<commit_before>{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%load r02.R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!Rscript r02.R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from wand.image import Image  \n",
    "\n",
    "imageFromPdf = Image(filename='Rplots.pdf')  \n",
    "pages = len(imageFromPdf.sequence)  \n",
    "\n",
    "image = Image(  \n",
    "  width=imageFromPdf.width,  \n",
    "  height=imageFromPdf.height * pages  \n",
    ")  \n",
    "for i in range(pages):  \n",
    "  image.composite(  \n",
    "  imageFromPdf.sequence[i],  \n",
    "  top=imageFromPdf.height * i,  \n",
    "  left=0  \n",
    ")  \n",
    "image.format=\"png\"  \n",
    "image "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
<commit_msg>Update a02.ipynb<commit_after>{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%cp RplotsOriginal.pdf Rplots.pdf",
    "%load r02.R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "!Rscript r02.R"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from wand.image import Image  \n",
    "\n",
    "imageFromPdf = Image(filename='Rplots.pdf')  \n",
    "pages = len(imageFromPdf.sequence)  \n",
    "\n",
    "image = Image(  \n",
    "  width=imageFromPdf.width,  \n",
    "  height=imageFromPdf.height * pages  \n",
    ")  \n",
    "for i in range(pages):  \n",
    "  image.composite(  \n",
    "  imageFromPdf.sequence[i],  \n",
    "  top=imageFromPdf.height * i,  \n",
    "  left=0  \n",
    ")  \n",
    "image.format=\"png\"  \n",
    "image "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}

{'fraction_non_alphanumeric': 0.22059823249490143, 'fraction_numerical': 0.010197144799456152, 'mean_word_length': 2.4380841121495327, 'pattern_counts': {'":': 72, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '4513002', 'n_tokens_mistral': 1238, 'n_tokens_neox': 1209, 'n_words': 212}