZQQGDp0qBiW4HfccYdgeZEfUvfu3dVQMdpyySWXSI8ePRxp1sMPP2wGHqhYsaJj5ToiXJIK6dOnj1x44YWqNliiIyADEwnYIUAraDu0svL61aLWUD5+NEKKtc+MNZrxRjaxeSslnN2OFTSCnBQsWDDhOq0FwAEH7pcSJUpYDye87cYypISFilAA5n5jWQtKK+gIED16ilbQHu0YiuU/AhhG1UX52qXvtPJF/VCUTitfu+3yQv5YlK8X5KQM3iPgOU9Y3kNEiUggOQTg1AIOPkqXLi3t2rVTbgvD1Qx3mDCwqlChgjRq1ChcNtvH586dK6tWrVLWzdWqVbN9vR8ugAHeggULpE6dOiresh/axDZ4kwAVsDf7hVKlGYH9+/crpbt3717VcvgrfuSRR0JSwNrbtm3bCjxyIT311FNy++23h8xr5+B7770n//73v9UlL730knz++edSuXJlO0Von/fHH3+UTp06mWumYekMt5tMJOAGARphuUGVZZKATQI//fSTGMoXlyJqT7j07bffmsoXeQy/1OHyx3rcWg6CkKOedEuI6mR1WBKpH9KNDdvrPAEqYOeZskQSsE2gatWqkjt3bvM6BDcIly677LKAU8H7ASdt7ASXE0kGG8VqlTWYQa1atbSSn8LqRSDj8azkFZERKNsYVvOKTMFywPAE1p9+S7DQ9Gs0JB36DEZS8KiE+79x48YyePDgAIVsvd8wR4z52bx586qh6HvuuUeC16Ra88e6DS9gKBMBA/r165eyoAXGmmLrm2isbUg0H5YVwbocD0OdO3dWQ/vBa57jrQP3Ifj60WOWDt+xePoNRplYHQE3teESwkzGa7zJZUjhqIY5HuuSljCXe/YwlyF5tmvCCmZnGVLYQjx4Aj/mUL5nzpzxoHTxi8RlSPGzS9WVXIaUKvKslwRIgARIgARcJMA5YBfhsmgSSDWBgwcPqmVKGFpF4ABYWzuREIjg1ltvlWuuuUYQmMHrCb6rIWu3bt1k165dSRcXS8zgKatKlSryyiuvJL1+VuhNAlTA3uwXSkUCjhB48MEH5Y8//lDzWH/++af079/fkXL/7//+T77//nvZtm2bIJAF1g57NX333XeCZVWQFZbdzz77bNJFHTZsmFpbjD4YOXKk/PDDD0mXgRV6jwAVsPf6hBKRgGMEgt/2nIpdG1yuU2EOHWu4paBgWYP3LVld2wyuM3jftYpZsKcJUAF7unsoHAkkRuCBBx4wgyagJFg3O5F69eplllu9enVPe4xq1qyZnH/++arZOXPmTEngiJ49e5qW6hiGhqU7EwnQCtrmPUAraJvAPJDdr30WqxX0pk2b5Msvv5TmzZubisiJbsHQ9o4dOwTLl7AUw6nkhhU0ljjCxSRcd5YtW9YpUW2Vg1ECBK9A9Cjrmm9bhXg0s1+/Y25bQVMB27yh/XqjcRmSzRvBA9ljVcAeENWWCG4oYFsCuJQZvx1YY42HFr8lv/4uuq2AOQTtt28C20MCQQT+/vtv+eabb2TPnj1BZ7y3i/W/y5Ytk19++SWqcHCXuWjRIlm/fn3UvMxAAl4kwGAMXuwVykQCDhHYsGGDdOzYUYx4wFOmTBG4vfRqwhz19OnTlXjdu3cXWFuHSvBGB09VCJ6ANHTo0JTM7YaSjcdIIFYCfAOOlRTzkYCGBKBwoXyR8Il9rybMkRrKFzK+/fbbYV0A4g3ZUL7I+8Ybb+CDiQS0IkAFrFV3UVgSsEegVKlSAReULFkyYN9LO4UKFQrwqVu0aNGwxl3nnnuuaYWNNni5XV5iTFm8RYAK2Fv9QWlIwFECiBN8yy23qAADiHOLYV2vJhjyvPzyy2qIHEub4DEqXCCE8uXLK4caWF6EIBYjRozwarMoFwmEJUAr6LBoQp/wq7UfraBD97eXj9IK2su980/ZaAX9TyZeP0IraK/3EOUjARIgARIggTgIcAg6Dmg6XIKlJ49nhXq+//77Y1rSoUObICNic06YMEHuvfdemTx5smNiHzhwQJ566inp27evLF26NGK58Cn88MMPy4ABAwRWxqlIkBUOHRAQwan4sljWgyHg3r17BxhDJdo+GFc9+uijyg/16tWrEy2O15OAbwhwCNpmV+oyBI2oL3A8j1SgQAHlCB7DzOGSLkPQ7777rvoxN9oBhdG6dWtjN+RnLH0Ghf7FF1+o65Ef62Zh6BMqtWrVStasWaNOIc+CBQvCGguFuj7RY++99578+9//NoupU6eOTJ061dyPd2P06NHy4osvmpd/8MEHan7VPBDnBpZB/fTTT+pqOKJAcIRIAczpiCNO0Cm8LJbvWArFi7tqDkHHjS69L1y+fLkJAG9IcEfoh7RixYqAZgTvB5y0sWMt5/jx42HfbE+ePGkqXxSPtzv8JTMZD1ZGnRs3bjQ2E/q0MkBBwfvxFA7HGitXrjQvhStGhOZjIgESEOEQtE/vAvj9NRKMdapVq2bsav0Jx/pGgoVskyZNjN2EPq28sKSlRo0aIcuDz2OrI/2LL75YypQpEzKvWwcx7GxNDRo0sO7GvW1lgHYifnCiCX1k7TPEJTYCIyRaNq8nAd0JcAjaZg/qMtRy5swZmTZtmuzdu1duvPFGKV68eMSW6jIEjUZgjhbxVOvXry81a9aM2C6cjKXPMLcMJxAIE9euXbuI60pPnDghH330kXIScdNNN0nBggWjyuB0hjlz5iinGnhQ+Ne//uVY8Rh6xzwtHmwQtceJhLnljz/+WI4cOSIdOnSQSFMhqI9D0E5QT24ZsXzHkiuRM7W5PQRNBWyzn/x6o+mkgG12WUwK2G6ZXsjPZUhe6IXYZcBvB4MxxM7LCzndVsBxDUHjDaRly5ZqwXylSpXE+Js1a5YXmFEGEjAJYA4SFs5MzhPAKMvBgwedL9hGiXCvCb/QsSTIipEOJhLwCoG4FPAdd9whtWvXlrfeeksNg8G/LP6uvvpqr7SLcpCAMpaqV6+eelDs0aOHYCiUyRkC33//vdStW1dNATz44IOCB51kp8cee0zN1SMeMYbOwyUo6LvuukvJivuBS6HCkeLxZBOISwFjXnHYsGFy5ZVXqmDc+ALgL9rcTrIbx/rSm8CoUaNk586dCsK8efNk9uzZ6Q3EwdYPHz5cBZdHkZjfhUJOZlq1apVMmjRJVYm34CeffDJs9V9++aVgzhwJc/wjR44Mm5cnSCCZBOJSwLBq/Oyzz5IpJ+siARLwEIFUvPFam2+nfjt5rXVwmwTcJhCzAsYTLuKI4g8L6du3b68sRY1j+OQbhtvdxfLtEOjfv79pzYwlNbBbYHKGwJAhQ6Rw4cKqMPwWYDQsmQnBGm677TZVJRzNwNNWuNSiRQu57rrr1OkSJUooD2bh8vI4CSSTQMxW0BjmWbt2bUTZYIwFK794E9wnoh4vJ1pBe7l3/ikbjG6wbChv3rz/PKn5kVRbQWNuFUuLDEXsFE47y5BgWIW+zZkzZ9Tq9+/fLwh5mD17zO8dUcu0k4FW0HZoeSOv21bQOWJtJtY6wugCCYoSglkTvAHRwtBKhNteIIAfWzwUwrsVk7MEoCidVr52JYRCjTXRRiVWUsyXLAK2HgXxI4a/Ro0aqU9j/+jRo8rpPxwZMJEACehLAH6tX3vttbCuOONpGazP4at64sSJKV+2FI/8vIYE3CIQ8xswBIDT+7lz5ypZrEN6cDdXtmzZiJaIbjWA5ZIACThDAEpy0KBBqjBYkM+cOVPgOjLRhKhRM2bMUMUgkATKxdszEwmkOwFbb8Aw5cfTbOfOndUntvGHuaAtW7Y45rou3TuF7SeBVBCwGlEi6MT8+fMTFgMWyFgGZCSEb/z999+NXX6SQFoTsKWA8aaLJ9fNmzdL5cqVzT88JeMPzjlgjci54LS+p9h4TQlceumlAZLD0jjRhN+MSy65xCwG87AwHmMiARIQycgK2v64XRCwhs7IyFDKFnFn8+fPL1gY/8ILL6gAAFDQDRs2tFusHDt2TPDk7eWEB5BYXd95uR3BssFCEz+WfjRW8mufwQAJVshOPfDCmQ6siVHu/fff71ikKSwBw3e7YsWK8swzz6jpquD7z7pvWCn7bf0u7kNM3SE8qN+SX79jiFttrKQI12eIHBYpvnW463A85mVI1kLKlSunYnxaLSBvuOEGNX+Ep1trMHjrddG2uQwpGiH3zjMYg3ts3So51cuQ3GoXfsyhfOFr2k+Jy5D06023lyHZGoI28OFG2rZtm7GrviyY28GTAJ50rYrZzMQNEiABEiABEiABk0BcCnjw4MFqKRI80SAWKbxgYXgJc0iIPdupUyezAm6QgA4EYBjUpUsXNez6/vvvRxQZlrwXX3yxuu9hLexUeuedd1T9t99+u/zxxx9OFctySIAEPEogriFotAUB0WHdCC9DCGCO+SPMR+3evVsp43jayyHoeKg5c026D0HfcsstgjCbSJgL//rrr+X8888PCRcGh9Z512XLlknx4sVD5o314Pr16wUuE410zTXXmMEGjGPBnxyCDibi7X0OQXu7f0JJ5/YQdNyL8erUqSP4syYYY+GPiQR0I7B9+3ZTZMw/ImpOKAUMpzNW5YuLsAQvUQW8Y8cOs35sWOUJOMEdEiAB3xCIawgawRgaN24s1apVk4suusj8s64j9A0hNiQtCPTs2dNsZ82aNdWSOvOAZQPWjhh+NlKpUqWkVq1axm7cn1dddVVAuYhfzEQCJOBvAnENQSPoAn6w4JISFotGYjAGg4R+n+k+BI0eW7duncCnOSL7wKAwUvrggw/UlEv37t0dc+6P6RxEHStdurRaYx+pfpzjEHQ0Qt46zyFob/VHLNK4PQRtWwFjeK5kyZJqiA5zZU4mzgE7SdNeWVTA9nh5ITcVsBd6IXYZqIBjZ+WVnG4rYNtD0FC6MBaZMGGC551meKUTKYceBDZt2iQwqIrF0cqaNWvkl19+idowPLD+/PPP6u06amZmIAESSCsCthUw6CBmb69evVRIQixBMv44B5xW946vGvvuu++qJUA333yzWo4USQk/99xz0qpVK7Xkrn///hE53HfffdKhQwdp2bKlOLlkKWKlPEkCJKAFAdtD0GjVr7/+GvLtl3PAWvR5SCHTfQgarlNhzWwkrPWFYVRwQvARGGFZFfSiRYvUvG1wXqzlhZ2EkXLnzi2rV692bM6YQ9AGWT0+OQStRz9ZpXR7CPp/FlTWWqNsw0oUCT9C+/fvF/x4W42xolzO0yTgOQLnnntugAIuUaJESBnhK/mcc85R692RAUq1YMGCIfPiewFjLsO/OZYqGX6OQ17AgyRAAmlFIK4haARbwBB0mTJl5NVXXxUMww0fPjytwLGx/iKAIAFYToS41k888UTEOLhjxoxRS++wTvjFF1+UAgUKhIQBl6zPP/+8VKhQQS3ZGz16dMh8PEgCJJCeBOIagr7uuuukadOmUrRoUfUmgOALbdq0kQ8//DChmMC0gk7dTZjuQ9CpIx9/zRyCjp9dKq7kEHQqqCdWp9tD0LbfgGHVidCDAwcOFNxQSOXLlxe48ps7d27I1mJ95eTJk0Oe40ESIAESIAESSEcCthUwliFhyG3FihUmL7jmmzFjRkhDFLju+/TTT5XltHkBN0ggCQQQd/WOO+6QunXrpswCGVHCBg0apIa14SfdqQQ/7F27dpX//Oc/AsOwSAlOQxDfF4ZlTCRAAt4hEJcR1ogRIwRWo5gDg1HK2LFjlWUohqGDE4almzdvrjz8BJ/DciZrzE8Yq2RkZARn89Q+jGi8LmM8wAzjID+1DcoXa3CRMG9buXJlFTgkHj7xXHP8+HFBxDBD8S5fvlymTZsWT1EB16BN99xzj3kMD7kDBgww960bePgdMmSIOjR9+nQVEL5jx47WLJ7bNu5FzwmWoEBoF15g/PQdM5D4+XfRzT6LSwHjC1y9enX5/PPP1dM31jniKXzfvn0BTukRXQZGLTDWCpVgwAWn90bC2kr4mGZKPgHcZEjhDIqSL1HiNSLEoDVhuVCfPn2sh1zdXrt2ral8URGW78HNZKIK5qOPPgqQG0ub8D0LlRBlyZrwRh4urzUft90hgO8Z+bvD1o1S0V958+aNGOMeI23xprgUMCozgjAYFUMJd+7c2YwFjKdyDEs3adJEeReCgRXmgnGdkTA0Z03I8+eff1oPeW4b8954s/Fb8qMRFoae58yZY3YVRmiSeX9hCRJCF27cuFHJgIfLrVu3mvLEu4G429blTfXr1w/bLjCwpiuuuCJsXmu+VG5jSSNsTayjY6mUx6m6aYTlFMnklROrEVa8EsWtgKNViGGWtm3bqmxYL4z9aA7uo5XJ8yRgh8C4cePk2WeflZUrVwos9evVq2fn8oTzQpFMnTpVMAeLMJ3wsuVEglLHUPaSJUvUEiesSgiXGjRooOrH2z8ci4RyLhLuWh4nARJwl4BrChgOCox4wYgw89tvv4WMr+pu81h6uhN4+OGHlbV+qkYt4LTj3nvvdbwbEAq0WbNmagonmhEW3nrxx0QCJOAtAjEr4GhDQjgfLsHLkNVoJFw+HvcfgWPHjikFaMwxe7mFsOaHIaCxvM4pWRFmECNA9BbnFFGWQwL+IBDzMqT58+cri2dYPYf6c8K60x9I2QoQwAPZgw8+qKzjMewJAyQvp8WLF6sRG/h5hicspxIMDWGweNlllymbCKfKZTkkQAL6E4jZExae4q0Wy6GaDl+3+fLlC3UqpmP0hBUTJlcyOW2EtWDBArUG1xAWQe7ff/99Yzepn7EYzl1//fUCq2UjffbZZwJjp0QSpl7QbiOBsbEsyjiWyCc9YSVCL/nX0ggr+cwTrTFWIyzovnhSzEPQmNOFxysmEoiFQLAFa/B+LGUkM481uhHqDd6PR5bgNmMfIwM6DMfH015eQwIkYI9AzEPQ0YrFEPXOnTujZeP5NCEARy0wEkIqVKiQPPTQQ55uOYy1jNEbrHNHYIZEE9b8GuuOMW0zdOhQKt9EofJ6EvARgZiHoKO1GVaW+IG54YYbomUNe55D0GHRuH7C6SFoQ2B4gUJUoFQuQYtlCBryYpoFi+ox7ORkQshOKGAsRXIycQjaSZrul8UhaPcZO12DZ4agozUMXq+YSCCYQLi4usH5vLCPaRb8OZ3wcMNEAiRAAsEEYp4DXrZsmfTs2TP4+oD9kSNHKr/PAQe5QwIpJPDdd9/Jpk2bpFGjRlKuXLkUSsKqSYAESCCQQMwKuEqVKoIlFZFS1apVI53mORJIKoF3331XHn30UVUnfFzPnj2bfniT2gOsjARIIBKBmBUw5vHgczZSSpW3oUgy8Vz6EoAvciNhbvebb76RLl26GIf4SQIkQAIpJRCXFfTXX3+twhFinSScDMAtXsmSJVV0pJS2hpWTgIXAJZdcYtkT5RQk4AB3SIAESCCFBGJ+A7bK2Lt3b+VkAWHQoIAxvIfhvhtvvNGajdskkFIC8MQF62P4IUdgEHijYiIBEiABrxCwrYDhSODAgQPyyCOPyNtvv60MXO6//361BhhzbIjpy0QCXiCAOJ6DBw9OaTAGL3CgDCRAAt4kYHsIGl58sJ4RSrhmzZoCK1OkokWLej7OqDe7gFKRAAmQAAmkIwHbb8CAhPBqNWrUkN9//102b94st9xyi8ydO1fFJ01HiGyzNwns3btXHnvsMdmwYYO0b99eMHXCRAIkQAJeIWD7DRiCYz0wLEwRXg0GWTDGeuutt4QOB7zSrZQDBJ577jllGLh+/XoZMWKELFy4kGBIgARIwDMEbClgLDPCH5waYF0wtmH9PGDAADUfPH36dM80jIKQwLZt2wIgbN26NWCfOyRAAiSQSgK2FHDr1q0Fhi0rV65Un9jGH6yg8XZRr169VLaFdZNAAIHbbrtNsmf/7y2OwAhGcIiATNwhARIggRQRsDUHPGfOHEFItTvuuEO98Roy40fO+KEzjvGTBFJNADF+v/rqK9myZYuKboSoTEwkQAIk4BUCthQwLKAx7zt58mQlP2KmItIL5n6pgL3SpZTDSuCCCy5QDjjopc1KhdskQAJeIGBrCNoQGJbPvXr1kjJlyij/0P3795fhw4cbp/lJAloSwBzxL7/8okZ5tGwAhSYBEtCKQFwKuEePHoI3iyeffFI1dtCgQeqtGNamTCSgI4EpU6bItddeq7y5de3alUpYx06kzCSgGQHbChiesFatWiUDBw5UHobQ3vLly5trgTVrP8UlAUXglVdekbNnz6rtxYsXyw8//EAyJEACJOAqAdsKGPPAsHpesWKFKRh+uLAuGJamTCSgI4FixYoFiB28H3CSOyRAAiTgAAFbRlhGfXBq0LBhQzn//POVs/uxY8cqQ5c2bdoYWfhJAloRePrppwVTKbt27ZJ77rlHKlWqpJX8FJYESEA/AnEp4I4dO6ooSJ9//rmcOnVKOnToIJUrV9av9ZSYBP5/AgipSUcyvB1IgASSScCWAsayI/xIIbg5Qg/CAxYTCZAACZAACZCAfQK2FDDedJcuXaqWH8Gx/cyZM9VQtP1qeYWXCOzYsUMtI4OBHZyslC1b1kvieU6W3bt3C6ZdTpw4oZbjVahQwXMyUiASIAHvE4hZAW/atEkWLVqkIsucc8458uijj8ro0aOpgL3fx1El7Natm+pXZITnKATYgLEdU2gCWAO/fPlydXLevHmCv5w5c4bOzKMkQAIkEIZAzFbQcGyPAAxQvkgtWrRQoQjDlMvDmhA4ePCgqXwhMh60/v77b02kT76YJ0+eNJUvasf3YufOnckXhDWSAAloTyBmBQxjK+tTPhTxsWPHtAeQ7g2Af+RatWqZGKpXry7Fixc397kRSCBXrlxSv3598yCMDzlkb+LgBgmQgA0CMQ9Bo0zD9zO2Dx06pBwXwBe0kfLnzx+gpI3j/PQ2gTfffFM++eQTwRww5vmZIhPA/C/8oeNtuHPnzvSDHhkXz5IACYQhYEsBYw7YGII2yrPuw51fp06djFP81IQA3oL79eun5n337dunidSpExMPmnfddVfqBGDNJEACviAQswJu0KBB1LlBeMhiIgESIAESIAESiE4gZgWMMIRFixaNXiJzkAAJkAAJkAAJRCUQsxFW1JKYgQRIgARIgARIIGYCVMAxo2JGEiABEiABEnCOABWwcyxZEgmQAAmQAAnETIAKOGZUzEgCJEACJEACzhGgAnaOJUsiARIgARIggZgJxGwFHXOJzOgJAnCqAb/Oe/fulVatWgnW+oZL8HKGNdy4plGjRpI7d+5wWXmcBEiABEjAIQJUwA6B9FoxTzzxhLz11ltKrPHjxwtiN4dTrHfffbfMnz9f5YWbxXfeecdrzaE8JEACJOA7AhyC9l2X/rdBn376qdmyjRs3yurVq8196waCMRjKF8cXLlwY1eGK9XpukwAJkAAJxEeACjg+bp6/qmrVqqaMefLkkfLly5v71o2CBQsGBBMoWbLkP9yNWvNzmwRIgARIwBkCHIJ2hqPnShk1apSMHDlSvc1iiLlYsWIhZUTc3wkTJsgrr7yi5oB79+7N4AIhSfEgCZAACThLgArYWZ6eKa1UqVJKAcciEOI8Y74YypjBGGIhxjwkQAIkkDgBDkEnzpAlkAAJkAAJkIBtAlTAtpHxAhIgARIgARJInAAVcOIMWQIJkAAJkAAJ2CZABWwbGS8gARIgARIggcQJUAEnzpAlkAAJkAAJkIBtAlTAtpHxAhIgARIgARJInAAVcOIMWQIJkAAJkAAJ2CZABWwbGS8gARIgARIggcQJUAEnzpAlkAAJkAAJkIBtAlTAtpHxAhIgARIgARJInAAVcOIMWQIJkAAJkAAJ2CZABWwbGS8gARIgARIggcQJUAEnzpAlkAAJkAAJkIBtAlTAtpHxAhIgARIgARJInADDESbOMK1K2Lhxo7z99ttSpEgR6dmzpxQqVCit2s/GkgAJkIBTBKiAnSKZBuUcOXJEbr31VtmzZ49q7fLly2XixIlp0HI2kQRIgAScJ+A5BZwnTx7nW+lgiTly5BCvyxhPc9GubNmyRWzbunXrTOWLOpYuXRoxfzxyuHGNX/sM/ZU7d27JyMhwA1vKysyePbtkZmaqv5QJ4ULFuXLlErTNr78ffmwXvlu4F91qm+cU8PHjx1249Z0rEh3hdRnjaS3ahR/0SG0rX768lCpVSnbu3KmqaNCgQcT88cjhxjV+7TP8MJw4cUJOnTrlBraUlYkHJrTtzJkzKZPBrYrPnj2rxXfGbvv9+h3Lnz+/nD59OmKfFShQwC4uM7/nFLApGTc8RyBv3rzy4YcfynvvvSeFCxeW22+/3XMyUiASIAES0IUAFbAuPeUROcuWLSsPPfSQR6ShGCRAAiSgLwEuQ9K37yg5CZAACZCAxgSogDXuPIpOAiRAAiSgLwEqYH37jpKTAAmQAAloTIAKWOPOo+gkQAIkQAL6EqAC1rfvKDkJkAAJkIDGBKiANe48ik4CJEACJKAvASpgffuOkpMACZAACWhMgApY486j6CRAAiRAAvoSoALWt+8oOQmQAAmQgMYEqIA17jyKTgIkQAIkoC8BKmB9+46SkwAJkAAJaEyACljjzqPoJEACJEAC+hKgAta37yg5CZAACZCAxgSogDXuPIpOAiRAAiSgLwEqYH37jpKTAAmQAAloTIAKWOPOo+gkQAIkQAL6EqAC1rfvKDkJkAAJkIDGBKiANe48ik4CJEACJKAvASpgffuOkpMACZAACWhMgApY486j6CRAAiRAAvoSoALWt+8oOQmQAAmQgMYEqIA17jyKTgIkQAIkoC8BKmB9+46SkwAJkAAJaEyACljjzqPoJEACJEAC+hKgAta37yg5CZAACZCAxgSogDXuPIpOAiRAAiSgLwEqYH37jpKTAAmQAAloTIAKWOPOo+gkQAIkQAL6EqAC1rfvKDkJkAAJkIDGBKiANe48ik4CJEACJKAvASpgffuOkpMACZAACWhMgApY486j6CRAAiRAAvoSoALWt+8oOQmQAAmQgMYEqIA17jyKTgIkQAIkoC8BKmB9+46SkwAJkAAJaEyACljjzqPoJEACJEAC+hKgAta37yg5CZAACZCAxgSogDXuPIpOAiRAAiSgLwEqYH37jpKTAAmQAAloTIAKWOPOo+gkQAIkQAL6EqAC1rfvKDkJkAAJkIDGBKiANe48ik4CJEACJKAvASpgffuOkpMACZAACWhMgApY486j6CRAAiRAAvoSoALWt+8oOQmQAAmQgMYEqIA17jyKTgIkQAIkoC8BKmB9+46SkwAJkAAJaEyACljjzqPoJEACJEAC+hKgAta37yg5CZAACZCAxgSogDXuPIpOAiRAAiSgLwEqYH37jpKTAAmQAAloTIAKWOPOo+gkQAIkQAL6EqAC1rfvKDkJkAAJkIDGBKiANe48ik4CJEACJKAvASpgffuOkpMACZAACWhMgApY486j6CRAAiRAAvoSoALWt+8oOQmQAAmQgMYEqIA17jyKTgIkQAIkoC8BKmB9+46SkwAJkAAJaEwgh5uyHzp0SD7//HPZv3+/lClTRlq1aiU5crhapZvNYdkkQAIkQAIk4BgBV9+A586dK5UrV5Z7771XCfzzzz87JjgLIgESIAESIAGdCbj6OtqoUSMpUKCA4pMzZ071JmyFdfbsWeuuZGZmBuxzhwRIgARIgAT8SiBbltJzXett2LBBPvzwQ+nfv7/kzZvXZDls2DDZtWuXud+2bVtp1qyZuc8NEiABEiABEvAyAUy1FixYMC4RXVfAq1evlhkzZsjdd98tRYoUCRDy5MmTYn0LPnjwoBw7diwgj9d28uTJI8ePH/eaWAnLY/QN5uv9lvzaZ2XLlpW//vpLTp065asug50I3gvOnDnjq3blzp1bihYtKjt27PBVu9AYv37HihUrJtBTULLhUv78+aV48eLhTkc87uoQ9Nq1a+Wrr76Sf/3rX5IvX75/CJIrV66AY0eOHPH8MDR+GJIwaBDAJRk7aFO2bNl82zY/9hnuCz/ej0ab/NhnRtuS8Z1OZh1+bpfxPXODp6sKGMPOp0+fljFjxijZL7/8cmnevLkb7WCZJEACJEACJKAVAVcV8KOPPqoVDApLAiRAAiRAAski4OoypGQ1Il3q2bRpk8BQ7dJLLxUYsKUivf3221KrVi1p3LixLF26NBUisE4SIAES8AUBKmCNuvGZZ56RFStWyOHDh+WNN96QhQsXJlX67du3y+OPP66Wk23evFkGDx6c1PpZGQmQAAn4iQAVsEa9eeDAgQBpg/cDTrqwA8VvNYxJdv0uNIlFkgAJkEDKCDqRQ1cAABnvSURBVFABpwy9/Yr79OkjWMqAVLNmTWnSpIn9QhK4okqVKtKmTRtVAiymsa6biQRIgARIID4CrhphxScSrwpHAJ7FFi1aJDt37hQow1T41X7ppZekb9++ysMZ/HszkQAJkAAJxEeACjg+bim7Cgv58ZfKBOXPRAIkQAIkkBgBDkEnxo9XkwAJkAAJkEBcBKiA48LGi0iABEiABEggMQJUwInx49UkQAIkQAIkEBcBKuC4sPEiEiABEiABEkiMABVwYvx4NQmQAAmQAAnERYAKOC5svIgESIAESIAEEiNABZwYP15NAiRAAiRAAnERoAKOC1v6XrRkyRLp3r279OvXT7Zu3Zp0EMePH5dbb71VeQKDHGfPnk26DBs3bpT77rtPevXqJb/++mvS62eFJEAC/iBARxz+6MektGL//v3Ss2dPOXr0qKoPCvijjz5KSt1GJXB/+f3336vdb775RoYOHSpPP/20cTopn3fffbf8/vvvqq6ffvpJFi9ebLoITYoArIQESMAXBPgG7ItuTE4jtm3bZipf1Lh+/frkVGypZcOGDZY9kdWrVwfsu71z8uRJQVhII+3bt092795t7PKTBEiABGImQAUcMypmhAvKqlWrmiDatWtnbidr4+abbw6o6vbbbw/Yd3snV65c0rp1a7OaOnXqSNmyZc19bpAACZBArAQ4BB0rKeaTnDlzyocffigzZ86UwoULS7NmzZJO5Z577pFy5crJF198Ie3bt5fGjRsnXYbRo0dLy5Yt5cSJE0oZIzIUEwmQAAnYJZAtK75rpt2L3Mr/999/y6FDh9wq3pFy8+TJIzAE8lsqUqSIQJFgSNVvya99dt5558muXbvk1KlTvuoyRPnCz9KZM2d81S7ch+ecc47s2LHDV+1CY/z6HStWrJj6fh08eDBsnxUoUECKFy8e9nykExyCjkQnSecwr/jnn3/GZNG7d+9eWbZsmeOSwboZoQ5jSQiHGOmGjKUM5iEBEiCBdCdABZziOwBLWho2bCjXXnuttGrVSg4cOBBWogkTJkjt2rUF86CXXXZZgEFU2ItiOHHdddfJ9ddfr+qHLJHSI488IldffbVg7jPZFtCR5OI5EiABEtCNABVwinvs9ddfV8OIEGPdunXywQcfhJUIc49GgqIeM2aMsRv3J95mrVa9W7Zskd9++y1keXhYmDx5sjqHYc/hw4eHzMeDJEACJEAC0QlQAUdn5GoOzJ1YU+7cua27AdswgrKm/PnzW3fj2g5VH+Y0QqXgvMH7oa7hMRIgARIggdAEqIBDc0na0T59+sill16q6sMw9C233BK27mHDhgkMVJAqVqyovDGFzRzjCRiFXHXVVWZuDHGXKlXK3LduwOjnoYceEizFgXFCsh1gWGXhNgmQAAnoToBW0DZ70C1rPwzpBr/hhhMNnqjy5csX7nRcx1EerKCPHDkS9frTp0+bDwJRM3sgg1t9luqm0Qo61T1gr37ch7SCtscs1blpBZ3qHkhS/bEqX4jjtPJFmXirxV8syXgLjyUv85AACZAACYQmwCHo0FwSPoplPc8995zMmTMn4bLiKQDrqXv37q2GtH/88ceIRWBJ0ahRo+T555+PaIWNQubNmyfXXHONckQRzQUj2t6xY0cZOHCg4K05UoKM4DVr1qxI2dS5F198UW688UYZN25c1LxuZDh8+LCMHTtWGcFh7ToTCZAACcRDgEPQNqnFMpy5dOnSgLlcWC8n220jlCR8NyNlz55d8EBQokSJkK2FMvvll1/UuUsuuURmzJgRMh8sprEEyUgwwlq7dq2xG/C5fPnygDZj2dQnn3wSkMfYQV7IYEQ2euaZZ6Rz587G6YBPzIO/8cYb5rEhQ4YIvGNFSrH0WaTrg8916dJFBWDA8QsvvFB55crIyAjO5vo+h6BdR+xoBRyCdhRnUgrjEHRSMDtbybfffhtQIKL2JDtt377drBKKLdybON5+DeWLC1atWiV79uwxr7VuTJkyxbqrXDEGHLDsTJs2zbInsmbNmoB96853331nKl8cj8Rr7ty51kuVW8yAAy7vwGkKoh8ZCUuzrKyN4/wkARIggWgEOAQdjVAc5+vWrRtwFZxWJDtZXaPBuCqcg41ChQoJgiwY6YILLlAWzsa+9TP4LT7SvHWLFi2slyqr7YADlp1gPldccYXlbOBm8Llw7Qq8yrk9zJPjbd5ICMRQunRpY5efJEACJBAzgYzHs1LMuV3OeOzYMcEbhpcTDJCizWdiiRCUGoylunbtqgLIJ9thP7xqYWgXMmBIt1atWmGxNm/eXFlgQxHidoBSDpXgLxpDMpivxfZ7770Xdlgbw6N4CPjjjz/UMquJEyeGjZkLJYahbwzRYegZzMLxatq0qfKli3lYDFs//PDDoUQNOBZLnwVcEGUHMiBVr15dsYVlayoS+glW68bQfSpkcKNOTJkgechNvSPNxH2YN29ewb3rt+T0d8wrfPD7ie8XAq+ES3goj9cwlnPA4aiGOe70fGKYapJ+mMEYko484Qo5B5wwwqQWwDngpOJ2pDLOATuCkYWQAAmQAAmQgLcIpP0cMIZGMWeLIdsVK1Y40jsYYsLcJOZTUfbWrVsdKReWzBj2RLkYfo2UELf3oosuUla6//rXvyJllRdeeEENJeNpb8SIERHz9u/fX5WJsjEEHSmhXHjWgqxWf9ORrnHyHIyjbr31VjW8/eSTTzpZNMsiARIggYQJpPUQ9ObNmwMCukdagmOQjmUI+v7775fp06cblyijnXBLcMxMMWzAAMm69haRiXr16hXySihI63w6LJiDjcNwIWIbV6tWLaAMzB0XLFgw4Bh2gpcWwQhr/fr1/8iHAz/88IN06tTJPNeoUSPBw04yEx4WPv30U7PK8ePHS5MmTcx93Tc4BK1XD3IIWq/+grQcgnaxz4KDzyPWrhMpeBlPpBCDduqDkZo1RQrsHWwoZqwJtl6PbTjsCE7h5A2uL7gOaznBLINZW/O6tR1cZ/C+W/WyXBIgARKIhUBaD0HXrFnTXJ4Dq9toQ7WxAEUeOIcwLDmxP2DAAHwknLp3726Wgafpvn37mvvBG4jvayRYI7dt29bYDfiEcw4jGARO4G0Yb1ahEpYWnXvuueapZs2amdvBGwgsAb5IeFO+9957g7O4vn/XXXcpy2pUVLlyZeW9y/VKWQEJkAAJxEggrYegwQgm5nA+gaUk4RSPlWUsQ9DIj7fgr776Sho0aBBTudY6Im3DoQXmqtu0aRPV9H3ZsmXKGxaUr/WBIFT5mF8Gi3r16oU6bR5DHnjKgiK2RlEyM1g28Ia8cuVKtU62ZMmSljPJ20Q//PXXX2re2m/hEzkEnbz7yImaOATtBMXkluH2EHTaK2C73RmrArZbbqrzcxlSqnvAfv1UwPaZpfIKKuBU0o+vbrcVcFoPQaNLMAcKa91gN4uhugtuGxEsYMOGDaFOx31sy5YtMnv27LAuIOMuOMYL4fAA7jPnz5+vhfMDzGeDF95soyW4ikSfoe+YSIAESMBLBHJ4SZhky4K4uldeeaUYxk2wXJ40aVJIMfbv36+GffHjj/liBFgIN68asoAwBzH0261bN2WxDM9GkKF8+fJhcrtz+MEHHzQDJWBo+6WXXnKnIgdK/fnnn5W3LHimKVCggHz88cdqfjdU0TNnzlTz5Bg2L1WqlBo6xxMtEwmQAAl4gUBavwFjaZChfNEZixYtCtsnCAJgWBLjjfGdd94Jm9fOiffff99cLoS3NOuyGTvlxJsXa5atS6Qwv+tla+GpU6eabuEgOxRwuPTuu++abhoRyQlz8kwkQAIk4BUCaa2Aq1atGtAP8NMaLgUbaJUrVy5cVlvHg992nSo3ViHgw9T6Vli4cOGQa4BjLc/tfMF8gvet9QefC9635uU2CZAACSSbQFoHYyhTpoxgaHndunVK6bz88stSoUKFkH2AgAFwToF5RwxbDx06NKoVcsiCgg5iqQ4sdU+dOiU333yz9OjRI2wggqBLHdnFcDq8VSFoAnggcEPwQ4EjFTlUSI0aNdQbOhyIwMMWljeFs/BGuzBqgfM9e/aUDh06OCSFN4phMAZv9EOsUjAYQ6ykvJOPwRi80xdKElpBe6xDYhDHr31GK+gYOt9DWWgF7aHOiFEUWkHHCIrZSIAESIAESEAnAmk9B6xTR7kpK5bqYOgbnrbC+XZ2s34/l/3rr7/KPffco7yhORWUw8+82DYSSCcCab0MKZ06OlxbYdENxWsoByyLWrhwYdh51XDl8Pg/CcDCHmxhZ4CEhxtYmTORAAmQAAjwDTjN7wM4IjGUL1BguY6XlyHp1F0Ih2goX8gNYz+sSWYiARIgARCgAk7z+wCWtIhdbCT4d7YuSzKO89M+gYoVK6r4zcaVCJARzmLbyMNPEiCB9CHAIej06euwLX399dfl66+/Vm4omzZtGjYfT9gjkJGRIXC08tlnn0n+/PmlVatW9gpgbhIgAV8ToAL2dffG1jhECerSpYtaf8zh59iYxZoLirdz586xZmc+EiCBNCLg2yFozL3RAX8a3clsKgmQAAloRsCXChgerWrVqqX+3nzzTc26hOKSAAmQAAmkAwHfKeADBw7I888/r/oOFqfPPvusGewgHTqUbSQBEiABEtCDgO8UMKxMYfxiJOzT8tSgwU8SIAESIAGvEPCdAkbAhMcee0xy5coliG40bNgwgRN0JhIgARIgARLwEgFfaqY77rhDWZ4i0g+Vr5duN8pCAiRAAiRgEPClAkbjcubMabSRnyRAAiRAAiTgOQK+G4L2CuGffvpJRo0aJd98841XRKIcJEACJEACHiLg2zfgVDL+8ccfpVOnTsqzFOR46aWXpE2bNqkUiXWTAAmQAAl4jIDnFDCCVns5YU45mowLFiwwlS/agrfgm266ycvNUnPlmDOP1jZPNyKMcLH0WZhLPX0Y/QUvZlarf08LHKNwWLWAKF3481OCYSjaxu+YPr2K7xbuQ7f6zHMK+Pjx457uHXRENBlr1qwZ0AbsR7sm4IIU7KBd+EH3upzxoImlz+IpN9XX4IfhxIkTcurUqVSL4mj9eGBC286cOeNouV4oDL4J+B3zQk/EJgNcyZ4+fTpinxUoUCC2wkLk8pwCDiGjdocaN24so0ePlnnz5knt2rXltttu064NFJgESIAESMBdAlTALvFt166d4I+JBEiABEiABEIRoBV0KCo8RgIkQAIkQAIuE6ACdhkwiycBEiABEiCBUASogENR4TESIAESIAEScJkAFbDLgFk8CZAACZAACYQiQAUcigqPkQAJkAAJkIDLBKiAXQbM4kmABEiABEggFAEq4FBUeIwESIAESIAEXCZABewyYBZPAiRAAiRAAqEIUAGHosJjJEACJEACJOAyASpglwGzeBIgARIgARIIRYAKOBQVHiMBEiABEiABlwlQAbsMmMWTAAmQAAmQQCgCVMChqPAYCZAACZAACbhMgArYZcAsngRIgARIgARCEaACDkWFx0iABEiABEjAZQJUwC4DZvEkQAIkQAIkEIpAtsysFOoEj6UXgVmzZsmZM2ekTZs26dVwjVs7bNgw6dmzp5QuXVrjVqSP6L/99ptMnz5dHnjggfRptOYt/eCDD9T3q2HDhq60JIcrpbJQ7QicPn1a8MekD4ETJ04In5/16a+zZ8/KyZMn9RGYksqpU6fUi4lbKDgE7RZZlksCJEACJEACEQhQAUeAw1MkQAIkQAIk4BYBzgG7RVazcnft2qWGM0uVKqWZ5Okr7tq1a6VixYqSJ0+e9IWgUcuPHDkiO3bskEqVKmkkdXqLunXrVvX9Kl68uCsgqIBdwcpCSYAESIAESCAyAQ5BR+bDsyRAAiRAAiTgCgEqYFewslASIAESIAESiEyAy5Ai80mLs19++aWsWLFCtbVQoUJy1113pUW7dW0klostWbJEMAdcuHBh6dChg2RkZOjaHN/LjaVHY8aMCWhn8+bNpUaNGgHHuOMtAl9//bVs2LBBihYtqvwj5MuXz3EBqYAdR6pfgatWrZJ7771XcuXKJdmyZdOvAWkm8YIFC9Sa7V69eslXX30l69evl2rVqqUZBX2ai+9Vv379lMCHDx+W1157TS688EJ9GpCGksJYDo5T8Lv43XffycKFC6VZs2aOk+AQtONI9SoQzgFgnbly5Ur58ccfBftM3iawfPlyueiii9Rb8BVXXEHl6+3uUtLlzJlT8PfJJ59I+/btJX/+/BpInb4i5siRQ/CwhNUh27dvd22lARVw+t5jquWHDh2SAgUKqD/j6TzNkXi++QcPHhRMG8B1KN6m8APB5H0CO3fulH379vGByftdZf4mwhUlRpiqVKniitQcgnYFqz6FYg6xf//+SuBLLrlEfvrpJzlw4ICaW9SnFeklKd6kWrRoIeXKlRPMSy1btkzatWuXXhA0bO2iRYukQYMGGkqefiKjry644AI17Izh6Pfee8/8nXSSBt+AnaSpYVl79uyRt99+W0kO4x4YjBQsWFDDlqSPyFC8eAtGwsMSHXHo0fdr1qyRmjVr6iFsmkuZO3duyZs3r6KAB17M47uR+AbsBlWNyoSHF8xHjR8/Xnbv3i1NmzaV7Nn5XOblLmzVqpV88cUX8v333wumEGi17uXe+q9smC7AH37YmbxPoG7duuqt9/fff5djx47J9ddf74rQ9ITlClb9CkXUDyheLmfRp+8wWuHWk7k+FCgpCbhHwO3vGBWwe33HkkmABEiABEggLAGONYZFwxMk4BwBzNViKIuJBEiABAwCVMAGCX6SgAsE4E2ncuXKaukJjKfq1Kkjv/76qws1iXIWEMq70p9//qkcrGAO0u2E6DEvvfSSqgbW2VWrVnW7SpZPAtoSoALWtusouNcJYP6oU6dOMnbsWLVW96+//pKuXbvKjTfe6HXR45YPXrqwRpmJBEggOgEq4OiMmIME4iIAr2JHjx41DaVg5HbffffJuHHjlCtJFPrNN9+opSlFihRRPp2xLAzp//2//ydPPPGE1K5dW8qXLy9Dhw5Vx/Fv9erV0rhxY7VWu0KFCjJq1CjznN2NzMxMGTZsmJx33nlStmxZefrpp1VcaJTTpEkTefPNN1X82tKlS8t//vMfs/iPP/5YLrvsMnXdiBEjlPU8HII8+OCDMn/+fLn99ttVXhj39e3bV/nTxdv/unXrzDK4QQJpTyDrC8hEAiTgEoGnnnoqM8utXWaW8/3MF198MXPz5s1mTVlvxJlZa64zJ02alJmlvDK7d++eOWDAAHV+4MCBmVkeyjJnzZqVmeWJJ7N69eoqH07WqlUrM0vpZWZ5Lsv86KOPMrMs1zP//vvvzCyftZmXXnqpWb6x8ccff2Rm/dBlZq3zNg6Zn2+99VZmllvLzCwHLJlLly7NzHLGkpkV6EGdz1LumVn+bzOz1q9mTp8+PTPL4jpz//79mVk+cjOzlq9lZinhzKyHgcwsxZpZsWLFzKwh7sysh4vMLCchmVnLo1R5qDdLwWdmOTPIzHr7z8xyw2jWzQ0SSHcCfANO+0cwAnCTwKOPPqrmZjEXijdVeNcx3ljxFgnvY23btlVrsR955BGZOXOmKc61114rLVu2VHPInTt3FuRHev311yVLUas1pVmKTzkMwBrueFKWApY777xTBQeAf+kePXpIlrI1i8p6EFDzuG3atFFv3HjLzXookKyHADWUjiAQvXv3Vvnxho815XBcAPemSPhEu0qVKqXqgYN7JhIggf8SoCMO3gkk4BIBGD3B8hkBE/CX9QaslBvmhVu3bi0wWEIYSCg+a9q2bZvavfrqq83DGIqeMmWK2oeyhUtDhCPEMDDqiTeIBurCcPfo0aPNui6//HJzu2TJkuY2lCuGlOGcwJoHTgvCpTJlypinMMx+/Phxc58bJJDuBKiA0/0OYPtdI/Dpp5/Ks88+q3w1G5XccMMNkjVMrOZCoZTr1asXYLSEN0zMtyJZ3xYRrQpvu3v37pWOHTtK1rC1UuLwrAR/0FlDeUYVtj6hPBs2bGh600JADqu1dKjwlJAbc8NGimTVHep64zp+kkC6E+AQdLrfAWy/awRgxIRIKlnzwMpnMxQbwtHhzRWKF24/4U7y559/VjK88847asjZeJudM2eOsp7GGmIMPyMeKRQkEq6FD2g4icdbJd5MrQlRd3C9NUF5W//g+xtBHCZOnKii9ECJw3jKGCK3XmvdRjD5xYsXy9y5c9Vb/BtvvGGexlsy5GUiARKIToBvwNEZMQcJxEUAkaZgEYylR08++aRy84m5ULwZFytWTJX5zDPPqOFkWCDD+TvCCxruQLFuGHOtmFtF9KM+ffqo9bzdunVTltMo4+KLL5arrrpKKXrrcC+GtqFcEevZSOeee66xqT5hgQ2/0pMnT1Zv1yVKlFDrlQcPHhyQL3inaNGiasga88V4qICfXLy5I2EdMqy0MTQOa28mEiCB8AToijI8G54hAccIYC4YyhDBL4ITlFiWdbGplHF+0KBBysgKy49OnDjxjwhVKAvDuxh+diIZihpvsNHSpk2b1Dww3vCRMDeNJUp42EDCGzxkNqLJqIP8RwIk8A8CfAP+BxIeIAHnCUAZhVNIeOM13oiDa0awhVABF2JRlMFlRdq3Ux4MszBv3KtXL/OtfcyYMWbxeGMP11YzEzdIgASEb8C8CUjAgwTgxhGK2Wpt7CUxd+7cqYzHEJcYTkGwnIqJBEjAHgEqYHu8mJsESIAESIAEHCFAK2hHMLIQEiABEiABErBHgArYHi/mJgESIAESIAFHCFABO4KRhZAACZAACZCAPQJUwPZ4MTcJkAAJkAAJOEKACtgRjCyEBEiABEiABOwRoAK2x4u5SYAESIAESMARAv8fubquQdN/FfkAAAAASUVORK5CYII="
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The basic idea in `ggplot2` is to map different plot aesthetics to variables in the dataset. In this plot, we map the x-axis to the variable `Sepal.Length` and the y-axis to the variable `Petal.Length`.\n",
"\n",
"#### Add Color\n",
"\n",
"Now suppose, we want to color the points based on the `Species`. `ggplot2` makes it really easy, since all you need to do is map the aesthetic `color` to the variable `Species`."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +\n",
" geom_point(aes(color = Species))"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 4,
"text": []
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that I could have included the color mapping right inside the `ggplot` line, in which case this mapping would have been applicable globally through all layers. If that doesn't make any sense to you right now, don't worry, as we will get there by the end of this tutorial.\n",
"\n",
"#### Add Line\n",
"\n",
"We are interested in the relationship between `Petal.Length` and `Sepal.Length`. So, let us fit a regression line through the scatterplot. Now, before you start thinking you need to run a `lm` command and gather the predictions using `predict`, I will ask you to stop right there and read the next line of code."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +\n",
" geom_point() + \n",
" geom_smooth(method = 'lm', se = F)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 5,
"text": []
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"
}
],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you are like me when the first time I ran this, you might be thinking this is voodoo! I thought so too, but apparently it is not. It is the beauty of `ggplot2` and the underlying notion of grammar of graphics.\n",
"\n",
"You can extend this idea further and have a regression line plotted for each `Species`."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color = Species)) +\n",
" geom_point() + \n",
" geom_smooth(method = 'lm', se = F)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 6,
"text": []
},
{
"metadata": {},
"output_type": "display_data",
"png": 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"
}
],
"prompt_number": 6
}
],
"metadata": {}
}
]
}

Introduction to ggplot2

This is a short demo on how to convert an R Markdown Notebook into an IPython Notebook using knitr and notedown.

This is an introduction to ggplot2. You can view the source as an R Markdown document, if you are using an IDE like RStudio, or as an IPython notebook, thanks to notedown.

We need to first make sure that we have ggplot2 and its dependencies installed, using the install.packages function.

Now that we have it installed, we can get started by loading it into our workspace

library(ggplot2)

We are now fully set to try and create some amazing plots.

Data

We will use the ubiqutous iris dataset.

head(iris)
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          5.1         3.5          1.4         0.2  setosa
## 2          4.9         3.0          1.4         0.2  setosa
## 3          4.7         3.2          1.3         0.2  setosa
## 4          4.6         3.1          1.5         0.2  setosa
## 5          5.0         3.6          1.4         0.2  setosa
## 6          5.4         3.9          1.7         0.4  setosa

Simple Plot

Let us create a simple scatterplot of Sepal.Length with Petal.Length.

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) + geom_point()

plot of chunk unnamed-chunk-3

The basic idea in ggplot2 is to map different plot aesthetics to variables in the dataset. In this plot, we map the x-axis to the variable Sepal.Length and the y-axis to the variable Petal.Length.

Add Color

Now suppose, we want to color the points based on the Species. ggplot2 makes it really easy, since all you need to do is map the aesthetic color to the variable Species.

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) + geom_point(aes(color = Species))

plot of chunk unnamed-chunk-4

Note that I could have included the color mapping right inside the ggplot line, in which case this mapping would have been applicable globally through all layers. If that doesn't make any sense to you right now, don't worry, as we will get there by the end of this tutorial.

Add Line

We are interested in the relationship between Petal.Length and Sepal.Length. So, let us fit a regression line through the scatterplot. Now, before you start thinking you need to run a lm command and gather the predictions using predict, I will ask you to stop right there and read the next line of code.

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) + geom_point() + geom_smooth(method = "lm", 
    se = F)

plot of chunk unnamed-chunk-5

If you are like me when the first time I ran this, you might be thinking this is voodoo! I thought so too, but apparently it is not. It is the beauty of ggplot2 and the underlying notion of grammar of graphics.

You can extend this idea further and have a regression line plotted for each Species.

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color = Species)) + geom_point() + 
    geom_smooth(method = "lm", se = F)

plot of chunk unnamed-chunk-6

## Introduction to ggplot2
[Download](example.Rmd)
This is a short demo on how to convert an R Markdown Notebook into an IPython Notebook using knitr and notedown.
This is an introduction to [ggplot2](http://github.com/hadley/ggplot2). You can view the source as an R Markdown document, if you are using an IDE like RStudio, or as an IPython notebook, thanks to [notedown](https://github.com/aaren/notedown).
We need to first make sure that we have `ggplot2` and its dependencies installed, using the `install.packages` function.
Now that we have it installed, we can get started by loading it into our workspace
```{r}
library(ggplot2)
```
We are now fully set to try and create some amazing plots.
#### Data
We will use the ubiqutous [iris](http://stat.ethz.ch/R-manual/R-patched/library/datasets/html/iris.html) dataset.
```{r}
head(iris)
```
#### Simple Plot
Let us create a simple scatterplot of `Sepal.Length` with `Petal.Length`.
```{r}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +
geom_point()
```
The basic idea in `ggplot2` is to map different plot aesthetics to variables in the dataset. In this plot, we map the x-axis to the variable `Sepal.Length` and the y-axis to the variable `Petal.Length`.
#### Add Color
Now suppose, we want to color the points based on the `Species`. `ggplot2` makes it really easy, since all you need to do is map the aesthetic `color` to the variable `Species`.
```{r}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +
geom_point(aes(color = Species))
```
Note that I could have included the color mapping right inside the `ggplot` line, in which case this mapping would have been applicable globally through all layers. If that doesn't make any sense to you right now, don't worry, as we will get there by the end of this tutorial.
#### Add Line
We are interested in the relationship between `Petal.Length` and `Sepal.Length`. So, let us fit a regression line through the scatterplot. Now, before you start thinking you need to run a `lm` command and gather the predictions using `predict`, I will ask you to stop right there and read the next line of code.
```{r}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length)) +
geom_point() +
geom_smooth(method = 'lm', se = F)
```
If you are like me when the first time I ran this, you might be thinking this is voodoo! I thought so too, but apparently it is not. It is the beauty of `ggplot2` and the underlying notion of grammar of graphics.
You can extend this idea further and have a regression line plotted for each `Species`.
```{r}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color = Species)) +
geom_point() +
geom_smooth(method = 'lm', se = F)
```
#!/usr/bin/Rscript
library(knitr)
opts_chunk$set(eval = FALSE, tidy = FALSE)
knit('example.Rmd', output = 'example.md')
all: example.ipynb example.html
example.md: example.Rmd
./knit
example.ipynb: example.md
notedown example.md | sed '/%%r/d' > example.ipynb
example.html: example.Rmd
R -e "knitr::knit2html('example.Rmd')"
@lwaldron
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Thanks, this approach worked for me! Although I had to make a couple changes:

  1. rmarkdown::render('example.Rmd') instead of knitr, and
  2. %%R (capital R) in the notedown command

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