IntegrationTest_txt_gensim.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO summa.preprocessing.cleaner: 'pattern' package not found; tag filters are not available for English\n"
     ]
    }
   ],
   "source": [
    "from dariah_topics import preprocessing as pre\n",
    "from dariah_topics import visualization as visual\n",
    "from dariah_topics import evaluation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Preprocessing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Liste mit Dateinamen erzeugen"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO preprocessing: Creating document list from TXT files ...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['corpus_txt/Lovecraft_AttheMountainofMadness.txt',\n",
       " 'corpus_txt/Howard_TheDevilinIron.txt',\n",
       " 'corpus_txt/Poe_ThePurloinedLetter.txt',\n",
       " 'corpus_txt/Lovecraft_TheShunnedHouse.txt',\n",
       " 'corpus_txt/Poe_TheMasqueoftheRedDeath.txt']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path_txt = \"corpus_txt\"\n",
    "#path_txt = \"grenzbote_plain/*/\"\n",
    "#path_txt = \"wiki/\"\n",
    "\n",
    "doclist_txt = pre.create_document_list(path_txt)\n",
    "assert doclist_txt, \"No documents found\"\n",
    "doclist_txt[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#####  Liste mit Dokumentenlabels erzeugen - (Funktion wird durch Thorsten's generischere Funktion ersetzt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO preprocessing: Creating document labels ...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['Lovecraft_AttheMountainofMadness',\n",
       " 'Howard_TheDevilinIron',\n",
       " 'Poe_ThePurloinedLetter',\n",
       " 'Lovecraft_TheShunnedHouse',\n",
       " 'Poe_TheMasqueoftheRedDeath']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doc_labels = list(pre.get_labels(doclist_txt))\n",
    "doc_labels[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Corpus laden"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "corpus_txt = pre.read_from_txt(doclist_txt)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Tokenisieren"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO preprocessing: Accessing TXT documents ...\n"
     ]
    }
   ],
   "source": [
    "doc_tokens = [list(pre.tokenize(txt)) for txt in list(corpus_txt)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Create Dictionaries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "id_types = pre.create_dictionary(doc_tokens)\n",
    "doc_ids = pre.create_dictionary(doc_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Sparse BOW Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "sparse_bow = pre.create_sparse_bow(doc_labels, doc_tokens, id_types, doc_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>doc_id</th>\n",
       "      <th>token_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1</th>\n",
       "      <th>8198</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8202</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16395</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 0\n",
       "doc_id token_id   \n",
       "1      8198      1\n",
       "       7         2\n",
       "       8         1\n",
       "       8202      1\n",
       "       16395     1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sparse_bow[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Topic Modeling with Gensim"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "##### Saving Sparse BOW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "pre.save_sparse_bow(sparse_bow, \"gensim_txt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Import Market Matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from gensim.models import LdaModel\n",
    "from gensim.corpora import MmCorpus\n",
    "from gensim.corpora import SvmLightCorpus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO gensim.matutils: initializing corpus reader from gensim_txt.mm\n",
      "INFO gensim.matutils: accepted corpus with 17 documents, 22232 features, 369906 non-zero entries\n"
     ]
    }
   ],
   "source": [
    "mm = MmCorpus(\"gensim_txt.mm\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO gensim.matutils: initializing corpus reader from gensim_txt.mm\n",
      "INFO gensim.matutils: accepted corpus with 17 documents, 22232 features, 369906 non-zero entries\n",
      "INFO gensim.corpora.svmlightcorpus: converting corpus to SVMlight format: corpus.svmlight\n",
      "INFO gensim.corpora.indexedcorpus: saving SvmLightCorpus index to corpus.svmlight.index\n"
     ]
    }
   ],
   "source": [
    "corpus = MmCorpus('gensim_txt.mm')\n",
    "SvmLightCorpus.serialize('corpus.svmlight', corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "doc2id = {value : key for key, value in doc_ids.items()}\n",
    "type2id = {value : key for key, value in id_types.items()}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "##### Remove Features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "type2id = {value : key for key, value in id_types.items()}\n",
    "sparse_bow_collapsed = sparse_bow.groupby(sparse_bow.index.get_level_values('token_id')).sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "sparse_bow_hapax = sparse_bow_collapsed.loc[sparse_bow_collapsed[0] == 1]\n",
    "hapax = [type2id[key] for key in sparse_bow_hapax.index.get_level_values('token_id')]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "len(hapax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "import os.path\n",
    "basepath = os.path.abspath('.')\n",
    "\n",
    "with open(os.path.join(basepath, \"tutorial_supplementals\", \"stopwords\", \"de.txt\"), 'r', encoding = 'utf-8') as f: \n",
    "    stopword_list = f.read().split('\\n')\n",
    "    \n",
    "stopword_list = set(stopword_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO preprocessing: Finding hapax legomena ...\n",
      "INFO preprocessing: Finding stopwords ...\n",
      "INFO preprocessing: Removing features ...\n"
     ]
    }
   ],
   "source": [
    "hapax_from_remove = pre.find_hapax(sparse_bow, id_types)\n",
    "stopwords_from_remove = pre.find_stopwords(sparse_bow, id_types, mfw=75)\n",
    "\n",
    "#features_to_be_removed = set(hapax_from_remove + stopwords_from_remove)\n",
    "features_to_be_removed = stopwords_from_remove\n",
    "\n",
    "sparse_bow_short = pre.remove_features(sparse_bow, id_types, features_to_be_removed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "75"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(features_to_be_removed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "pre.save_sparse_bow(sparse_bow_short, \"gensim_txt\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO gensim.matutils: initializing corpus reader from gensim_txt.mm\n",
      "INFO gensim.matutils: accepted corpus with 17 documents, 22232 features, 369906 non-zero entries\n"
     ]
    }
   ],
   "source": [
    "mm = MmCorpus(\"gensim_txt.mm\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "#### Convert sparse_bow to list of (doc, tokens) tuples (like doc2bow)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "doc2bow_list = []\n",
    "\n",
    "for doc in sparse_bow_short.index.groupby(sparse_bow_short.index.get_level_values('doc_id')):\n",
    "    temp = [(token, count) for token, count in zip(sparse_bow_short.loc[doc].index, sparse_bow_short.loc[doc][0])]\n",
    "    doc2bow_list.append(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(doc2bow_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO gensim.models.ldamodel: using symmetric alpha at 0.05\n",
      "INFO gensim.models.ldamodel: using symmetric eta at 4.49781855799937e-05\n",
      "INFO gensim.models.ldamodel: using serial LDA version on this node\n",
      "INFO gensim.models.ldamodel: running online LDA training, 20 topics, 10 passes over the supplied corpus of 17 documents, updating model once every 17 documents, evaluating perplexity every 17 documents, iterating 20x with a convergence threshold of 0.001000\n",
      "INFO gensim.models.ldamodel: -12.542 per-word bound, 5961.7 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 0, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #18 (0.050): 0.058*\"decidedly\" + 0.031*\"appertain\" + 0.031*\"invaluable\" + 0.025*\"cease\" + 0.015*\"grovelling\" + 0.011*\"namelessly\" + 0.011*\"vowed\" + 0.010*\"flickered\" + 0.010*\"village-alive\" + 0.010*\"outwitted\"\n",
      "INFO gensim.models.ldamodel: topic #0 (0.050): 0.066*\"decidedly\" + 0.032*\"appertain\" + 0.027*\"cease\" + 0.023*\"invaluable\" + 0.017*\"namelessly\" + 0.015*\"vine-shaded\" + 0.012*\"vowed\" + 0.012*\"grovelling\" + 0.011*\"ascended\" + 0.010*\"village-alive\"\n",
      "INFO gensim.models.ldamodel: topic #12 (0.050): 0.052*\"decidedly\" + 0.037*\"appertain\" + 0.024*\"invaluable\" + 0.019*\"cease\" + 0.015*\"vowed\" + 0.014*\"namelessly\" + 0.014*\"vine-shaded\" + 0.014*\"grovelling\" + 0.010*\"ascended\" + 0.009*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #9 (0.050): 0.071*\"decidedly\" + 0.032*\"invaluable\" + 0.031*\"appertain\" + 0.027*\"cease\" + 0.016*\"grovelling\" + 0.015*\"vowed\" + 0.014*\"village-alive\" + 0.012*\"namelessly\" + 0.011*\"vine-shaded\" + 0.010*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #4 (0.050): 0.054*\"decidedly\" + 0.033*\"invaluable\" + 0.030*\"appertain\" + 0.019*\"grovelling\" + 0.018*\"cease\" + 0.015*\"vowed\" + 0.015*\"namelessly\" + 0.011*\"village-alive\" + 0.010*\"exhibitions\" + 0.010*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic diff=6.502449, rho=1.000000\n",
      "INFO gensim.models.ldamodel: -8.145 per-word bound, 283.0 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 1, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #13 (0.050): 0.067*\"decidedly\" + 0.028*\"appertain\" + 0.027*\"invaluable\" + 0.023*\"cease\" + 0.014*\"grovelling\" + 0.012*\"village-alive\" + 0.011*\"namelessly\" + 0.009*\"friendship\" + 0.009*\"vowed\" + 0.009*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #6 (0.050): 0.043*\"decidedly\" + 0.025*\"invaluable\" + 0.022*\"appertain\" + 0.015*\"cease\" + 0.014*\"grovelling\" + 0.011*\"namelessly\" + 0.011*\"vine-shaded\" + 0.010*\"vowed\" + 0.008*\"flickered\" + 0.008*\"ascended\"\n",
      "INFO gensim.models.ldamodel: topic #0 (0.050): 0.062*\"decidedly\" + 0.030*\"appertain\" + 0.027*\"cease\" + 0.021*\"invaluable\" + 0.016*\"namelessly\" + 0.016*\"vine-shaded\" + 0.012*\"vowed\" + 0.012*\"grovelling\" + 0.010*\"ascended\" + 0.010*\"robert\"\n",
      "INFO gensim.models.ldamodel: topic #17 (0.050): 0.048*\"decidedly\" + 0.029*\"appertain\" + 0.019*\"invaluable\" + 0.018*\"cease\" + 0.014*\"grovelling\" + 0.013*\"namelessly\" + 0.010*\"vine-shaded\" + 0.009*\"vowed\" + 0.008*\"ascended\" + 0.008*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #15 (0.050): 0.050*\"decidedly\" + 0.026*\"invaluable\" + 0.022*\"appertain\" + 0.018*\"cease\" + 0.012*\"grovelling\" + 0.012*\"vowed\" + 0.011*\"village-alive\" + 0.010*\"vine-shaded\" + 0.008*\"namelessly\" + 0.008*\"friendship\"\n",
      "INFO gensim.models.ldamodel: topic diff=2.457180, rho=0.577350\n",
      "INFO gensim.models.ldamodel: -7.665 per-word bound, 203.0 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 2, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #5 (0.050): 0.059*\"decidedly\" + 0.040*\"invaluable\" + 0.030*\"appertain\" + 0.024*\"cease\" + 0.019*\"grovelling\" + 0.014*\"namelessly\" + 0.013*\"village-alive\" + 0.012*\"vowed\" + 0.010*\"ascended\" + 0.009*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #13 (0.050): 0.059*\"decidedly\" + 0.025*\"appertain\" + 0.024*\"invaluable\" + 0.020*\"cease\" + 0.012*\"grovelling\" + 0.010*\"village-alive\" + 0.009*\"namelessly\" + 0.008*\"friendship\" + 0.008*\"vowed\" + 0.008*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #2 (0.050): 0.047*\"decidedly\" + 0.033*\"cease\" + 0.030*\"appertain\" + 0.029*\"invaluable\" + 0.018*\"grovelling\" + 0.014*\"namelessly\" + 0.011*\"vine-shaded\" + 0.011*\"friendship\" + 0.010*\"flickered\" + 0.010*\"vowed\"\n",
      "INFO gensim.models.ldamodel: topic #18 (0.050): 0.050*\"decidedly\" + 0.027*\"invaluable\" + 0.027*\"appertain\" + 0.021*\"cease\" + 0.013*\"grovelling\" + 0.009*\"namelessly\" + 0.008*\"outwitted\" + 0.008*\"vowed\" + 0.008*\"village-alive\" + 0.008*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #14 (0.050): 0.054*\"decidedly\" + 0.032*\"appertain\" + 0.029*\"invaluable\" + 0.016*\"cease\" + 0.015*\"namelessly\" + 0.014*\"vowed\" + 0.013*\"grovelling\" + 0.013*\"flickered\" + 0.013*\"vine-shaded\" + 0.011*\"friendship\"\n",
      "INFO gensim.models.ldamodel: topic diff=1.962158, rho=0.500000\n",
      "INFO gensim.models.ldamodel: -7.417 per-word bound, 170.8 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 3, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #17 (0.050): 0.030*\"decidedly\" + 0.018*\"appertain\" + 0.012*\"invaluable\" + 0.011*\"cease\" + 0.009*\"grovelling\" + 0.008*\"namelessly\" + 0.006*\"vine-shaded\" + 0.006*\"vowed\" + 0.005*\"ascended\" + 0.005*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #8 (0.050): 0.028*\"decidedly\" + 0.018*\"invaluable\" + 0.013*\"appertain\" + 0.010*\"cease\" + 0.008*\"grovelling\" + 0.007*\"vowed\" + 0.007*\"village-alive\" + 0.006*\"namelessly\" + 0.006*\"vine-shaded\" + 0.005*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #12 (0.050): 0.043*\"appertain\" + 0.040*\"decidedly\" + 0.026*\"vowed\" + 0.019*\"refracted\" + 0.018*\"cease\" + 0.016*\"invaluable\" + 0.015*\"vine-shaded\" + 0.010*\"namelessly\" + 0.010*\"flickered\" + 0.009*\"grovelling\"\n",
      "INFO gensim.models.ldamodel: topic #11 (0.050): 0.069*\"decidedly\" + 0.039*\"appertain\" + 0.027*\"cease\" + 0.022*\"invaluable\" + 0.016*\"vowed\" + 0.016*\"grovelling\" + 0.015*\"namelessly\" + 0.014*\"vine-shaded\" + 0.012*\"flickered\" + 0.011*\"village-alive\"\n",
      "INFO gensim.models.ldamodel: topic #10 (0.050): 0.064*\"decidedly\" + 0.029*\"appertain\" + 0.028*\"invaluable\" + 0.021*\"cease\" + 0.019*\"vowed\" + 0.016*\"namelessly\" + 0.015*\"grovelling\" + 0.015*\"flickered\" + 0.014*\"village-alive\" + 0.014*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic diff=1.455649, rho=0.447214\n",
      "INFO gensim.models.ldamodel: -7.280 per-word bound, 155.4 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 4, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #12 (0.050): 0.043*\"appertain\" + 0.035*\"decidedly\" + 0.028*\"vowed\" + 0.022*\"refracted\" + 0.018*\"cease\" + 0.015*\"vine-shaded\" + 0.014*\"invaluable\" + 0.010*\"flickered\" + 0.010*\"namelessly\" + 0.009*\"princess\"\n",
      "INFO gensim.models.ldamodel: topic #9 (0.050): 0.072*\"decidedly\" + 0.037*\"invaluable\" + 0.035*\"appertain\" + 0.022*\"cease\" + 0.016*\"grovelling\" + 0.013*\"friendship\" + 0.012*\"vine-shaded\" + 0.011*\"robert\" + 0.011*\"namelessly\" + 0.009*\"village-alive\"\n",
      "INFO gensim.models.ldamodel: topic #14 (0.050): 0.041*\"decidedly\" + 0.025*\"appertain\" + 0.022*\"invaluable\" + 0.012*\"cease\" + 0.012*\"namelessly\" + 0.011*\"vowed\" + 0.010*\"grovelling\" + 0.010*\"flickered\" + 0.010*\"vine-shaded\" + 0.008*\"friendship\"\n",
      "INFO gensim.models.ldamodel: topic #3 (0.050): 0.047*\"decidedly\" + 0.019*\"invaluable\" + 0.017*\"appertain\" + 0.015*\"cease\" + 0.011*\"grovelling\" + 0.010*\"vowed\" + 0.008*\"mantel-piece\" + 0.008*\"namelessly\" + 0.007*\"village-alive\" + 0.006*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #19 (0.050): 0.028*\"decidedly\" + 0.017*\"appertain\" + 0.015*\"invaluable\" + 0.014*\"cease\" + 0.011*\"vowed\" + 0.009*\"grovelling\" + 0.008*\"namelessly\" + 0.008*\"village-alive\" + 0.006*\"vine-shaded\" + 0.005*\"refracted\"\n",
      "INFO gensim.models.ldamodel: topic diff=1.079668, rho=0.408248\n",
      "INFO gensim.models.ldamodel: -7.195 per-word bound, 146.5 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 5, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #19 (0.050): 0.022*\"decidedly\" + 0.013*\"appertain\" + 0.012*\"invaluable\" + 0.011*\"cease\" + 0.008*\"vowed\" + 0.007*\"grovelling\" + 0.006*\"namelessly\" + 0.006*\"village-alive\" + 0.005*\"vine-shaded\" + 0.004*\"refracted\"\n",
      "INFO gensim.models.ldamodel: topic #13 (0.050): 0.032*\"decidedly\" + 0.013*\"appertain\" + 0.013*\"invaluable\" + 0.011*\"cease\" + 0.006*\"grovelling\" + 0.006*\"village-alive\" + 0.005*\"namelessly\" + 0.005*\"friendship\" + 0.004*\"vowed\" + 0.004*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #2 (0.050): 0.031*\"decidedly\" + 0.021*\"cease\" + 0.020*\"appertain\" + 0.019*\"invaluable\" + 0.012*\"grovelling\" + 0.009*\"namelessly\" + 0.007*\"vine-shaded\" + 0.007*\"friendship\" + 0.006*\"flickered\" + 0.006*\"vowed\"\n",
      "INFO gensim.models.ldamodel: topic #11 (0.050): 0.070*\"decidedly\" + 0.041*\"appertain\" + 0.026*\"cease\" + 0.023*\"invaluable\" + 0.019*\"vowed\" + 0.015*\"grovelling\" + 0.015*\"namelessly\" + 0.014*\"flickered\" + 0.013*\"vine-shaded\" + 0.010*\"village-alive\"\n",
      "INFO gensim.models.ldamodel: topic #10 (0.050): 0.063*\"decidedly\" + 0.029*\"appertain\" + 0.027*\"invaluable\" + 0.022*\"cease\" + 0.019*\"vowed\" + 0.016*\"namelessly\" + 0.016*\"flickered\" + 0.016*\"grovelling\" + 0.015*\"village-alive\" + 0.015*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic diff=0.808197, rho=0.377964\n",
      "INFO gensim.models.ldamodel: -7.139 per-word bound, 141.0 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 6, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #13 (0.050): 0.024*\"decidedly\" + 0.010*\"appertain\" + 0.010*\"invaluable\" + 0.008*\"cease\" + 0.005*\"grovelling\" + 0.004*\"village-alive\" + 0.004*\"namelessly\" + 0.003*\"friendship\" + 0.003*\"vowed\" + 0.003*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #14 (0.050): 0.027*\"decidedly\" + 0.016*\"appertain\" + 0.015*\"invaluable\" + 0.008*\"cease\" + 0.008*\"namelessly\" + 0.007*\"vowed\" + 0.007*\"grovelling\" + 0.006*\"flickered\" + 0.006*\"vine-shaded\" + 0.005*\"friendship\"\n",
      "INFO gensim.models.ldamodel: topic #12 (0.050): 0.041*\"appertain\" + 0.028*\"vowed\" + 0.027*\"decidedly\" + 0.026*\"refracted\" + 0.017*\"cease\" + 0.016*\"vine-shaded\" + 0.012*\"invaluable\" + 0.011*\"meshes\" + 0.010*\"sit-up\" + 0.009*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #11 (0.050): 0.069*\"decidedly\" + 0.042*\"appertain\" + 0.025*\"cease\" + 0.023*\"invaluable\" + 0.020*\"vowed\" + 0.015*\"grovelling\" + 0.014*\"namelessly\" + 0.014*\"flickered\" + 0.013*\"vine-shaded\" + 0.009*\"village-alive\"\n",
      "INFO gensim.models.ldamodel: topic #16 (0.050): 0.018*\"decidedly\" + 0.009*\"invaluable\" + 0.008*\"appertain\" + 0.006*\"cease\" + 0.006*\"vowed\" + 0.006*\"grovelling\" + 0.005*\"vine-shaded\" + 0.005*\"namelessly\" + 0.004*\"village-alive\" + 0.004*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic diff=0.612289, rho=0.353553\n",
      "INFO gensim.models.ldamodel: -7.102 per-word bound, 137.4 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 7, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #8 (0.050): 0.007*\"decidedly\" + 0.005*\"invaluable\" + 0.003*\"appertain\" + 0.003*\"cease\" + 0.002*\"grovelling\" + 0.002*\"vowed\" + 0.002*\"village-alive\" + 0.002*\"namelessly\" + 0.002*\"vine-shaded\" + 0.001*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #16 (0.050): 0.014*\"decidedly\" + 0.007*\"invaluable\" + 0.006*\"appertain\" + 0.005*\"cease\" + 0.005*\"vowed\" + 0.004*\"grovelling\" + 0.004*\"vine-shaded\" + 0.003*\"namelessly\" + 0.003*\"village-alive\" + 0.003*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #4 (0.050): 0.016*\"decidedly\" + 0.010*\"invaluable\" + 0.009*\"appertain\" + 0.006*\"grovelling\" + 0.005*\"cease\" + 0.005*\"vowed\" + 0.005*\"namelessly\" + 0.003*\"village-alive\" + 0.003*\"mantel-piece\" + 0.003*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #14 (0.050): 0.021*\"decidedly\" + 0.013*\"appertain\" + 0.012*\"invaluable\" + 0.006*\"cease\" + 0.006*\"namelessly\" + 0.006*\"vowed\" + 0.005*\"grovelling\" + 0.005*\"flickered\" + 0.005*\"vine-shaded\" + 0.004*\"friendship\"\n",
      "INFO gensim.models.ldamodel: topic #17 (0.050): 0.008*\"decidedly\" + 0.005*\"appertain\" + 0.003*\"invaluable\" + 0.003*\"cease\" + 0.002*\"grovelling\" + 0.002*\"namelessly\" + 0.002*\"vine-shaded\" + 0.002*\"vowed\" + 0.001*\"ascended\" + 0.001*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic diff=0.469262, rho=0.333333\n",
      "INFO gensim.models.ldamodel: -7.076 per-word bound, 134.9 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 8, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #17 (0.050): 0.006*\"decidedly\" + 0.004*\"appertain\" + 0.002*\"invaluable\" + 0.002*\"cease\" + 0.002*\"grovelling\" + 0.002*\"namelessly\" + 0.001*\"vine-shaded\" + 0.001*\"vowed\" + 0.001*\"ascended\" + 0.001*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic #4 (0.050): 0.012*\"decidedly\" + 0.007*\"invaluable\" + 0.007*\"appertain\" + 0.004*\"grovelling\" + 0.004*\"cease\" + 0.004*\"vowed\" + 0.004*\"namelessly\" + 0.002*\"village-alive\" + 0.002*\"mantel-piece\" + 0.002*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #1 (0.050): 0.011*\"decidedly\" + 0.006*\"appertain\" + 0.004*\"invaluable\" + 0.004*\"cease\" + 0.003*\"vowed\" + 0.003*\"grovelling\" + 0.003*\"vine-shaded\" + 0.002*\"flickered\" + 0.002*\"village-alive\" + 0.002*\"namelessly\"\n",
      "INFO gensim.models.ldamodel: topic #2 (0.050): 0.015*\"decidedly\" + 0.011*\"cease\" + 0.010*\"appertain\" + 0.009*\"invaluable\" + 0.006*\"grovelling\" + 0.004*\"namelessly\" + 0.004*\"vine-shaded\" + 0.003*\"friendship\" + 0.003*\"flickered\" + 0.003*\"vowed\"\n",
      "INFO gensim.models.ldamodel: topic #3 (0.050): 0.017*\"decidedly\" + 0.007*\"invaluable\" + 0.006*\"appertain\" + 0.005*\"cease\" + 0.004*\"grovelling\" + 0.004*\"vowed\" + 0.003*\"mantel-piece\" + 0.003*\"namelessly\" + 0.002*\"village-alive\" + 0.002*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic diff=0.363085, rho=0.316228\n",
      "INFO gensim.models.ldamodel: -7.058 per-word bound, 133.2 perplexity estimate based on a held-out corpus of 17 documents with 369906 words\n",
      "INFO gensim.models.ldamodel: PROGRESS: pass 9, at document #17/17\n",
      "INFO gensim.models.ldamodel: topic #3 (0.050): 0.013*\"decidedly\" + 0.005*\"invaluable\" + 0.005*\"appertain\" + 0.004*\"cease\" + 0.003*\"grovelling\" + 0.003*\"vowed\" + 0.002*\"mantel-piece\" + 0.002*\"namelessly\" + 0.002*\"village-alive\" + 0.002*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #10 (0.050): 0.062*\"decidedly\" + 0.029*\"appertain\" + 0.027*\"invaluable\" + 0.022*\"cease\" + 0.019*\"vowed\" + 0.017*\"flickered\" + 0.016*\"namelessly\" + 0.016*\"grovelling\" + 0.016*\"vine-shaded\" + 0.015*\"village-alive\"\n",
      "INFO gensim.models.ldamodel: topic #1 (0.050): 0.008*\"decidedly\" + 0.004*\"appertain\" + 0.003*\"invaluable\" + 0.003*\"cease\" + 0.002*\"vowed\" + 0.002*\"grovelling\" + 0.002*\"vine-shaded\" + 0.002*\"flickered\" + 0.002*\"village-alive\" + 0.001*\"namelessly\"\n",
      "INFO gensim.models.ldamodel: topic #13 (0.050): 0.010*\"decidedly\" + 0.004*\"appertain\" + 0.004*\"invaluable\" + 0.003*\"cease\" + 0.002*\"grovelling\" + 0.002*\"village-alive\" + 0.002*\"namelessly\" + 0.001*\"friendship\" + 0.001*\"vowed\" + 0.001*\"vine-shaded\"\n",
      "INFO gensim.models.ldamodel: topic #17 (0.050): 0.004*\"decidedly\" + 0.003*\"appertain\" + 0.002*\"invaluable\" + 0.002*\"cease\" + 0.001*\"grovelling\" + 0.001*\"namelessly\" + 0.001*\"vine-shaded\" + 0.001*\"vowed\" + 0.001*\"ascended\" + 0.001*\"flickered\"\n",
      "INFO gensim.models.ldamodel: topic diff=0.283172, rho=0.301511\n"
     ]
    }
   ],
   "source": [
    "model = LdaModel(corpus=mm, id2word=type2id, num_topics=20, passes = 10, iterations = 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(5, 0.48155632419791006),\n",
       " (7, 0.015074485821617953),\n",
       " (9, 0.14674192638340758),\n",
       " (10, 0.19320042554799227),\n",
       " (11, 0.15558887034794608)]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.get_document_topics(doc2bow_list[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['decidedly',\n",
       " 'appertain',\n",
       " 'invaluable',\n",
       " 'cease',\n",
       " 'vowed',\n",
       " 'grovelling',\n",
       " 'vine-shaded',\n",
       " 'flickered',\n",
       " 'village-alive',\n",
       " 'namelessly']"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Anzeige der keywords für topic n\n",
    "n = 1\n",
    "topic_nr_x = model.get_topic_terms(n)\n",
    "\n",
    "topicTerms = [type2id[i[0]] for i in topic_nr_x]\n",
    "topicTerms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>ascended</td>\n",
       "      <td>robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>flickered</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>namelessly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>cease</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>friendship</td>\n",
       "      <td>flickered</td>\n",
       "      <td>vowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>mantel-piece</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>mantel-piece</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>appertain</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>ascended</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>smoothed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vowed</td>\n",
       "      <td>flickered</td>\n",
       "      <td>ascended</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>your-eye</td>\n",
       "      <td>tar-like</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>person</td>\n",
       "      <td>exhibitions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>flickered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>friendship</td>\n",
       "      <td>robert</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>outwitted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>flickered</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>village-alive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>vowed</td>\n",
       "      <td>flickered</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>ben-sheep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>appertain</td>\n",
       "      <td>vowed</td>\n",
       "      <td>refracted</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>cease</td>\n",
       "      <td>meshes</td>\n",
       "      <td>sit-up</td>\n",
       "      <td>penguin</td>\n",
       "      <td>invaluable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>friendship</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>flickered</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>friendship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>friendship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>flickered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vowed</td>\n",
       "      <td>ascended</td>\n",
       "      <td>flickered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>refracted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0           1           2           3            4              5  \\\n",
       "0   decidedly   appertain       cease  invaluable   namelessly    vine-shaded   \n",
       "1   decidedly   appertain  invaluable       cease        vowed     grovelling   \n",
       "2   decidedly       cease   appertain  invaluable   grovelling     namelessly   \n",
       "3   decidedly  invaluable   appertain       cease   grovelling          vowed   \n",
       "4   decidedly  invaluable   appertain  grovelling        cease          vowed   \n",
       "5   decidedly  invaluable       cease   appertain   grovelling     namelessly   \n",
       "6   decidedly  invaluable   appertain       cease   grovelling     namelessly   \n",
       "7   decidedly   appertain  invaluable       cease     your-eye       tar-like   \n",
       "8   decidedly  invaluable   appertain       cease   grovelling          vowed   \n",
       "9   decidedly  invaluable   appertain       cease   grovelling     friendship   \n",
       "10  decidedly   appertain  invaluable       cease        vowed      flickered   \n",
       "11  decidedly   appertain       cease  invaluable        vowed      flickered   \n",
       "12  appertain       vowed   refracted   decidedly  vine-shaded          cease   \n",
       "13  decidedly   appertain  invaluable       cease   grovelling  village-alive   \n",
       "14  decidedly   appertain  invaluable       cease   namelessly          vowed   \n",
       "15  decidedly  invaluable   appertain       cease   grovelling          vowed   \n",
       "16  decidedly  invaluable   appertain       cease        vowed     grovelling   \n",
       "17  decidedly   appertain  invaluable       cease   grovelling     namelessly   \n",
       "18  decidedly  invaluable   appertain       cease   grovelling     namelessly   \n",
       "19  decidedly   appertain  invaluable       cease        vowed     grovelling   \n",
       "\n",
       "                6              7              8              9  \n",
       "0           vowed     grovelling       ascended         robert  \n",
       "1     vine-shaded      flickered  village-alive     namelessly  \n",
       "2     vine-shaded     friendship      flickered          vowed  \n",
       "3    mantel-piece     namelessly  village-alive    vine-shaded  \n",
       "4      namelessly  village-alive   mantel-piece    vine-shaded  \n",
       "5   village-alive       ascended      outwitted       smoothed  \n",
       "6     vine-shaded          vowed      flickered       ascended  \n",
       "7      grovelling    vine-shaded         person    exhibitions  \n",
       "8   village-alive     namelessly    vine-shaded      flickered  \n",
       "9          robert    vine-shaded     namelessly      outwitted  \n",
       "10     namelessly     grovelling    vine-shaded  village-alive  \n",
       "11     grovelling     namelessly    vine-shaded      ben-sheep  \n",
       "12         meshes         sit-up        penguin     invaluable  \n",
       "13     namelessly     friendship          vowed    vine-shaded  \n",
       "14     grovelling      flickered    vine-shaded     friendship  \n",
       "15  village-alive    vine-shaded     namelessly     friendship  \n",
       "16    vine-shaded     namelessly  village-alive      flickered  \n",
       "17    vine-shaded          vowed       ascended      flickered  \n",
       "18      outwitted          vowed  village-alive    vine-shaded  \n",
       "19     namelessly  village-alive    vine-shaded      refracted  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Topic probabilities - zum Testen der Funktion\n",
    "topics = model.show_topics(num_topics = model.num_topics, formatted=False)\n",
    "keywords = []\n",
    "\n",
    "num_topics = model.num_topics\n",
    "topics_df = pre.pd.DataFrame(index = range(num_topics), columns= range(10))\n",
    "\n",
    "for topic, values in topics:\n",
    "    keyword = [value[0] for value in values]\n",
    "    topics_df.loc[topic] = keyword\n",
    "\n",
    "topics_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>ascended</td>\n",
       "      <td>robert</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>flickered</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>namelessly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>cease</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>friendship</td>\n",
       "      <td>flickered</td>\n",
       "      <td>vowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>mantel-piece</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>mantel-piece</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>appertain</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>ascended</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>smoothed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vowed</td>\n",
       "      <td>flickered</td>\n",
       "      <td>ascended</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>your-eye</td>\n",
       "      <td>tar-like</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>person</td>\n",
       "      <td>exhibitions</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>flickered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>friendship</td>\n",
       "      <td>robert</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>outwitted</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>flickered</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>village-alive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>vowed</td>\n",
       "      <td>flickered</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>ben-sheep</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>appertain</td>\n",
       "      <td>vowed</td>\n",
       "      <td>refracted</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>cease</td>\n",
       "      <td>meshes</td>\n",
       "      <td>sit-up</td>\n",
       "      <td>penguin</td>\n",
       "      <td>invaluable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>friendship</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>flickered</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>friendship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>friendship</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>flickered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vowed</td>\n",
       "      <td>ascended</td>\n",
       "      <td>flickered</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>refracted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0           1           2           3            4              5  \\\n",
       "0   decidedly   appertain       cease  invaluable   namelessly    vine-shaded   \n",
       "1   decidedly   appertain  invaluable       cease        vowed     grovelling   \n",
       "2   decidedly       cease   appertain  invaluable   grovelling     namelessly   \n",
       "3   decidedly  invaluable   appertain       cease   grovelling          vowed   \n",
       "4   decidedly  invaluable   appertain  grovelling        cease          vowed   \n",
       "5   decidedly  invaluable       cease   appertain   grovelling     namelessly   \n",
       "6   decidedly  invaluable   appertain       cease   grovelling     namelessly   \n",
       "7   decidedly   appertain  invaluable       cease     your-eye       tar-like   \n",
       "8   decidedly  invaluable   appertain       cease   grovelling          vowed   \n",
       "9   decidedly  invaluable   appertain       cease   grovelling     friendship   \n",
       "10  decidedly   appertain  invaluable       cease        vowed      flickered   \n",
       "11  decidedly   appertain       cease  invaluable        vowed      flickered   \n",
       "12  appertain       vowed   refracted   decidedly  vine-shaded          cease   \n",
       "13  decidedly   appertain  invaluable       cease   grovelling  village-alive   \n",
       "14  decidedly   appertain  invaluable       cease   namelessly          vowed   \n",
       "15  decidedly  invaluable   appertain       cease   grovelling          vowed   \n",
       "16  decidedly  invaluable   appertain       cease        vowed     grovelling   \n",
       "17  decidedly   appertain  invaluable       cease   grovelling     namelessly   \n",
       "18  decidedly  invaluable   appertain       cease   grovelling     namelessly   \n",
       "19  decidedly   appertain  invaluable       cease        vowed     grovelling   \n",
       "\n",
       "                6              7              8              9  \n",
       "0           vowed     grovelling       ascended         robert  \n",
       "1     vine-shaded      flickered  village-alive     namelessly  \n",
       "2     vine-shaded     friendship      flickered          vowed  \n",
       "3    mantel-piece     namelessly  village-alive    vine-shaded  \n",
       "4      namelessly  village-alive   mantel-piece    vine-shaded  \n",
       "5   village-alive       ascended      outwitted       smoothed  \n",
       "6     vine-shaded          vowed      flickered       ascended  \n",
       "7      grovelling    vine-shaded         person    exhibitions  \n",
       "8   village-alive     namelessly    vine-shaded      flickered  \n",
       "9          robert    vine-shaded     namelessly      outwitted  \n",
       "10     namelessly     grovelling    vine-shaded  village-alive  \n",
       "11     grovelling     namelessly    vine-shaded      ben-sheep  \n",
       "12         meshes         sit-up        penguin     invaluable  \n",
       "13     namelessly     friendship          vowed    vine-shaded  \n",
       "14     grovelling      flickered    vine-shaded     friendship  \n",
       "15  village-alive    vine-shaded     namelessly     friendship  \n",
       "16    vine-shaded     namelessly  village-alive      flickered  \n",
       "17    vine-shaded          vowed       ascended      flickered  \n",
       "18      outwitted          vowed  village-alive    vine-shaded  \n",
       "19     namelessly  village-alive    vine-shaded      refracted  "
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "topics_df = pre.gensim2dataframe(model)\n",
    "topics_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "      <th>16</th>\n",
       "      <th>17</th>\n",
       "      <th>18</th>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>appertain</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>decidedly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>vowed</td>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>refracted</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>appertain</td>\n",
       "      <td>invaluable</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>appertain</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>decidedly</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "      <td>cease</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>namelessly</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>cease</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>your-eye</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>vowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vowed</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>tar-like</td>\n",
       "      <td>vowed</td>\n",
       "      <td>friendship</td>\n",
       "      <td>flickered</td>\n",
       "      <td>flickered</td>\n",
       "      <td>cease</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vowed</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>grovelling</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>mantel-piece</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>robert</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>meshes</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>namelessly</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>grovelling</td>\n",
       "      <td>flickered</td>\n",
       "      <td>friendship</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>ascended</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>grovelling</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>sit-up</td>\n",
       "      <td>friendship</td>\n",
       "      <td>flickered</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vowed</td>\n",
       "      <td>village-alive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ascended</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>flickered</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>mantel-piece</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>flickered</td>\n",
       "      <td>person</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>penguin</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>ascended</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>vine-shaded</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>robert</td>\n",
       "      <td>namelessly</td>\n",
       "      <td>vowed</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>smoothed</td>\n",
       "      <td>ascended</td>\n",
       "      <td>exhibitions</td>\n",
       "      <td>flickered</td>\n",
       "      <td>outwitted</td>\n",
       "      <td>village-alive</td>\n",
       "      <td>ben-sheep</td>\n",
       "      <td>invaluable</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>friendship</td>\n",
       "      <td>friendship</td>\n",
       "      <td>flickered</td>\n",
       "      <td>flickered</td>\n",
       "      <td>vine-shaded</td>\n",
       "      <td>refracted</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            0              1            2              3              4   \\\n",
       "0    decidedly      decidedly    decidedly      decidedly      decidedly   \n",
       "1    appertain      appertain        cease     invaluable     invaluable   \n",
       "2        cease     invaluable    appertain      appertain      appertain   \n",
       "3   invaluable          cease   invaluable          cease     grovelling   \n",
       "4   namelessly          vowed   grovelling     grovelling          cease   \n",
       "5  vine-shaded     grovelling   namelessly          vowed          vowed   \n",
       "6        vowed    vine-shaded  vine-shaded   mantel-piece     namelessly   \n",
       "7   grovelling      flickered   friendship     namelessly  village-alive   \n",
       "8     ascended  village-alive    flickered  village-alive   mantel-piece   \n",
       "9       robert     namelessly        vowed    vine-shaded    vine-shaded   \n",
       "\n",
       "              5            6            7              8            9   \\\n",
       "0      decidedly    decidedly    decidedly      decidedly    decidedly   \n",
       "1     invaluable   invaluable    appertain     invaluable   invaluable   \n",
       "2          cease    appertain   invaluable      appertain    appertain   \n",
       "3      appertain        cease        cease          cease        cease   \n",
       "4     grovelling   grovelling     your-eye     grovelling   grovelling   \n",
       "5     namelessly   namelessly     tar-like          vowed   friendship   \n",
       "6  village-alive  vine-shaded   grovelling  village-alive       robert   \n",
       "7       ascended        vowed  vine-shaded     namelessly  vine-shaded   \n",
       "8      outwitted    flickered       person    vine-shaded   namelessly   \n",
       "9       smoothed     ascended  exhibitions      flickered    outwitted   \n",
       "\n",
       "              10           11           12             13           14  \\\n",
       "0      decidedly    decidedly    appertain      decidedly    decidedly   \n",
       "1      appertain    appertain        vowed      appertain    appertain   \n",
       "2     invaluable        cease    refracted     invaluable   invaluable   \n",
       "3          cease   invaluable    decidedly          cease        cease   \n",
       "4          vowed        vowed  vine-shaded     grovelling   namelessly   \n",
       "5      flickered    flickered        cease  village-alive        vowed   \n",
       "6     namelessly   grovelling       meshes     namelessly   grovelling   \n",
       "7     grovelling   namelessly       sit-up     friendship    flickered   \n",
       "8    vine-shaded  vine-shaded      penguin          vowed  vine-shaded   \n",
       "9  village-alive    ben-sheep   invaluable    vine-shaded   friendship   \n",
       "\n",
       "              15             16           17             18             19  \n",
       "0      decidedly      decidedly    decidedly      decidedly      decidedly  \n",
       "1     invaluable     invaluable    appertain     invaluable      appertain  \n",
       "2      appertain      appertain   invaluable      appertain     invaluable  \n",
       "3          cease          cease        cease          cease          cease  \n",
       "4     grovelling          vowed   grovelling     grovelling          vowed  \n",
       "5          vowed     grovelling   namelessly     namelessly     grovelling  \n",
       "6  village-alive    vine-shaded  vine-shaded      outwitted     namelessly  \n",
       "7    vine-shaded     namelessly        vowed          vowed  village-alive  \n",
       "8     namelessly  village-alive     ascended  village-alive    vine-shaded  \n",
       "9     friendship      flickered    flickered    vine-shaded      refracted  "
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "doc_topic = topics_df.T\n",
    "doc_topic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "## Visualisierung "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"lda_model = 'out_easy/corpus.lda'\\ncorpus = 'out_easy/corpus.mm'\\ndictionary = 'out_easy/corpus.dict'\\ndoc_labels = 'out_easy/corpus_doclabels.txt'\\ninteractive  = False\\n\\nvis = visual.Visualization(lda_model, corpus, dictionary, doc_labels, interactive)\""
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''lda_model = 'out_easy/corpus.lda'\n",
    "corpus = 'out_easy/corpus.mm'\n",
    "dictionary = 'out_easy/corpus.dict'\n",
    "doc_labels = 'out_easy/corpus_doclabels.txt'\n",
    "interactive  = False\n",
    "\n",
    "vis = visual.Visualization(lda_model, corpus, dictionary, doc_labels, interactive)'''"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "##### Create a document-topic matrix (that is a pandas data frame actually)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "doc_topic = visual.create_doc_topic(mm, model, doc_labels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "##### Visualize document-topic matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/home/sina/.local/lib/python3.5/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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4JE9WGVbAaZLWwpP/C8jp35kuXl7/jhYYak/GfmvhjmETPMrN8mlDgIGSbqS8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\n4y0NAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc966b85e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "visual.doc_topic_heatmap(doc_topic)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "source": [
    "##### Visualize topic distribution in a single document"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/home/sina/.local/lib/python3.5/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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DRwE7AnektMHAm2n5q0D/CvvOBUame2DrkQVKgJWBvwLzlN1X26us7tLIZxyLRjhAm8c6\n707ghFyeIcCjwA6SPpvSlpO0EVkwCuCddH4OzJXTFBH3Ad9O7V4hHYMTc2WPrFC/mfURvSJARcQ0\nsg/rGWTTP1Nymw8Hjkk302eRXXEDnATsKmkG8ATw+VJxqcwbgBfJ7k1NAh5O6R+TfVCeJ2k6MA34\nQtr3aOBiSU9SezR1E9kH6qR6uldj/U6yqci7IuKTlHYxcKSyBzU2Bj4q3zciHiILUk8DPyO750NE\nzACmA8+SBdAHy/YdKukpsgBzcoW2VjvWeT9I5cxMbWyOiL8ARwJXpfIfATZJQf+S1M7bSec13Qe8\nIuWdClwQER8CZwMD0wMVM4CzKtRvZn2E2n+Bb22RtA3wk4jYpafbsjSSFBMm+H1t1ghz57YwaVJL\nu/aRRESo7ZyL6033oHoFSaeRPXVWz70nMzOroldM8fUmEXFeRKwfEY+0ndvMzKpxgDIzs0JygDIz\ns0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0Jy\ngDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIzs0JygDIz\ns0JygDIzs0JygDIzs0Ia0NMNMGuEuXNberoJZn1SU9OQbqtLEdFtlZl1B0nh97VZcUgiItTe/TzF\nZ2ZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZm\nheQAZWZmheQAZWZmheQAZWZmheSf27A+6cgjW3q6Cd2qqWkIZ511Uk83w6xLOUBZnzR8eEtPN6Fb\n+fevrC/yFJ+ZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZ\nmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRVSmwFK0h8k\nDcmtD5V0a2ObZWZmS7t6RlBrRsT7pZWIeA/4TOOaZGZmVl+AWiBp3dKKpKYGtsfMzAyAAXXk+R7w\nkKR70vquwL81rklmZmZ1BKiIuFXSGOALgIDTIuJPDW+ZmZkt1apO8UnaKP0dAawJ/BF4CVgrpZmZ\nmTVMrXtQ305//6vC66L2ViRpgqR/b3cLs30frJI+UdIB7ShnmKSZaXkXSTe3Y9+xkr5Vb/72tqeD\n+8+RtEqF9A4f6+4iaV9Jn6sj3zckHd4dbTKzYqk6xRcRx6S/O3Vfc6q2ZceuLK7KclttuBmoO6C1\nQ91t6OJ9e4yk/sB+wC3Ac7XyRsSvuqVRZlY49fw/qEGSTpR0jaTJko6XNKiewiWdLmm2pPuBTXLp\nG0i6XdLjku6TtHFKX0PS9ZKmS5omabuUPi+370WSnpV0J7BGLn2UpNZU5u2S1kzpW5fKA75ZoY2S\n9LykVXPrL5SPTCSNl3RhWp4o6QJJD0l6sTSKk3S1pD1z+0yUtH8aKd0v6Yn02q5COxaWn9ZvlrRz\nWr5Y0hRJMyVNyO8GnCZphqRHJW1QodyKx7osz+jUl6mSHsxN746XdKOkeyU9J+l7KX1YOgdXSHom\nvTeWbeM83CvpfElTgNOAfYAfSXpS0vqSvpb6OE3StbnyFo4GUxnnSnostWeH8r6YWd9Rz2PmlwFb\nA78GLgFGpbSaJI0CvgKMAPYGRuc2/zdwfESMBk4FfpHSfw60RsTIVM/TKT1SmQcAG0XEpsB4YPuU\nPgC4EPhyKnMicE7a9zeprq0qtTMiArgcKE0j7QFMj4h3K2XPLa8VETsAY4HzUtrVwLjUpoHAbsBt\nwNvAHhGxTdp+IZVVGxF9NyLGAFsCzZI2z217LyJGkE29XlBh32rHOu9ZYKeI2BqYAPwwt200sD8w\nEjgonVfILjguiojNgHnAcW2cB4CBETEmIs4BbgJOjYhRETEH+F3athXZqOqYKseif0RsC5wMtFTJ\nY2Z9QD2PmY9IH0Ild0l6po79dgJuiIj5wHxJNwFIWoEssFwrSSnvwPR3N+AIWBg45i1eJDsBV6Xt\nb2rRo++bAJuntoks8L4haWVgcESU7mFdDuzJkiYCN5J9wB+d1ttyY2rHs5JKI7nbgQtScNoLuD8i\n5qd2XCRpJPApsFEd5eeNk/R1svO1FrAZMCttuzr9vQr4aX6nNo513hDgt2nkFCz+vrir9B+1JV0P\n7Aj8HnglIh5Nea4ATgDuoMJ5yJU1uUYft5D0/dSWFVJZlVyf/k4FhtUoz8x6uXoC1FOSRkfE45BN\nmQFP1ll+pRFBP7Kr/lEVttVzT6VSHgGz0ohmUaI0uJ4yI+I1SW9L2hUYAxxaRzvml9VPCkatZEHw\nYODKtP1k4K2IGKHs/svfK5T3CYuPaEtTXMOBU4CtI+JDSRNL20rNr7IMtY913tnAPRFxgKRhwL01\nyqx2PIMq5yHnoxptmATsExGzJI0HdqmSr3TcP6XG+7e1tWXh8vDhzQwf3lyjajPrSq2trbS2tna6\nnHqm+LYAHkv3Wl4EpgAj072CWoHqfmB/ZfewViKbCiMi5gFzJB1YyqhFj63fDRyX0vpJWrGUJVfm\nuLRtbbL/NAwwG1hdi+5ZDZC0WUR8AHwgafuUr9bTYJeSjQQmp9Fbeyi3PBk4imykURoFDAbeTMtf\nBfpX2Hcu2XGVpPXIAiXAysBfgXnpfs5eZXUfnP6OAx7Jb2jjWOetDLyelo8q2/ZFSUMkLUf2YMND\nKb1J0rZp+RDgAaqchwr1QTY6Xjm3viLwVhp9HlZln3KqtqG5uWXhy8HJrHs1NzfT0tKy8NVR9QSo\nfcmmpL6UXhuntAOBg6rtFBHTyD6sZwC3kgW2ksOBY5Q9vDCL7IY5wEnArpJmAE8Any8Vl8q8AXiR\n7N7UJODhlP5xas95kqYD08j+YzFkU3YXp2BaK/DcRDa1NKlGnoXdq7F+J9lU5F0R8UlKuxg4UtmD\nGhuz+Eii1LeHyILU08DPyKawiIgZwHSy+0RXAA+W7TtU0lNkU2wnV2hrtWOd92PgXElTWfI9MYVs\nWm06cG1ElC5KZgPfTNO9Q4FftnEeyo/Z1cCp6cGM9YEzUl0PpL5WUu9ozsz6ANUzWEg35UuPej8Q\nEU/Xyt8bSdoG+ElEVJtaWuqkqbatI+LEsvRhwC0RsUXPtKw2STFhwtIVu+bObWHSpJaeboZZRZKI\niKozHtXU85j58cA1QFN6XSPpuPY3sbgknQZcy6L/nGxtW7oigJl1u3oekvhXYExE/BVA0jlkU2sX\nN7Jh3SkizmPRo+KWRMRlVPgvBRHxMtl/HzAza5h67kEJ+Di3/jE1bk6bmZl1haojKEkD0k3+y4FH\nJf0ubdqfOv6jrpmZWWfUmuKbAoyKiB9JupfsyTQBx5b+T5SZmVmj1ApQC6fxUkByUDIzs25TK0Ct\nrho/2RARP622zczMrLNqBaj+ZP+73w9EmJlZt6sVoN6MiLO6rSVmZmY5tR4z98jJzMx6TK0AtXu3\ntcLMzKxM1QBV5Qf7zMzMukU93yRhZmbW7RygzMyskBygzMyskBygzMyskBygzMyskBygzMyskByg\nzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskGr9YKFZrzV3bktPN6FbNTUN\n6ekmmHU5RURPt8GsS0kKv6/NikMSEdHuH8H1FJ+ZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWS\nA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSA5SZmRWSf27D+qQjj2yp\nmN7UNISzzjqpextjZh3iAGV90vDhLRXTl7bfiTLrzTzFZ2ZmheQAZWZmheQAZWZmheQAZWZmheQA\nZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZm\nheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQAZWZmheQA\nZWZmhdRtAUrSBEn/3sF9H6ySPlHSAe0oZ5ikmWl5F0k3d6Q93UXSvpI+V0e+b0g6vB3lri3pms61\nrmK5cySt0sF9K57L3nCezKwxBvR0A+oRETt2ZXFVlgtFUn9gP+AW4LlaeSPiV+0pOyLeBL7S8dZV\nL7oBZTayXDMrsIaOoCSdLmm2pPuBTXLpG0i6XdLjku6TtHFKX0PS9ZKmS5omabuUPi+370WSnpV0\nJ7BGLn2UpNZU5u2S1kzpW5fKA75ZoY2S9LykVXPrL5SPBCSNlvSQpKmSHpS0UUofL+lGSfdKek7S\n91L6sNTOKyQ9I+kaScu20dZ7JZ0vaQpwGrAP8CNJT0paX9LXJE1Jx+baXHkLR6epjHMlPZbas0OF\nPudHkuMl/S61Y7akc1P6sZLOy+0zXtIFafmG1PaZkr6WL7q8/LR+Su64VOxD8sVU7nOS9q7Q7uUl\nXZr6NlXS2PI8ZtZ3NCxASRpFdpU+AtgbGJ3b/N/A8RExGjgV+EVK/znQGhEjgVHA0yk9UpkHABtF\nxKbAeGD7lD4AuBD4cipzInBO2vc3qa6tKrUzIgK4HChNke0BTI+Id8uyPgvsFBFbAxOAH+a2jQb2\nB0YCB6W+QxaUL4qIzYB5wHFttBVgYESMiYhzgJuAUyNiVETMAX6Xtm1FNqo6plKfgP4RsS1wMtBS\nJU9+VLIlcBDZuRonaR3gOiA/5XYwMDktH5XaPhr4f5KGtlF+Xq0+DEvl/gvwS0nLlO17OnB36ttu\nwH9KWq5KPWbWyzVyim8n4IaImA/Ml3QTgKQVyALLtZKU8g5Mf3cDjoCFgWPe4kWyE3BV2v6mpHtS\n+ibA5sBdqcx+wBuSVgYGR0TpHtblwJ4V2joRuBG4ADg6rZcbAvw2jZyCxY/dXRHxfurf9cCOwO+B\nVyLi0ZTnCuAE4I5Kbc2VNZnqtpD0/dSWFVJZlVyf/k4FhtUor+TuiPhrav8zZIHiYUkvSRoDvAhs\nHBEPp/wnSdovLa8LbARMqaMegBGSzq7Sh2sAIuJFSS8B5fff/gkYK+nUtL4M0ATMLq+ktbVl4fLw\n4c0MH95cZ/PMrLNaW1tpbW3tdDmNvgdV6Sq6H/BeRIyqsK2eew2V8giYFRGLTWdJGlxPmRHxmqS3\nJe0KjAEOrZDtbOCeiDhA0jDg3hptqlZnVGtrzkc1mjoJ2CciZkkaD+xSJd/89PdT6jvH83PL+X2u\nIRs5PQfcANlDC2QXEttGxHxJ9wL5aTqAT4D+ufX89ok1+pA/bmLJ4yiykecLbXWoubmlrSxm1iDN\nzc00NzcvXD/zzDM7VE4j70HdD+wvaZCklYCxABExD5gj6cBSRkkj0uLdwHEprZ+kFUtZcmWOS9vW\nBnZN6bOB1bXontUASZtFxAfAB5K2T/lqPel2KdkoZ3IavZVbGXg9LR9Vtu2Lkoak6ab9gIdSepOk\nbdPyIcAD1dpapU3zUr0lKwJvSRoIHFajL3lqO0tV15P1ZxyLRnaDyS4w5it7wnC7Cvu9TdbHoZIG\nkU3ZldTqw0HKfBZYnyVHRncAJ5ZWJI3sYL/MrBdoWICKiGlkH2ozgFtZfArocOAYZQ8vzCJ7GADg\nJGBXSTOAJ4DPl4pLZd5ANt30NNlo4uGU/jFwIHCepOnANOALad+jgYslPUnt0dRNZFNOk6ps/zFw\nrqSpLHncppB9mE8Hro2IJ1P6bOCbadpsKPDLNtpa3r6rgVPTAwHrA2ekuh4guydWSb2juWoW5k/T\nls8ATRHxREr+AzBQ0tNk984eKd83Ij4BzgIeB+4sa+v3avThlbTtVuAbEfGPsu1np7pnpPfIWe3s\nm5n1Iqo8WFj6SNoG+ElEVJs2q7bfeGDriDixLH0YcEtEbNGFzbQ6SIoJEyq/r+fObWHSpJbubZDZ\nUk4SEdHu2Zxe8f+gGk3SacCxVL731BmO/mZmHeSvOgIi4ryIWD8iHmk79xL7XlY+ekrpL0fEiEr7\nmJlZ2xygzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMys\nkBygzMzy50xUAAAHBUlEQVSskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskByg\nzMyskBygzMyskBygzMyskBygzMyskBygzMyskBygzMyskAb0dAPMGmHu3JaK6U1NQ7q3IWbWYYqI\nnm6DWZeSFH5fmxWHJCJC7d3PU3xmZlZIDlBmZlZIDlBmXaC1tbVP19cTdS4NfeyJOnuijx3lAGXW\nBZaGDxn3sW/U6QBlZmbWSQ5QZmZWSH7M3PocSX5TmxVMRx4zd4AyM7NC8hSfmZkVkgOUmZkVkgOU\nmZkVkgOU9VqS9pT0nKTnJZ1WYfsykq6W9IKkRyQ1Nbi+nSRNlfSxpAM6U1c76jxZ0tOSpku6S9J6\nDa7vG5JmSJom6X5Jn+tMffXUmct3oKQFkkY1uk5J4yX9SdKT6XV0I+tLeb6SzuVMSVd0pr566pT0\n03Qen5Q0W9K7Da5vPUn3pPqmS9qrzUIjwi+/et2L7OLqRWAYMBCYDnyuLM+/ARen5YOBqxtcXxOw\nOTAJOKCb+rgLsGxaPrYb+rhibnkscHuj+1iqF7gPeBgY1Q3HdTzw8258r24ITAVWTuurdcdxzeU/\nHrikwX38FfCNtLwpMKetcj2Cst5qDPBCRLwcER8DVwP7luXZF7gsLV8H7N7I+iLilYiYBXTVo7H1\n1HlfRPxvWn0UWKfB9f01t7oisKAT9dVVZ3I2cB4wv5P1tafOdj8W3Yn6vg78V0R8CBARf+mGOvMO\nAa5qcH0LgJXT8hDg9bYKdYCy3mod4NXc+mss+eG8ME9EfAq8L2mVBtbX1dpb5zHA7Y2uT9Jxkl4E\nzgVO7ER9ddUpaSSwbkTc1sm66q4zOSBNRV0jad0G17cxsImkByU9LOlLnaiv3joBSFPfw4F7Glzf\nmcARkl4FbgFOaKtQByjrrSpd3ZaPXMrzqEKerqyvq9Vdp6TDga2BHze6voi4OCI2BE4DzuhEfW3W\nKUnA+cApbezTZXUmNwHDI2IkcDeLRuKNqm8A2TTfzsChwCWSVl5ir66ts2QccF2kubcG1ncIMDEi\n1gP2Btq8z+YAZb3Va2T3fErWBd4oy/MqsB6ApP5k8/vvNbC+rlZXnZL2AL4DjE3TKw2tL2cysF8n\n6qunzpWAzwOtkuYA2wG/7+SDEm32MyLeyx3LX5MF/4bVl/L8PiIWRMRcYDawUYPrLBlH56b36q3v\nGOAagIh4FFhW0mo1S+2Km4B++dXdL6A/i27KLkN2U3bTsjzHseghiXF07gGCNuvL5Z0IfLmb+rhV\nyvPZbqpvw9zyWGBKo+ssy38vsFU39HOt3PL+wMMNru9LwKS0vBrwMjC00ccV2AT4Yze9d24Fxqfl\nTYHX2iy3sw3zy6+eegF7kl1pvgB8O6WdCfxLWh5EdsX2AtkDBMMbXN82ZKO2ecCfgZnd0Me7gDeB\nJ4FpwI0Nru9nwKxU3921gklX1VmW9x46+RRfnf08J/VzWurnxo3uI/AT4GngKeCg7jiuwATgnM7W\nVecx3RR4MAWvJ4Hd2yrT38VnZmaF5HtQZmZWSA5QZmZWSA5QZmZWSA5QZmZWSA5QZmZWSA5QZmZW\nSA5QZtYhkj5NP50wU9JkSct2c/375n/uQ9KZknbrzjZYYzlAmVlHfRQRoyJiC+Bjsp/7WEz6Lr0u\nl766aj+yr0ECICImRERnvvDUCsYBysy6wgPAhpKGpR+tu0zSTGBdSYekHzmcIenc0g6S5qUfzZuV\nfmxx1ZQ+Mv3A5HRJv5M0OKXfK+l8SVPIvqh2H+BHaRS3vqSJpR+KlLR7Sn9K0iWSBqb0OZJalP2w\n5FOSNu7m42Tt4ABlZh0lAEkDgL2AmSl9I+CiNLL6hOxnOZqBkcBoSfukfCuQfZff5sD9ZF+7A9k3\nh58a2TeJz8qlAwyMiDERcQ7ZN46fmkZxcxY2ShpE9n2IB0XElmQ/oPdvuTL+FBFbA78ETu38YbBG\ncYAys45aTtKTwBSyLze9NKXPjYjH0/Jo4N6IeDciFgD/Q/aTEpD9gN01afkKYMf0ExODI+LBlH5Z\nLj9k36DeltIXoL5UpYwb0t+pZF9uagU1oKcbYGa91t8iYrGfvUi3nD7KJ1H/7zeVvhi0Vv6Pamyr\nt87Sr/J+ij8DC80jKDPrqGpBIJ/+GLCzpFXSgw2HAK1pWz/gwLR8GPBgZD95/q6kHVL6EcB9VeqZ\nx6KfEM97DhgmaYNcGa0V8lnB+erBzDqq2k8hLEyPiLckfYdFAeK2iLglLX8EjJF0BvA2cHBKHw/8\nStJywB+Bo6rUdzXwa0knkAW6SHXOl3QUcF0Kio8Dv2qjzVZA/rkNM+sRkuZFxEo93Q4rLk/xmVlP\n8dWx1eQRlJmZFZJHUGZmVkgOUGZmVkgOUGZmVkgOUGZmVkgOUGZmVkj/BzONAuqnoEgrAAAAAElF\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc965eeb0b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "visual.plot_doc_topics(doc_topic, 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('decidedly', 0.0082714017814873881),\n",
       " ('appertain', 0.0042683514741966334),\n",
       " ('invaluable', 0.0031566492745889042),\n",
       " ('cease', 0.0030601959371338106),\n",
       " ('vowed', 0.0020525735788667933),\n",
       " ('grovelling', 0.001966584166650413),\n",
       " ('vine-shaded', 0.0018564894853656821),\n",
       " ('flickered', 0.0016438404492069684),\n",
       " ('village-alive', 0.0016250602644918911),\n",
       " ('namelessly', 0.001421754146588437)]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "items = model.show_topic(1)\n",
    "keywords = [item[0] for item in items]\n",
    "keywords\n",
    "items = model.show_topic(1)\n",
    "propabilities = [item[1] for item in items]\n",
    "propabilities\n",
    "items"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from '/home/sina/.local/lib/python3.5/site-packages/matplotlib/pyplot.py'>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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Y6j1M70vfpfel7zJxfmGdXpvXn+tK9GVVJrypXGAiM5AgeWrx0fJK+JojOCMe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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc9661daf28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "topic_nr = 3\n",
    "number_of_keywords = 10\n",
    "visual.show_wordle_for_topic(model, topic_nr, number_of_keywords)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "source": [
    "![success](http://cdn2.hubspot.net/hub/128506/file-446943132-jpg/images/computer_woman_success.jpg)"
   ]
  }
 ],
 "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": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}