DataPreprocessing.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 241
    },
    "id": "KZpgrQt_myfH",
    "outputId": "ccbddfd9-a4d0-4447-ca77-5095f76caff1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3000"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from konlpy.tag import Okt\n",
    "import pandas as pd\n",
    "import os\n",
    "import numpy as np\n",
    "import re\n",
    "import urllib.request\n",
    "from konlpy.tag import Okt\n",
    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "\n",
    "okt = Okt()\n",
    "\n",
    "path_dir = 'data'\n",
    "\n",
    "file_list = os.listdir(path_dir)\n",
    "\n",
    "file_list=file_list[0:3000]\n",
    "len(file_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "BJQ_pRNGm8-s",
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from tqdm.notebook import tqdm\n",
    "for file_name in tqdm(file_list):\n",
    "    try:\n",
    "        df=pd.read_csv(os.path.join(path_dir,file_name),error_bad_lines=False,header=None)\n",
    "    except:\n",
    "        continue\n",
    "    df=df[[2,5]]\n",
    "    df.columns=['rate','comment']\n",
    "    \n",
    "    #한글빼고 모두 제거\n",
    "    df['comment'] = df['comment'].str.replace(\"[^ㄱ-ㅎㅏ-ㅣ가-힣 ]\",\"\")\n",
    "    #nan  제거\n",
    "    df = df.dropna(how = 'any')\n",
    "    df=df.reset_index(drop=True)\n",
    "    # 불용어\n",
    "    stopwords = ['의','가','이','은','들','는','좀','잘','걍','과','도','를','으로','자','에','와','한','하다']\n",
    "    comments=[]\n",
    "    for sentence in df['comment']:\n",
    "        tmp = okt.morphs(sentence, stem=True) # 토큰화\n",
    "        tmp = [word for word in tmp if not word in stopwords] # 불용어 제거\n",
    "        comments.append(tmp)\n",
    "    \n",
    "    y=df['rate']\n",
    "\n",
    "    #tokenizer \n",
    "\n",
    "    if (len(comments)!=y.shape[0]):\n",
    "        continue\n",
    "    # if x.shape!=y.shape:\n",
    "    #     continue\n",
    "    drop_comments = [index for index, sentence in enumerate(comments) if len(sentence) < 1]\n",
    "    x = np.delete(comments, drop_comments, axis=0)\n",
    "    y = y.drop(drop_comments, axis=0)\n",
    "  \n",
    "\n",
    "    if file_name==file_list[0]:\n",
    "        x_train=x\n",
    "        y_train=y\n",
    "    else:\n",
    "        if x.ndim!=y.ndim:\n",
    "            continue\n",
    "        x_train=np.concatenate((x_train,x),axis=0)\n",
    "        y_train=np.concatenate((y_train,y),axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "qT_jyOML02mE"
   },
   "outputs": [],
   "source": [
    "dff=pd.DataFrame()\n",
    "dff['x']=x_train\n",
    "dff['y']=y_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "FEbV8p5lR6ua"
   },
   "outputs": [],
   "source": [
    "dff.to_csv(\"data_0_3000.csv\",index=False,encoding='utf-8-sig')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 170
    },
    "id": "MGWqw5gKIOEp",
    "outputId": "b3354058-4991-4b71-f02d-b240daed3722"
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "pSC9yvJ4G9-A"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "a=pd.read_csv(\"data_0_3000.csv\")\n",
    "b=pd.read_csv(\"data_3000_6000.csv\")\n",
    "c=pd.read_csv(\"data_6000_12000.csv\")\n",
    "d=pd.read_csv(\"data_12000_14000.csv\")\n",
    "e=pd.read_csv(\"data_14000_all.csv\")\n",
    "vec=pd.concat([a,b,c,d,e])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "wj4AMF36HM1S",
    "outputId": "d9663925-4d5d-46e8-db13-9e625d3688d3"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n",
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n",
      "ERROR:root:Internal Python error in the inspect module.\n",
      "Below is the traceback from this internal error.\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3343, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-6-1bccd1c4e65e>\", line 1, in <module>\n",
      "    vec\n",
      "NameError: name 'vec' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1169, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 316, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 350, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 1490, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 1448, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\importlib\\__init__.py\", line 126, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 994, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 971, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "ModuleNotFoundError: No module named 'tensorflow_core.estimator'\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3343, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-6-1bccd1c4e65e>\", line 1, in <module>\n",
      "    vec\n",
      "NameError: name 'vec' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3263, in run_ast_nodes\n",
      "    if (await self.run_code(code, result,  async_=asy)):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3360, in run_code\n",
      "    self.showtraceback(running_compiled_code=True)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2047, in showtraceback\n",
      "    value, tb, tb_offset=tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1436, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1336, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1193, in structured_traceback\n",
      "    tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1150, in format_exception_as_a_whole\n",
      "    last_unique, recursion_repeat = find_recursion(orig_etype, evalue, records)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 451, in find_recursion\n",
      "    return len(records), 0\n",
      "TypeError: object of type 'NoneType' has no len()\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'TypeError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1169, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 316, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 350, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 1490, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 1448, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\importlib\\__init__.py\", line 126, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 994, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 971, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "ModuleNotFoundError: No module named 'tensorflow_core.estimator'\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3343, in run_code\n",
      "    exec(code_obj, self.user_global_ns, self.user_ns)\n",
      "  File \"<ipython-input-6-1bccd1c4e65e>\", line 1, in <module>\n",
      "    vec\n",
      "NameError: name 'vec' is not defined\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'NameError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3263, in run_ast_nodes\n",
      "    if (await self.run_code(code, result,  async_=asy)):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3360, in run_code\n",
      "    self.showtraceback(running_compiled_code=True)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2047, in showtraceback\n",
      "    value, tb, tb_offset=tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1436, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1336, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1193, in structured_traceback\n",
      "    tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1150, in format_exception_as_a_whole\n",
      "    last_unique, recursion_repeat = find_recursion(orig_etype, evalue, records)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 451, in find_recursion\n",
      "    return len(records), 0\n",
      "TypeError: object of type 'NoneType' has no len()\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'TypeError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2895, in _run_cell\n",
      "    return runner(coro)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\async_helpers.py\", line 68, in _pseudo_sync_runner\n",
      "    coro.send(None)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3072, in run_cell_async\n",
      "    interactivity=interactivity, compiler=compiler, result=result)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 3282, in run_ast_nodes\n",
      "    self.showtraceback()\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2047, in showtraceback\n",
      "    value, tb, tb_offset=tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1436, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1336, in structured_traceback\n",
      "    self, etype, value, tb, tb_offset, number_of_lines_of_context\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1211, in structured_traceback\n",
      "    chained_exceptions_tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1150, in format_exception_as_a_whole\n",
      "    last_unique, recursion_repeat = find_recursion(orig_etype, evalue, records)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 451, in find_recursion\n",
      "    return len(records), 0\n",
      "TypeError: object of type 'NoneType' has no len()\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\interactiveshell.py\", line 2044, in showtraceback\n",
      "    stb = value._render_traceback_()\n",
      "AttributeError: 'TypeError' object has no attribute '_render_traceback_'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 1169, in get_records\n",
      "    return _fixed_getinnerframes(etb, number_of_lines_of_context, tb_offset)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 316, in wrapped\n",
      "    return f(*args, **kwargs)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\IPython\\core\\ultratb.py\", line 350, in _fixed_getinnerframes\n",
      "    records = fix_frame_records_filenames(inspect.getinnerframes(etb, context))\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 1490, in getinnerframes\n",
      "    frameinfo = (tb.tb_frame,) + getframeinfo(tb, context)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 1448, in getframeinfo\n",
      "    filename = getsourcefile(frame) or getfile(frame)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 696, in getsourcefile\n",
      "    if getattr(getmodule(object, filename), '__loader__', None) is not None:\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\inspect.py\", line 733, in getmodule\n",
      "    if ismodule(module) and hasattr(module, '__file__'):\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\tensorflow\\__init__.py\", line 50, in __getattr__\n",
      "    module = self._load()\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\site-packages\\tensorflow\\__init__.py\", line 44, in _load\n",
      "    module = _importlib.import_module(self.__name__)\n",
      "  File \"C:\\Users\\test\\anaconda3\\envs\\youtube\\lib\\importlib\\__init__.py\", line 126, in import_module\n",
      "    return _bootstrap._gcd_import(name[level:], package, level)\n",
      "  File \"<frozen importlib._bootstrap>\", line 994, in _gcd_import\n",
      "  File \"<frozen importlib._bootstrap>\", line 971, in _find_and_load\n",
      "  File \"<frozen importlib._bootstrap>\", line 953, in _find_and_load_unlocked\n",
      "ModuleNotFoundError: No module named 'tensorflow_core.estimator'\n"
     ]
    }
   ],
   "source": [
    "vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vec.to_csv(\"data_all.csv\",index=False,encoding='utf-8-sig')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "h7ZSQItbqRsX",
    "outputId": "7b8a0201-891e-430b-8c1e-7267054faf67"
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.preprocessing.text import Tokenizer\n",
    "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
    "\n",
    "tokenizer = Tokenizer()\n",
    "tokenizer.fit_on_texts(vec['x'])\n",
    "\n",
    "threshold = 2\n",
    "total_cnt = len(tokenizer.word_index) # 단어의 수\n",
    "rare_cnt = 0 # 등장 빈도수가 threshold보다 작은 단어의 개수를 카운트\n",
    "total_freq = 0 # 훈련 데이터의 전체 단어 빈도수 총 합\n",
    "rare_freq = 0 # 등장 빈도수가 threshold보다 작은 단어의 등장 빈도수의 총 합\n",
    "\n",
    "# 단어와 빈도수의 쌍(pair)을 key와 value로 받는다.\n",
    "for key, value in tokenizer.word_counts.items():\n",
    "    total_freq = total_freq + value\n",
    "\n",
    "    # 단어의 등장 빈도수가 threshold보다 작으면\n",
    "    if(value < threshold):\n",
    "        rare_cnt = rare_cnt + 1\n",
    "        rare_freq = rare_freq + value\n",
    "\n",
    "print('단어 집합(vocabulary)의 크기 :',total_cnt)\n",
    "print('등장 빈도가 %s번 이하인 희귀 단어의 수: %s'%(threshold - 1, rare_cnt))\n",
    "print(\"단어 집합에서 희귀 단어의 비율:\", (rare_cnt / total_cnt)*100)\n",
    "print(\"전체 등장 빈도에서 희귀 단어 등장 빈도 비율:\", (rare_freq / total_freq)*100)\n",
    "vocab_size = total_cnt - rare_cnt + 1\n",
    "print(f\"vocab_size={vocab_size}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERROR! Session/line number was not unique in database. History logging moved to new session 151\n"
     ]
    }
   ],
   "source": [
    "vec=pd.read_csv(\"data_all.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>10.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>['불멸', '명작', '영화인', '을', '꿈꾸다', '사람', '라면', '반...</td>\n",
       "      <td>9.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>['년', '훨씬', '지나다', '아직도', '생각', '가슴', '벅차다']</td>\n",
       "      <td>10.0</td>\n",
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       "      <th>3</th>\n",
       "      <td>['오랜', '만', '다시', '보아', '너무', '예쁘다', '사랑스럽다', ...</td>\n",
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       "      <td>['지금', '극장', '걸리다', '있다', '건', '축약', '판', '분',...</td>\n",
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       "      <td>['기', '대안', '고', '보다', '괜찮다']</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6482539</th>\n",
       "      <td>['기네스', '팰트로으', '연기', '너무', '인상', '적다', '영화', ...</td>\n",
       "      <td>10.0</td>\n",
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       "    <tr>\n",
       "      <th>6482540</th>\n",
       "      <td>['기네스', '팰트로우', '만', '보이다', '영화', '노잼']</td>\n",
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       "    <tr>\n",
       "      <th>6482541</th>\n",
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       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>6482542</th>\n",
       "      <td>['ㅋㅋ', '멀다', '허전하다', '답답']</td>\n",
       "      <td>7.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6482543 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                         x     y\n",
       "0        ['배경음', '감동', '적', '인', '선율', '영사기', '에서', '나오...  10.0\n",
       "1        ['불멸', '명작', '영화인', '을', '꿈꾸다', '사람', '라면', '반...   9.0\n",
       "2             ['년', '훨씬', '지나다', '아직도', '생각', '가슴', '벅차다']  10.0\n",
       "3        ['오랜', '만', '다시', '보아', '너무', '예쁘다', '사랑스럽다', ...  10.0\n",
       "4        ['지금', '극장', '걸리다', '있다', '건', '축약', '판', '분',...  10.0\n",
       "...                                                    ...   ...\n",
       "6482538                      ['기', '대안', '고', '보다', '괜찮다']   8.0\n",
       "6482539  ['기네스', '팰트로으', '연기', '너무', '인상', '적다', '영화', ...  10.0\n",
       "6482540            ['기네스', '팰트로우', '만', '보이다', '영화', '노잼']   1.0\n",
       "6482541  ['찌질하다', '순수하다', '살', '남자', '아이', '성장기', '부모',...   7.0\n",
       "6482542                         ['ㅋㅋ', '멀다', '허전하다', '답답']   7.0\n",
       "\n",
       "[6482543 rows x 2 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "tokenizer = Tokenizer(oov_token=\"<OOV>\")\n",
    "tokenizer.fit_on_texts(vec['x'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[2]]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tokenizer.texts_to_sequences([\"'영화'\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'<OOV>': 1,\n",
       " \"'영화'\": 2,\n",
       " \"'보다'\": 3,\n",
       " \"'을'\": 4,\n",
       " \"'재밌다'\": 5,\n",
       " \"'좋다'\": 6,\n",
       " \"'이다'\": 7,\n",
       " \"'너무'\": 8,\n",
       " \"'있다'\": 9,\n",
       " \"'정말'\": 10,\n",
       " \"'없다'\": 11,\n",
       " \"'만'\": 12,\n",
       " \"'다'\": 13,\n",
       " \"'진짜'\": 14,\n",
       " \"'적'\": 15,\n",
       " \"'같다'\": 16,\n",
       " \"'최고'\": 17,\n",
       " \"'감동'\": 18,\n",
       " \"'않다'\": 19,\n",
       " \"'연기'\": 20,\n",
       " \"'되다'\": 21,\n",
       " \"'재미있다'\": 22,\n",
       " \"'생각'\": 23,\n",
       " \"'로'\": 24,\n",
       " \"'아니다'\": 25,\n",
       " \"'점'\": 26,\n",
       " \"'요'\": 27,\n",
       " \"'에서'\": 28,\n",
       " \"'스토리'\": 29,\n",
       " \"'나오다'\": 30,\n",
       " \"'볼'\": 31,\n",
       " \"'것'\": 32,\n",
       " \"'ㅋㅋ'\": 33,\n",
       " \"'인'\": 34,\n",
       " \"'보고'\": 35,\n",
       " \"'더'\": 36,\n",
       " \"'그'\": 37,\n",
       " \"'배우'\": 38,\n",
       " \"'안'\": 39,\n",
       " \"'내'\": 40,\n",
       " \"'자다'\": 41,\n",
       " \"'재미'\": 42,\n",
       " \"'만들다'\": 43,\n",
       " \"'사람'\": 44,\n",
       " \"'평점'\": 45,\n",
       " \"'그냥'\": 46,\n",
       " \"'나'\": 47,\n",
       " \"'말'\": 48,\n",
       " \"'가다'\": 49,\n",
       " \"'고'\": 50,\n",
       " \"'지루하다'\": 51,\n",
       " \"'게'\": 52,\n",
       " \"'못'\": 53,\n",
       " \"'시간'\": 54,\n",
       " \"'내용'\": 55,\n",
       " \"'하고'\": 56,\n",
       " \"'중'\": 57,\n",
       " \"'마지막'\": 58,\n",
       " \"'ㅠㅠ'\": 59,\n",
       " \"'수'\": 60,\n",
       " \"'까지'\": 61,\n",
       " \"'때'\": 62,\n",
       " \"'네'\": 63,\n",
       " \"'들다'\": 64,\n",
       " \"'모르다'\": 65,\n",
       " \"'왜'\": 66,\n",
       " \"'역시'\": 67,\n",
       " \"'아'\": 68,\n",
       " \"'오다'\": 69,\n",
       " \"'그렇다'\": 70,\n",
       " \"'완전'\": 71,\n",
       " \"'주다'\": 72,\n",
       " \"'많다'\": 73,\n",
       " \"'꼭'\": 74,\n",
       " \"'이렇다'\": 75,\n",
       " \"'아깝다'\": 76,\n",
       " \"'넘다'\": 77,\n",
       " \"'ㅋ'\": 78,\n",
       " \"'괜찮다'\": 79,\n",
       " \"'싶다'\": 80,\n",
       " \"'액션'\": 81,\n",
       " \"'사랑'\": 82,\n",
       " \"'감독'\": 83,\n",
       " \"'기대'\": 84,\n",
       " \"'짱'\": 85,\n",
       " \"'거'\": 86,\n",
       " \"'정도'\": 87,\n",
       " \"'아쉽다'\": 88,\n",
       " \"'많이'\": 89,\n",
       " \"'처음'\": 90,\n",
       " \"'느낌'\": 91,\n",
       " \"'재다'\": 92,\n",
       " \"'알다'\": 93,\n",
       " \"'장면'\": 94,\n",
       " \"'ㅎㅎ'\": 95,\n",
       " \"'다시'\": 96,\n",
       " \"'저'\": 97,\n",
       " \"'기'\": 98,\n",
       " \"'ㅋㅋㅋ'\": 99,\n",
       " \"'아이'\": 100,\n",
       " \"'돈'\": 101,\n",
       " \"'슬프다'\": 102,\n",
       " \"'지'\": 103,\n",
       " \"'나다'\": 104,\n",
       " \"'좋아하다'\": 105,\n",
       " \"'듯'\": 106,\n",
       " \"'느끼다'\": 107,\n",
       " \"'반전'\": 108,\n",
       " \"'또'\": 109,\n",
       " \"'추천'\": 110,\n",
       " \"'뭐'\": 111,\n",
       " \"'눈물'\": 112,\n",
       " \"'작품'\": 113,\n",
       " \"'대박'\": 114,\n",
       " \"'재미없다'\": 115,\n",
       " \"'하나'\": 116,\n",
       " \"'멋지다'\": 117,\n",
       " \"'무섭다'\": 118,\n",
       " \"'끝'\": 119,\n",
       " \"'두'\": 120,\n",
       " \"'한번'\": 121,\n",
       " \"'면'\": 122,\n",
       " \"'난'\": 123,\n",
       " \"'남다'\": 124,\n",
       " \"'하'\": 125,\n",
       " \"'보기'\": 126,\n",
       " \"'웃다'\": 127,\n",
       " \"'별로'\": 128,\n",
       " \"'이야기'\": 129,\n",
       " \"'굿'\": 130,\n",
       " \"'임'\": 131,\n",
       " \"'중간'\": 132,\n",
       " \"'뻔하다'\": 133,\n",
       " \"'없이'\": 134,\n",
       " \"'대'\": 135,\n",
       " \"'랑'\": 136,\n",
       " \"'영'\": 137,\n",
       " \"'가슴'\": 138,\n",
       " \"'이렇게'\": 139,\n",
       " \"'분'\": 140,\n",
       " \"'라'\": 141,\n",
       " \"'기대하다'\": 142,\n",
       " \"'마음'\": 143,\n",
       " \"'조금'\": 144,\n",
       " \"'이해'\": 145,\n",
       " \"'아름답다'\": 146,\n",
       " \"'차다'\": 147,\n",
       " \"'먹다'\": 148,\n",
       " \"'드라마'\": 149,\n",
       " \"'그리고'\": 150,\n",
       " \"'함'\": 151,\n",
       " \"'인생'\": 152,\n",
       " \"'결말'\": 153,\n",
       " \"'엔'\": 154,\n",
       " \"'부분'\": 155,\n",
       " \"'크다'\": 156,\n",
       " \"'서'\": 157,\n",
       " \"'전'\": 158,\n",
       " \"'하지만'\": 159,\n",
       " \"'번'\": 160,\n",
       " \"'편'\": 161,\n",
       " \"'해주다'\": 162,\n",
       " \"'주인공'\": 163,\n",
       " \"'이영화'\": 164,\n",
       " \"'지금'\": 165,\n",
       " \"'그래도'\": 166,\n",
       " \"'부터'\": 167,\n",
       " \"'안되다'\": 168,\n",
       " \"'명작'\": 169,\n",
       " \"'받다'\": 170,\n",
       " \"'연기력'\": 171,\n",
       " \"'웃기다'\": 172,\n",
       " \"'별'\": 173,\n",
       " \"'끝나다'\": 174,\n",
       " \"'때문'\": 175,\n",
       " \"'개'\": 176,\n",
       " \"'인데'\": 177,\n",
       " \"'이고'\": 178,\n",
       " \"'야하다'\": 179,\n",
       " \"'현실'\": 180,\n",
       " \"'울다'\": 181,\n",
       " \"'솔직하다'\": 182,\n",
       " \"'우리'\": 183,\n",
       " \"'에게'\": 184,\n",
       " \"'오랜'\": 185,\n",
       " \"'성'\": 186,\n",
       " \"'이상'\": 187,\n",
       " \"'이건'\": 188,\n",
       " \"'이런'\": 189,\n",
       " \"'눈'\": 190,\n",
       " \"'ㅠ'\": 191,\n",
       " \"'님'\": 192,\n",
       " \"'여'\": 193,\n",
       " \"'ㅎ'\": 194,\n",
       " \"'씨'\": 195,\n",
       " \"'여운'\": 196,\n",
       " \"'걸'\": 197,\n",
       " \"'본'\": 198,\n",
       " \"'가족'\": 199,\n",
       " \"'연출'\": 200,\n",
       " \"'라고'\": 201,\n",
       " \"'ㅜㅜ'\": 202,\n",
       " \"'이나'\": 203,\n",
       " \"'지만'\": 204,\n",
       " \"'나름'\": 205,\n",
       " \"'전개'\": 206,\n",
       " \"'제'\": 207,\n",
       " \"'근데'\": 208,\n",
       " \"'보여주다'\": 209,\n",
       " \"'년'\": 210,\n",
       " \"'한국'\": 211,\n",
       " \"'잼'\": 212,\n",
       " \"'뭔가'\": 213,\n",
       " \"'화'\": 214,\n",
       " \"'음악'\": 215,\n",
       " \"'멋있다'\": 216,\n",
       " \"'일'\": 217,\n",
       " \"'내내'\": 218,\n",
       " \"'속'\": 219,\n",
       " \"'이랑'\": 220,\n",
       " \"'긴장감'\": 221,\n",
       " \"'애'\": 222,\n",
       " \"'되어다'\": 223,\n",
       " \"'매력'\": 224,\n",
       " \"'영상'\": 225,\n",
       " \"'잇다'\": 226,\n",
       " \"'믿다'\": 227,\n",
       " \"'ㅡㅡ'\": 228,\n",
       " \"'기억'\": 229,\n",
       " \"'감'\": 230,\n",
       " \"'버리다'\": 231,\n",
       " \"'어떻다'\": 232,\n",
       " \"'늘다'\": 233,\n",
       " \"'약간'\": 234,\n",
       " \"'가장'\": 235,\n",
       " \"'라는'\": 236,\n",
       " \"'몰입'\": 237,\n",
       " \"'다른'\": 238,\n",
       " \"'소재'\": 239,\n",
       " \"'알바'\": 240,\n",
       " \"'니'\": 241,\n",
       " \"'알'\": 242,\n",
       " \"'계속'\": 243,\n",
       " \"'맞다'\": 244,\n",
       " \"'즐겁다'\": 245,\n",
       " \"'귀엽다'\": 246,\n",
       " \"'실망'\": 247,\n",
       " \"'강추'\": 248,\n",
       " \"'아주'\": 249,\n",
       " \"'스릴'\": 250,\n",
       " \"'인간'\": 251,\n",
       " \"'여자'\": 252,\n",
       " \"'말다'\": 253,\n",
       " \"'기분'\": 254,\n",
       " \"'쓰레기'\": 255,\n",
       " \"'어'\": 256,\n",
       " \"'시리즈'\": 257,\n",
       " \"'잔잔하다'\": 258,\n",
       " \"'남자'\": 259,\n",
       " \"'살다'\": 260,\n",
       " \"'이쁘다'\": 261,\n",
       " \"'노래'\": 262,\n",
       " \"'줄'\": 263,\n",
       " \"'에는'\": 264,\n",
       " \"'표현'\": 265,\n",
       " \"'웃음'\": 266,\n",
       " \"'필요없다'\": 267,\n",
       " \"'ㅋㅋㅋㅋ'\": 268,\n",
       " \"'모든'\": 269,\n",
       " \"'모두'\": 270,\n",
       " \"'같이'\": 271,\n",
       " \"'끄다'\": 272,\n",
       " \"'내다'\": 273,\n",
       " \"'자체'\": 274,\n",
       " \"'최악'\": 275,\n",
       " \"'죽다'\": 276,\n",
       " \"'대단하다'\": 277,\n",
       " \"'후회'\": 278,\n",
       " \"'야'\": 279,\n",
       " \"'연'\": 280,\n",
       " \"'함께'\": 281,\n",
       " \"'높다'\": 282,\n",
       " \"'이라'\": 283,\n",
       " \"'친구'\": 284,\n",
       " \"'영화관'\": 285,\n",
       " \"'한국영'\": 286,\n",
       " \"'엄청'\": 287,\n",
       " \"'깊다'\": 288,\n",
       " \"'캐릭터'\": 289,\n",
       " \"'뿐'\": 290,\n",
       " \"'쓰다'\": 291,\n",
       " \"'인지'\": 292,\n",
       " \"'움'\": 293,\n",
       " \"'우리나라'\": 294,\n",
       " \"'어리다'\": 295,\n",
       " \"'딱'\": 296,\n",
       " \"'개인'\": 297,\n",
       " \"'모습'\": 298,\n",
       " \"'대한'\": 299,\n",
       " \"'이네'\": 300,\n",
       " \"'보이다'\": 301,\n",
       " \"'미치다'\": 302,\n",
       " \"'아프다'\": 303,\n",
       " \"'극장'\": 304,\n",
       " \"'굳다'\": 305,\n",
       " \"'울'\": 306,\n",
       " \"'최고다'\": 307,\n",
       " \"'유치하다'\": 308,\n",
       " \"'원작'\": 309,\n",
       " \"'공감'\": 310,\n",
       " \"'지다'\": 311,\n",
       " \"'위'\": 312,\n",
       " \"'초반'\": 313,\n",
       " \"'부족하다'\": 314,\n",
       " \"'빠지다'\": 315,\n",
       " \"'느껴지다'\": 316,\n",
       " \"'용'\": 317,\n",
       " \"'코믹'\": 318,\n",
       " \"'따뜻하다'\": 319,\n",
       " \"'돼다'\": 320,\n",
       " \"'무슨'\": 321,\n",
       " \"'짜다'\": 322,\n",
       " \"'급'\": 323,\n",
       " \"'재밋'\": 324,\n",
       " \"'기다'\": 325,\n",
       " \"'신선하다'\": 326,\n",
       " \"'처럼'\": 327,\n",
       " \"'후'\": 328,\n",
       " \"'간만'\": 329,\n",
       " \"'코미디'\": 330,\n",
       " \"'진심'\": 331,\n",
       " \"'특히'\": 332,\n",
       " \"'낮다'\": 333,\n",
       " \"'감사하다'\": 334,\n",
       " \"'개봉'\": 335,\n",
       " \"'예쁘다'\": 336,\n",
       " \"'밖에'\": 337,\n",
       " \"'인가'\": 338,\n",
       " \"'빼다'\": 339,\n",
       " \"'보지'\": 340,\n",
       " \"'유쾌하다'\": 341,\n",
       " \"'제일'\": 342,\n",
       " \"'나쁘다'\": 343,\n",
       " \"'집중'\": 344,\n",
       " \"'후반'\": 345,\n",
       " \"'시키다'\": 346,\n",
       " \"'이라는'\": 347,\n",
       " \"'훌륭하다'\": 348,\n",
       " \"'적다'\": 349,\n",
       " \"'수준'\": 350,\n",
       " \"'스릴러'\": 351,\n",
       " \"'떨어지다'\": 352,\n",
       " \"'너'\": 353,\n",
       " \"'영화로'\": 354,\n",
       " \"'에요'\": 355,\n",
       " \"'생각나다'\": 356,\n",
       " \"'소름'\": 357,\n",
       " \"'잔인하다'\": 358,\n",
       " \"'이제'\": 359,\n",
       " \"'앞'\": 360,\n",
       " \"'오늘'\": 361,\n",
       " \"'기도'\": 362,\n",
       " \"'치다'\": 363,\n",
       " \"'해보다'\": 364,\n",
       " \"'시작'\": 365,\n",
       " \"'몰입도'\": 366,\n",
       " \"'제대로'\": 367,\n",
       " \"'놀라다'\": 368,\n",
       " \"'극'\": 369,\n",
       " \"'공포영화'\": 370,\n",
       " \"'전혀'\": 371,\n",
       " \"'살'\": 372,\n",
       " \"'보단'\": 373,\n",
       " \"'분들'\": 374,\n",
       " \"'에도'\": 375,\n",
       " \"'충분하다'\": 376,\n",
       " \"'건'\": 377,\n",
       " \"'잊다'\": 378,\n",
       " \"'따다'\": 379,\n",
       " \"'웃기'\": 380,\n",
       " \"'음'\": 381,\n",
       " \"'이지만'\": 382,\n",
       " \"'관객'\": 383,\n",
       " \"'영화인'\": 384,\n",
       " \"'보다는'\": 385,\n",
       " \"'사실'\": 386,\n",
       " \"'화려하다'\": 387,\n",
       " \"'시'\": 388,\n",
       " \"'인상'\": 389,\n",
       " \"'력'\": 390,\n",
       " \"'감정'\": 391,\n",
       " \"'새롭다'\": 392,\n",
       " \"'라면'\": 393,\n",
       " \"'요즘'\": 394,\n",
       " \"'공포'\": 395,\n",
       " \"'오'\": 396,\n",
       " \"'가볍다'\": 397,\n",
       " \"'이란'\": 398,\n",
       " \"'다르다'\": 399,\n",
       " \"'위해'\": 400,\n",
       " \"'어른'\": 401,\n",
       " \"'꿀잼'\": 402,\n",
       " \"'엔딩'\": 403,\n",
       " \"'반'\": 404,\n",
       " \"'봄'\": 405,\n",
       " \"'역사'\": 406,\n",
       " \"'대사'\": 407,\n",
       " \"'허다'\": 408,\n",
       " \"'냐'\": 409,\n",
       " \"'이유'\": 410,\n",
       " \"'하정우'\": 411,\n",
       " \"'아무'\": 412,\n",
       " \"'써다'\": 413,\n",
       " \"'다음'\": 414,\n",
       " \"'대해'\": 415,\n",
       " \"'아들'\": 416,\n",
       " \"'해'\": 417,\n",
       " \"'무엇'\": 418,\n",
       " \"'그렇게'\": 419,\n",
       " \"'데'\": 420,\n",
       " \"'한테'\": 421,\n",
       " \"'마다'\": 422,\n",
       " \"'시대'\": 423,\n",
       " \"'삶'\": 424,\n",
       " \"'만점'\": 425,\n",
       " \"'꽤'\": 426,\n",
       " \"'노잼'\": 427,\n",
       " \"'점수'\": 428,\n",
       " \"'대안'\": 429,\n",
       " \"'동안'\": 430,\n",
       " \"'관람'\": 431,\n",
       " \"'완벽하다'\": 432,\n",
       " \"'보고오다'\": 433,\n",
       " \"'의미'\": 434,\n",
       " \"'절대'\": 435,\n",
       " \"'작'\": 436,\n",
       " \"'애니메이션'\": 437,\n",
       " \"'건지다'\": 438,\n",
       " \"'맘'\": 439,\n",
       " \"'세'\": 440,\n",
       " \"'세상'\": 441,\n",
       " \"'아직도'\": 442,\n",
       " \"'뒤'\": 443,\n",
       " \"'그리다'\": 444,\n",
       " \"'지루함'\": 445,\n",
       " \"'욕'\": 446,\n",
       " \"'식'\": 447,\n",
       " \"'킬링타임'\": 448,\n",
       " \"'엄마'\": 449,\n",
       " \"'안타깝다'\": 450,\n",
       " \"'분위기'\": 451,\n",
       " \"'전체'\": 452,\n",
       " \"'힘들다'\": 453,\n",
       " \"'황정민'\": 454,\n",
       " \"'몇'\": 455,\n",
       " \"'남'\": 456,\n",
       " \"'그저'\": 457,\n",
       " \"'실화'\": 458,\n",
       " \"'날'\": 459,\n",
       " \"'구성'\": 460,\n",
       " \"'재'\": 461,\n",
       " \"'만큼'\": 462,\n",
       " \"'든'\": 463,\n",
       " \"'아쉬움'\": 464,\n",
       " \"'이번'\": 465,\n",
       " \"'살리다'\": 466,\n",
       " \"'비다'\": 467,\n",
       " \"'이후'\": 468,\n",
       " \"'매우'\": 469,\n",
       " \"'돋다'\": 470,\n",
       " \"'드리다'\": 471,\n",
       " \"'이지'\": 472,\n",
       " \"'탄탄하다'\": 473,\n",
       " \"'애니'\": 474,\n",
       " \"'준'\": 475,\n",
       " \"'올해'\": 476,\n",
       " \"'전쟁'\": 477,\n",
       " \"'물'\": 478,\n",
       " \"'간'\": 479,\n",
       " \"'스케일'\": 480,\n",
       " \"'신'\": 481,\n",
       " \"'행복하다'\": 482,\n",
       " \"'구'\": 483,\n",
       " \"'훨씬'\": 484,\n",
       " \"'놈'\": 485,\n",
       " \"'대한민국'\": 486,\n",
       " \"'이에요'\": 487,\n",
       " \"'그런'\": 488,\n",
       " \"'갈수록'\": 489,\n",
       " \"'스럽다'\": 490,\n",
       " \"'어렵다'\": 491,\n",
       " \"'흥미진진'\": 492,\n",
       " \"'팬'\": 493,\n",
       " \"'즐기다'\": 494,\n",
       " \"'뭔'\": 495,\n",
       " \"'그럭저럭'\": 496,\n",
       " \"'ㅜ'\": 497,\n",
       " \"'개연'\": 498,\n",
       " \"'아버지'\": 499,\n",
       " \"'이상하다'\": 500,\n",
       " \"'명'\": 501,\n",
       " \"'ㅎㅎㅎ'\": 502,\n",
       " \"'터지다'\": 503,\n",
       " \"'안보'\": 504,\n",
       " \"'상영'\": 505,\n",
       " \"'소리'\": 506,\n",
       " \"'편이'\": 507,\n",
       " \"'너무나'\": 508,\n",
       " \"'찍다'\": 509,\n",
       " \"'상미'\": 510,\n",
       " \"'이야'\": 511,\n",
       " \"'집'\": 512,\n",
       " \"'주'\": 513,\n",
       " \"'부'\": 514,\n",
       " \"'평가'\": 515,\n",
       " \"'예고편'\": 516,\n",
       " \"'일본'\": 517,\n",
       " \"'이라고'\": 518,\n",
       " \"'나가다'\": 519,\n",
       " \"'서다'\": 520,\n",
       " \"'그러나'\": 521,\n",
       " \"'찾다'\": 522,\n",
       " \"'낫다'\": 523,\n",
       " \"'멀다'\": 524,\n",
       " \"'장난'\": 525,\n",
       " \"'얼마나'\": 526,\n",
       " \"'대다'\": 527,\n",
       " \"'넘치다'\": 528,\n",
       " \"'아직'\": 529,\n",
       " \"'수작'\": 530,\n",
       " \"'시나리오'\": 531,\n",
       " \"'씬'\": 532,\n",
       " \"'어울리다'\": 533,\n",
       " \"'가지'\": 534,\n",
       " \"'만하'\": 535,\n",
       " \"'혼자'\": 536,\n",
       " \"'햇'\": 537,\n",
       " \"'장르'\": 538,\n",
       " \"'긴장'\": 539,\n",
       " \"'두다'\": 540,\n",
       " \"'놓다'\": 541,\n",
       " \"'기다리다'\": 542,\n",
       " \"'쯤'\": 543,\n",
       " \"'배우다'\": 544,\n",
       " \"'니까'\": 545,\n",
       " \"'머리'\": 546,\n",
       " \"'평론가'\": 547,\n",
       " \"'누구'\": 548,\n",
       " \"'조'\": 549,\n",
       " \"'상황'\": 550,\n",
       " \"'돋보이다'\": 551,\n",
       " \"'살짝'\": 552,\n",
       " \"'이병헌'\": 553,\n",
       " \"'추억'\": 554,\n",
       " \"'원'\": 555,\n",
       " \"'배경'\": 556,\n",
       " \"'굉장하다'\": 557,\n",
       " \"'첨'\": 558,\n",
       " \"'나라'\": 559,\n",
       " \"'강동원'\": 560,\n",
       " \"'제목'\": 561,\n",
       " \"'죽이다'\": 562,\n",
       " \"'엉'\": 563,\n",
       " \"'미국'\": 564,\n",
       " \"'부모님'\": 565,\n",
       " \"'화보'\": 566,\n",
       " \"'책'\": 567,\n",
       " \"'비'\": 568,\n",
       " \"'ㅠㅠㅠ'\": 569,\n",
       " \"'순간'\": 570,\n",
       " \"'들이다'\": 571,\n",
       " \"'엄청나다'\": 572,\n",
       " \"'얘기'\": 573,\n",
       " \"'중반'\": 574,\n",
       " \"'짱짱'\": 575,\n",
       " \"'쉬다'\": 576,\n",
       " \"'강'\": 577,\n",
       " \"'사회'\": 578,\n",
       " \"'허무하다'\": 579,\n",
       " \"'그대로'\": 580,\n",
       " \"'자신'\": 581,\n",
       " \"'보'\": 582,\n",
       " \"'그래서'\": 583,\n",
       " \"'남기다'\": 584,\n",
       " \"'예상'\": 585,\n",
       " \"'점도'\": 586,\n",
       " \"'꿈'\": 587,\n",
       " \"'감성'\": 588,\n",
       " \"'필요하다'\": 589,\n",
       " \"'좀비'\": 590,\n",
       " \"'확실하다'\": 591,\n",
       " \"'다운'\": 592,\n",
       " \"'억지'\": 593,\n",
       " \"'마무리'\": 594,\n",
       " \"'볼거리'\": 595,\n",
       " \"'비슷하다'\": 596,\n",
       " \"'상'\": 597,\n",
       " \"'흘리다'\": 598,\n",
       " \"'어색하다'\": 599,\n",
       " \"'결국'\": 600,\n",
       " \"'요소'\": 601,\n",
       " \"'전편'\": 602,\n",
       " \"'힘'\": 603,\n",
       " \"'풀다'\": 604,\n",
       " \"'설정'\": 605,\n",
       " \"'뭘'\": 606,\n",
       " \"'타다'\": 607,\n",
       " \"'갈다'\": 608,\n",
       " \"'실제'\": 609,\n",
       " \"'진부하다'\": 610,\n",
       " \"'최근'\": 611,\n",
       " \"'흥행'\": 612,\n",
       " \"'캐스팅'\": 613,\n",
       " \"'짜증나다'\": 614,\n",
       " \"'예요'\": 615,\n",
       " \"'한편'\": 616,\n",
       " \"'더욱'\": 617,\n",
       " \"'적당하다'\": 618,\n",
       " \"'답답하다'\": 619,\n",
       " \"'싫다'\": 620,\n",
       " \"'유해진'\": 621,\n",
       " \"'제발'\": 622,\n",
       " \"'언제'\": 623,\n",
       " \"'흥미롭다'\": 624,\n",
       " \"'정신'\": 625,\n",
       " \"'교훈'\": 626,\n",
       " \"'디즈니'\": 627,\n",
       " \"'대로'\": 628,\n",
       " \"'밉다'\": 629,\n",
       " \"'충격'\": 630,\n",
       " \"'오락'\": 631,\n",
       " \"'펑펑'\": 632,\n",
       " \"'잘생기다'\": 633,\n",
       " \"'보내다'\": 634,\n",
       " \"'어설프다'\": 635,\n",
       " \"'길다'\": 636,\n",
       " \"'상상력'\": 637,\n",
       " \"'한마디'\": 638,\n",
       " \"'짧다'\": 639,\n",
       " \"'이름'\": 640,\n",
       " \"'필요'\": 641,\n",
       " \"'그래픽'\": 642,\n",
       " \"'인거'\": 643,\n",
       " \"'판타지'\": 644,\n",
       " \"'굿굿'\": 645,\n",
       " \"'라서'\": 646,\n",
       " \"'빨리'\": 647,\n",
       " \"'만화'\": 648,\n",
       " \"'다소'\": 649,\n",
       " \"'차라리'\": 650,\n",
       " \"'담다'\": 651,\n",
       " \"'몇번'\": 652,\n",
       " \"'냥'\": 653,\n",
       " \"'액션영화'\": 654,\n",
       " \"'로맨스'\": 655,\n",
       " \"'들어가다'\": 656,\n",
       " \"'귀'\": 657,\n",
       " \"'현'\": 658,\n",
       " \"'온'\": 659,\n",
       " \"'타임'\": 660,\n",
       " \"'문제'\": 661,\n",
       " \"'사랑스럽다'\": 662,\n",
       " \"'비교'\": 663,\n",
       " \"'딸'\": 664,\n",
       " \"'상당하다'\": 665,\n",
       " \"'역대'\": 666,\n",
       " \"'이기다'\": 667,\n",
       " \"'일단'\": 668,\n",
       " \"'읽다'\": 669,\n",
       " \"'만나다'\": 670,\n",
       " \"'건가'\": 671,\n",
       " \"'얼굴'\": 672,\n",
       " \"'바라다'\": 673,\n",
       " \"'존재'\": 674,\n",
       " \"'누가'\": 675,\n",
       " \"'쓸다'\": 676,\n",
       " \"'시원하다'\": 677,\n",
       " \"'평'\": 678,\n",
       " \"'당시'\": 679,\n",
       " \"'진정하다'\": 680,\n",
       " \"'주연'\": 681,\n",
       " \"'인물'\": 682,\n",
       " \"'잘만'\": 683,\n",
       " \"'짐'\": 684,\n",
       " \"'실감'\": 685,\n",
       " \"'맛'\": 686,\n",
       " \"'기대다'\": 687,\n",
       " \"'국민'\": 688,\n",
       " \"'순수하다'\": 689,\n",
       " \"'상상'\": 690,\n",
       " \"'히'\": 691,\n",
       " \"'나이'\": 692,\n",
       " \"'흐르다'\": 693,\n",
       " \"'어느'\": 694,\n",
       " \"'그것'\": 695,\n",
       " \"'해도'\": 696,\n",
       " \"'달다'\": 697,\n",
       " \"'화면'\": 698,\n",
       " \"'형'\": 699,\n",
       " \"'싸우다'\": 700,\n",
       " \"'대작'\": 701,\n",
       " \"'볼때'\": 702,\n",
       " \"'슬픔'\": 703,\n",
       " \"'뛰어나다'\": 704,\n",
       " \"'떠나다'\": 705,\n",
       " \"'열'\": 706,\n",
       " \"'손'\": 707,\n",
       " \"'바로'\": 708,\n",
       " \"'박수'\": 709,\n",
       " \"'틈'\": 710,\n",
       " \"'뻔'\": 711,\n",
       " \"'만으로도'\": 712,\n",
       " \"'닿다'\": 713,\n",
       " \"'머'\": 714,\n",
       " \"'에서는'\": 715,\n",
       " \"'멋'\": 716,\n",
       " \"'여기'\": 717,\n",
       " \"'죠'\": 718,\n",
       " \"'도대체'\": 719,\n",
       " \"'봣'\": 720,\n",
       " \"'또한'\": 721,\n",
       " \"'류'\": 722,\n",
       " \"'말고'\": 723,\n",
       " \"'유아인'\": 724,\n",
       " \"'ㅡ'\": 725,\n",
       " \"'아빠'\": 726,\n",
       " \"'궁금하다'\": 727,\n",
       " \"'멜로'\": 728,\n",
       " \"'단순하다'\": 729,\n",
       " \"'다만'\": 730,\n",
       " \"'걸작'\": 731,\n",
       " \"'네이버'\": 732,\n",
       " \"'무조건'\": 733,\n",
       " \"'어디'\": 734,\n",
       " \"'무난'\": 735,\n",
       " \"'독특하다'\": 736,\n",
       " \"'실망하다'\": 737,\n",
       " \"'에선'\": 738,\n",
       " \"'불쌍하다'\": 739,\n",
       " \"'전작'\": 740,\n",
       " \"'다가'\": 741,\n",
       " \"'어이없다'\": 742,\n",
       " \"'끼리'\": 743,\n",
       " \"'사'\": 744,\n",
       " \"'둘'\": 745,\n",
       " \"'만들어지다'\": 746,\n",
       " \"'관'\": 747,\n",
       " \"'글'\": 748,\n",
       " \"'마블'\": 749,\n",
       " \"'억'\": 750,\n",
       " \"'엇'\": 751,\n",
       " \"'판'\": 752,\n",
       " \"'존나'\": 753,\n",
       " \"'바'\": 754,\n",
       " \"'뜨다'\": 755,\n",
       " \"'빠져들다'\": 756,\n",
       " \"'지루'\": 757,\n",
       " \"'쩔다'\": 758,\n",
       " \"'스타일'\": 759,\n",
       " \"'감탄'\": 760,\n",
       " \"'심장'\": 761,\n",
       " \"'사건'\": 762,\n",
       " \"'자극'\": 763,\n",
       " \"'흥미'\": 764,\n",
       " \"'만족'\": 765,\n",
       " \"'옛날'\": 766,\n",
       " \"'이하'\": 767,\n",
       " \"'막'\": 768,\n",
       " \"'초'\": 769,\n",
       " \"'그나마'\": 770,\n",
       " \"'래'\": 771,\n",
       " \"'첫'\": 772,\n",
       " \"'잡다'\": 773,\n",
       " \"'소중하다'\": 774,\n",
       " \"'가보다'\": 775,\n",
       " \"'께'\": 776,\n",
       " \"'추하다'\": 777,\n",
       " \"'만해'\": 778,\n",
       " \"'등'\": 779,\n",
       " \"'런가'\": 780,\n",
       " \"'여러'\": 781,\n",
       " \"'출연'\": 782,\n",
       " \"'선택'\": 783,\n",
       " \"'완성'\": 784,\n",
       " \"'예술'\": 785,\n",
       " \"'생기다'\": 786,\n",
       " \"'장'\": 787,\n",
       " \"'흠'\": 788,\n",
       " \"'죽'\": 789,\n",
       " \"'나르다'\": 790,\n",
       " \"'신나다'\": 791,\n",
       " \"'점주'\": 792,\n",
       " \"'훈훈하다'\": 793,\n",
       " \"'영웅'\": 794,\n",
       " \"'엿'\": 795,\n",
       " \"'심하다'\": 796,\n",
       " \"'거의'\": 797,\n",
       " \"'에서도'\": 798,\n",
       " \"'억지스럽다'\": 799,\n",
       " \"'듣다'\": 800,\n",
       " \"'터'\": 801,\n",
       " \"'당하다'\": 802,\n",
       " \"'눈물나다'\": 803,\n",
       " \"'원래'\": 804,\n",
       " \"'찡하다'\": 805,\n",
       " \"'따르다'\": 806,\n",
       " \"'여서'\": 807,\n",
       " \"'떼다'\": 808,\n",
       " \"'평범하다'\": 809,\n",
       " \"'나서다'\": 810,\n",
       " \"'진실'\": 811,\n",
       " \"'당신'\": 812,\n",
       " \"'덥다'\": 813,\n",
       " \"'맨'\": 814,\n",
       " \"'일이'\": 815,\n",
       " \"'보시'\": 816,\n",
       " \"'진'\": 817,\n",
       " \"'목소리'\": 818,\n",
       " \"'약하다'\": 819,\n",
       " \"'힘드다'\": 820,\n",
       " \"'환상'\": 821,\n",
       " \"'총'\": 822,\n",
       " \"'점점'\": 823,\n",
       " \"'당'\": 824,\n",
       " \"'나중'\": 825,\n",
       " \"'시절'\": 826,\n",
       " \"'모'\": 827,\n",
       " \"'맞추다'\": 828,\n",
       " \"'자기'\": 829,\n",
       " \"'간다'\": 830,\n",
       " \"'세계'\": 831,\n",
       " \"'그런데'\": 832,\n",
       " \"'항상'\": 833,\n",
       " \"'곳'\": 834,\n",
       " \"'이르다'\": 835,\n",
       " \"'강하다'\": 836,\n",
       " \"'재밋어'\": 837,\n",
       " \"'코'\": 838,\n",
       " \"'단'\": 839,\n",
       " \"'휴'\": 840,\n",
       " \"'망하다'\": 841,\n",
       " \"'졸다'\": 842,\n",
       " \"'시사회'\": 843,\n",
       " \"'설명'\": 844,\n",
       " \"'만이'\": 845,\n",
       " \"'전부'\": 846,\n",
       " \"'노력'\": 847,\n",
       " \"'주제'\": 848,\n",
       " \"'물론'\": 849,\n",
       " \"'소설'\": 850,\n",
       " \"'저런'\": 851,\n",
       " \"'쫌'\": 852,\n",
       " \"'취향'\": 853,\n",
       " \"'포스터'\": 854,\n",
       " \"'지나다'\": 855,\n",
       " \"'복수'\": 856,\n",
       " \"'아저씨'\": 857,\n",
       " \"'용이'\": 858,\n",
       " \"'빠르다'\": 859,\n",
       " \"'으로는'\": 860,\n",
       " \"'년대'\": 861,\n",
       " \"'에겐'\": 862,\n",
       " \"'이리'\": 863,\n",
       " \"'거리'\": 864,\n",
       " \"'란'\": 865,\n",
       " \"'습'\": 866,\n",
       " \"'연기자'\": 867,\n",
       " \"'예전'\": 868,\n",
       " \"'ㄷㄷ'\": 869,\n",
       " \"'줄거리'\": 870,\n",
       " \"'피'\": 871,\n",
       " \"'땜'\": 872,\n",
       " \"'동화'\": 873,\n",
       " \"'조연'\": 874,\n",
       " \"'러닝'\": 875,\n",
       " \"'일어나다'\": 876,\n",
       " \"'인정'\": 877,\n",
       " \"'넣다'\": 878,\n",
       " \"'깔끔하다'\": 879,\n",
       " \"'천재'\": 880,\n",
       " \"'여주'\": 881,\n",
       " \"'통쾌하다'\": 882,\n",
       " \"'지키다'\": 883,\n",
       " \"'리얼'\": 884,\n",
       " \"'재난영화'\": 885,\n",
       " \"'게임'\": 886,\n",
       " \"'그닥'\": 887,\n",
       " \"'정우성'\": 888,\n",
       " \"'쵝오'\": 889,\n",
       " \"'진지하다'\": 890,\n",
       " \"'어제'\": 891,\n",
       " \"'가능하다'\": 892,\n",
       " \"'초딩'\": 893,\n",
       " \"'편하다'\": 894,\n",
       " \"'소'\": 895,\n",
       " \"'불다'\": 896,\n",
       " \"'유머'\": 897,\n",
       " \"'역할'\": 898,\n",
       " \"'오히려'\": 899,\n",
       " \"'가치'\": 900,\n",
       " \"'키'\": 901,\n",
       " \"'새'\": 902,\n",
       " \"'쏘다'\": 903,\n",
       " \"'화가'\": 904,\n",
       " \"'화이팅'\": 905,\n",
       " \"'배'\": 906,\n",
       " \"'더빙'\": 907,\n",
       " \"'타'\": 908,\n",
       " \"'울리다'\": 909,\n",
       " \"'며'\": 910,\n",
       " \"'드'\": 911,\n",
       " \"'아무리'\": 912,\n",
       " \"'덕분'\": 913,\n",
       " \"'메세지'\": 914,\n",
       " \"'뭐라다'\": 915,\n",
       " \"'군'\": 916,\n",
       " \"'법'\": 917,\n",
       " \"'고생'\": 918,\n",
       " \"'자꾸'\": 919,\n",
       " \"'과거'\": 920,\n",
       " \"'질'\": 921,\n",
       " \"'만은'\": 922,\n",
       " \"'비추다'\": 923,\n",
       " \"'참신하다'\": 924,\n",
       " \"'선'\": 925,\n",
       " \"'감상'\": 926,\n",
       " \"'작가'\": 927,\n",
       " \"'잠'\": 928,\n",
       " \"'만족하다'\": 929,\n",
       " \"'오래'\": 930,\n",
       " \"'왠지'\": 931,\n",
       " \"'티비'\": 932,\n",
       " \"'그게'\": 933,\n",
       " \"'무겁다'\": 934,\n",
       " \"'히어로'\": 935,\n",
       " \"'갑자기'\": 936,\n",
       " \"'방금'\": 937,\n",
       " \"'감다'\": 938,\n",
       " \"'답'\": 939,\n",
       " \"'재미나'\": 940,\n",
       " \"'개그'\": 941,\n",
       " \"'크게'\": 942,\n",
       " \"'현재'\": 943,\n",
       " \"'진행'\": 944,\n",
       " \"'그녀'\": 945,\n",
       " \"'조니뎁'\": 946,\n",
       " \"'색다르다'\": 947,\n",
       " \"'적절하다'\": 948,\n",
       " \"'치고'\": 949,\n",
       " \"'희생'\": 950,\n",
       " \"'성하다'\": 951,\n",
       " \"'이라도'\": 952,\n",
       " \"'랄'\": 953,\n",
       " \"'접'\": 954,\n",
       " \"'수가'\": 955,\n",
       " \"'씩'\": 956,\n",
       " \"'입'\": 957,\n",
       " \"'젤'\": 958,\n",
       " \"'예'\": 959,\n",
       " \"'좀더'\": 960,\n",
       " \"'중요하다'\": 961,\n",
       " \"'돌아가다'\": 962,\n",
       " \"'눈빛'\": 963,\n",
       " \"'졸리다'\": 964,\n",
       " \"'라도'\": 965,\n",
       " \"'갖다'\": 966,\n",
       " \"'안다'\": 967,\n",
       " \"'ㅠㅠㅠㅠ'\": 968,\n",
       " \"'여전하다'\": 969,\n",
       " \"'만에'\": 970,\n",
       " \"'발전'\": 971,\n",
       " \"'여배우'\": 972,\n",
       " \"'속편'\": 973,\n",
       " \"'으로도'\": 974,\n",
       " \"'겁나다'\": 975,\n",
       " \"'보이'\": 976,\n",
       " \"'대체'\": 977,\n",
       " \"'만큼은'\": 978,\n",
       " \"'댓글'\": 979,\n",
       " \"'귀신'\": 980,\n",
       " \"'더럽다'\": 981,\n",
       " \"'팀'\": 982,\n",
       " \"'왕'\": 983,\n",
       " \"'뮤지컬'\": 984,\n",
       " \"'되게'\": 985,\n",
       " \"'감명'\": 986,\n",
       " \"'미래'\": 987,\n",
       " \"'무'\": 988,\n",
       " \"'전형'\": 989,\n",
       " \"'전쟁영화'\": 990,\n",
       " \"'지겹다'\": 991,\n",
       " \"'식상하다'\": 992,\n",
       " \"'로는'\": 993,\n",
       " \"'다큐'\": 994,\n",
       " \"'순'\": 995,\n",
       " \"'불편하다'\": 996,\n",
       " \"'뭉클하다'\": 997,\n",
       " \"'땐'\": 998,\n",
       " \"'흐름'\": 999,\n",
       " \"'거기'\": 1000,\n",
       " ...}"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(tokenizer.word_index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "id": "nPbvJKPdrIQf"
   },
   "outputs": [],
   "source": [
    "# tokenizer = Tokenizer(118798)\n",
    "# tokenizer.fit_on_texts(vec['x'])\n",
    "x_train = tokenizer.texts_to_sequences(vec['x'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " [21, 145, 158, 451, 1957, 7874, 4387, 8],\n",
       " [237, 43, 3830, 3, 50, 18, 3710, 59, 8, 1979],\n",
       " [241, 8313, 5645, 11427, 2384, 280, 46, 631, 305, 59, 336, 10],\n",
       " [9, 306, 8625, 151, 5265, 2683, 15, 1],\n",
       " [294, 997, 144, 52, 1327, 1920, 2],\n",
       " [39, 151, 16, 1, 1005, 1426, 59, 10, 499, 17, 3, 106],\n",
       " [275, 1975, 2, 178, 112, 6],\n",
       " [47, 266, 17, 1163, 228, 20, 15],\n",
       " [5015, 14, 587, 3, 4425, 34, 34, 581, 1953, 3979, 15, 1, 12],\n",
       " [1, 160, 151, 1167],\n",
       " [40, 208],\n",
       " [6998, 297, 3, 34, 2976, 53, 692, 442, 679, 433, 5685, 3, 59, 8],\n",
       " [967, 441, 36, 17, 2885, 102, 18, 9, 16, 2295, 1],\n",
       " [507, 145, 1],\n",
       " [1484, 16, 1, 2264, 466, 411, 31, 24],\n",
       " [2920, 751, 2, 2712, 3, 73, 2, 672, 2712, 7, 17],\n",
       " [57, 152, 359, 154, 444, 3, 3782, 345, 52],\n",
       " [96, 1060, 1, 2264, 662, 43, 8],\n",
       " [2305, 140, 6145, 72, 1, 3, 2, 68, 272, 8, 234, 16, 33, 1],\n",
       " [43176, 151, 27, 36, 280, 174, 1669, 59, 8],\n",
       " [47, 266],\n",
       " [57, 93, 3, 377, 10],\n",
       " [19339],\n",
       " [39, 151, 5192, 15, 1],\n",
       " [9, 16, 1, 354],\n",
       " [122, 7077, 337, 188, 168, 3736, 300, 232, 5],\n",
       " [1360,\n",
       "  1566,\n",
       "  545,\n",
       "  1649,\n",
       "  5192,\n",
       "  20,\n",
       "  61,\n",
       "  60,\n",
       "  39,\n",
       "  151,\n",
       "  16,\n",
       "  1,\n",
       "  200,\n",
       "  6145,\n",
       "  1,\n",
       "  17,\n",
       "  2038],\n",
       " [145, 1],\n",
       " [615, 2823, 258, 151, 3, 650, 272, 145, 28, 190],\n",
       " [106, 146, 72, 765, 1985, 645, 393, 9665, 1269, 38, 243, 154, 8, 78, 17, 348],\n",
       " [1, 38, 423, 8, 151, 8],\n",
       " [64, 65, 69, 64, 45, 242, 11733, 111, 103],\n",
       " [233, 50, 158, 3494, 561, 17, 3, 1267, 59, 8],\n",
       " [16, 1, 2264, 2026, 135, 662, 10],\n",
       " [74, 13, 2305, 200, 22],\n",
       " [296, 14, 33, 22, 4455, 1042, 514, 7085, 1896, 16, 112, 56, 115],\n",
       " [168, 517, 296, 14, 33, 852, 24],\n",
       " [74, 1, 25, 471],\n",
       " [145, 214, 255, 180, 615, 145, 553],\n",
       " [67, 9, 116, 1, 195, 441, 607, 18],\n",
       " [151, 298, 1154, 2305, 938, 915, 26],\n",
       " [142, 6896, 833, 166, 1084, 4339, 29, 17, 3, 89, 106, 161, 1],\n",
       " [1, 218, 151, 63],\n",
       " [23424, 294, 825, 1399],\n",
       " ...]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "skqo3k-CFHtJ",
    "outputId": "be3faa8c-e2f3-41fa-8771-ddf4f1d7326b"
   },
   "outputs": [],
   "source": [
    "drop_train = [index for index, sentence in enumerate(x_train) if len(sentence) < 1]\n",
    "x = np.delete(x_train, drop_train, axis=0)\n",
    "y = np.delete(np.array(vec['y']), drop_train, axis=0)\n",
    "print(len(x))\n",
    "print(len(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 314
    },
    "id": "xdZuy2jVwuAi",
    "outputId": "0865edae-06c0-4e70-92ee-5ceb501a7292"
   },
   "outputs": [],
   "source": [
    "print('리뷰의 최대 길이 :',max(len(l) for l in x))\n",
    "print('리뷰의 평균 길이 :',sum(map(len, x))/len(y))\n",
    "plt.hist([len(s) for s in x], bins=50)\n",
    "plt.xlabel('length of samples')\n",
    "plt.ylabel('number of samples')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "4BB9B3wv2301"
   },
   "outputs": [],
   "source": [
    "def below_threshold_len(max_len, nested_list):\n",
    "  cnt = 0\n",
    "  for s in nested_list:\n",
    "    if(len(s) <= max_len):\n",
    "        cnt = cnt + 1\n",
    "  print('전체 샘플 중 길이가 %s 이하인 샘플의 비율: %s'%(max_len, (cnt / len(nested_list))*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "4N8G7w4V28bF",
    "outputId": "b052c1fb-721b-4c89-cf55-853b326e0f49"
   },
   "outputs": [],
   "source": [
    "max_len = 40\n",
    "below_threshold_len(max_len,x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "RBZIBhoD29iF"
   },
   "outputs": [],
   "source": [
    "x = pad_sequences(x, maxlen = max_len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "CGwkbMEv29kg"
   },
   "outputs": [],
   "source": [
    "new_data=pd.DataFrame()\n",
    "new_data['comment']=x.tolist()\n",
    "new_data['rate']=y\n",
    "new_data.to_csv(\"data_0_all_finish.csv\",index=False,encoding='utf-8-sig')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_data['rate'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "idx=new_data[new_data['rate']==10.0].index\n",
    "idx_10=idx[:2650000]\n",
    "del_10=new_data.drop(idx_10)\n",
    "\n",
    "idx=new_data[new_data['rate']==9.0].index\n",
    "idx_10=idx[:140000]\n",
    "del_10=del_10.drop(idx_10)\n",
    "\n",
    "idx=new_data[new_data['rate']==8.0].index\n",
    "idx_10=idx[:110000]\n",
    "del_10=del_10.drop(idx_10)\n",
    "\n",
    "idx=new_data[new_data['rate']==1.0].index\n",
    "idx_10=idx[:10000]\n",
    "del_10=del_10.drop(idx_10)\n",
    "\n",
    "del_10['rate'].value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "del_10.to_csv(\"data_0_all_finish_del.csv\",index=False,encoding='utf-8-sig')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>comment</th>\n",
       "      <th>rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>6.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>5.0</td>\n",
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       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
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       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>3571030</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>8.0</td>\n",
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       "    <tr>\n",
       "      <th>3571031</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>10.0</td>\n",
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       "      <th>3571032</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>1.0</td>\n",
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       "      <th>3571033</th>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>7.0</td>\n",
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       "    <tr>\n",
       "      <th>3571034</th>\n",
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       "      <td>7.0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>3571035 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   comment  rate\n",
       "0        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   6.0\n",
       "1        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   7.0\n",
       "2        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   5.0\n",
       "3        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   5.0\n",
       "4        [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   7.0\n",
       "...                                                    ...   ...\n",
       "3571030  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   8.0\n",
       "3571031  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  10.0\n",
       "3571032  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   1.0\n",
       "3571033  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   7.0\n",
       "3571034  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   7.0\n",
       "\n",
       "[3571035 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_data=pd.read_csv(\"data_0_all_finish_del.csv\")\n",
    "new_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8sk4-p8yO5dG"
   },
   "source": [
    "3000 6000 vocab size == 118798"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "-mR3Nihgw62J",
    "outputId": "ee9cfc18-beb5-4223-cf36-04e8558c9372"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tensorflow.keras.layers import Embedding, Dense, LSTM\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.models import load_model\n",
    "from tensorflow.keras.callbacks import EarlyStopping, ModelCheckpoint\n",
    "X=pd.read_csv(\"data_0_all_finish_del.csv\")\n",
    "X['comment']=X['comment'].map(eval)\n",
    "x_train=np.array(X['comment'])\n",
    "x=[]\n",
    "for i in x_train:\n",
    "    x.append(np.asarray(i).astype('float32'))\n",
    "x=np.asarray(x)\n",
    "y=np.asarray(X['rate'])\n",
    "y=y.reshape(-1,1)\n",
    "\n",
    "x.shape,y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "VcLKHVDb-88Z"
   },
   "outputs": [],
   "source": [
    "model = Sequential()\n",
    "model.add(Embedding(118798,1000))\n",
    "model.add(LSTM(128,input_shape=(30,1)))\n",
    "model.add(Dense(1, activation='relu'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "zbzsY1GDoMrC"
   },
   "outputs": [],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "HeeCNWfk--5X"
   },
   "outputs": [],
   "source": [
    "es = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=4)\n",
    "mc = ModelCheckpoint('best_model.h5', monitor='val_loss', mode='min', verbose=1, save_best_only=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.python.client import device_lib\n",
    "\n",
    "print(device_lib.list_local_devices())\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "eFpZbIuy_Ozl"
   },
   "outputs": [],
   "source": [
    "model.compile(optimizer='Adam', loss='mse', metrics=[\"mae\"])\n",
    "history = model.fit(x, y, epochs=20, callbacks=[es, mc], batch_size=16000, validation_split=0.2,verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "nBGMSub__5fk",
    "outputId": "5d91df93-b68d-4261-c137-8c1d0300b36b"
   },
   "outputs": [],
   "source": [
    "loaded_model = load_model('best_model.h5')\n",
    "loaded_model.evaluate(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "OheoiJE-AAp_"
   },
   "outputs": [],
   "source": [
    "def sentiment_predict(new_sentence):\n",
    "    stopwords = ['의','가','이','은','들','는','좀','잘','걍','과','도','를','으로','자','에','와','한','하다']\n",
    "    new_sentence = okt.morphs(new_sentence, stem=True) # 토큰화\n",
    "    new_sentence = [word for word in new_sentence if not word in stopwords] # 불용어 제거\n",
    "    encoded = tokenizer.texts_to_sequences([new_sentence]) # 정수 인코딩 위에서 fit 해야함\n",
    "    pad_new = pad_sequences(encoded, maxlen = max_len)\n",
    "    score = float(loaded_model.predict(pad_new))\n",
    "    return score"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "전처리.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "youtube",
   "language": "python",
   "name": "youtube"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.13"
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 },
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