0503_감성분석.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 0. 데이터로딩"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['cv', 'tfidf', 'tdm_cv', 'tdm_tfidf'])\n"
     ]
    }
   ],
   "source": [
    "import joblib\n",
    "import pandas as pd\n",
    "def get_nouns(text):\n",
    "    return 1\n",
    "with open('tdm.pkl', 'rb') as f:\n",
    "    data = joblib.load(f)\n",
    "    print(data.keys())\n",
    "    locals().update(data)\n",
    "    del data\n",
    "df = pd.read_csv('review_full.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. 감성사전"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression #평점예측용 모델\n",
    "# from sklearn.linear_model import LogisticRegression #긍/부정분류"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = LinearRegression()\n",
    "model.fit(tdm_cv, df.평점)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.22413808565925408"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.score(tdm_cv, df.평점)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.12263052,  0.12787418,  0.01271373, -0.06115039,  0.04225387,\n",
       "       -0.02870932, -0.0455514 , -0.0195337 ,  0.04705164, -0.04324456])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.coef_[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>단어</th>\n",
       "      <th>계수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>!!</td>\n",
       "      <td>0.122631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>!!!</td>\n",
       "      <td>0.127874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>가게</td>\n",
       "      <td>0.012714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>가격</td>\n",
       "      <td>-0.061150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>가도</td>\n",
       "      <td>0.042254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>후식</td>\n",
       "      <td>0.043163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>후회</td>\n",
       "      <td>0.164468</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>휴가</td>\n",
       "      <td>0.146536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>휴식</td>\n",
       "      <td>0.160904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>흥미</td>\n",
       "      <td>0.060499</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      단어        계수\n",
       "0     !!  0.122631\n",
       "1    !!!  0.127874\n",
       "2     가게  0.012714\n",
       "3     가격 -0.061150\n",
       "4     가도  0.042254\n",
       "..   ...       ...\n",
       "995   후식  0.043163\n",
       "996   후회  0.164468\n",
       "997   휴가  0.146536\n",
       "998   휴식  0.160904\n",
       "999   흥미  0.060499\n",
       "\n",
       "[1000 rows x 2 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "sent_df = pd.DataFrame({'단어': cv.get_feature_names(), '계수': model.coef_})\n",
    "sent_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>단어</th>\n",
       "      <th>계수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>673</th>\n",
       "      <td>입안</td>\n",
       "      <td>0.380151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>927</th>\n",
       "      <td>하나하나</td>\n",
       "      <td>0.353758</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>785</th>\n",
       "      <td>진짜</td>\n",
       "      <td>0.343156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>551</th>\n",
       "      <td>예술</td>\n",
       "      <td>0.302380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>813</th>\n",
       "      <td>최고</td>\n",
       "      <td>0.297262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>구사</td>\n",
       "      <td>0.001282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>534</th>\n",
       "      <td>여성</td>\n",
       "      <td>0.001137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>846</th>\n",
       "      <td>코스</td>\n",
       "      <td>0.000754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>376</th>\n",
       "      <td>사이드</td>\n",
       "      <td>0.000530</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>536</th>\n",
       "      <td>여자</td>\n",
       "      <td>0.000281</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>580 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       단어        계수\n",
       "673    입안  0.380151\n",
       "927  하나하나  0.353758\n",
       "785    진짜  0.343156\n",
       "551    예술  0.302380\n",
       "813    최고  0.297262\n",
       "..    ...       ...\n",
       "85     구사  0.001282\n",
       "534    여성  0.001137\n",
       "846    코스  0.000754\n",
       "376   사이드  0.000530\n",
       "536    여자  0.000281\n",
       "\n",
       "[580 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pos_df = sent_df[sent_df['계수']>0].sort_values(by='계수', ascending=False)\n",
    "pos_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>단어</th>\n",
       "      <th>계수</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>817</th>\n",
       "      <td>최악</td>\n",
       "      <td>-1.560181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>무례</td>\n",
       "      <td>-1.305833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>282</th>\n",
       "      <td>무시</td>\n",
       "      <td>-0.783516</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>596</th>\n",
       "      <td>위생</td>\n",
       "      <td>-0.692878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>863</th>\n",
       "      <td>태도</td>\n",
       "      <td>-0.691100</td>\n",
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       "    <tr>\n",
       "      <th>844</th>\n",
       "      <td>케익</td>\n",
       "      <td>-0.000758</td>\n",
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       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>약간</td>\n",
       "      <td>-0.000518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>뉴욕</td>\n",
       "      <td>-0.000298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>264</th>\n",
       "      <td>메뉴</td>\n",
       "      <td>-0.000263</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>420 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "     단어        계수\n",
       "817  최악 -1.560181\n",
       "280  무례 -1.305833\n",
       "282  무시 -0.783516\n",
       "596  위생 -0.692878\n",
       "863  태도 -0.691100\n",
       "..   ..       ...\n",
       "834  카페 -0.000820\n",
       "844  케익 -0.000758\n",
       "512  약간 -0.000518\n",
       "145  뉴욕 -0.000298\n",
       "264  메뉴 -0.000263\n",
       "\n",
       "[420 rows x 2 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "neg_df = sent_df[sent_df['계수']<0].sort_values(by='계수')\n",
    "neg_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. 감성분석"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>계수</th>\n",
       "      <th>극성</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>단어</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>!!</th>\n",
       "      <td>0.122631</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>!!!</th>\n",
       "      <td>0.127874</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>가게</th>\n",
       "      <td>0.012714</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>가격</th>\n",
       "      <td>-0.061150</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>가도</th>\n",
       "      <td>0.042254</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>후식</th>\n",
       "      <td>0.043163</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>후회</th>\n",
       "      <td>0.164468</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>휴가</th>\n",
       "      <td>0.146536</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>휴식</th>\n",
       "      <td>0.160904</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>흥미</th>\n",
       "      <td>0.060499</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 2 columns</p>\n",
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      ],
      "text/plain": [
       "           계수   극성\n",
       "단어                \n",
       "!!   0.122631  1.0\n",
       "!!!  0.127874  1.0\n",
       "가게   0.012714  1.0\n",
       "가격  -0.061150 -1.0\n",
       "가도   0.042254  1.0\n",
       "..        ...  ...\n",
       "후식   0.043163  1.0\n",
       "후회   0.164468  1.0\n",
       "휴가   0.146536  1.0\n",
       "휴식   0.160904  1.0\n",
       "흥미   0.060499  1.0\n",
       "\n",
       "[1000 rows x 2 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "sent_df['극성'] = np.sign(sent_df['계수'])\n",
    "sent_df.set_index('단어', inplace=True)\n",
    "sent_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence = '음식 최악 서비스 안좋음'\n",
    "words = sentence.split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['음식', '최악', '서비스', '안좋음']"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.5074878825622927"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent_df.reindex(words).계수.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sent_df.reindex(words).극성.sum()"
   ]
  }
 ],
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