ucsd_newspapers.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First let's change our current working directory to the folder where the data is located using `os.chdir`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import os\n",
    "os.chdir(\"E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's confirm that the changes are in effect by checking the current working directory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw'"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.getcwd()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's open one of the newspaper's files and have a look at the contents. We'll start with the *Student Newspapers*, just because it's listed first alphabetically. We'll list all the files in the directory, open the first one and inspect the content by displaying the first 2000 characters in the file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['bb0001069r-1.pdf.txt',\n",
       " 'bb0001070k-1.pdf.txt',\n",
       " 'bb0035197d-1.pdf.txt',\n",
       " 'bb0035198x-1.pdf.txt',\n",
       " 'bb0035199f-1.pdf.txt',\n",
       " 'bb0035200w-1.pdf.txt',\n",
       " 'bb0069327q-1.pdf.txt',\n",
       " 'bb00693287-1.pdf.txt',\n",
       " 'bb0069329r-1.pdf.txt',\n",
       " 'bb01034597-1.pdf.txt']"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "journal_name = 'Student Newspapers'\n",
    "path = os.path.join(os.getcwd(), journal_name)\n",
    "files = os.listdir(path)\n",
    "files[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`os.listdir()` returns the names of the files but not their path, which we need to be able to open them. For now we'll just use `os.path.join()` again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "UnicodeDecodeError",
     "evalue": "'cp949' codec can't decode byte 0xe2 in position 112: illegal multibyte sequence",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m                        Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-60-07ba77832afe>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0mfile\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mos\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfiles\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfile\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'r'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mcontent\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mread\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mcontent\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;36m2000\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mUnicodeDecodeError\u001b[0m: 'cp949' codec can't decode byte 0xe2 in position 112: illegal multibyte sequence"
     ]
    }
   ],
   "source": [
    "file = os.path.join(path, files[0])\n",
    "with open(file, 'r') as fp:\n",
    "    content = fp.read()\n",
    "    \n",
    "content[:2000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Woops. Encoding error. Let's fix this by specifying the encoding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nInleS\\nvo,.2,o.t i\\n\\nS.D. State\\nSummer\\nSchool\\n350 classes in 36 depart-\\n\\nments will be offered in San\\nDiego State’s summer ses-\\nsions. The courses will lead\\nto bachelor of science, bache-\\nlor of arts, teaching creden-\\ntials and master’s degrees.\\nThe intersession, first of\\n\\nthe three siimmor ~o~inn~\\nruns from June 13 to June 24.\\nStudents may earn up to two\\nacademic units of credit (3\\nquarter units at UCSD).\\nTerm 1, a six-week session,\\n\\nwill follow, from June 27 to\\nAugust 5, with a maximum of\\nsix units of credit being of-\\nfered. Registration will be\\nheld on June 27.\\nThe final summer session,\\n\\nTerm 2, will be a three-week\\nsession from August 8 to\\nAugust 27. Three academic\\nunits may be earned. Regis-\\ntration will be held on Au-\\ngu st 8.\\nSummer fees will be $18.50\\n\\nfor each semester unit, with\\na parking fee of $5 required\\nonly during the six week ses-\\nsion, Term 1.\\n\\nSan Diego, California\\n\\nBIG MEN VOTE \"NO\" ON GUANO: Riparm riparia, the cliff\\nswallow, will have to find o friendlier nesting place than the\\nUCSD Library. (See \"Guest Editorial\"\\n\\nThree Professors Make\\nAmerican Academy\\n\\nDr. Pearce\\n\\ntors, historians, writers and\\nartists. Four women were\\nhonored and 10 foreign coun-\\ntries, including Russia,\\nEngland, Israel and Greece,\\nwere represented.\\nAs Chairman of the Depart-\\n\\nment of Neuroscience, Dr.\\nLivingston heads the first\\ndepartment established at\\nthe UCSD School of Medi-\\ncine. He was born in Boston,\\nMassachusetts and received\\nboth his undergraduate and\\nmedical degrees from Stan-\\nford University. He was asso-\\nciated with the National\\nInstitutes of Health prior to\\njoining the UCSD faculty in\\n1965.\\nDr. Pearce received his\\n\\nB.S. and M.A. degrees from\\nUCLA and his Ph.D. from\\nJohns Hopkins University in\\n1945. He is the author of many\\nbooks, his principal works\\nbeing The Savages of America,\\n\\nDr. Livingston\\n\\nThree faculty members\\nfrom the University of Cal-\\nifornia, San Diego have been\\nnamed among 150 leaders of\\nscholarship, the professions,\\nbusiness and international af-\\nfairs'"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = os.path.join(path, files[0])\n",
    "with open(file, 'r', encoding = 'utf8') as fp:\n",
    "    content = fp.read()\n",
    "    \n",
    "content[:2000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, let's get rid of the hyphenation using regular expressions (for which we'll need the **re** package). We'll create a specific function for it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nInleS\\nvo,.2,o.t i\\n\\nS.D. State\\nSummer\\nSchool\\n350 classes in 36 departments will be offered in San\\nDiego State’s summer sessions. The courses will lead\\nto bachelor of science, bachelor of arts, teaching credentials and master’s degrees.\\nThe intersession, first of\\n\\nthe three siimmor ~o~inn~\\nruns from June 13 to June 24.\\nStudents may earn up to two\\nacademic units of credit (3\\nquarter units at UCSD).\\nTerm 1, a six-week session,\\n\\nwill follow, from June 27 to\\nAugust 5, with a maximum of\\nsix units of credit being offered. Registration will be\\nheld on June 27.\\nThe final summer session,\\n\\nTerm 2, will be a three-week\\nsession from August 8 to\\nAugust 27. Three academic\\nunits may be earned. Registration will be held on Augu st 8.\\nSummer fees will be $18.50\\n\\nfor each semester unit, with\\na parking fee of $5 required\\nonly during the six week session, Term 1.\\n\\nSan Diego, California\\n\\nBIG MEN VOTE \"NO\" ON GUANO: Riparm riparia, the cliff\\nswallow, will have to find o friendlier nesting place than the\\nUCSD Library. (See \"Guest Editorial\"\\n\\nThree Professors Make\\nAmerican Academy\\n\\nDr. Pearce\\n\\ntors, historians, writers and\\nartists. Four women were\\nhonored and 10 foreign countries, including Russia,\\nEngland, Israel and Greece,\\nwere represented.\\nAs Chairman of the Department of Neuroscience, Dr.\\nLivingston heads the first\\ndepartment established at\\nthe UCSD School of Medicine. He was born in Boston,\\nMassachusetts and received\\nboth his undergraduate and\\nmedical degrees from Stanford University. He was associated with the National\\nInstitutes of Health prior to\\njoining the UCSD faculty in\\n1965.\\nDr. Pearce received his\\n\\nB.S. and M.A. degrees from\\nUCLA and his Ph.D. from\\nJohns Hopkins University in\\n1945. He is the author of many\\nbooks, his principal works\\nbeing The Savages of America,\\n\\nDr. Livingston\\n\\nThree faculty members\\nfrom the University of California, San Diego have been\\nnamed among 150 leaders of\\nscholarship, the professions,\\nbusiness and international affairs elected to membership\\nin the Am'"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "def preprocess(text):\n",
    "    return re.sub('\\-\\n+', '', text)\n",
    "\n",
    "content = preprocess(content)\n",
    "content[:2000]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we want to be able to load all the files in the directory and apply the preprocessing to them. To do that, we'll first define a function that will return the full path of all the files in the directory and will makes sure that we are only dealing with text files (so that we don't try to open a folder or another filetype that would cause an error):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0001069r-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0001070k-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035197d-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035198x-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035199f-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035200w-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0069327q-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb00693287-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0069329r-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb01034597-1.pdf.txt']"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def load_files(directory):\n",
    "    path = os.path.join(os.getcwd(), directory)\n",
    "    files = os.listdir(path)\n",
    "    files = [os.path.join(path, _) for _ in files if '.txt' in _]\n",
    "    return files\n",
    "\n",
    "load_files(path)[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once we have all the files, we'll create a new function `load_data` to each file one by one, preprocess it and store the result in memory in an array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def load_data(files):\n",
    "    X = []\n",
    "    for file in files:\n",
    "        with open(file, 'r', encoding = 'utf8') as fp:\n",
    "            content = fp.read()\n",
    "            content = preprocess(content)\n",
    "        X.append(content)\n",
    "    return X"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's actually run the function and get the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "files = load_files(journal_name)\n",
    "documents = load_data(files)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "646"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(documents)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we'll vectorize the documents. We'll only keep terms that appear in less than 80% of the documents and at least twice in the corpus. We'll limit the number of features to 5000."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import TfidfVectorizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "vectorizer = TfidfVectorizer(max_df=0.8, min_df=2, max_features=5000, stop_words='english')\n",
    "X = vectorizer.fit_transform(documents)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we'll apply non-negative matrix factorization to do topic modeling. We'll try with 25 topics first:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from sklearn.decomposition import NMF\n",
    "nmf = NMF(n_components=25, init = 'nndsvd').fit(X)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's have a look at nmf.components_ to understand the output and try to interprete the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(25, 5000)"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.shape(nmf.components_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.04770388,  0.02705699,  0.        , ...,  0.00333239,\n",
       "         0.00721114,  0.02602281],\n",
       "       [ 0.        ,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.00745978,  0.00579664],\n",
       "       [ 0.        ,  0.        ,  0.00568511, ...,  0.        ,\n",
       "         0.        ,  0.00607028],\n",
       "       ..., \n",
       "       [ 0.01358303,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        ,  0.        ],\n",
       "       [ 0.00883111,  0.00680038,  0.        , ...,  0.        ,\n",
       "         0.00641064,  0.01085206],\n",
       "       [ 0.00666498,  0.        ,  0.        , ...,  0.        ,\n",
       "         0.        ,  0.        ]])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nmf.components_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2499, 2051, 2049, ..., 2602, 4747, 4960], dtype=int64)"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nmf.components_[0].argsort()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "item\n",
      "workers\n"
     ]
    }
   ],
   "source": [
    "vocabulary = vectorizer.get_feature_names()\n",
    "print(vocabulary[2499])\n",
    "print(vocabulary[4960])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nmf.components_[0][2499]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.1017209030802835"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nmf.components_[0][4960]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([4960, 4747, 2602, ..., 2049, 2051, 2499], dtype=int64)"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nmf.components_[0].argsort()[::-1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's now print the top 10 words for the first topic:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['workers',\n",
       " 'union',\n",
       " 'labor',\n",
       " 'ufw',\n",
       " 'strike',\n",
       " 'mexico',\n",
       " 'mexican',\n",
       " 'north',\n",
       " 'city',\n",
       " 'april']"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[vocabulary[i] for i in nmf.components_[0].argsort()[::-1][:10]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's create a function that will allow us to do that for all the topics:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def display_topics(model, vocabulary, no_words):\n",
    "    for index, topic in enumerate(model.components_):\n",
    "        print(\"Topic\", index, \":\")\n",
    "        print(\" \".join([vocabulary[i] for i in topic.argsort()[::-1][:no_words]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Topic 0 :\n",
      "workers union labor ufw strike mexico mexican north city april police company health industry border\n",
      "Topic 1 :\n",
      "revelle provost dean revellations quarter resident blake feb plaza argo orientation humanities spring seniors dr\n",
      "Topic 2 :\n",
      "ol lhc hc ill lhe ha arc ith bc thc tile ot el ihc pm\n",
      "Topic 3 :\n",
      "black blacks white african bsu negro dr voice king whites malcolm sisters afro brothers garvey\n",
      "Topic 4 :\n",
      "soviet cr review soviets reagan crocker nicaragua sandinistas communist union freedom sandinista conservative gorbachev dr\n",
      "Topic 5 :\n",
      "sandscript team dr hall kerr club galbraith shores freshman senate editor matthews mr freshmen sports\n",
      "Topic 6 :\n",
      "que en los el para las una se sus del su por es workers clue\n",
      "Topic 7 :\n",
      "indicator 534 info peace pm meets collective resource ch cable morley op 7pm 1990 mondays\n",
      "Topic 8 :\n",
      "asian islander korean japanese momentum pacific americans asians chinese ethnic culture identity 1992 stereotypes tile\n",
      "Topic 9 :\n",
      "daycare reg chancellor fee care communications childcare tenure graduate mceiroy referendum armitage mcelroy parents cep\n",
      "Topic 10 :\n",
      "iraq bush war saddam 2003 iraqi kerry oil military hussein www lraq tbr terrorism terrorists\n",
      "Topic 11 :\n",
      "research war dr military ida defense scripps murphy vietnam regents ruling scientists classified mcgill strike\n",
      "Topic 12 :\n",
      "media indicator council alternative 1986 budget progressive funding maccrone paper constitution album 202 chancellor proposal\n",
      "Topic 13 :\n",
      "africa south african apartheid divestment africans bakke investment struggle regents uc penn 1985 israel investments\n",
      "Topic 14 :\n",
      "jewish jews zionist zionism israel palestine arab palestinian israeli zionists semitism draft anti palestinians arabs\n",
      "Topic 15 :\n",
      "socialism revolution war party marx soviet socialist revolutionary stalin workers movement russian draft capitalist russia\n",
      "Topic 16 :\n",
      "cia saxon uc coors hearings chile attiyeh agency research murphy senate 1975 intelligence communications angola\n",
      "Topic 17 :\n",
      "review clinton tax bush conservative liberal conservatives federal democrats republican spending republicans taxes editor 1994\n",
      "Topic 18 :\n",
      "nuclear plant weapons energy radioactive plants reactor radiation water safety missiles missile arms systems soviet\n",
      "Topic 19 :\n",
      "reagan salvador military nicaragua pm el draft april workers war peace protest central aid nicaraguan\n",
      "Topic 20 :\n",
      "commuter cab revelle lounge quarter dean plaza grade finals argo love 534 drop classes revellations\n",
      "Topic 21 :\n",
      "ill ihe il io ih ihal li lit al lilt lh lll lhe ihc thai\n",
      "Topic 22 :\n",
      "referendum rimac fee fees ops op council gsa ucb election price uc cooperative referenda bylaws\n",
      "Topic 23 :\n",
      "police war vietnam vietnamese white nixon law cleaver human north kind city got woman military\n",
      "Topic 24 :\n",
      "rcc revelle council commuter parking programming committees april plaza cab elected input intern affecting body\n"
     ]
    }
   ],
   "source": [
    "display_topics(nmf, vocabulary, 15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that we can also use nmf to get the distribution of each of our topic within a specific document (what percentage of document a concerns topic 1, 2 or 3? ) by normalizing the results of the NMF over the corpus:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "doc_topics = nmf.transform(X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(646, 25)"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(doc_topics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.01322529,  0.        ,  0.01075261,  0.00593091,\n",
       "        0.27822003,  0.        ,  0.        ,  0.00929646,  0.        ,\n",
       "        0.00431371,  0.01570553,  0.01114917,  0.0077475 ,  0.00769204,\n",
       "        0.01791881,  0.        ,  0.03688016,  0.0015401 ,  0.        ,\n",
       "        0.01337364,  0.00523631,  0.02769023,  0.02175224,  0.01639838])"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doc_topics[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.50482312014044284"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(doc_topics[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "doc_topics = doc_topics / np.sum(doc_topics, axis=1, keepdims=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.02619786,  0.        ,  0.02129977,  0.01174848,\n",
       "        0.55112378,  0.        ,  0.        ,  0.01841528,  0.        ,\n",
       "        0.00854499,  0.03111095,  0.02208531,  0.01534697,  0.0152371 ,\n",
       "        0.03549523,  0.        ,  0.07305561,  0.00305077,  0.        ,\n",
       "        0.02649174,  0.01037257,  0.05485135,  0.04308883,  0.03248341])"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doc_topics[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's have a look at what metadata we can work with by opening the csv file corresponding to the corpus we're looking at. We will use the **pandas** package to load the csv file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "# we've stored the name of the journal in a variable earlier, we can reuse this here so that we can more easily switch to another corpus in the future\n",
    "df = pd.read_csv(journal_name + '.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Object Unique ID', 'Level', 'File name', 'File use',\n",
       "       'Type of Resource', 'Language', 'Title', 'Subtitle', 'Translation',\n",
       "       'Variant', 'Variant.1', 'Variant.2', 'Begin date', 'Date:creation',\n",
       "       'End date', 'File name 2', 'File use 2', 'Identifier:filename',\n",
       "       'Identifier:local', 'Note:local attribution', 'Note:note',\n",
       "       'Note:note.1', 'Note:note.2', 'Note:note.3', 'Note:publication',\n",
       "       'Note:publication.1', 'Note:series', 'Subject:topic'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And the first entries..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Object Unique ID</th>\n",
       "      <th>Level</th>\n",
       "      <th>File name</th>\n",
       "      <th>File use</th>\n",
       "      <th>Type of Resource</th>\n",
       "      <th>Language</th>\n",
       "      <th>Title</th>\n",
       "      <th>Subtitle</th>\n",
       "      <th>Translation</th>\n",
       "      <th>Variant</th>\n",
       "      <th>...</th>\n",
       "      <th>Identifier:local</th>\n",
       "      <th>Note:local attribution</th>\n",
       "      <th>Note:note</th>\n",
       "      <th>Note:note.1</th>\n",
       "      <th>Note:note.2</th>\n",
       "      <th>Note:note.3</th>\n",
       "      <th>Note:publication</th>\n",
       "      <th>Note:publication.1</th>\n",
       "      <th>Note:series</th>\n",
       "      <th>Subject:topic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>http://library.ucsd.edu/ark:/20775/bb8772477z</td>\n",
       "      <td>Object</td>\n",
       "      <td>20775-bb8772477z-0-1.pdf</td>\n",
       "      <td>document-service</td>\n",
       "      <td>text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sandscript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Special Collections &amp; Archives, UC San Diego, ...</td>\n",
       "      <td>PDF file includes photographs</td>\n",
       "      <td>\"UCSD's first weekly student newspaper.\" Frequ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...</td>\n",
       "      <td>La Jolla, CA</td>\n",
       "      <td>Volume 1, Issue 1</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>http://library.ucsd.edu/ark:/20775/bb9352689j</td>\n",
       "      <td>Object</td>\n",
       "      <td>20775-bb9352689j-0-1.pdf</td>\n",
       "      <td>document-service</td>\n",
       "      <td>text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sandscript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Special Collections &amp; Archives, UC San Diego, ...</td>\n",
       "      <td>\"UCSD's first weekly student newspaper.\" Frequ...</td>\n",
       "      <td>PDF file includes photographs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...</td>\n",
       "      <td>La Jolla, CA</td>\n",
       "      <td>Volume 1, Issue 2</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>http://library.ucsd.edu/ark:/20775/bb6007948n</td>\n",
       "      <td>Object</td>\n",
       "      <td>20775-bb6007948n-0-1.pdf</td>\n",
       "      <td>document-service</td>\n",
       "      <td>text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sandscript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Special Collections &amp; Archives, UC San Diego, ...</td>\n",
       "      <td>\"UCSD's first weekly student newspaper.\" Frequ...</td>\n",
       "      <td>PDF file includes photographs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>La Jolla, CA</td>\n",
       "      <td>Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...</td>\n",
       "      <td>Volume 1, Issue 3</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>http://library.ucsd.edu/ark:/20775/bb6622290j</td>\n",
       "      <td>Object</td>\n",
       "      <td>20775-bb6622290j-0-1.pdf</td>\n",
       "      <td>document-service</td>\n",
       "      <td>text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sandscript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Special Collections &amp; Archives, UC San Diego, ...</td>\n",
       "      <td>\"UCSD's first weekly student newspaper.\" Frequ...</td>\n",
       "      <td>PDF file includes photographs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...</td>\n",
       "      <td>La Jolla, CA</td>\n",
       "      <td>Volume 1, Issue 4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>http://library.ucsd.edu/ark:/20775/bb6758810b</td>\n",
       "      <td>Object</td>\n",
       "      <td>20775-bb6758810b-0-1.pdf</td>\n",
       "      <td>document-service</td>\n",
       "      <td>text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sandscript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Special Collections &amp; Archives, UC San Diego, ...</td>\n",
       "      <td>PDF file includes photographs</td>\n",
       "      <td>\"UCSD's first weekly student newspaper.\" Frequ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...</td>\n",
       "      <td>La Jolla, CA</td>\n",
       "      <td>Volume 1, Issue 5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Object Unique ID   Level  \\\n",
       "0  http://library.ucsd.edu/ark:/20775/bb8772477z  Object   \n",
       "1  http://library.ucsd.edu/ark:/20775/bb9352689j  Object   \n",
       "2  http://library.ucsd.edu/ark:/20775/bb6007948n  Object   \n",
       "3  http://library.ucsd.edu/ark:/20775/bb6622290j  Object   \n",
       "4  http://library.ucsd.edu/ark:/20775/bb6758810b  Object   \n",
       "\n",
       "                  File name          File use Type of Resource Language  \\\n",
       "0  20775-bb8772477z-0-1.pdf  document-service             text      NaN   \n",
       "1  20775-bb9352689j-0-1.pdf  document-service             text      NaN   \n",
       "2  20775-bb6007948n-0-1.pdf  document-service             text      NaN   \n",
       "3  20775-bb6622290j-0-1.pdf  document-service             text      NaN   \n",
       "4  20775-bb6758810b-0-1.pdf  document-service             text      NaN   \n",
       "\n",
       "        Title Subtitle  Translation Variant      ...      Identifier:local  \\\n",
       "0  Sandscript      NaN          NaN     NaN      ...                   NaN   \n",
       "1  Sandscript      NaN          NaN     NaN      ...                   NaN   \n",
       "2  Sandscript      NaN          NaN     NaN      ...                   NaN   \n",
       "3  Sandscript      NaN          NaN     NaN      ...                   NaN   \n",
       "4  Sandscript      NaN          NaN     NaN      ...                   NaN   \n",
       "\n",
       "                              Note:local attribution  \\\n",
       "0  Special Collections & Archives, UC San Diego, ...   \n",
       "1  Special Collections & Archives, UC San Diego, ...   \n",
       "2  Special Collections & Archives, UC San Diego, ...   \n",
       "3  Special Collections & Archives, UC San Diego, ...   \n",
       "4  Special Collections & Archives, UC San Diego, ...   \n",
       "\n",
       "                                           Note:note  \\\n",
       "0                      PDF file includes photographs   \n",
       "1  \"UCSD's first weekly student newspaper.\" Frequ...   \n",
       "2  \"UCSD's first weekly student newspaper.\" Frequ...   \n",
       "3  \"UCSD's first weekly student newspaper.\" Frequ...   \n",
       "4                      PDF file includes photographs   \n",
       "\n",
       "                                         Note:note.1 Note:note.2 Note:note.3  \\\n",
       "0  \"UCSD's first weekly student newspaper.\" Frequ...         NaN         NaN   \n",
       "1                      PDF file includes photographs         NaN         NaN   \n",
       "2                      PDF file includes photographs         NaN         NaN   \n",
       "3                      PDF file includes photographs         NaN         NaN   \n",
       "4  \"UCSD's first weekly student newspaper.\" Frequ...         NaN         NaN   \n",
       "\n",
       "                                    Note:publication  \\\n",
       "0  Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...   \n",
       "1  Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...   \n",
       "2                                       La Jolla, CA   \n",
       "3  Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...   \n",
       "4  Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...   \n",
       "\n",
       "                                  Note:publication.1        Note:series  \\\n",
       "0                                       La Jolla, CA  Volume 1, Issue 1   \n",
       "1                                       La Jolla, CA  Volume 1, Issue 2   \n",
       "2  Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...  Volume 1, Issue 3   \n",
       "3                                       La Jolla, CA  Volume 1, Issue 4   \n",
       "4                                       La Jolla, CA  Volume 1, Issue 5   \n",
       "\n",
       "  Subject:topic  \n",
       "0           NaN  \n",
       "1           NaN  \n",
       "2           NaN  \n",
       "3           NaN  \n",
       "4           NaN  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We notice that the filenames listed do not exactly correspond to the names of the raw text files we have used before, nor are they listed in the same order:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0001069r-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0001070k-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035197d-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035198x-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035199f-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0035200w-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0069327q-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb00693287-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb0069329r-1.pdf.txt',\n",
       " 'E:\\\\Code Projects\\\\UCSD Newspapers\\\\ucsdHistory_raw 2\\\\ucsdHistory_raw\\\\Student Newspapers\\\\bb01034597-1.pdf.txt']"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "files[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For that reason we will need to process our filenames and match them to the appropriate row in the dataframe as well as to the appropriate topic distribution in the NMF matrix we created earlier from the corpus.\n",
    "\n",
    "We notice that the Object Unique ID of each row can be found in the filenames of the text files we have, so let's use that to match the raw text to the rows of the csv. Let's do a test with the first file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'bb0001069r'"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_id = files[0].split('\\\\')[-1].split('-')[0]\n",
    "file_id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0      False\n",
       "1      False\n",
       "2      False\n",
       "3      False\n",
       "4      False\n",
       "5      False\n",
       "6      False\n",
       "7      False\n",
       "8      False\n",
       "9      False\n",
       "10     False\n",
       "11     False\n",
       "12     False\n",
       "13     False\n",
       "14     False\n",
       "15     False\n",
       "16     False\n",
       "17     False\n",
       "18     False\n",
       "19     False\n",
       "20     False\n",
       "21     False\n",
       "22     False\n",
       "23     False\n",
       "24     False\n",
       "25     False\n",
       "26     False\n",
       "27     False\n",
       "28     False\n",
       "29      True\n",
       "       ...  \n",
       "616    False\n",
       "617    False\n",
       "618    False\n",
       "619    False\n",
       "620    False\n",
       "621    False\n",
       "622    False\n",
       "623    False\n",
       "624    False\n",
       "625    False\n",
       "626    False\n",
       "627    False\n",
       "628    False\n",
       "629    False\n",
       "630    False\n",
       "631    False\n",
       "632    False\n",
       "633    False\n",
       "634    False\n",
       "635    False\n",
       "636    False\n",
       "637    False\n",
       "638    False\n",
       "639    False\n",
       "640    False\n",
       "641    False\n",
       "642    False\n",
       "643    False\n",
       "644    False\n",
       "645    False\n",
       "Name: Object Unique ID, dtype: bool"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Object Unique ID'].str.contains(file_id)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Object Unique ID</th>\n",
       "      <th>Level</th>\n",
       "      <th>File name</th>\n",
       "      <th>File use</th>\n",
       "      <th>Type of Resource</th>\n",
       "      <th>Language</th>\n",
       "      <th>Title</th>\n",
       "      <th>Subtitle</th>\n",
       "      <th>Translation</th>\n",
       "      <th>Variant</th>\n",
       "      <th>...</th>\n",
       "      <th>Identifier:local</th>\n",
       "      <th>Note:local attribution</th>\n",
       "      <th>Note:note</th>\n",
       "      <th>Note:note.1</th>\n",
       "      <th>Note:note.2</th>\n",
       "      <th>Note:note.3</th>\n",
       "      <th>Note:publication</th>\n",
       "      <th>Note:publication.1</th>\n",
       "      <th>Note:series</th>\n",
       "      <th>Subject:topic</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>http://library.ucsd.edu/ark:/20775/bb0001069r</td>\n",
       "      <td>Object</td>\n",
       "      <td>20775-bb0001069r-0-1.pdf</td>\n",
       "      <td>document-service</td>\n",
       "      <td>text</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Sandscript</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Special Collections &amp; Archives, UC San Diego, ...</td>\n",
       "      <td>\"UCSD's first weekly student newspaper.\" Frequ...</td>\n",
       "      <td>PDF file includes photographs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>La Jolla, CA</td>\n",
       "      <td>Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...</td>\n",
       "      <td>Volume 2, Issue 14</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 Object Unique ID   Level  \\\n",
       "29  http://library.ucsd.edu/ark:/20775/bb0001069r  Object   \n",
       "\n",
       "                   File name          File use Type of Resource Language  \\\n",
       "29  20775-bb0001069r-0-1.pdf  document-service             text      NaN   \n",
       "\n",
       "         Title Subtitle  Translation Variant      ...      Identifier:local  \\\n",
       "29  Sandscript      NaN          NaN     NaN      ...                   NaN   \n",
       "\n",
       "                               Note:local attribution  \\\n",
       "29  Special Collections & Archives, UC San Diego, ...   \n",
       "\n",
       "                                            Note:note  \\\n",
       "29  \"UCSD's first weekly student newspaper.\" Frequ...   \n",
       "\n",
       "                      Note:note.1 Note:note.2 Note:note.3 Note:publication  \\\n",
       "29  PDF file includes photographs         NaN         NaN     La Jolla, CA   \n",
       "\n",
       "                                   Note:publication.1         Note:series  \\\n",
       "29  Vol. 1, no. 1 (10 Feb. 1965)- Ceased with issu...  Volume 2, Issue 14   \n",
       "\n",
       "   Subject:topic  \n",
       "29           NaN  \n",
       "\n",
       "[1 rows x 28 columns]"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['Object Unique ID'].str.contains(file_id)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's try to extract the date for this particular row. There are several date columns (BeginDate, EndDate, ...) but they all seem to be equivalent, so let's go with BeginDate..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "29    6/3/66\n",
       "Name: Begin date, dtype: object"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_date = df['Begin date'][df['Object Unique ID'].str.contains(file_id)]\n",
    "test_date"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are getting the right value, but the format of the output tells us that the data type returned is not exactly standard. Let's confirm this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(test_date)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This is a variable type specific to pandas, so we might run into trouble when trying to perform standard operations over it or sending it to some package's function. Let's make sure we only get the value and not the **pandas** Series cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['6/3/66']\n",
      "<class 'numpy.ndarray'>\n"
     ]
    }
   ],
   "source": [
    "test_date = df['Begin date'][df['Object Unique ID'].str.contains(file_id)].values\n",
    "print(test_date)\n",
    "print(type(test_date))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Almost there..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6/3/66\n",
      "<class 'str'>\n"
     ]
    }
   ],
   "source": [
    "test_date = df['Begin date'][df['Object Unique ID'].str.contains(file_id)].values[0]\n",
    "print(test_date)\n",
    "print(type(test_date))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok. So now we have a standard string. Which is good, but not ideal in case we want to perform some calculations on the date (substraction or extracting the month, year...). We can use the **dateparser** package to help us:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'datetime.datetime'>\n",
      "2066-06-03 00:00:00\n"
     ]
    }
   ],
   "source": [
    "import dateparser\n",
    "parsed = dateparser.parse(test_date)\n",
    "print(type(parsed))\n",
    "print(parsed)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A little parsing mistake here but we can handle that later. Let's iterate over all our files and store the results:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from collections import defaultdict\n",
    "yearbook = defaultdict(list)\n",
    "\n",
    "for i, file in enumerate(files):\n",
    "    doc_year = dateparser.parse(df['Begin date'][df['Object Unique ID'].str.contains(file.split('\\\\')[-1].split('-')[0])].values[0]).year\n",
    "    \n",
    "    # handles the 2k bug\n",
    "    if doc_year > 2018:\n",
    "        doc_year -= 100\n",
    "    \n",
    "    # fetches the corresponding distribution for the document. our files and topic distribution matrix have the same index\n",
    "    topic_distribution = doc_topics[i]\n",
    "    \n",
    "    # stores the result in an array\n",
    "    yearbook[doc_year].append(topic_distribution)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's compute the mean distribution of topics for each year (maybe absolute values would be better) and store the result in a dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1965</th>\n",
       "      <th>1966</th>\n",
       "      <th>1967</th>\n",
       "      <th>1968</th>\n",
       "      <th>1969</th>\n",
       "      <th>1970</th>\n",
       "      <th>1971</th>\n",
       "      <th>1972</th>\n",
       "      <th>1973</th>\n",
       "      <th>1974</th>\n",
       "      <th>...</th>\n",
       "      <th>1997</th>\n",
       "      <th>2001</th>\n",
       "      <th>2002</th>\n",
       "      <th>2003</th>\n",
       "      <th>2004</th>\n",
       "      <th>2005</th>\n",
       "      <th>2008</th>\n",
       "      <th>2009</th>\n",
       "      <th>2011</th>\n",
       "      <th>2012</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.011302</td>\n",
       "      <td>0.011517</td>\n",
       "      <td>0.015021</td>\n",
       "      <td>0.029503</td>\n",
       "      <td>0.078251</td>\n",
       "      <td>0.118395</td>\n",
       "      <td>0.098351</td>\n",
       "      <td>0.081024</td>\n",
       "      <td>0.131259</td>\n",
       "      <td>0.182561</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.031215</td>\n",
       "      <td>0.012703</td>\n",
       "      <td>0.027841</td>\n",
       "      <td>0.041550</td>\n",
       "      <td>0.046514</td>\n",
       "      <td>0.037877</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.049272</td>\n",
       "      <td>0.058735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.042124</td>\n",
       "      <td>0.071630</td>\n",
       "      <td>0.039267</td>\n",
       "      <td>0.016406</td>\n",
       "      <td>0.006810</td>\n",
       "      <td>0.003401</td>\n",
       "      <td>0.007302</td>\n",
       "      <td>0.013926</td>\n",
       "      <td>0.016893</td>\n",
       "      <td>0.005266</td>\n",
       "      <td>...</td>\n",
       "      <td>0.011816</td>\n",
       "      <td>0.000635</td>\n",
       "      <td>0.004679</td>\n",
       "      <td>0.004638</td>\n",
       "      <td>0.000488</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013548</td>\n",
       "      <td>0.004895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.013531</td>\n",
       "      <td>0.017928</td>\n",
       "      <td>0.020172</td>\n",
       "      <td>0.006005</td>\n",
       "      <td>0.005200</td>\n",
       "      <td>0.018357</td>\n",
       "      <td>0.002773</td>\n",
       "      <td>0.021425</td>\n",
       "      <td>0.025967</td>\n",
       "      <td>0.011100</td>\n",
       "      <td>...</td>\n",
       "      <td>0.016917</td>\n",
       "      <td>0.040725</td>\n",
       "      <td>0.025785</td>\n",
       "      <td>0.010749</td>\n",
       "      <td>0.017693</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.063794</td>\n",
       "      <td>0.007572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.011480</td>\n",
       "      <td>0.002343</td>\n",
       "      <td>0.009468</td>\n",
       "      <td>0.124238</td>\n",
       "      <td>0.135488</td>\n",
       "      <td>0.186333</td>\n",
       "      <td>0.185166</td>\n",
       "      <td>0.094740</td>\n",
       "      <td>0.270111</td>\n",
       "      <td>0.114178</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.013057</td>\n",
       "      <td>0.022298</td>\n",
       "      <td>0.007244</td>\n",
       "      <td>0.004865</td>\n",
       "      <td>0.010237</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000063</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.013867</td>\n",
       "      <td>0.008611</td>\n",
       "      <td>0.002500</td>\n",
       "      <td>0.008220</td>\n",
       "      <td>0.015973</td>\n",
       "      <td>0.010105</td>\n",
       "      <td>0.048761</td>\n",
       "      <td>0.038008</td>\n",
       "      <td>0.000837</td>\n",
       "      <td>0.001988</td>\n",
       "      <td>...</td>\n",
       "      <td>0.022923</td>\n",
       "      <td>0.016059</td>\n",
       "      <td>0.018011</td>\n",
       "      <td>0.004980</td>\n",
       "      <td>0.003728</td>\n",
       "      <td>0.012905</td>\n",
       "      <td>0.011893</td>\n",
       "      <td>0.016292</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.014324</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       1965      1966      1967      1968      1969      1970      1971  \\\n",
       "0  0.011302  0.011517  0.015021  0.029503  0.078251  0.118395  0.098351   \n",
       "1  0.042124  0.071630  0.039267  0.016406  0.006810  0.003401  0.007302   \n",
       "2  0.013531  0.017928  0.020172  0.006005  0.005200  0.018357  0.002773   \n",
       "3  0.011480  0.002343  0.009468  0.124238  0.135488  0.186333  0.185166   \n",
       "4  0.013867  0.008611  0.002500  0.008220  0.015973  0.010105  0.048761   \n",
       "\n",
       "       1972      1973      1974    ...         1997      2001      2002  \\\n",
       "0  0.081024  0.131259  0.182561    ...     0.000000  0.031215  0.012703   \n",
       "1  0.013926  0.016893  0.005266    ...     0.011816  0.000635  0.004679   \n",
       "2  0.021425  0.025967  0.011100    ...     0.016917  0.040725  0.025785   \n",
       "3  0.094740  0.270111  0.114178    ...     0.000000  0.013057  0.022298   \n",
       "4  0.038008  0.000837  0.001988    ...     0.022923  0.016059  0.018011   \n",
       "\n",
       "       2003      2004      2005      2008      2009      2011      2012  \n",
       "0  0.027841  0.041550  0.046514  0.037877  0.000000  0.049272  0.058735  \n",
       "1  0.004638  0.000488  0.000000  0.000000  0.000000  0.013548  0.004895  \n",
       "2  0.010749  0.017693  0.000000  0.000000  0.000000  0.063794  0.007572  \n",
       "3  0.007244  0.004865  0.010237  0.000000  0.000063  0.000000  0.009276  \n",
       "4  0.004980  0.003728  0.012905  0.011893  0.016292  0.000000  0.014324  \n",
       "\n",
       "[5 rows x 42 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "finals = {v: np.mean(yearbook[v], axis = 0) for v in yearbook}\n",
    "res = pd.DataFrame.from_dict(finals)\n",
    "res.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's transpose and plot the data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x16be4ce0e10>"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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P3XbbbXjHO96BV199Fe94xztw2223KarO2cw4fAcwGNPJstls0YOxMUqRzWaL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dZTHfgib05ASSQZocfXs7iMIqkQafUQdWpIqglGuwfoi8R4dsrPhypdGGWN+BydNl7qnOCD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Vfiu2q3GooQne+IVqyD5ahdh7LqfrM+m0dXLwbAAKYxN93F3b9Za0smz5ciY9/DBDv/qa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2l85ShRI0fSs+J5yra3cP1zk9Hp5fT89W8MbNzIs7eZaIo3YI99hCR5kOs6PibJ6sNgGMRvbyXx\nfhWSApTWRBTxCbSax1MlDico92FN6+TSyQUo4uLoUHlZXXofCoWKDQs2kKL/R6Tgia1VfHuqnTOP\nzETudCI67IgDA4QHBhDtjt+e+xGbzhJurkL0SQQDKggJQ+fXvxG/QsWgMpqg3khsihVrihWFxYLc\nYkFuNqGwWJAZDARbW/GWleE5cBCxrw8UCqLGDicyPhZnQT8OoZxIJIAgKDEZx6AzTeKDlhq2tx5i\nQfoCbtQuZu/bbyHIZMxbvgplj4DzgoOwS45cpsesUiELefCVvoXY34j59vs57PoQ8wQb9MXwaeIb\n7A/KCSpU6IUgo6WTTJJ2YyOeT7kJvRxet1gY9lUX0WIEZ6aJePlpet98gfdWy9lnUDCnXyKj28qk\nZA/j7ed4JOM+jkvzSLL7sQ4EMPoDqAIiavdJcFUyrksipq+ZjuFL6ClcDIKA0+ajaHoyY5emsGbL\nDVzyYTWFLRFi16wh9s47KK18kP2tv9IcGcep/rP4ZSIKEZLcccT6U1HKtMjlahRyDXK5ErkgRy77\nrQm/NbkMuUxOo1rgQDToJBmX+6OIQ4FM4URU7AT5eeRSHNGyy4lSFKKQKRAQsbfV0X3hNJ7+blTK\nKFLyx5AxcjLm+CRsvjBvH2uhstvNcLOOkpYIs+ZlMmJaKgqFAoVCjlKh4PS2Fs5sb2fconQaz1yg\no/oDBJkBrfkahk09gMr6NU92/536hCQOakKIN/4J6+OPYVmxAhgiX9lQvYFvjt+LW6ZhqT6aLHcj\nTmUKi2fn8/iiwn+7F/v7D3Hu/F8IBm0MS7uVjIy7kMl+K+zzO4dslOPvgKsTVHoqHVOo9Czk8pS/\ns8XxPC5fFIvXjOTI16/QUXuemqW3cvsTf0bMFHDd7adYNh/T/s/oDWZz3PBXljw853+3YZxijJVu\nm76MoEZNUKsmGK0ioItCKYUwuxwY3AMYBvtw6E2UFk+m3xxHzKCdkvoGSspPkebowanUsD17Cs3T\nFpGTl8pcFyRVDCA3qnBOVLO9fD92u53s7Gx8W79GjIrCvGgZdXV1iKEwo+XZFPvTCEo+9jd+R0n1\nSdSRADtLBDS33MCt0x9E5uyEH++Chr0MmJR066+lq7Ub97HzZLeFkElwwRrNyYwRzGltI7Gzg41r\nH2dDZiGfal9C+Wsblm9tdFlAu0jOuLtP8s62L2kvczHMUYRMkmNOjCZvghVLlpxPv/gIpaAhJPmI\nSxsFpQY2XuKjN9rAu7vv5nX7LWiLixmbbmF8uoXRaWYMGgXdfz3JnsSTvCb7mFhNLA9N/hvr2tXU\nev2sjg1Q8NAqhjdLpN9cgN55ACKhoerZsasgfxERmUTpycsIh11MnLCdrrCaeScvsOqnjexO/Bmf\nSUtW7+NsH5/KhvNhilq9nLbtwFhoJ6v/KgI+J+XNXyKL+LH22rAMDCAAEuA0aZEXu5GnhhjhsSNX\nRxiQXYW7dQJCy3q8bUEEhYQ2M4ghz482OsAZz9WUOuagC35COH6QSenN5NmdKMMSL5vMfGbSs2PZ\nThJ1/2qM/mcJ+0MceWYLx7T1hBG56KKLSBg+kuVnG+kKBPloeAazT6yD0vcJTX0B2+42BrduJaxU\n0JKawLh5FzPw4UcQraWvwMi09BOc6k/mqLOIqtVr+VFUcVtqHE9mJf0e5Shvc/DViVZ2n+uh3xME\nFUjTEtEo5KwMH2Hss28T3y/y/e1FzMy/AcURD35dCOU8Kw2bZeijohgbCrJfWcqncd9iVwQo6p7A\n1Oar0BgFltwzCUuiDs/x47TecCPap6/Gnt+GWhVHbOxsLJYpyOVaxIjI6h2r6WnpQSZKdEZ3EhYk\nRvgDzOqFqfvCyALJJD72CLr5F/HqundwS33oDTpcLhdKpZLCwkKGjxzOpt5NfFP7DTOc8KKjn7fm\nf8l7AQtXGw18/XMto2OieexyI0e7D3Go/RBVfVVISMRp4pgqtDvvAAAgAElEQVSWMo2xhmK6fzhA\nXUc1ysJkDhlqESMiKxpKUNnCWMR4krU5WDXpyMUQ7j1P0pQ8i6bUeYQMR1mo/Y5hdBJFAMf0dZhm\n3/2va117gs7778JT78KRLeeuy0DjHcFrl73FR/WP0uhoZLsvmv2V2VQ7L8IeW8oM3XYm+ytQECGE\ngnZNDlVxE9F2nKU4XM+Y8LsIMhlKQCWFeVe2nmmyEwyGbqBCXMKb+DkbESkOKhgdULCr6HUCshCx\ndfeiK9xKueowK3wr+ThlNtNjRV4piEYdFYNSYUYuVzPY2813L68mbW4det0wxsovR171I0LbEIW5\nw6Cg0xxNdaeVjrqRyJUXo9HHYs3UoDmxHX1XJT3rVnPP9ggmuYJFfjUJAyLJuQ0sCqxDLlcgLP8C\nhk36fZ4kScL+TS2D5b18uCiB70I2FFIAk8aKRgC1ow+Nu4voSB+aiJ+QKNIbKEThi0GS+lAPnkcR\n9uM2xHN6xHiiRImLqlyMqrFRUvYmNouP2thkRo5MIjLxV/rPmeg6lIbccCOd8iA/6CTm2vbRXXwZ\n61fNIME4VLg6uHUr3etexzbjSc74Iti1Mo4XaXi6IJWd4kdsbviBlQezUYZhVGUdGeue58PcYj5o\n60EjdjEp8isq5x56Zak0u7uJSBGiAhKfvTpEsWx+8F6+MO/kgcrdnBk2geqGLEzFh9BYQjT8kkhW\n0dXMZguSe4AL77gJyrWULXiVuAwjC65Kov2++/CdOs25W2fzhOUQ5ux3aPcr2VV5DxdS1lBR18ra\ntWuhZQ+df19Fr2hA7lJgCOeC3U+vT0dlxrVIMjmFNRuIHagGQJSB3GQgKlqOQuEBKYIoRtFiV2EM\nelEH/wtvriAgV4NcFURUyPAak4kbMwVlTAwDYZGqtlb6AgFClgT2i6lUSrGMzU3gzlnZTM6K+QP+\na8Tnw334MK5du3DvP0DE6USIikIxPptgiYKBzEYCyj4AtNpsYixTsVimYjZPQC4fKqiKRCJ8eGg9\nB8pOM8VZwmj7MNQyPUaFGtVvXsqIJOGNhFHGyUheNgqlVUXHAw/g2b+fwYUiXRM05D4XYPeE2fw0\n/xJGh72sW34FKpmM70uP0N61nbi4Vl4OXEWXkMRKRRk3HE5EP2jAoQ2SJ7sTMdDNakM6p1MyCRhv\nwUqYV2vX82zyvTREmRjU/QPTVx0WyR30ct87z5Le0crZ2ctRjVuGXhwCbBBkAmMWDiMmSYfD7+DG\nn67n4m9bmFoRwjdnPKcWxJOh/Z6KLg0HejT8OdTC+yYzZzSqoQMQ4P8+IPf/qwiSQEHPZCa3XE5S\nagw6k41zB98jtWgEl639M6UnF9AQTOch1vKnODO3v/gYoc5OsndsR1CpuHn7anpqK3m78xXWaF2U\neyNcZ7tAgrKEnPFWJlyS8Qea73DYTX39i3R0foVWm01R4UsYDL8VzDs7h4zhU59A0AUKDYR9oLFw\nVPkUZxtSMKn6cfp1LE59n6RLrsGdPIsH3v2Aiw8cJm2gg8CzsRRHz0Kz92XaAyN4S1jExbdMZXrG\ntP/dhnGhRit9mZmNPCKikP79zfa/Eo9KSVOckXaLnohMhj46hvExC4mVJ9On6OGE/xj9fhfRJgtj\nJkwkKTGDrX97lExrGpetf5tgMEhdXR01NTV0n2+j2FNEJloqgi14uz6hoLwTrxoqF+Wz/JENaNU6\nKp6bh62slZgGJVEh6DPI6MxOpSi2g4qOXEbUnGdQo+PDG25n0VWXsuZcK7fzKRe320kKFGJ742MG\nowU23prDcVkTy/OWc0/B/bSctVN5vJPyVgdd8ggmYz0WmY2qcALRrnSseg2fzTGyKHSIaxSvo9qk\nJPHBT8nOnfD7fDj8Dp764RH2BA8xwTqea0qe5u46ByEpwlOJIRpevpFl+0OYxg6SOFwJo1bAmBsg\n7h8h/4bG12hufpPikR8SGzvE+76738l1Zxt49se/817hSaxiIhXZz7K0V84D2UZ2Pn8HSf5BYvpF\noj1+BCmChIDdbKLfGsuo+AskX76CljH3sLPsM3LUr7OvajZWu4/JYhrxwfn4s58h3heL+3Anzoo+\nQCCUpiY4MpqO9JGoUstQ6foIeeX4z2mJ6w1wT56aGFMK385//h/K9O/2icdDWVkZx4+cwON3Y47o\nKUqfSvSUTO7s78Utimwckcl4kw7RPkD/fYsYKB0AuRLzypV4Jo7nhzdfIn/KDBynTpJTeR69L0R0\nJsieeI/d326ir72V8uW3s9uczM0psSwUVWzaVkewo5tYIYwv2kG/rIlj42fhijKR0PoUT37eTEYP\n/HWZjIrMf825WnnqWZrNlVQX7iLPOYx8Rzq9TiMpfSV0Gs6zPW8DGVFKFmRPY7jQhf7WE/iLI/hv\nSSIUsiOKbmQyFVL0GLbYBjloa0JEwBCRWOxyM96pw3xchbJF5LusGZRPXcyHt02nYvdZDpb/wsjc\nsSy55hJaW1s5e/YsFdUVHDYepiO6g1m6WSS5Z7K68R7kWgMrJ33EKXHIqElTq1gQZ2R+rIEJRh3O\nwACHOw5zsP0gRzuP4g65UcgU5MrSsPV3MqAPcE3zaHK1GejMMegsQ00VpcfV4kU4XIbywCaOTHmR\nFLWCyfFfEhMeKmoJLt2LkFiILEqOLEqB4GzB99nDtH9WhuiXYb1mCqY/v8Et393H8fBxEv3LsGm2\nsCJpFpce2s+O3ucJqpykz3iNiHkeBYV30FS3H9/5nRT3niQv2Pr7ejTHTWR7/Ey2yEfw1vk3yQoe\nozd8I7vDOVxQ9iHKBPQRLZnKJIpmjuN7xy98bf+Qq888wraCdzEEYri0Zs0/rXAEmdKPTOlDrgwg\nV4UJ+9qIhPeSeUk7UjgWMaDFoGogtlMivt2PGT8RSaBXk0B3vBx7so+IUkDZKhD7VwXemSJMlvD6\nzbQrUrG0m5kX3oIjYuWdxOsJp3nJjHJRqAthijah1CSgUMXDtgSkdoHOovWkGdIx9wSQWstAEhDl\nVoSsmXgtEzlyqB+FV4ktthEpzsXF1nl4bP1EOkJ0KtU8OwoqdHqS+gMsOj3AbbKnOCBzUK0fzcJs\nHX7TXtoOWQn3rsEri+dVbYDbOzYQisDJ1Hk8fvsyxqZbkCSJn9Z+Sps7jZY4BcI4Ldn7DuDqraXD\n1MjO8d1c2lTAFeZRVO/eSP9D11PtaaCirwpf2DM0vTINWbpCxuuLyFLlkS5ko7/regS/F++yuyjQ\nvEUw7OP9lsnIPYPE5V5K/LgvkUd10Lg9iXwxmRnmbZw5MIagW8mpMQ8x56Jo5K/9GdHpJOaZJ/lT\n+H36NHNojZrDawkC13w9nf6iVayvNnLttdeSG+2GD2bhXvYaFa6N+P1d5Oc9Q1LSldT9tJdv9oYw\n+hQMaHcTDm5jRZ8f/WCAsF9BWNSBTE5ILrJHGE5BVCvDo5pQaOXI4xORJ2agSByG3FOPrG0vAZQc\n7M3AevnjFF90CZ2dnezatYvm5mYEtY4jvkRqg0bmFiRwx6wsRqf9o0ZFdDhw7d+Pa/duPIePIPn9\nCIZoGJeId4QHe3oLqEChMGGxTCHGMg2LZQpRUUlIkoSnoY3ugxdwN7gQPQpUggadSo3yN4NblCTc\nkRDuiJtudwvKRBmz7l2JxmQgIkmUDnrY0uugqf4NHvxmK7rjcqrnziM5MQnT558SnDKFLclJrLzx\nRjL+ibVTkiR6Bmv4y4UmtntTKIxU8XpVPZauOSiFMnb27+D7vAUcK5mKTOwnwfUNIddxlCGJtzYo\nkenjaLv/Prrrt+GQNEz8+iTxff08d+MaDowZgh81yETi5R6M2EkKVxD01dPj7aHX20tIDLLkqMQ1\nByPUpELTKpGiOJG3GzJ5vfc8QaWOXxLnIBKgyxihXRikxdWKT/T9Pga5ICdJl0SiLp1zilk0izFM\n1Qe5Py0Ghb+G5pZ38QdtmM0zSUr6ExI6OmprqD11lO6mWpBBXGYeyYUl6K3JhCMioigSFkVEMUxY\nFAlHRMJiGDEiYvcF2NVqo9PnJ1YQmJFmQqMQECMiTbYWynWHyDRk8crMl8k2Z1O5dyc73/s7I+Zc\nxPBFSZw7/2fudr+NL9pKmdJN1y03k7DuGYxXXMHUDWOZ0G5lle9hLpW5yfDU068axuP5WfSX9yOG\nI+ROSGDswnQkVQU15x7C7+8gLW01mRn3I5eroadmKF2i8huIiCDIQBIhZTyMvxkKL6PysI2Dm2pR\nKGVcsiRMSu3T0F1BY9okvjydz9I9O2iel8W8K6aiOPACTf5xtBW/zIPhW1iSu4RHJj7yv9swLiko\nkDYXDSdQVYV89Dy6ChZzwe6nQR7ijFWG3apAFQmjbh3E1OIiVQY5FhWFmUYKZo3C53bicdgRW7wY\nag2IYYEqfwUNg3XIJCUySQVCFIKgAVkUAkoEuYnCicWMvyIbvWXoMN9S1sr931Ryn1bBYq8akQin\nfYcx1u0krbGfAYsKhShgGAzgVUF9tpy0YXZGF5Uglayl84nnCTS0Yk/Tc8eI+3HqTYglFqJjNOiD\ndTzUdY4l4klsVZU071IRlsGONfPJL3qA8lYH5W0O6npdRH5bhgRBJEdyMWPeeCK/dvP5LD1Ok4Ij\n43MoP3oFgcB5QhvVpL3wBYXJJexr3cfTx55mMDDItT0LuVh+KQ+nK+mLF3it93M+qdjOXV+DOi+K\nrCfXIgxfMoS1+0/ictVw8tQSrNZFFBW+8ofPXmzs4s36dp7b9zkv5+/DIEwhxjOVezd9SGJPD6IA\nbmM0wkiIcc5BnTIXX1aEn71VBDyDXB/ZRHJqBtKSdznZsJZBdzNv1zzHjG4l00MyrknYSJSpjOlB\nP8u6/aQ7J+PZVY4QEPEXRegbb8WmnIg+eQc9x/IoE3o5NKqfpdZkpqnqiImZQUb6XRiNJb/3uaOj\ng9LSUqqqqhBFEWXASEFUBqP9Zi7o5KwZM3RzfdKnZU5hDKqjP9P/7ruITifGXBlxxT6U9+9DMqby\n6YN30t/eSkrBcBYk1RPcdZy+GhNyk4n4xx6lwt5D6U+72D3rWspzkhld5+fiMi9BuZfBaBt6byw7\nxsRTma7mmv19LN35KmZHM2cXXIUtKRGFz40pS0/8pHR0UXr8gwFq3oggG9VPW9EZqtprKCyfT+pg\nPpUJ+7Fl7GSiz85xGdSqVWiAqW1aLjoQQnfzl6jNMs6rfmK3fQdlg11IwDi/n2VON6O9GrpLDezO\nn4NXp2Px3Lk4rfnc8tkpQuEwl6uqkQsSbYnTiDFoidOpMUaL7Bn4Ky3eCsaIc7C2xqOWQiSpBlkd\n3ECzLJVdwhjSx5ZwUm3l55CZNlUMeqWCWRYD82MMzIoxoJdLlPeWc7D9IAfbD9I02MRzU59jcdZi\nAPx+PxcuXKC6upr6+noikQgmk4mpp07T7symK2kylydXkCg+Q0SKpjPwFTB0qZAkiVDDDgLVW5Bp\nTegW3osqIx9ZlAKH4GaVay0DUf0A3Nk2EcfgaPSuPAwle2hKT+SUdjangwEiPhFLrRNPr48CZRd3\nK7exMLIPf1hJiIUohXai5GU0yxbzYs4U9lmKGDYY4fLOCMsKM4iblYaglNPl7mL+5vkUm0s4az9D\nctQalMES7ooSkZ3vIuDzEzHKEbVKQkGRkF8iFABn5wnUxtNkLOgkEtLSfy6O7tNKouPUTJynINnd\ni7G1AaXXRUSuxJ82AjE2k8EvK3GVOclcYENlDP/unApENGwdeApbOJcR2m1M0n+OUgj+rieiIBCW\naRnwvYgY+YfR8T8RSQCZUoZMq8R0eQa2159gm9PPOzfeQZ9cQUmjl7+2PkNRkgdh8d852/MWfQMH\nqNuyhEh4Ie/r/bx/XTYVn76Bs6OFakMhM1eshgonrhoXVakKRiuDTOp2srNjA7rYZLx+K59P3kZE\nHiEsDKXkyCQ5sf5kUlCSl1xD3+Cl/Kpfjt2gJK89yLxyL2ZPhAmlzxDt7SE4KY/iYfvY2ncF9TYb\nHvNIlNZCRqakEZX6FBF5G7ZdSVyrLacnOJP+72txJo7E0HcOldVKypvr2RQ+zouVW3AmPMnieDPv\nFg5D+G4VUu0O1stWk5o/miXThsObY+GKDwkVzKOq6m4G7EdIMV9CzmAyW3+uYKfpNoa3hYjTneby\nCS2oCmZB1uzf6eo/P97C41uq2HtdLJmhOug9Bz3VQ8yd/kEkCSocCZweSOGiYjmaYQXs7U+gqjsA\nciUng0mcD8dyycgUbp+ZRUHiEElWqKcH1+7duHbvxlt6EkQRIVZHeIyOwYJe/Fl+BIUCo3HM715h\nna4QT30H3QfqcDe7iHgUqGVadEolin8ygj1SGF+URDBJS1cOrO99Gnu4lzn5axHsidTWVCMZjMSO\nKKE8BF2BEKPDe7hb9jZ2Ucvk8qvxfrwR3dw5qHNz6X/7HTqyMulYtow//Sc4tf+QTZ029h35gjfO\nPYdTmsch7e08W6SmS6Nicflu5IM/cCTDyZj4Maw4CCk/nOD4IxdTl6Em1NLC5evPoPVKvLRURn1S\nHCUNI+mKi6cyx0hInUxYlYqAQKZYxmjpHLKOfjz1bWjckNHn56JyF0GtEcd9Pfj9s5hQeRqjppHa\n7xP43VUsl6PKzcE/KhdbXhy9SVo6ND7OuwfYLU7BI0sg2vEVGb5fWGoOkhsVwSZGcUFegk45AnO9\nD9+pBvx9dqJNZkbMWcDIuReht/wf8s7/s95KEi99fpYPqjtQKAQemRXHipww27/xcCbSzM70z/GE\nPPx53J+5MvdKDm/6jNIt3zL12pUISRvZMZjAW/I7eDsnlZL7bkd0OPBdPIVrLd9xR+8yTrmnsCfg\nJ8d/mimzl/HUpUV4nUHO7Gyh+nAjloLvMOfsRa1KY/jwlzAZxwzVPhx+HRr2/GYMR4agT0cuh3Gr\nIbH49/73NDv55Z0K5t5QSGqBBSIR+speZN0xP7e99S3dOWbKtBYuS6kmoizEN2c9xfMyeeyLGyj5\nuoJlP535320Y52eNkN5/7juCzc14z5QT8XpxZw2nzJqIXSEQH5TIkyvxiRI2hw/B0U+Mpw9dKIBX\na0FliEGp0BLwRwj9N0OQkBCFABEhhCqiR2KoejY2VoN1diK37j3PiGQjX9w8gUifh7bPy9D2y2mR\n2Tjq+pbc6rP4o2TYxoVJK1jFnAV3oz3/Gex4lEgwhK0umeibXkNv6aBqx8fc4r6ZLmLwj45BHiOn\nyN3AjrJb+ZtuLjt6R/L03u9Qh8I8M2cWbabLGZVqYlSqieJUE6NSTJi0SiKiRPt5O69/V8NXM/S8\nmJvCDcmxhEKDHDtwEWGvjcZtGkqXTeZY1zFiomKI11pJao1hZfdlxIe0oCjlFdNWrvrKhskUR+7W\nX5Hr/oh9KUkSdvtRLtQ+RTjsZOKEHf9g8flNQoEwv354htFtfra6XyO2/jwjmyWCegPKhfNwFeUz\ndulybG+8hv2DDUSWL8IYWMxgTD+75I34vG6uE7aSKutlcP79vD94nO+Vd9IUNpDkEenp82FwdDPR\nvJGp8dWkqyNIHgXmY7Godw0gd8GgfhiNuSUIC4t4S/oCu0zk5LLv6O36kta2DwmF7BiN0wkGLqOq\nqpfOzk4UciVq7//H3ntHWVaUe/+f2unk1Dl3T0/PTPfknBhyRkUQBMWsCIgZQb1yk3hFMN2rol4V\nA4rARbggSJY8zAwzwwyTp2c6T+dz+pzuk89O9f5xhgmC4ff+XL/fXe96n7Vq1a596uxQu/aubz31\nfZ6nBl+xgdMuXsKi0xt5ZTTFh7qHCJdcfrA9i7bvVTzdv8dbnMKcs4yqz91Aw+IQ4s5zIdoMH32K\ndCZPMZulpnQI7r0STv0C+fp3M3zTl3F6DxFvWsXBlsswjRCPLdPYOTdM5dQO1k3sp6t3Lq9WJ3lp\n7QWcsTfBZ+7/EdH4QboXfYTxyhWcuE6i6BJLy1ISM/jzTWTCh1B0iT81G+Eq2LOfoWfWY/RZLsOm\nyvJCkSvSGV4K+HnS78dWBPUz1cz4SuSNNBFL59LsDO/OThNwa5h61cbp1SjNcZm+PMq+7HnE4yqn\nnrqOmnlruOfux/AUD5OoXMmkXkkiWyKeT+DU3IniHaM4ejl2+rixlE9xeLt4hc9pv6OOJKo4/hLa\nQmPSW0ePr4FebwND3gb0ilbaG7tY1Tqf9lgVBbuA6qocOnSIffv2lelNjkM4HGbBggUsWLCAxsZG\nnOlp9lz6QTZ1fp4lc3rYkLmJUv3pZFf9AGPfk7j7Xya5dZDiSALPvJWELv4M4EUWHdyijVu0edLe\nyg+b7yLo+Dlj+CxqE2sI4uXMoHbSUnIRSR7wBHWCIY2J5ASL+Rg5uQ6PnMar7mTSnUWFOoImTRwU\ndoe6eK5iJTurV9M+5xQub6hlUdDH+x9/P7sTu9G1GOP13+W+pfM4rSKEtFxmnhkk+/IwatRD7PK5\neGeX3znLLHHPzV+gUBhHmhqlXJH1V7yfle+49JibQ1wXDj4Kr3wPRneCdJESZgYDlLROas6pRxz8\nAyy5CjZ8HqtQZMvT0+zebhOI2MSWDpIsDpBPxAllM0SzWWoLLiExh2mlnplQA8rsWqgKkx9TyOzO\nolR6qbm0lTFjjP94/VtI+xDndFzGR5d+AcU0kTfeAJs24Xzpy2w5tZPb9+8hG1iB15J8uu8JPhv/\nDkPLPkRfxS7yI4Kh52/mVXWMtUvm8q4GP69tf5yeQ6+Tq3o3ETPMlg6HeaOPsmbYoqv9Knxn1VF5\n3hwyySK3P3gH3cU9rNq+kzrPCmIrPoU/0gvV/4TqLiGq3I7wenhIKfKrUgZHSjpnXK7+zr+wON5D\n6wVxequX8fRuD6suvozE6gi3bL6FubG5fO+0f6N/3yfJZQdYvrlENFzHoZ9kAAhs2EDjt7/FtMfh\noocvJ1H7VWK+Sp5dOY+IrkGiB364mt7Ks7k/s5ybrv0A2vcXwLm3QGwW7uEn6Mk/w5FaSTBl8e10\nlMjgO0jUvp1zdxeoqA9w0ScWEak+vtz88V9v58BYmpe/eGa5n07sg8duhKFNpI1mft9dhVbZwjmr\nK3htpMjWTDUKLut5jfW8hq360Grn421cSMmpJXMwTWbbAYp7yvQN2Rgku9glscgh1RJA+ueghVai\n+BdjJ2LI3UkCoyWiOYUKqRFRlGMGg5aUTCow4Bfsi2lsqtU5UKHi/KkRr5PFn34ERRYp+dfheDrL\nfRaBF8kG5Qhvc/4N3CxnrP0DdeEOkr+5m4lbb8W3fDn+NWuY+tGPONLcROdPf0rLrJMncMMH9jJ5\n740sFZvZEl7Ce5d8i5LqoTln85XuFDWzvoVZGuR3kwYDluT2XzhsXCC482IfS1JhPvHrBCqCjVeE\nUIwjCH8Xw/s0KsdB+AzWX/l+2k45j5v39fF4URKdmeK8Vx7jwrYm9PYuXn16gtZxi8V7/hNVzZP8\nuMXcPVFq6w9TeufDKA3zKe7ZQ2HP3nK+dy9uOg1A95wu/vHaGyh4vHzTmqCt6imms0/gCg8jnlXs\nHdYQO8epGnDRXMFErMiB1gzxJkljpJnWcCstoZZyHmigVQtS6TiIQhJyibJtVH7q6HaibISbS+Dm\nprhz+Cbu0+vp0xXWKvs4JxegApXTLpvh5kIPm8a3cG7rufzLmn/m5Z/8hO7NL3Pupy9hzPwm1zq/\nolUL8wcZZ/j663l1ruA7l6nc0n8jN5aqaCz1IWq7eOLzZxxz9zc9vZ19+26iWBpiuuds4rsvZn1n\nL/Pde9GSB+AN4mWsHdZcW7aF8L05WqCTMbETBfTGIGgufX3f5b59Bzjz6wfxBA0614/w0FAzKSvI\nWVd+hs7TV5G444ck772Hgi5Zufvg/2xg3FY7T9581c8QogzQCrZNSSgIKfG5Lh5UsG1wzXJEGemA\nELhCYJh5/P4ohuFHFuJMuCmKRiU6ZavHpHecRLgHx+ij3gcLlm6gYf5int78AmN7irRPLsPrBJBI\nSgIWdsVYf8U8/JU+hvYlGHu6l4YpCykcjlRtR6t7jXzNLtK5a1hVswr7O/+OM7ib5gtVPNoYdJwD\n7/g+GH4mnvoG1+zLcjBQQnpcvpc9zLpiPyvX3o8s6VyUTHHFT75MaKbIwJev4JL3f/Ut2+eJO/fw\nlSoTvdbHxjWdGIpC1syyY/hJXt/7j9yfUklLgTz6oRJqM03xIFlfDxdlz+by5PkYtoo1+CL1N78H\n/+JyhDPHcUnHCxw5/Dr93a+QnnSwss0Ew41UN9YRqfUTrfETrfXjFS6Tv9qN7DlI/9Bj1A8dIOuF\nB9erjJ//JX71zg8AkH3xRY5cex3Rd19O9CvXMfjCb/BtXE5WzfNU6ABF02F+Q5Kfx5axLbKIWjnG\n2xNe9vtUtvu9WIqBLk1mub3UloY5RXuChfog48UYLQdXE/rdLrypJBNRlUfWSPpnncW7PfOpnTOH\ncMRHf/9GDh+exrI8BAIlKvUmct1zaOqo4swPdGJFdV5KZvhC9xGavQa/jo9if+e72GN9KNFmciuv\n5DXZjulIQhVeVsztYf7gZ2HehYgr7obiNPKHazGVKBtjP6V/bxozW6L5yNPMGniCou7hvtOreXLl\nCMJ4L/G6i+jqH6W9fzuPnfkOVk4V+Ndf/phA33ZmTvs4dVWrka7LwYCHcTvNTD6Jawo0O4DqeAGB\nt36I0mQtilai8ZQf4Y2NEciso7JnBYdyOr9tfoElrXNZ1P84q8cP8KgvyH3BEEFD5ROpac7Kpjls\ntmHursDoGScTDHF4/hk486JUtO/HqNhDb98iJiY6qKnOEI8HqQxV8MkbPoUQKkcyR7j2mWuZzMf5\nyopv0BZYQTxTIp4plUFzpsRQfIaBeIZ4zqRGTtEiJmkRE8xRxpglxmkWk9SKJEEKJ/XtpBYhaVQx\ng5eM4ievByn6YpR8UbKeCDOqn6TqJ6X4iSs+WnYdZvXrMSaqOnhbyxc5FGxh3cwufPEC3VsaUTMO\nv7nsfTx9wcV4VQWvouBRFLyKwKso+B2T2DN3o9gmOXtZN+MAACAASURBVM9qFvRWMjw/y+I5HmbJ\ndl7aOUouY7KoKsi6phheV+IWHZy8SSj+WQJiNxLBwIIb8PIunB2TeP29RDr6UDOvIsZ2IqRLVvWx\nKbKU7rp19MXgj6MPkAu/k5tWfOaYsd0bUhpMk7q/G3uqSHB9A+EL2lAMlanhI/z25huoaGjkgus/\nT1VzOQw3VhG6Hyu7L+x9HpDlIAINyyE9gtz3B4QsIRHkY5eQsxZhT6dwkmVjrclCiN2VF2DqIVoH\nn6Rt8EmUP0Nhs1UPB+a9n3jNcmomttM28AA5r0E6ECQTCJLXJsh50sSrz2dBfy9LDh/gu1d9jMc2\nnH3sGIblEs25TEY1WtJJfnnoRgwtx6GFGoO/vx2z0McQe6nPjeHq1VDxHryWxusdFuePjbHhjA3o\nh16msCuPVjefunfG0Yo9kOwjd3iSoV8dpukjK1CXV7FNfRpDBFgRuhpNVOA6XgoFjcd6i/zEG+NA\nfZR//cUPOX3bRqovLXHvwFwOBrpovPRqPnbqbLrTW7nxxRuJeWLcccatjO29gfq+w8wZytH7fAd6\n5yqaf/RDhKry1U238MtkNVZgHQ8vn8OqE6NgPvJp3Nfv5XvuB7no8g8y74HTj//miUDHWfQ0hukr\nPM60I2ip/Rf+ZYeHktrAe3eWfe+ef/VCmudXYDkuy255houXNnDrha3w4u2w5cdIT5htxSW8fMCm\n/awLyM1byuY9e8lLyZCoIKkGWdEgaAtbBPsOUbNjH817D1M1mQKgr6WRLUuX8tKS1Ryun42LQlXW\nZfW4xZIphzlZlyZLEhWgHB1bSlIyrsKQXzBQqTPYFiBd7yOgqWhC4CAxXUnRkWQdhxnbIWnZJC2H\nk9CFtAmSY2GwCqW3mwFDZbSiFUU6NE10s7Z/gLWySG19PVXjUxi/vQ+ttYXgOecw/dOfMT1vHmt/\ndz/CMJgc6GPjvb+idex3rKgY5fetH+Sf51zD5NFzXojOV55P4jEdRmc/Sr7iYYJ3avgmFNIfq6M6\n2YL74C6UYIjm//xPfF3z4JFPwa57cdd9hqd7K9j34rMAqJqGY9uMdSzkj2dcyrjmYc1ojlO2msTS\nKWb3P4rC69SZOm46jffqpbRPPwGX/bxsQHtiE7gu1tAQ/72/hy95YsRyWf7pxVupOLUHNwj+bV7s\n/gX0uxrxTBpN1+hcPJem+RWkPUkGc6MMFhIMWTMMuQWGcTjBNTQB16XFsmmxLFpsm1bLplXx0eqJ\nEfVVIfyVEKhiymrhv/64hPHGEg8VoWjBGeS4xfMlaqMB7lp4Nt8fe4lqfzW3rvs6h3/yOyb6DrP+\nk0F+mp/NH8Q72bqmC/faq/lNZ4IHmsc45+CtPCglbeYebvvUNaxtr8RxSvT1f5ehoZ/j9TYyv+Or\nBPbvwX35+3idSabtekatLurnVhM78yqYdfoxJwtSSuxEAXMgTWkgjTkwgz1V5tpbgSnGV/yUI544\nxR/PZmn3fpo/PJ9Y5gm2ZC7k1ZEMVTLLiu4ppCnR3/U2Ptj4OJuv3/c/GxgvaZ4vn/6He3i8UuHb\nlS4pBa4qKVz94qtou15D2kWkmQfXJFvjpbvL4cWuaXwzjVw3fBWaq7Ejn2LSLC87hdP91MR3Ekvt\nJUCR0IqlVH70I/hXrkSox31GZs0sDx76Pfc+80dWjK6jLtOOggJI/IrA0HMYczZR0/w69QffhSfT\nTM8ZnwVsgk8rhB5TcbwKfVc2ET9tMQvGJli59wlsIfhF0zx+ruSwpI3marSZCg+O9fDTaIxvN19K\nPvw2XK2KplQ3X//BN2iYKLHl6tW8/ZrbqAvUHdNeFXMWN35/Kw+sDfCJmiz+/Ga2T2znwNQB5NFP\nTZ3m8uGMycbh84llfbztlZepyMzgCsFAnYeSoTAr8HaKrWeQUxSKlT7SpstMPI/rHH8O/ohNZUMV\ntiWZnshTyBz3GoCU+KwZ/JkRPM40O2fVI+fW8KL7U5L+FI+d9wsaZIj+S9+F1tBA2733oByNgJfs\n20763hH2iCC3dlr0x+qocot8of/HtLRsRnUCOEYaE4Ox8Ht4rrCMlzPVlPw+hFsgUHgdT+4FRPEw\nimuyphsu36TRMnk8YIatqhR8PvJ+P9lQkEKth1yzzXhVFT2RTvZVd3LEU48tym685vXs49MP/ZIF\nfSOkK/wMXLSalvB5NI9WYRkOR+osBrIKmQHBYu+jnBr+BXu1K/GZY7SJV3hg6ltM2G0MaC77DIcp\nLctc437eu3EPHeOwf24l/eeuYROz2LRwA0iX2VaRe558gPwTTxD74Gewc4tQox5SZ3jYtGsrw8NH\niEZgyaJqKqIuM4lRRg96mDp4Kt7oKLPPfo2xRJBDhxR03ceC+rl0HAox5U3yndl389Xzvs5iDIrf\nvQi/tzz4PW/4mDgYZNE2HdPQOLx8OQs//SW8oprESJbkSJap0TQldzfFcA+TuRCKYrFy5SMEgioz\nxgK+3d+Dg8IPz/4RS2uO01TeSmzHZWAqT/d4hu7xNAeP5kPJAhIIk2W2Gme+N06TNkGVmqBaJIm4\nOcJujpCTJ+jm8LtvbWAkJezYsYEtjV/gdOMHLIg9x/7RJuRmKAQCPP/BaxnvWENJUyipAlOBkgJF\nAaaAomvjnRyiNjPE6qHZiKkCC658nCfHPsk9W4/QEPHytUsWcnZX7ZvP/dK34fmvU1p6O8ndi3EL\nFsH1jYTPaUHxHvXOUEhB/8sUe57D7HmOcHqQlKLw9aparqSBlQ3zEJEWiJ6Qwo24jiD95ADZTaNo\nlV5iV8zD0xqmmMti+HxlLfHYrjIY3n0/FKch0ly2EVj6Xoi1Hb/OQprJ6y4kf3icYtIAXUeLRlGi\nMRRfGKEFMGWIfZ4ljHobCDt5lqkpKtsq8XQ0oM6tQsRgaiDBy39IkpmRzGtN0+QfwU3P4E5PI4/m\nifHDBHJFQkUBmk78hps4dNoyfrjzB4SMADes+BwxTwRpOjz8dD9/qIGCR/DhxDNcN3EHzyc/TzHV\nQH/yCSZjq1jodOGogtcWJlijvMCC7DBz86PUlUaY2t6A7Lodj7uN6tBtSG8D8V0aydctWt+TY9cK\nBUsXrNo5ja/41kD/1fAiXu5fzBkvb+Ejt/6Q80ct6i2DXwxOYakKl61o5KzFJv/22hdwpMP3Tvsa\npW03sH5nH73OXNwXfHS89CKHUod4x3PfI115DV+cVccNbXUnn2hmGPn9Zeymi76Fn+dS3zZQdZh7\nPjStZsbO8fGnP46dP8Sn6lQULILqZ3nv9DzmzZS4qjdIaiyHc0YNm6sFm5/u52NdB7l+9MfESlM8\nHjuTfXs0ZN7imdMuZt+85SedXnFdFvUcZMPr29iwazt1yQSOEHTPaef1JfM4sLiNgBZj4ZCHWQkP\ntQUvlcIgpCjHxh7Tdcm4BWxPEU+zF+/pC8k0RDlSshkqlBgqmhwpmgwWTIaLJuYJ+EEAdR6dFq9B\ns9egxWfQ4jVo8Xpo9uq80P8A33vtdhZEW7h5+cfo776Zg3Y1r4jr2ae0M6Xo+KwSnX376Nq/jUU9\n3awYGMfWNEZntTG7+zD52e1MnL2Bw1tf4m3NvUR8Jf5pxTd5ODyPOXaJW4504zl4gEMDR6jJFulq\neQd6tJ3Sgd9jdj9G7u0Gpdo8sbtU7CpIX2yjjwp84zFCymxqWgcJqPso1V3IS4Vl7N7yMk1dC+no\nXEj1ZIadOwr8dvlqNs4P4LNtbpwepbOtxOcP3cqpoaVcd3c3yr5pqhbnqfro+xAX3FrmyxZSkEsg\nc1P8e9zim7koy4nzeecbKMoggZyH0tYQ+3uj5B2dqF5gacUoCyITeNXjA7YUOgQqEcFq8Fdh+yoY\n8/oZ1DQGFYcht8iglWGolGC0EMc5YfIbMkK0hlppCZe1zOFds5nZrLPoAy188w/97JMmioAL/Qf4\nqHUveqPOFyNexsxpPt71UYy7d4NIErh4khvEHVwSCPLjFbP4xHOfZHBggJ7eT1PlDnHu+lO45ZLF\nzKR3sX//TeTzvbRUvJPZYyrKjt+Ug3UBJb2O1/w3s6evGceWzFlZw7LlNXgyZhkID87g5srufJWA\nhtEawWgNkQ5upWf6FlzXYeszl/LORx5ArGmmc9arHLbfh2/ZZRz+5bfYEdBYkI1zxrx+vGdexdMd\n6zh//nv+ZwPjrvYFcu4PfsurfliQtfnS3gxdKYlQ9L/635Ttsj3vYIaGmVJUHjKDGMUk504Osjbe\nT0OuHz0TB0AJhfAvX45vxQr02hpEMMR/bBnj+ZE8Z8916Ta34s810Blfj+EeDUGMJFgxTmtHiOnQ\nRkKVD6L+KkjtVpOphV5S75LEYzn2FVX2FVSUvMPX4klWlEoc0BsYcj5KRd0Yjc7d1MQdXllxLT8u\nabyqaKAEcLwL0K0At3//C3QNZrjzfJWNKz20Rztoi7QR7ZvNb2IryBkJQpM3oUtBzPIyrVgIqRGz\n1nN6wsepe/fBiB9bD5BrasE7Zykjo1O4RT8lT1WZrwMgXfzk0SvGUGsP44ulae88jbmLLsXrP67x\nKBQKbNm4lfTDO4kMjJFzHPKRJqzGTjK2F9s8/pLZikXOmGJWxkTJ5QisWoEWCqCoCooqyLkuu7J5\nek0LDajOThHLpehqDWPObESEJAHVQ8PqNWRL9zOU20qPU8vmXB1D+V7AwRV+TN8iTO9SXK2L5QOC\nzqGD+KxBvIUS3kIefy5DRTpL1XSKqukk6tH+7CgGBV8VqVADU+Em8r4qKnMzSGmxO9bEjqo2CipI\nNYehFKgQCtUORB3wOgbeUpizQz9ngf8ZAP5YuIRvOpdyWNUJ6gXa2jcxqb+CY0ve1XQpl++rZObe\nB5GBCIH3foDfWoLD0su13Qcxu3tR5qzCVOpJ+/JkZQ7XdlGkjrS9uJaHN/iyb0jTApfzP7Yer7+8\ntDo6Osqrr77Knj17cF2XFllFi6zgjqbfct25n2bN5ikyP/tHtNMvZOLBF9AcyR+X6fzXqS5KOMxF\n7RdxacelzK+cf2wQtE2H5FiO/bsP4YsWaJ2T5JWhx7itewte4XBddYkmX5BoZBXR2Bpi0TUEA10I\nqSBdCa4EIRCGchIl4Q3JmzaHJ7J0j2fKYHkiTfd4hkTWfFNdAAWXIHlCFAiJQnlbFAhRoKaQpHFq\nA1K4eEfvZ9mRHnbVdPDA2euoqo3T7o8z34wwO9VJIDUfxTXedPy0a/N8WlJqeY27M/OZlnCF18+1\nkRABr16+D11FGAqKoSJ0BaG5WH39FI/4MFpCRC/pwGgI/sXvE6lBxg8+Q673ZdpK46gzR8qW1ifq\nz4QK4UaItuCodeSHfFiFSoxF8wmcvhgx+GIZEE/sAdUDXe+AZe8va1T+JIiNlBIciTOdodQzgpPV\nsOIO1nD2mIYFAXptAKMlxKgt2bxlHNtyWXfJbBaf2YRQBAN7Ejzzi/0oiuC8jy+gufOt/Y7untzN\n+554HxWeGC+864/0F4b5yJMfwaN6uOuCu07yFOM4Lo/cvZ87zSw7Znupocgntj+H07cW5m/BObCW\n6SCsrP8RF6WfwZYKo0o1/Z4GeiOtHNFrueyPOtG2C3iitoiKl5X//U0MaZH6gk4hdIj2iX8honQw\nUkizZXiM0UKKUETSUqNSLGWZmrBwpnwMByI8tWQhiVovAjhlymFFWvJs3xR9rsOZC1WGjO+RLE5y\n25ovs/ah67E1ycGXa2msPZWftxf42cpPsCIa5eHl807yQ3xMnvwH5JYf81P9aj72pdvQtPLkKWfl\nuObpa9if3M8PzvoBKytns3vPdWQy+9iZuYZvh8+jvmSyfnuJ+cMWOcOm2h2jUpnC8miMGTU4o6O4\nOow1NFMwFIoSpvGyQcmybHw//h2b0adTKBQpdVpk5zdBZC2emU6MXCUB4SNwAgguOQ4ppcREuMR0\nVZ6ZyhRj5DkivQx5axny1pPVTqbfxYRDs0enJRikxeeh0ZA0anlq1Qw1JBFOCtNMYllJTGsKy0xi\nWkksq7zfdY+vHk3bgoHQu/nCum/gSMnGVJb7x5M8Fp+m6EpaVLi8dy8X3PEfCMuiZ1Ybnd2HKHhU\ngqrFc11r+d4VHyUdCPC+J3/P+558GMO2Uf0abtjL3ooWhqL1nB5dSa0xm8ncNDOTO6ndfR+l2nqm\nPjAfUX0QAgMgXLBU1KEgc/qmaPRMk+gN8HhiHomQn6pCiGzFGbie2bTXFqi9YgFfs1y2zORYEwlw\nge8wv95yEx+NdLD8kQP4t6iE203qN7goZgqQFBSDG+Z+iYdqz+Hc/LO8z/sTvKZDflclB1+vQkqF\n9kYfyxY10tzaiJ02KY1MUxwYJ39gkNLABK4tQCgYs2bhW7QI76JF+BYvwtPZWfZZfoJYjsVIdoTB\n9CCD6UGGMkPlPD3EWG4M4Sq8e/cX0Vwdj+1nomGSidZKth02yJYclupDvFc8xPb2NE+KHMtiS1j4\nRJE5y6f40ewP0eMs4PDZKzjrvtPxx+fQPXYZnXoP93/l40yO/ojBoZ8StsIsnKjE27e1zB0GqF0M\np92A23YB5kiRbHeS6d0J9HTp+DsVU1E6ijj1U1jRcQocIZ/vI5/vxbbThEILGchcz7zP3Ei6tYYN\nK7eTsj9G3rkU6dq42SPsMPbQP36QK85rpmn4flA0xD9N/P2AsRDiAuB7lIOL3imlvO1PfvcAvwZW\nAFPAlVLKgb90TGPefNl8x8/4yPP3cMlDz6NKyWCTYFNnIxO1s6mw2mguNBMrVuNBRxegCYmpFilV\nJmgOPYlZuRW7XpIt+Xl26EqeHFqK4wpW4GHDeIrmXD/N6jCh+CHc4cFj55aaxPWC9IHrk7h+KEYU\nEnWzmQktwSw1YmVqsIvlgUH3JAhMpHDCBoO1MxwMHWDcP0zGM0WF5rDQB0vDM6xKZOkYyOEqCv0t\nlXT0x1FWXwcX3g5Af67IHb39/NdUEdd1qS5M8fmff4f5R1yeW9nEaHMIywlSkTuN6VCAqvQEoSJI\nqaC4Oh7Hh+DNXgyO3ZfiktYnaB+bIKrkqVm3gOyeJwjv2ownU555yaowpYpF9MyqRq5eSHN7Ow0N\nDRw6dIjBRx9j5c5uPPEBhD9C1fXXUvG+96D4fGUL5OkS/7Cll/7hDNXJEapTo0QKAbx6EFX3okoV\nXBXTEVgOKFLBi4JmAw6UI8i+td8aUymS9aQo+LKUfCp5qaLkBcWgIF7jZ6Cmkng4dow6gpTUTts0\nJa2yV4ysg6doE847RGyBV5zsa1VxCriKRArfn72GY+2IxAYs1aJOPQJIDjmz8AqHgFJCugLFMdDk\nm8HXnxOhmqhGDtXIlb0RGHkMn4YvGCQQjhGK1BCKNuALBvCHDWrbwoi3CLqRyWTYtm0b27Zuo1As\nEJMBDoQPsmbpfNZ+8k4A+lpqOLBoJUsuvAB/p5/f9/2e54aeo+SU6Ih28M7Z7+SC2NmEp7yYI1ms\nkSxO2mSjtp1bw/9JvV3NV2c+TMA/Ri68n0LkIKZ/vNyOlg/f9Fz8yU78qU48mRYUTUcJG6ih40l5\nYzv8xraO4tcRiiCRLdEXz1IoDJON7yQz8zoFZz9CKaDi4s01EpiZTVQuJFa5EF9TJf7mED3fvIWd\n9tto73sEa9Fsti47hZ2Jabon89huua18Wp7W0DCd+jBL5AwrfbXMquqEcAeP7BwkMVTFj0Ml2kIe\nbm6pocswkKZTTpaLNB3co7k0y7ni14lc0IZ/Re1bPpO/SWwT0sNlf8JvkWR6FHHywjO2bz7F8Nso\nec/BdQPl67NcpOUc3zZdpH305TpBlJCB0RzCaAmV86YQiuf4yllupsQLdx9kYM8UjfOi1M2K8NpT\ng1Q1Bbnw2kWEq0420P1Tufqpq3l1/FWuXnQ1j/Q+guM63HXhXbSGW99UV7qSjQ8c5snXx3jutChm\nxuKjz5Z5liO1NgvW3UqdcYSMG6G3WMHrKR/7swZ5aaMpOeYkS/z76Gcp6YIPz/sa//n9Ins/p1Pb\nkecp8S4GzHdwqNsllShguKBbLi2WyixLod1W8MvyN9PBQUVl2q+wabbBvnYvRa9CRcHlwrjD1GCG\njcUEVXPvIS/6+I0yi8W9L/DSikoKwyG+VvvPTHhrufuhX9Gxag2hs8/CaG8/eVKYjeP++0IGnCoC\ny6+kNuLDsgs83vsoifwE5zSdQWuwEdO2GMxl6J2ZYNoxUKWLJh3ahIubXc7EiE5RBnDCHUxnBaW8\nBYoH0P/q9wvK2ltNlBOKwFKhqJc194WASiZokNQgpbiUNIGpC0q6AEMh6odKo0C1mKRGDlJj9lFT\nPESl1Y+hFbF0BdNQsHQF+WcuRVF8GEYFul6BocfQjQoMvRJdryDtOPzywANYRgv/fs6d6H+iDMvY\nDo+OjHL/8BhbTIOG+Djf/4+vEk2nmZxbQ6SU5btv/wjPdq6nKzHGv25/nq5iCcUbAU8EkwB5x8eM\n6+Phiip6dJ0NI0Vq4wn8Y9uICpdo13kUNQ9jtmDMLSCrD2PUHsZT3YsWitM1mGLB0BT7fW080b8E\nUmVwa/gCtC1ZRntnO21VCo9kC9zidpBF55NH7uGzQ7/h8DwPwadUSpv8oAgUrw4BH0e8EeLeAFFf\nihrfKCUzyNS4jvQEqFu4iJZVawk2NqOGQyjBEGooiBIOo3jKCjs7laK4dy+FPXso7i7zlZ1E2X0e\nuo63cwGe+UvxzJ6P3tCGEqzEzdm4OQsna+JkLNyciZu1KBYKjOkJBmSG6XiZt32w7mVemPUAuB6q\n8hcxnVxOKqdTK5Ksjt3HltphPKqPtTsDRM9v5A79Bv6hSnDnjvdjjV9MKN3Bd6+ai5H9OuroXuaO\nGoTi8XJvVXScjispNX8cMxWi1D+DNZ7DUfOYgXGcxiRWZZyUO0jeGUQLTiKU45pyTatCUxuR1INs\nRA1fRPqzNxLNpll6Vg/73KswntyMp2EeoXOuAq2e/GiKp0fvxlV0zl77AQxzJ+03fO7vA4yFECpw\nCDgXGAa2Ae+VUu4/oc71wGIp5XVCiPcAl0opr/xLx61oa5G/uXIW0qsyFY1gGxF8bhhFKgghkcIB\nrYTqdTGUIkZqFF8mgdejI/MZ8OkYs1oRLTFKcopSaYyiWSJRqCBthdAVm5gm8douCg6KauOqeVSj\niHbC0sSfE9cyKKRayY0sITvUSdquQJMetD/RRAkFpGJjU0TzmFRFUiywn6bR3YfAoXvRrynYEcyC\nTTFvkUsXyWRM8kUHxQT1T5pfIikYCqYuqVRTDKsJPLlp6pIuDYkkqlPA195E1YbVRFYsYrD3a2Tk\nJsQzKl9ZnOO2hwI0j1lU33Mbw9YDJBLPoikRfNkN7Hm+m/adaerGMiAdpKozUVPDeG0VTaPjVE1O\nIDxhQm97L3X/eC2q/82D44xlc+72Q4znTbzTT7Es8zylqJcZM02qlMZxS2/6z4miuCqGY2C4HnQ7\nQLhYSXW+iepcPRWFGjx2EMXxosiTga2NS9GQ6BEvas5FKTgob9F1XVxKep4ZT5ykf5Tx0ACJWB8B\nf5K8peJNzaJlej6NM3OpLNQjUJCKhRKexghaOLogW9LIZ3Qs08B1dQwhqQjmyGkTjMg0qCatXps6\nTx7NyKHqJRTNRGglFKVEYJdJ6CUbzTQprcuQfWeefDGM6zbR3LyBOR1nEQrNL7uo+d8Uy7J4fcsO\nNj2/kZSbwRUO1dOHsK0I6fpG3nP5e5g3bx7SldjJIsnBMZ4aeIrH0k+zX+lBkQqrsgs4N7OOU4Jr\neTayhe/Kn9Ep5nCb9ytEtTAoogwEFYGlTpFR95BVd5ERuyhy5OiVCIRUAQFSIGQ5L4+YSrnMCWUU\nhFBwVRNHLYMjPVdLYGYhEW0VFdXr8bc0YDSHjlMV3rjnzb/gvl/opNXGY/tUTELqBKo6TdZrMOwP\ncFgaHCz6SaIiBfh1k86oy2mHoxzyWCy/fC4fXt/2F8OTviFvfB/fSiP+d5WjwNncu5/8xl2UzDYc\nvaOsvdYV0FUUXSlrsQ0VoSnHNdxv7NdV1IiB0RJGjRh/9ZqllBzYNMbG+w9jlRzmrqnlzPd1HgvF\n/JdkMjfJ2Q+UOcVhI8wvL/glc2Nl948ZM8NwZpiR7AjDmWGGs8OMZEYwdjXQ0XsKzy5IsnC4ktHo\nFDvqb6PFyNPhcZnjdWnzOBhHL3vC8tGdCXAwU8EprzfxLt8HGZl8DsX/W9LvcnhqxuCJtAZSUDkz\nl+bkKloyHdTlo2gIVM1FhG0qYiptNRGaIlHcnENyMs9MooBVdHitVuOpNoNd1TqKK1k3aXPecImW\nzCghpZcN3EZPZRe3z72YR42L+Jz8JivtbbgjGlqfIDYVpbl1EeFZFehKHDG+G5nofhN0dQAUDano\nmKiYCGyhIhUNXZEoMkuKGDY6jT4fDyUayS65HmPbH0gM9OFEqqgzczROTBLI1WFWL8ataAV/JSWv\njxlDJanBtCpIK5K8AibgSIHHlhiWxGNJPLbEZ7kYtkSz/7Y+LdQSim6i6RaqbqJpFoZaRBc5DDeN\nx5nGQw6PLOATNr5QBG9FA3p1E0ZdG0bDHIzKenSvdmxiKaVEIlGkhMw4xA/gdr+IO7QXmRpGFrJI\nXIa8MR6u2cALntV89N4HaZ6Y4KkNZ1PUK5g1bREtgi28WIoPUw1gakFc9c0KC8NMo9pFCr7qYxzW\ngAIVmiCmCly/Qk+Vxu6Yxp6oSndI4frh33Jz/894rOpUng6vZeHQ64TGU6RSKnm7fI5ab4bKxgAP\nrr6KP0QWUu3O0DB1B991NtH6gkW+5RoSRZVXhkbQ8jk6CocJpfO4Mwq6K1BtB/HXlJO6juIPovj8\nCG8QYfgQug+hepEY4OqAF6EHQT/629GE5kMYBqpfR436USsDqEEDNaijHM03vzLGgZ1xlq+qQQSO\n8FJ8I1v01znkPYKTm4tInkk+14ZhjFDV+Csy3gwrMjqbu24jmjtAPnUnhYFPcPXs/VxkPELrcIFI\n2kRKBUtfSDZ6LVmrgoI1iBkYwwyNY1VMUvKNJo3oEgAAE4FJREFUYIvkCTeq4rpVmGYl6VSQ6aSP\nXCFCKRfFtX0IqaG4GkiNyGSa9pFx3A4/CaUJO6vhiVShVdZhW4JSwcbM27juyW37qZ/8nQJ8CCHW\nAf8qpTz/aPkfAKSU3zihzlNH62wWQmjAOFAt/8LB583zyB/9uOnP/QyoCFEeRN8YUKVlgeWi6F5U\nXwChGCiKhhAaQuhI6WDbGfKlDGOZIMliDAHU+l0M28eujA+fZrKi5jUMPUAsuoaqqrPx+2ehaaET\nUpAjMyP89x+fIbVNEDSjeBU/HuFBuAquLXFdiXQkfw8mipQO3un7WHFwPxvne7ntI1/jorEHaH/+\nGc7YA9GcS7G6hpor3k3Nuy9HrzvObXOcAlufu4iCPUTkrkr0+AzWl+Yzre1G08K0tFxNc9MH0bRy\ndLBt49v45Us/ZMNLOit7FdzJA8hcHOGLYMy7kJobP0Zw5V96LrA7k+ei7Yewgc/EVZIVggdEiaJQ\niGS3oabvRXUS6G4An9OCkLVItRKPkCxNpxkRRygIk9pCLRXFOiwjCmoAjwa6N0faP84gA6RyGUKl\nGKFSJTV2C0amBqMYJq9lyfriZPzDzPiHyelpdMdDrdlCmzWPynwjnpkwmEeBj4BwpZfctIlju2WG\nSV2BRMUg+73bOaC+hquUVW5NwSbmV86nq6KLjmwTDVt9bMlv487ah5hWM7w9dRofjL+DoOtHIpkW\nOSb0SeLeOCktTlFPo2km0Uya8HiOnuZ2YqEFnH7OucyePfvvDrCcvMXrd77AzvhBhtUpHK/Ntad8\nkGBawxrJYo5kkaWjE0FVoNcHGKub5mnvKzyReZaEmSBkhMiYGTY0buA7p38Hv+7/yycFSqVJUtOv\nksseKvPepYvEPZpLpOMgTQvXtHFNG2nauJaDtGxcywYHgvoCKmtOI9w2F63a/9e1sbkE7re7yFpR\nZmhlJriKGaOLGaeBmZyfmSkTxzquOhUKuD6TjJqjaBrUFAOc9qkOFi1s+X/T5P/HSTpRYGokS9vi\nqv9H/fO6Z65jy9gWLpp1EUWneAwIp830SfVCRoimYBNNoSZajixGf6UZb5PC3LMjBPx+wsEAkUCI\nQMCHbkhyhb2kpl9lOvUq0zOv4R7lniupaoK5DtINm+kZX8KR197HHCmoJURQGHgVia7Z+ITAz5vB\nUUEBWwH36GQPRSAkuKbLsCF5otHgySadGY9CXc7hgqEi/zj5ERJaJWtP+TGXD8e5cfxxVGMXHgbw\nl6YJ5J3j7vGERk6JoVQtxje2kVG1jm+tOYXnplN0zfoUe0phso5LtaFxSU2US2tjLAv5EUKQSDzP\nY7u/xc18lVlTCeyNw1yWeIKA9FIXmE8+Oo+pmjDJmMp4QDLqUxnzGIwbPizl5IlMjBmqmaBajlHN\n5LFUwwQVTKEh0LUwmhJBcSpRnAqEEwYzBHYATB+u6UOWDBzTwClpWJbAMsE0wbIEpiWwLAXTVrFs\nFUf+9ckUgC6K6EoJQykipI0rBa7UcNBwpI6LhiM1XP46pRJAuA66lUa3ZtDsLKqTRZVZcPMIUUCK\nIo5qkvH5ONg0i/3tXcRyGpWZ40m1y+OEAsRUQUwTRDSB4oOQt4e20n+hiiSWYtPvr2JXoIUD1JBM\nCYLjCWricYQwGG3pYsfSsygoftbPbOKavufpn3Mxdyjz0ESRC6zfox02iYWX0da1jIpoHbJoIdN5\nZDqDm8kg0zlkJg3ZHG4uizALCCuHsPJg5cHMgp1HOEWkXSjbYVl/WRl1kigKSiCAGo2i1dagNzYi\nIhX0HSrQtLSJWHsNIhgEx0N8MsmWqV284uxhk3ea3MwarPRCPNXPYlRswqCSjGcuRnELnxifw4fF\n8wQKDqbiZzQ0n6HKCEVvFlvPI10Nx/Ljmn7sUohiLkYxH8UuhrDMIK7px7W9qBgoUke4ajnqzV9Z\nHRFYuIqLI2ykYuMKB92rEAh5CcUCxKrC5CeH6N36IovXn8E5n3zn3w0YXw5cIKW8+mj5A8AaKeWn\nTqiz92id4aPl3qN1En/uuK2N7fLb//ofNM6upr2riarq6qMgV/27gId8vp9N+5/jRxtL7BgvL+/V\n+if51vmb6Jx1OVVVZ6H8DXzmv0VcV+I6Lo7t0n9omO2bdjHSFwcpcFUTb1CnojpERXUF1dVVVFZU\nEo1G0TQNKWHatHlgbArzri9z2fN7mIwIamYkjiJIr11H1wc+QPS0U08yIjxRSqVJXn3+XGwni/SB\npoVobv4YLc0fPgaITxQpJRtHNnLPprs4/fAi1k/OIhdVeWbtAZKR7N90z4fyFs+Ji48u74FR2Il/\n+mGkGsT0LsT0LsTRm0AIFAlRBFWKSiMKH9qdJpBMMHhqG7NlECdpkZ4qkEkWySSLlI4S7k21SDww\nxGRkkKnoEcb9A2SVGVRHp1Y2srh1Pp21c+mIdjA7OpuGYAOKOO7bNjNVJDGcZWoky9RIjmCFh+bO\nCuo7IhgnaCNTxRQHpg6wP7mf/VPlNJIdOel+F8YW8OWum+j0zCm7AivZR12COciSfTR3yGQzjGQm\nGc1NUlJs1l54Ku0L5/xNbfq/K9J2ST14mKmdw3jQysakmkCvD2I0lpPeGESv8SO041pS27XZPLqZ\nR3sfJeqNctOqm960rPk/Toa3AwLqF5cNm04Q6UpyMyYz8Twz8QIzk4UTtnM0dYW46Lq/+k38v/I3\nyo6JHXzoyQ+hKzqNwUYag400hZpOyhuDjUQ8kZP+1/PaJM/8Yh+u89Zjj6IKdI+K7lUxfOCt6EcJ\n7gN9B6HqITyZZpq3f+kkHrmjC4xKHyKqkdIzjCoT9DgD7Cruo88dJKFPU1LK3HYhNBAGUpSBmCt0\nEDqq46Uu1YqmrmCipp2xKj9f6f0p1w/fS5+3hY7CEIooT7yKbpSs20bJiFIIG8xU5UhXD+HqZQ6t\nUgwiphrB9J1EkPnTke1PW+DJ8CruqrqAruIARdVgQouRFyev3PlllppjgHeCWneSenuSRmuChtIE\nIauEbjkYloNh2RiWRLdcdEtiWC6aLf+ugdik1LClB0sGKckgphvEdAOYMoAp/VgygCl9mK4fU3qx\npBdT+pBSK89PFBXF8KIGw6ixOrRwEC1koHk1VFVB0QSqVrZdUTWBm50hWBUgUBvGF/GgvMWE+q1w\njeM4pNNppqenT0gzTE/myMUdZN6Hx4yg2gHeeFJeATGtTGC0JVgSbHmUaifL+/7/sNISOAjhouAi\nhIvARZEOAhdxQq64TrnsnpwUx0G4NsJxysm1/7rmWhFIBaQiKKmCnO5iaaAInWrXoKAEyWshLOEH\nYYD4G1ZEZQmkCbKE4IRtWYKjZSFNpDSPlRf09DEd1Hju1DzBhZ1otbXYtk0+nz+WcrkcpnnUlkVK\nlh5UCKdcvnjfY//zgLEQ4hrgGoCWlpYVg4OD/H8hG7v/V3t3HyPHWR9w/PvbN3LOi2M7ORNwSOKS\nhETipYkJkSoFBCVQIpFKLTQNgggQ/EGooII/0gqBBEIqVVshpEoVUmJCVCWqCqhGBKIooUIFEuK0\nCeTsQEzIi41rE/vss2Pv3u3ujz/mOXv9crbvhG8v2e9HGs0zzzwzN+P9eeY3s8/Mbuaeh3/FrW+/\nkivWnN4kZdbk5CRTU1OMj48zNnbi/nqz9s50uesrn+Ky+39M50+v510f/wyt1cc+KX88U1MTTDz6\nN4yveQ+vufhjNJvLT7pMZvLAcw/wvYe+w1O933CgMcfPjs5h6xnvoN26nPP6W3ntuRezduUbeNXY\nmZzfarC61WT1K5qMtxqsbDaOeVAl+znnHcLpdrdKkneVoSTMU7sOsqe9h7e89XJef92FC+/veQr2\ndvayefdmNu3axPlj53PD2hsOJd1LUWZy4LHfQbdfJcGrlxGn0FVgVGTm6e8OMYL2T+9nWXPZvP9v\n7J/ssG/XQaY7PWbaPWY6Xabbs+UeM+1uNW+23O7ROdglJveyvAZnX3Qul15zIasuX0Fz+SuOuOAb\nlJnsOLCDiRcmeGbqGaZ703R6HTq9TilPs6/bZt9Mm/0zbV7sdjjY69Dudmh3VrGmfwX//NtvsK+9\nim3tS9naXcvW7h+xP1dSS6gT1BPODliV04yf/RuWr9pC67zn6a/YCo153M2jSrJub36QTbUrGO9O\n8sqZXazp7uCizjbWTL/ARe1JVk53aXSbNLtn0Oy1CFpEtCCapbtGA2rNMt081IUjak2yPlvXrC4s\na01oDNa1qul6i6g3yUaTqLeqto0WNBrVvMZsu2b1bz/Q7SoG78gfMa5+XpkXd8CuJ4kzlhFrrobG\nwruU/SG122327NnD7l172P70bl54dj/7fnuQ7lR1AVaLpBZ96pHVwOF+3I0IGrUqgW8mTLbq1Fbc\nzZun/o+xmQZZ7ob3s0afOv2s06dOlvHhuloZN+hnneTI9seMD7Wv089G1f6YdR45nmudOdthPDmU\n7R9KD48znWW61p+h3utQ63eo99rUugep99oDw5HTtUN1nWOeqzgVe88a4+s3Ntl3wQwnuqOcmfR6\nPfr9Po0Dfd7xP8v5/F0/WNpdKdatW5cbN2482fZJkiRJCzbTbtMaGzulxPhULvMfAS6NiEsiogXc\nBGw4qs0G4JZS/kvgwRMlxZIkSdJiaJbfWDgVjZM1yMxuRHwSuI/qdW13ZOZERHwR2JiZG4Dbgbsi\nYguwmyp5liRJkl4yTpoYA2TmvcC9R9V9fqDcBt73h900SZIkafH4dI4kSZKEibEkSZIEmBhLkiRJ\ngImxJEmSBJgYS5IkSYCJsSRJkgSYGEuSJEmAibEkSZIEmBhLkiRJgImxJEmSBJgYS5IkSYCJsSRJ\nkgSYGEuSJEmAibEkSZIEmBhLkiRJgImxJEmSBJgYS5IkSYCJsSRJkgSYGEuSJEmAibEkSZIEmBhL\nkiRJgImxJEmSBJgYS5IkSYCJsSRJkgSYGEuSJEkARGYO5w9H/A54dih/fOk7D3hh2BuhlyRjRwth\n3GihjB0txDDi5qLMPP9kjYaWGGtuEbExM9cNezv00mPsaCGMGy2UsaOFWMpxY1cKSZIkCRNjSZIk\nCTAxXqq+PuwN0EuWsaOFMG60UMaOFmLJxo19jCVJkiS8YyxJkiQBJsaLJiLuiIidEfHEQN0bI+Kn\nEfGLiPhuRJxT6j8QEY8NDP2IeFOZd3VpvyUivhYRMax90uk3z7hpRsSdpX5zRPzdwDLvjohflri5\nbRj7osU1z9hpRcT6Uv94RLxtYBmPOSMkIi6MiB9GxKaImIiIT5X6lRFxf0Q8VcYrSn2UuNgSET+P\niKsG1nVLaf9URNwyrH3S6beAuHldORZ1IuKzR61ruOerzHRYhAG4DrgKeGKg7hHgraX8EeBLx1nu\n9cCvB6Z/BlwLBPB94M+GvW8OSyNugJuBe0p5GfAMcDFQB34NrAVawOPAlcPeN4clFTu3AutLeRx4\nFKiVaY85IzQAFwBXlfLZwK+AK4F/BG4r9bcBXynl95S4iBInD5f6lcDTZbyilFcMe/8clkzcjANv\nBr4MfHZgPUM/X3nHeJFk5o+A3UdVXwb8qJTvB/7iOIv+NXAPQERcAJyTmQ9lFUHfBP789GyxloJ5\nxk0CZ0ZEAxgDpoEp4BpgS2Y+nZnTVPF04+nedg3XPGPnSuDBstxOYA+wzmPO6MnM7Zn5v6W8D9gM\nvJrqmHFnaXYnh+PgRuCbWXkIOLfEzbuA+zNzd2ZOUsXbuxdxV7SI5hs3mbkzMx8BZo5a1dDPVybG\nwzXB4Q/8fcCFx2nzV8DdpfxqYOvAvK2lTqNlrrj5T+BFYDvwHPBPmbmbKkaeH1jeuBldc8XO48B7\nI6IREZcAV5d5HnNGWERcDPwx8DCwOjO3l1n/D6wu5bmOLx53RtQpxs1chh43JsbD9RHgExHxKNVX\nD9ODMyPiLcCBzHzieAtrZM0VN9cAPeBVwCXAZyJi7XA2UUvUXLFzB9UJaCPwVeAnVLGkERURZwHf\nAj6dmVOD88q3B77SSsd4OcRNY9gbMMoy80ngeoCIuAy44agmN3H4bjHANmDNwPSaUqcRcoK4uRn4\nQWbOADsj4sfAOqqr78FvI4ybETVX7GRmF/jb2XYR8ROqPoKTeMwZORHRpEpu/j0zv12qd0TEBZm5\nvXSV2Fnqt3H848s24G1H1f/36dxuDdc842Yuc8XTovGO8RBFxHgZ14DPAf82MK8GvJ/SvxiqPjzA\nVERcW54M/xDwX4u60Rq6E8TNc8Dby7wzqR6EeZLqgatLI+KSiGhRXXBtWOzt1vDNFTsRsazEDBHx\nTqCbmZs85oye8jnfDmzOzH8ZmLUBmH2zxC0cjoMNwIfK2ymuBfaWuLkPuD4iVpQ3EVxf6vQytIC4\nmcvQz1feMV4kEXE31dXzeRGxFfgCcFZE3FqafBtYP7DIdcDzmfn0Uav6BPANqoervl8GvUzNM27+\nFVgfERNUT4ivz8yfl/V8kuqkVAfuyMyJxdsLDcM8Y2ccuC8i+lR3Zz44sCqPOaPlT6g+/19ExGOl\n7u+BfwD+IyI+CjxLdeMG4F6qN1NsAQ4AHwbIzN0R8SWqRAfgi+WZB708zStuIuKVVF23zgH6EfFp\nqrdPTA37fOUv30mSJEnYlUKSJEkCTIwlSZIkwMRYkiRJAkyMJUmSJMDEWJIkSQJMjCVJkiTAxFiS\nJEkCTIwlSZIkAH4P/me5bLkXGwYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x16be4bbc828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "res.transpose().plot(figsize=(12,12))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}