Plots.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "Plots 3 and 6 from the paper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "plt.style.use('ggplot')\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "%matplotlib inline\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import csv, codecs\n",
    "from matplotlib import colors, ticker, cm\n",
    "import seaborn as sns\n",
    "sns.set(color_codes=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# degree distribution plots\n",
    "data_file = \"dataset/node_stats.csv\"\n",
    "\n",
    "in_degrees = list()\n",
    "out_degrees = list()\n",
    "in_degrees_ref = list()\n",
    "out_degrees_ref = list()\n",
    "with codecs.open(data_file, \"r\", encoding=\"utf-8\") as f:\n",
    "    csv_reader = csv.reader(f,delimiter=';', quotechar='\"')\n",
    "    next(csv_reader, None)  # skip the headers\n",
    "    for row in csv_reader:\n",
    "        if len(row) < 10:\n",
    "            continue\n",
    "        internal_id,bid,title,author,lb,year,consultation,indegree,outdegree,degree = row\n",
    "        in_degrees.append(int(indegree))\n",
    "        out_degrees.append(int(outdegree))\n",
    "        if lb == \"True\":\n",
    "            in_degrees_ref.append(int(indegree))\n",
    "            if int(outdegree)>0:\n",
    "                out_degrees_ref.append(int(outdegree))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "37626\n",
      "71650\n",
      "3933\n"
     ]
    }
   ],
   "source": [
    "print(len(in_degrees))\n",
    "print(sum(in_degrees))\n",
    "print(sum(in_degrees_ref))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Huk939wfk7OyspKQzatGilaRbfxhHRoZp4MBXrX8sX7qUIXf3W+v8fhsVKlTW/v0JuT7D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\nAQAADo9AAwAAHB6BBgAAOLz/D2sl79bONpBqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112110978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(in_degrees, bins=150, kde=False, rug=False, hist=True, label=\"All\")\n",
    "sns.distplot(in_degrees_ref, bins=150, kde=False, rug=False, hist=True, color=\"red\", label=\"Reference monographs\")\n",
    "plt.legend(loc=\"best\",fontsize=14)\n",
    "plt.ylabel(\"Number of cited monographs\", fontsize=14)\n",
    "plt.xlabel(\"In-degree\", fontsize=14)\n",
    "plt.xlim([0,100])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6mzZt0LffrlFk5BlNnDju/0/Tf/SF9JKSkvTJJzP0739v1MWLv2vDhvWKi7tnPSPL1jL1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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112110828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(in_degrees, bins=150, log=True, label=\"All\")\n",
    "plt.hist(in_degrees_ref, bins=150, log=True, color=\"red\", label=\"Reference monographs\")\n",
    "plt.legend(loc=\"best\",fontsize=14)\n",
    "plt.ylabel(\"Number of cited monographs\", fontsize=14)\n",
    "plt.xlabel(\"In-degree\", fontsize=14)\n",
    "plt.xlim([0,80])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ub731ls6ePatXX31V69evl4eHR6bHXLgQm6M1Yq/d0IULsfZ/3j6e2f7ZzXl7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\nAKZHoAEAAKZHoAEAAKb3/wDpxMIJsdQlBwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11550f278>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(out_degrees_ref, bins=600, kde=False, rug=False, hist=True, label=\"Reference monographs\")\n",
    "plt.legend(loc=\"best\",fontsize=14)\n",
    "plt.ylabel(\"Number of citing monographs\", fontsize=14)\n",
    "plt.xlabel(\"Out-degree\", fontsize=14)\n",
    "plt.xlim([0,620])\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    ""
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [conda env:lb_main_analysis]",
   "language": "python",
   "name": "conda-env-lb_main_analysis-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3.0
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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