aspect_sa/LDA_keywords

LDA_keywords.ipynb

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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>topic</th>\n",
       "      <th>relevance_score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01 update</th>\n",
       "      <td>4</td>\n",
       "      <td>1.198091</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02 day</th>\n",
       "      <td>1</td>\n",
       "      <td>1.198399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02 update</th>\n",
       "      <td>0</td>\n",
       "      <td>1.188615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03 day</th>\n",
       "      <td>2</td>\n",
       "      <td>1.199999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04 update</th>\n",
       "      <td>4</td>\n",
       "      <td>1.199999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zyx zy</th>\n",
       "      <td>0</td>\n",
       "      <td>5.199787</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zyxel forum</th>\n",
       "      <td>3</td>\n",
       "      <td>1.199998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zz aint</th>\n",
       "      <td>3</td>\n",
       "      <td>1.199998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>zzzs rate</th>\n",
       "      <td>0</td>\n",
       "      <td>1.195343</td>\n",
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       "    <tr>\n",
       "      <th>zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzi case</th>\n",
       "      <td>2</td>\n",
       "      <td>1.199992</td>\n",
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       "<p>1358778 rows × 2 columns</p>\n",
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      "text/plain": [
       "                                      topic  relevance_score\n",
       "01 update                                 4         1.198091\n",
       "02 day                                    1         1.198399\n",
       "02 update                                 0         1.188615\n",
       "03 day                                    2         1.199999\n",
       "04 update                                 4         1.199999\n",
       "...                                     ...              ...\n",
       "zyx zy                                    0         5.199787\n",
       "zyxel forum                               3         1.199998\n",
       "zz aint                                   3         1.199998\n",
       "zzzs rate                                 0         1.195343\n",
       "zzzzzzzzzzzzzzzzzzzzzzzzzzzzzzi case      2         1.199992\n",
       "\n",
       "[1358778 rows x 2 columns]"
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   "source": [
    "# index names\n",
    "docnames = ['Doc' + str(i) for i in range(len(data))]\n",
    "\n",
    "# Make the pandas dataframe\n",
    "df_document_topic = pd.DataFrame(np.round(lda_output, 2), columns=topic_names, index=docnames)\n",
    "\n",
    "# Get dominant topic for each document\n",
    "dominant_topic = np.argmax(df_document_topic.values, axis=1)\n",
    "df_document_topic['dominant_topic'] = dominant_topic\n",
    "\n",
    "# Topic-Keyword Matrix\n",
    "df_topic_keywords = pd.DataFrame(lda_model.components_)\n",
    "\n",
    "# Assign Column and Index\n",
    "df_topic_keywords.columns = vectorizer.get_feature_names()\n",
    "df_topic_keywords.index = topicnames\n",
    "\n",
    "df_topic_no = pd.DataFrame(df_topic_keywords.idxmax())\n",
    "df_scores = pd.DataFrame(df_topic_keywords.max())\n",
    "\n",
    "tmp = pd.merge(df_topic_no, df_scores, left_index=True, right_index=True)\n",
    "tmp.columns = ['topic', 'relevance_score']\n",
    "\n",
    "display(tmp)"
   ]
  }
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