数据预处理.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "plt.style.use('seaborn')\n",
    "sns.set(font_scale=2)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = pd.read_csv('data/train.csv')\n",
    "test_df  = pd.read_csv('data/nlp_test.csv')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 观察训练和测试数据的前几行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>category_A</th>\n",
       "      <th>category_B</th>\n",
       "      <th>category_C</th>\n",
       "      <th>category_D</th>\n",
       "      <th>category_E</th>\n",
       "      <th>category_F</th>\n",
       "      <th>Question Sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>QC0000000001</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>病情描述：病人是典型的“三高”，想吃拜阿司匹林做为预防用药，但是出现过敏症状。曾经治疗情况和...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QC0000000002</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>病情描述：我父亲78岁,小脑梗塞，表现左眼双视，经住院输液治疗现在恢复一月余，现在看人不重影...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>QC0000000003</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>病情描述：医生您好！我想问一下，我妈脑梗塞今天住院十一天了，情况好转，可以下床活动和清楚表达...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>QC0000000004</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>停药反跳的血压是身体真实状况吗?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>QC0000000005</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>病情描述：医生：银杏叶片生产厂很多，价格差别很大，应怎样选择？曾经治疗情况和效果：头部紧束感...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             ID  category_A  category_B  category_C  category_D  category_E  \\\n",
       "0  QC0000000001           0           1           0           0           0   \n",
       "1  QC0000000002           0           1           0           0           0   \n",
       "2  QC0000000003           0           1           0           0           0   \n",
       "3  QC0000000004           1           0           0           0           0   \n",
       "4  QC0000000005           0           1           0           0           0   \n",
       "\n",
       "   category_F                                  Question Sentence  \n",
       "0           0  病情描述：病人是典型的“三高”，想吃拜阿司匹林做为预防用药，但是出现过敏症状。曾经治疗情况和...  \n",
       "1           0  病情描述：我父亲78岁,小脑梗塞，表现左眼双视，经住院输液治疗现在恢复一月余，现在看人不重影...  \n",
       "2           0  病情描述：医生您好！我想问一下，我妈脑梗塞今天住院十一天了，情况好转，可以下床活动和清楚表达...  \n",
       "3           0                                   停药反跳的血压是身体真实状况吗?  \n",
       "4           0  病情描述：医生：银杏叶片生产厂很多，价格差别很大，应怎样选择？曾经治疗情况和效果：头部紧束感...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>Question Sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>QCT1000000001</td>\n",
       "      <td>乙肝抗体多久打一次乙肝抗体多久打一次，戊型肝炎的传播途径是怎样的，伴侣中有一个是乙肝携带，不...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QCT1000000002</td>\n",
       "      <td>十日观察法我没被狗咬伤，我想问问，狂犬病不是有十日观察法吗，那如果说狗咬人时狗得了狂犬病，可...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>QCT1000000003</td>\n",
       "      <td>我的乙肝大三阳十年了，现在能治的好了吗沈阳肝病携带者能治好，我的乙肝大三阳十年了，现在能治的...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>QCT1000000004</td>\n",
       "      <td>治疗丙肝哪里治疗最好丙肝的预防与治疗，治疗丙肝哪里治疗最好，丙肝表现症状是什么呢？丙肝有哪些...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>QCT1000000005</td>\n",
       "      <td>婚检乙肝上千倍婚检乙肝上千倍，我父亲肝硬化失代偿期，有单个结节癌变。有乙肝病史已经射频手术，...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ID                                  Question Sentence\n",
       "0  QCT1000000001  乙肝抗体多久打一次乙肝抗体多久打一次，戊型肝炎的传播途径是怎样的，伴侣中有一个是乙肝携带，不...\n",
       "1  QCT1000000002  十日观察法我没被狗咬伤，我想问问，狂犬病不是有十日观察法吗，那如果说狗咬人时狗得了狂犬病，可...\n",
       "2  QCT1000000003  我的乙肝大三阳十年了，现在能治的好了吗沈阳肝病携带者能治好，我的乙肝大三阳十年了，现在能治的...\n",
       "3  QCT1000000004  治疗丙肝哪里治疗最好丙肝的预防与治疗，治疗丙肝哪里治疗最好，丙肝表现症状是什么呢？丙肝有哪些...\n",
       "4  QCT1000000005  婚检乙肝上千倍婚检乙肝上千倍，我父亲肝硬化失代偿期，有单个结节癌变。有乙肝病史已经射频手术，..."
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.head(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 我们能看到数据的字段包含微博id，微博发布时间，微博中文内容，微博图片，微博视频 和情感倾向(标签)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((5000, 8), (3000, 2))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_df.shape, test_df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.concat([train_df,test_df],sort=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 多标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'category_A')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df['category_A'].value_counts().plot.bar()\n",
    "plt.title('category_A')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'category_B')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df['category_B'].value_counts().plot.bar()\n",
    "plt.title('category_B')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'category_C')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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1+fn5Dg+NclXXrl2vtYsijZ4GM4qIiIghjVEQERERQ7r1YODcuVJqanSxpSny9/clP9/44UIicmPo317T5e7uhp9f7Q9bU1AwUFNjVVBowvR3J9Iw9G/v5qNbDyIiImJIQUFEREQMKSiIiIiIIZfHKPzrX/9i2rRphvunTJnCs88+a/9zbm4u8+bNY8+ePRQWFtKlSxfGjRtHbGxsrc+SLy4uZuHChaSnp3Py5EnatWvH8OHDeeqpp/D19XWqr66uJjk5maSkJI4fP463tzcRERFMnTrV6cExIiIiUj8uB4WvvvoKgP/6r/+ibdu2Tvt/9rOf2b8/cuQIjz76KCUlJfTt25c77riDzMxMZs6cyf79+3njjTcc2paUlPDYY49hsVgICgpiyJAhHDp0iPfff59t27aRlJRkf9a9zUsvvURqaip+fn4MGjSIkydPsmbNGjZv3syyZcsIDQ29qjdCREREnLkcFA4fPgzAa6+9VusSqDZWq5W4uDhKSkqYM2cOUVFRwKVHr06cOJG0tDSGDRvGiBEj7G0SExOxWCxER0eTkJCAu7s7VVVVvPjii6xatYrExERefvlle/369etJTU2lV69e/POf/7SHiKSkJOLj45k+fTqrVq3Sg19ERESukctjFI4cOUK7du2uGBIAMjIysFgshIeH20MCQNu2bYmPjwdgyZIl9u3FxcUkJyfj6+vLtGnT7LclPD09iY+Pp3Xr1qSkpFBWVmZvs3jxYgCmT5/ucKUhJiaGu+++G4vFQmZmpqunJiIiIgZcCgonTpyguLiYXr161Vlre4Ts0KFDnfaFhYXh7+/Pnj17KCm5tCjH7t27KS8vJyIiwmksgo+PDwMHDqS8vJzdu3cDl4LF/v37adOmDf369XM6hu24W7dudeXURERE5ApcCgq28Qn+/v7MnDmTYcOGcccddzBixAj++te/UlFRYa/NysoCwGw21/paQUFB1NTUkJ2d7VAfEhJSa3337t0BsFgswKXHxlqtVoKDg2sdFGmrP3r0qCunJiIiIlfgUlCwjU9ITU0lLS2NHj160KdPH/Ly8pg7dy4TJkygvLwcwP4Y2YCAgFpfy7b97NmzAJw5c8al+vz8fJfqAwMDHepFRESk/q7qisLIkSPZvHkzf//731m6dCmffvopt912G/v27SMxMRGACxcuAODt7V3ra9m228Yc2L62aNHiutR7eXk51ImIiEj9uTTrYe7cuZw4cYIuXbrQvHlz+/Zbb72VP//5z/zqV79ixYoVPPfcc/bbAUYzDmxPtbZ9vdH19eXv77x2w82i8mI1zZt5NHQ3bqiAgJZ1FzVRP4W/P2m6buZ/ez9VLgUFLy8vevToUeu+n/3sZ7Rv356TJ09y7NgxTCYTgP1WxOVs4xlsda7W264g1FVfWVnpUF9f+fklN+3DTQICWjL6uVUN3Q2pp7Q3ozhz5nxDd0PESUBAS/1sNlHu7m6GH5CvyxLO7dq1Ay7ddrCNEbCNQbjc5WMMrnd9XWMkRERExHV1BoWSkhJefvllpk6dSlVVVa013377LQC33HKLffaCbTbDD1mtVnJycvDw8CA4OBjgivWAfXZEz549AejRowfu7u727ZfLyckBjGddiIiIiOvqDAo+Pj5s2LCBdevW2dcy+KGtW7dy7tw5zGYzt9xyC4MHDwZg48aNTrV79+6loKCAsLAw+5oJ/fv3x9vbmx07djgNQCwtLWXHjh2YTCbCwsIA7N/n5+ezd+9ep2Okp6cDEBkZWdepiYiISB3qDApubm5ER0cDMHPmTPLy8uz7vvnmGxISEgB48sknAQgPDyckJISMjAxWrlxpry0oKLDXTpo0yb7dZDIxZswYioqKSEhIsF+1qKqqYsaMGRQXFzNu3DiHxZhiY2MBSEhIoKCgwL59xYoVbN++nV69ejFgwICrfCtERETkcm5WF6YHlJeX8+tf/5o9e/Y4fLrPzMyksrKSSZMmMX36dHv9gQMHmDBhAmVlZfTp04fAwEB27dpFUVER0dHRzJw50+H1CwsLiYmJITc3l86dOxMaGsrhw4c5ceIEoaGhLF26FB8fH4c2zzzzDGvXrqV169aEh4eTl5fHgQMHaNWqFcuXLzdcwMlVGswojZUGM0pjpcGMTdeVBjO6FBTg0myCDz74gLS0NI4dO0bz5s0JDQ1l/PjxDB8+3Kk+KyuLuXPn2sNE165diYmJYezYsXh4OE/tKiwsZP78+aSnp5Ofn0+HDh0YNmwYU6ZMcXpyJFy64rB06VJSUlI4fvw4fn5+9OvXj6lTp9KtWzdXTumKFBSksVJQkMZKQaHpui5B4adGQUEaKwUFaawUFJquGz49UkRERG5OCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgY8qxPo8LCQu6//37OnDmDxWJx2p+bm8u8efPYs2cPhYWFdOnShXHjxhEbG4u7u3M2KS4uZuHChaSnp3Py5EnatWvH8OHDeeqpp/D19XWqr66uJjk5maSkJI4fP463tzcRERFMnTqVoKCg+pySiIiI1KJeVxQSEhI4c+ZMrfuOHDnCww8/zOrVq+nYsSODBw/m1KlTzJw5k7i4OKf6kpISHnvsMRYtWoSbmxtDhgzBzc2N999/n3HjxnH+/HmnNi+99BLx8fGcOnWKQYMG0alTJ9asWcODDz7I4cOH63NKIiIiUourDgqffvopa9asqXWf1WolLi6OkpIS5syZw0cffcT8+fNZt24dPXv2JC0tjXXr1jm0SUxMxGKxEB0dzZo1a5g7dy7r1q0jKiqKrKwsEhMTHerXr19PamoqvXr1YsOGDcybN4+UlBQSEhIoKytj+vTpWK3Wqz0tERERqcVVBYW8vDxmzpzJXXfdhYeHh9P+jIwMLBYL4eHhREVF2be3bduW+Ph4AJYsWWLfXlxcTHJyMr6+vkybNs1+W8LT05P4+Hhat25NSkoKZWVl9jaLFy8GYPr06bRs2dK+PSYmhrvvvhuLxUJmZubVnJaIiIgYuKqg8D//8z9UVFTw+uuv17p/27ZtAAwdOtRpX1hYGP7+/uzZs4eSkhIAdu/eTXl5OREREU5jEXx8fBg4cCDl5eXs3r0buBQs9u/fT5s2bejXr5/TMWzH3bp169WcloiIiBhwOSgsX76cbdu28fzzz9O1a9daa7KysgAwm8217g8KCqKmpobs7GyH+pCQkFrru3fvDmAfMJmdnY3VaiU4OLjWQZG2+qNHj7p6WiIiInIFLgWFb775hr/85S9ERETw6KOPGtadPn0agICAgFr327afPXsWwD4gsq76/Px8l+oDAwMd6kVEROTa1BkUqquriYuLw83Njddeew03NzfD2gsXLgDg7e1d637bdtuYA9vXFi1aXJd6Ly8vhzoRERG5NnWuo7Bo0SL27dvHrFmz6Nix4xVrbbcDjMKEbTaC7euNrr8W/v7O6zeINBYBAS3rLhJpAPrZvPlcMSgcOXKEefPmERkZydixY+t8MZPJBEB5eXmt+ysqKhzqXK23XUGoq76ystKh/lrk55dQU3NzTrPUP+Sm78wZ5/VFRBpaQEBL/Ww2Ue7uboYfkK8YFN5++20uXrxIVVUVzz//vMO+mpoaAPv2F198kcDAQL766ivOnj1LcHCw0+tdPsbANqbANmbhWuvrGiMhIiIiV+eKQcF2rz8jI8OwJi0tDYBnnnmGkJAQtmzZQlZWFgMGDHCos1qt5OTk4OHhYQ8RttkOttkPl7PNjujZsycAPXr0wN3d3b79cjk5OYDxrAsRERG5OlcczLhkyRIsFkut/9kWXLL9+dZbb2Xw4MEAbNy40em19u7dS0FBAWFhYfY1E/r374+3tzc7duxwGoBYWlrKjh07MJlMhIWFAdi/z8/PZ+/evU7HSE9PByAyMvJq3wcRERGpxXV9emR4eDghISFkZGSwcuVK+/aCggISEhIAmDRpkn27yWRizJgxFBUVkZCQQFVVFQBVVVXMmDGD4uJixo0b57AYU2xsLHDpeRMFBQX27StWrGD79u306tXL6WqGiIiI1I+btZ5TBEJDQ6murnZ6euSBAweYMGECZWVl9OnTh8DAQHbt2kVRURHR0dHMnDnTob6wsJCYmBhyc3Pp3LkzoaGhHD58mBMnThAaGsrSpUvx8fFxaPPMM8+wdu1aWrduTXh4OHl5eRw4cIBWrVqxfPlywwWcrsbNPphx9HOrGrobUk9pb0ZpwJg0ShrM2HRdaTDjdb2iANC7d2+Sk5MZMWIEx48fJyMjg44dO5KQkMArr7ziVN+mTRuSkpIYP348VVVVbNq0CXd3dyZPnsyHH37oFBIA3njjDV544QUCAwPZsmULeXl5jBo1iuTk5OsSEkREROSSel9RuNnpioI0VrqiII2Vrig0XT/qFQURERG5eSgoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYsjT1cLq6mqWLVtGSkoKubm5tGjRgttvv53HH3+cIUOGONXn5uYyb9489uzZQ2FhIV26dGHcuHHExsbi7u6cT4qLi1m4cCHp6emcPHmSdu3aMXz4cJ566il8fX1r7U9ycjJJSUkcP34cb29vIiIimDp1KkFBQVf3LoiIiEit3KxWq9WVwri4OFatWoWvry9hYWFcvHiR3bt3c/HiRaZOncrvf/97e+2RI0d49NFHKSkpoW/fvvj7+5OZmUlxcTGjR4/mjTfecHjtkpISYmNjsVgsBAUFYTabOXToEN9++y09evQgKSmJli1bOrR54YUXSE1Nxc/Pj/79+3Py5EkOHjyIyWRi2bJlhIaGXtMbk59fQk2NS29NkxMQ0JLRz61q6G5IPaW9GcWZM+cbuhsiTgICWupns4lyd3fD39/5Qzm4eEVhzZo1rFq1iqCgIJYuXUq7du0A+Prrr3nkkUeYP38+o0aNolu3blitVuLi4igpKWHOnDlERUUBUFBQwMSJE0lLS2PYsGGMGDHC/vqJiYlYLBaio6NJSEjA3d2dqqoqXnzxRVatWkViYiIvv/yyvX79+vWkpqbSq1cv/vnPf9pDRFJSEvHx8UyfPp1Vq1bh5uZWv3dMREREABfHKHzyyScAPP/88/aQABASEsLo0aOpqakhIyMDgIyMDCwWC+Hh4faQANC2bVvi4+MBWLJkiX17cXExycnJ+Pr6Mm3aNPttCU9PT+Lj42ndujUpKSmUlZXZ2yxevBiA6dOnO1xpiImJ4e6778ZisZCZmXl174SIiIg4cSkozJ07l7S0NO655x6nfaWlpQB4eHgAsG3bNgCGDh3qVBsWFoa/vz979uyhpKQEgN27d1NeXk5ERITTWAQfHx8GDhxIeXk5u3fvBi4Fi/3799OmTRv69evndAzbcbdu3erKqYmIiMgVuBQUmjdvjtlspnnz5g7bN23axGeffYbJZLL/gs7KygLAbDbX+lpBQUHU1NSQnZ3tUB8SElJrfffu3QGwWCwAZGdnY7VaCQ4OrnVQpK3+6NGjrpyaiIiIXIHLsx5sysvLiYuLIysri+zsbDp27MicOXPstyROnz4NQEBAQK3tbdvPnj0LwJkzZ1yqz8/Pd6k+MDDQoV5ERETq76rXUfj+++9Zt26d/YoA/N+nfYALFy4A4O3tXWt723bbmAPb1xYtWlyXei8vL4c6ERERqb+rvqLQvn17du7cibu7O9u3b+fVV19l5syZlJWV8cQTT9hvBxjNOLDNxrR9vdH19WU0TUSkMQgIaFl3kUgD0M/mzeeqg4LJZMJkMgEwcuRIOnToQExMDAsXLmTChAn2feXl5bW2r6iosL/OD7/WVW+7glBXfWVlpUN9fd3s6yhI06a56tIYaR2FputK6yhc8xLOd955J126dKGkpIQTJ07YxwjYxiBc7vIxBte7vq4xEiIiIuK6OoOC1Wplzpw5PPvss1RVVdVaY5sNUVVVZZ+9YJvNcPlr5eTk4OHhQXBwMMAV6wH7WIiePXsC0KNHD9zd3R3GSPxQTk4OYDzrQkRERFxXZ1Bwc3Nj48aNrFmzxr6o0g+dOHGC3NxcTCYTQUFBDB48GICNGzc61e7du5eCggLCwsLsayb0798fb29vduzY4TQAsbS0lB07dmAymQgLCwOwf5+fn8/evXudjpGeng5AZGRkXacmIiIidXDp1kN0dDQAs2bN4tSpU/bteXl5/PGPf6SqqorY2Fi8vLwIDw8nJCSEjIwMVq5caa8tKCggISEBgEmTJtm3m0wmxowZQ1FREQkJCfarFlVVVcyYMYPi4mLGjRvnsBhTbGwsAAkJCRQUFNi3r1ixgu3bt9OrVy8GDBhw1W+GiIiIOHLpoVAXL17k97//PVu2bMFkMtG3b1+qq6v58ssvKSsrIzIykvnz59tvQRw4cIAJEyZQVlZGnz59CAwMZNeuXRQVFREdHc3MmTMdXr+wsJCYmBhyc3Pp3LkzoaGhHD58mBMnThAaGsrSpUvx8fFxaPPMM8+wdu1aWrduTXh4OHl5eRw4cIBWrVqxfPlywwWcXHWzD2bUQ6GaLj0UShorDWZsuq40mNHlp0dWV1ezfPlyUlNTyc7Oxt3dHbPZzIMPPkh0dLTTKolZWVnMnTuXzMxMKisr6dq1KzExMYwdO9a+3PMPFRYWMn/+fNLT08nPz6dDhw4MGzaMKVOmOD05Ei5dcVi6dCkpKSkcP34cPz8/+vXrx9SpU+nWrZsrp3RFCgrSWCkoSGOloNB0XZeg8FOjoCCNlYKCNFYKCk3XDZ0eKSIiIjcvBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMebpaWF1dzUcffcTHH39MTk4O1dXVdO7cmfvuu4/Jkyfj5eXlUJ+bm8u8efPYs2cPhYWFdOnShXHjxhEbG4u7u3M+KS4uZuHChaSnp3Py5EnatWvH8OHDeeqpp/D19a21P8nJySQlJXH8+HG8vb2JiIhg6tSpBAUF1eOtEBERkcu5Wa1Wa11F1dXV/O53v2Pz5s2YTCb69OmDp6cnX375JcXFxfTp04d//vOftGjRAoAjR47w6KOPUlJSQt++ffH39yczM5Pi4mJGjx7NG2+84fD6JSUlxMbGYrFYCAoKwmw2c+jQIb799lt69OhBUlISLVu2dGjzwgsvkJqaip+fH/379+fkyZMcPHgQk8nEsmXLCA0NvaY3Jj+/hJqaOt+aJikgoCWjn1vV0N2Qekp7M4ozZ843dDdEnAQEtNTPZhPl7u6Gv7/zh3Jw8dZDcnIymzdvpmfPnnz22Wd88MEHLFq0iHXr1nHXXXfx5Zdf8re//Q0Aq9VKXFwcJSUlzJkzh48++oj58+ezbt06evbsSVpaGuvWrXN4/cTERCwWC9HR0axZs4a5c+eybt06oqKiyMrKIjEx0aF+/fr1pKam0qtXLzZs2MC8efNISUkhISGBsrIypk+fjgv5R0REROrgUlD4+OOPAXjxxRe55ZZb7Nvbtm3LK6+8AsDq1asByMjIwGKxEB4eTlRUlENtfHw8AEuWLLFvLy4uJjk5GV9fX6ZNm2a/LeHp6Ul8fDytW7cmJSWFsrIye5vFixcDMH36dIcrDTExMdx9991YLBYyMzNdfxdERESkVi4FBT8/P7p3707v3r2d9nXr1g2A06dPA7Bt2zYAhg4d6lQbFhaGv78/e/bsoaSkBIDdu3dTXl5ORESE01gEHx8fBg4cSHl5Obt37wYuBYv9+/fTpk0b+vXr53QM23G3bt3qyqmJiIjIFbgUFBYsWMDatWsxmUxO+w4ePAhA+/btAcjKygLAbDbX+lpBQUHU1NSQnZ3tUB8SElJrfffu3QGwWCwAZGdnY7VaCQ4OrnVQpK3+6NGjrpyaiIiIXME1TY+0Wq3MnTsXgOHDhwP/d2UhICCg1ja27WfPngXgzJkzLtXn5+e7VB8YGOhQLyIiIvV3TUHhrbfeYteuXbRr147JkycDcOHCBQC8vb1rbWPbbhtzYPtqmzFxrfW2aZo/HNMgIiIi9ePyOgqXe+edd/jHP/5B8+bNSUxMpG3btgD22wFubm61trPNRrB9vdH19WU0TUSkMQgIaFl3kUgD0M/mzeeqg0JVVRUzZsxgxYoVeHl5MW/ePPr372/fbxvHUF5eXmv7iooKhzpX621XEOqqr6ysdKivr5t9HQVp2jRXXRojraPQdF3zOgo2paWlTJkyhRUrVtCqVSvee+89IiMjHWpsYwRsYxAud/kYg+tdX9cYCREREXGdy0GhqKiI8ePHs23bNjp06MCyZcscriTY2GYv2GYz/JDVaiUnJwcPDw+Cg4PrrAfssyN69uwJQI8ePXB3d7dvv1xOTg5gPOtCREREXOdSUKisrOSJJ57g0KFD9iWVjX4RDx48GICNGzc67du7dy8FBQWEhYXZ10zo378/3t7e7Nixw2kAYmlpKTt27MBkMhEWFgZg/z4/P5+9e/c6HSM9PR3A6UqHiIiIXD2XgsLcuXPZv38/HTp0YMmSJfY1E2oTHh5OSEgIGRkZrFy50r69oKCAhIQEACZNmmTfbjKZGDNmDEVFRSQkJFBVVQX831iI4uJixo0b57AYU2xsLAAJCQkUFBTYt69YsYLt27fTq1cvBgwY4MqpiYiIyBXU+VCowsJCIiMjKS8vp1evXvYFjWpje9jTgQMHmDBhAmVlZfTp04fAwEB27dpFUVER0dHRzJw50+kYMTEx5Obm0rlzZ0JDQzl8+DAnTpwgNDSUpUuX4uPj49DmmWeeYe3atbRu3Zrw8HDy8vI4cOAArVq1Yvny5YYLOLnqZh/MqIdCNV16KJQ0VhrM2HRdaTBjnUFh69at/Pa3v3XpQLbVE+HSmIO5c+eSmZlJZWUlXbt2JSYmhrFjx+Lh4eHUtrCwkPnz55Oenk5+fj4dOnRg2LBhTJkyxenJkXDpisPSpUtJSUnh+PHj+Pn50a9fP6ZOnWpfVvpaKChIY6WgII2VgkLTdU1B4adKQUEaKwUFaawUFJqu6zY9UkRERH5aFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExVO+gkJqaSs+ePfn3v/9d6/7c3Fz++Mc/EhkZSZ8+fRg9ejRLly6lpqam1vri4mL+8pe/MGLECHr37s0vfvEL/vznP1NSUlJrfXV1NUlJSYwZM4a77rqLgQMH8uyzz5Kbm1vfUxIREZHL1Cso7Nu3j5kzZxruP3LkCA8//DCrV6+mY8eODB48mFOnTjFz5kzi4uKc6ktKSnjsscdYtGgRbm5uDBkyBDc3N95//33GjRvH+fPnndq89NJLxMfHc+rUKQYNGkSnTp1Ys2YNDz74IIcPH67PaYmIiMhlrjoorF+/nt/85jeUlZXVut9qtRIXF0dJSQlz5szho48+Yv78+axbt46ePXuSlpbGunXrHNokJiZisViIjo5mzZo1zJ07l3Xr1hEVFUVWVhaJiYlOfUhNTaVXr15s2LCBefPmkZKSQkJCAmVlZUyfPh2r1Xq1pyYiIiKXcTkonDp1iri4OJ5++mlqampo165drXUZGRlYLBbCw8OJioqyb2/bti3x8fEALFmyxL69uLiY5ORkfH19mTZtGu7ul7rk6elJfHw8rVu3JiUlxSGYLF68GIDp06fTsmVL+/aYmBjuvvtuLBYLmZmZrp6aiIiIGHA5KCQmJrJq1Spuv/12VqxYQffu3Wut27ZtGwBDhw512hcWFoa/vz979uyxjz3YvXs35eXlRERE4Ovr61Dv4+PDwIEDKS8vZ/fu3cClYLF//37atGlDv379nI5hO+7WrVtdPTUREREx4HJQ6N69O6+//jrJycn07NnTsC4rKwsAs9lc6/6goCBqamrIzs52qA8JCTE8LoDFYgEgOzsbq9VKcHCw/epDbfVHjx515bRERETkCjxdLXziiSdcqjt9+jQAAQEBte63bT979iwAZ86ccak+Pz/fpfrAwECHehEREam/676OwoULFwDw9vaudb9tu23Mge1rixYtrku9l5eXQ52IiIjUn8tXFFxlux3g5uZW637bbATb1xtdX1/+/r51F4k0kICAlnUXiTQA/WzefK57UDCZTACUl5fXur+iosKhztV62xWEuuorKysd6usrP7+Empqbc4ql/iE3fWfOOK8tItLQAgJa6meziXJ3dzP8gHzdbz3YxgjYxiBc7vIxBte7vq4xEiIiIuK66x4UbLMXbLMZfshqtZKTk4OHhwfBwcF11gP22RG2mRY9evTA3d3dvv1yOTk5gPGsCxEREXHddQ8KgwcPBmDjxo1O+/bu3UtBQQFhYWH2NRP69++Pt7c3O3bscBqAWFpayo4dOzCZTISFhQHYv8/Pz2fv3r1Ox0hPTwcgMjLyup6XiIjIT9F1Dwrh4eGEhISQkZHBypUr7dsLCgpISEgAYNKkSfbtJpOJMWPGUFRUREJCAlVVVQBUVVUxY8YMiouLGTdunMNiTLGxsQAkJCRQUFBg375ixQq2b99Or169GDBgwPU+NRERkZ+cGzLrYfbs2UyYMIGXX36ZlJQUAgMD2bVrF0VFRURHR/OLX/zCoc2zzz5LZmYm//rXv9izZw+hoaEcPnyYEydOEBoaytNPP+1Qf99997F+/XrWrl3LL3/5S8LDw8nLy+PAgQO0atWK119//XqfloiIyE/Sdb+iANC7d2+Sk5MZMWIEx48fJyMjg44dO5KQkMArr7ziVN+mTRuSkpIYP348VVVVbNq0CXd3dyZPnsyHH36Ij4+PU5s33niDF154gcDAQLZs2UJeXh6jRo0iOTnZcJVHERERuTpuVj1msVY3+/TI0c+tauhuSD2lvRmlKWjSKGl6ZNP1o06PFBERkZuHgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGFBRERETEkIKCiIiIGFJQEBEREUMKCiIiImJIQUFEREQMKSiIiIiIIQUFERERMaSgICIiIoYUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihhQURERExJCCgoiIiBhSUBARERFDCgoiIiJiSEFBREREDCkoiIiIiCEFBRERETGkoCAiIiKGmnxQ2L59O48//jgDBgygb9++jB8/nm3btjV0t0RERG4KTToopKamMmnSJPbt20fv3r2566672LdvH5MnT2bFihUN3T0REZEmz7OhO1Bfp0+fJj4+npYtW7J8+XLMZjMABw4cYNKkSbz66qsMGTKEW265pYF7KiIi0nQ12SsKS5cupbKykokTJ9pDAkDv3r2ZPHkyFRUVuqogIiJyjZpsULCNQxg6dKjTvmHDhgGwdevWH7VPIiIiN5smGRSsVitZWVm4u7vTvXt3p/3dunXD3d2drKwsrFZrA/RQRETk5tAkg0JRURGVlZW0adOG5s2bO+339PTEz8+PCxcuUFpa2gA9FBERuTk0ycGMFy5cAKBFixaGNd7e3gCUlpbi6+t71cdwd3erX+eaiEA/4/dOGr+b/efzZuXr642XV5P8367LAgJaNnQXbpiKiipKSsobuhs3xJX+n9Ikf2Ld3eu+EHKttxz8/HyuqX1j995Lwxu6C3IN/P2vPvyKyLXx8vLEy+un92+vSd56MJlMAFRUVBjW2PZd6aqDiIiIXFmTDAq+vr6YTCbOnTtHVVWV0/6qqirOnTuHl5cXrVq1aoAeioiI3ByaZFBwc3OjR48eVFdXc+zYMaf9ubm51NTUOKyvICIiIlevSQYFgMGDBwOQnp7utM+2LTIy8kftk4iIyM2myQaFBx98EC8vL959913+85//2LcfPHiQRYsW4e3tTWxsbAP2UEREpOlzszbhFYmWLVvGjBkzaNasGREREVitVjIzM6mqquL1118nKiqqobsoIiLSpDXpoACwadMmFi1axOHDh2nevDk9e/bkySefZODAgQ3dNRERkSavyQcFERERuXGa7BgFERERufEUFERERMSQgoKIiIgYUlAQERERQwoKIiIiYqhJPj1S5IdKS0spKyvDarViMpnq9VhxERGpnYKCNDmnT59m5cqVbN26la+//prycsfnw3t5eWE2m4mMjOSRRx6hbdu2DdRTEZGmT+soSJOSnJzMq6++SkVFBVarFXd3d/z8/PDy8gIuPV783Llz1NTUAJceMz5z5kzuv//+huy2iEiTpaAgTcYXX3zB5MmT8fX1ZfLkyQwbNoxu3brh4eHhUFddXU1ubi4bNmzgvffeo6ysjPfff58BAwY0UM9FRJouBQVpMh5//HH27dvHRx99xO233+5Sm4MHD/LII4/Qv39/3n///RvcQxGRm4/GKEiTcejQIQYMGOBySAC44447iIiIcHjCqIhcvb17915T+759+16nnsiPTUFBmoxmzZo53WZwhZubG5WVlTegRyI/HbGxsbi5udWrrZubG4cPH77OPZIfi4KCNBlms5mdO3eSnZ1NcHCwS20OHTrEjh07uOuuu25w70RubrNnz2bWrFmUlZXRrl07goKCGrpL8iPRGAVpMrZv386vf/1rWrVqxcSJE7n33nsJDg7G09Mx79bU1JCbm8vGjRt59913KSkpYcGCBURGRjZQz0VuDvv27WPy5MnU1NSwcuVKQkJCGrpL8iNQUJAmJTU1lVdeeYWLFy8C4O7uTps2bfD29sbNzY3y8nIKCwuprq7GarXi5eXFtGnTiI2NbeCei9wc1q9fz9SpU+nduzcrV65s6O7Ij0BBQZqcM2fOsGTJEr744guysrKcxh+YTCZ69OjB4MGDefDBB+nUqVMD9VTk5hQXF0daWhp//vOfiYqKaujuyA2moCBNXlFRERcuXMDNzQ0fHx8t4Sxyg+Xl5ZGYmEj37t357W9/29DdkRtMQUFEREQM6emRIiIiYkhBQURERAwpKIiIiIghBQURERExpKAgIiIihv4/L6IWhGQQQnQAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df['category_C'].value_counts().plot.bar()\n",
    "plt.title('category_C')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'category_D')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7AeAX4sb+bYEaBfj7afgzq+u6G6ilNW/G6qe67gSAXwxuPQAAAFMEBQAAYIqgAAAATBEUAACAKYICAAAwRVAAAACmCAoAAMBUrdZROHPmjO69916dPHlSdrvdrT0nJ0dJSUnas2ePzpw5o1tvvVWjR49WfHy8fHzcs0lRUZEWLFigtLQ0HTt2TC1atNDgwYP1+OOPKygoyK2+qqpKKSkpSk5O1tGjRxUQEKA+ffpo8uTJCg8Pr80pAQCAGtTqikJiYqJOnjxZY9vhw4f1wAMP6NNPP1WrVq3Uv39/HT9+XDNmzFBCQoJbfXFxsR5++GEtXLhQFotFd955pywWi9555x2NHj1aP/3kvrTMiy++qGnTpun48eO644471Lp1a61du1YjR47UoUOHanNKAACgBpcdFD755BOtXbu2xjbDMJSQkKDi4mLNmjVLH3zwgebNm6f169crMjJSa9as0fr16132mTNnjux2u+Li4rR27VrNnTtX69evV2xsrDIzMzVnzhyX+g0bNmjVqlXq1KmTNm7cqKSkJKWmpioxMVGlpaWaOnWqDMO43NMCAAA1uKygkJeXpxkzZqh79+7y9fV1a09PT5fdbld0dLRiY2Od25s3b65p06ZJkpYsWeLcXlRUpJSUFAUFBWnKlCnO2xJ+fn6aNm2amjZtqtTUVJWWljr3Wbx4sSRp6tSpatz4P+v5jxkzRv369ZPdbldGRsblnBYAADBxWUHhhRdeUHl5uV5//fUa27dt2yZJGjhwoFtbVFSUQkJCtGfPHhUXF0uSdu/erbKyMvXp08dtLEJgYKD69u2rsrIy7d69W9L5YPHVV1+pWbNm6tmzp9sxHMfdunXr5ZwWAAAw4XFQWL58ubZt26Znn31Wt912W401mZmZkiSbzVZje3h4uKqrq5WVleVSHxERUWN9u3btJMk5YDIrK0uGYah9+/Y1Dop01B85csTT0wIAABfhUVD4v//7P/31r39Vnz599NBDD5nWnThxQpIUGhpaY7tj+6lTpyTJOSDyUvX5+fke1YeFhbnUAwCAK3PJoFBVVaWEhARZLBa99tprslgsprVnz56VJAUEBNTY7tjuGHPg+NqoUaOrUu/v7+9SBwAArswl11FYuHCh9u3bp5kzZ6pVq1YXrXXcDjALE47ZCI6v17r+SoSEuK/fANQXoaGNL10E1AE+mzeeiwaFw4cPKykpSTExMRo1atQlX8xqtUqSysrKamwvLy93qfO03nEF4VL1FRUVLvVXIj+/WNXVN+Y0S36Qvd/Jk+7riwB1LTS0MZ9NL+XjYzH9A/miQWH27Nk6d+6cKisr9eyzz7q0VVdXS5Jz+/PPP6+wsDB98803OnXqlNq3b+/2eheOMXCMKXCMWbjS+kuNkQAAAJfnokHBca8/PT3dtGbNmjWSpCeffFIRERHasmWLMjMz1bt3b5c6wzCUnZ0tX19fZ4hwzHZwzH64kGN2RGRkpCSpQ4cO8vHxcW6/UHZ2tiTzWRcAAODyXHQw45IlS2S322v8z7HgkuN/33LLLerfv78kadOmTW6vtXfvXhUUFCgqKsq5ZkKvXr0UEBCgHTt2uA1ALCkp0Y4dO2S1WhUVFSVJzu/z8/O1d+9et2OkpaVJkmJiYi73fQAAADW4qk+PjI6OVkREhNLT07Vy5Urn9oKCAiUmJkqSJkyY4NxutVo1YsQIFRYWKjExUZWVlZKkyspKTZ8+XUVFRRo9erTLYkzx8fGSzj9voqCgwLl9xYoV2r59uzp16uR2NQMAANSOxajlFIGOHTuqqqrK7emR+/fv17hx41RaWqpu3bopLCxMu3btUmFhoeLi4jRjxgyX+jNnzmjMmDHKyclRmzZt1LFjRx06dEi5ubnq2LGjli5dqsDAQJd9nnzySa1bt05NmzZVdHS08vLytH//fjVp0kTLly83XcDpctzogxmHP7O6rruBWlrzZiwDxlAvMZjRe11sMONVvaIgSV27dlVKSoqGDBmio0ePKj09Xa1atVJiYqJefvllt/pmzZopOTlZY8eOVWVlpTZv3iwfHx9NnDhR77//vltIkKQ33nhDzz33nMLCwrRlyxbl5eVp2LBhSklJuSohAQAAnFfrKwo3Oq4ooL7iigLqK64oeK/rekUBAADcOAgKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAlJ+nhVVVVVq2bJlSU1OVk5OjRo0aqXPnznrkkUd05513utXn5OQoKSlJe/bs0ZkzZ3Trrbdq9OjRio+Pl4+Pez4pKirSggULlJaWpmPHjqlFixYaPHiwHn/8cQUFBdXYn5SUFCUnJ+vo0aMKCAhQnz59NHnyZIWHh1/euwAAAGpkMQzD8KQwISFBq1evVlBQkKKionTu3Dnt3r1b586d0+TJk/XHP/7RWXv48GE99NBDKi4uVo8ePRQSEqKMjAwVFRVp+PDheuONN1xeu7i4WPHx8bLb7QoPD5fNZtPBgwf1/fffq0OHDkpOTlbjxo1d9nnuuee0atUqBQcHq1evXjp27JgOHDggq9WqZcuWqWPHjlf0xuTnF6u62qO3xuuEhjbW8GdW13U3UEtr3ozVyZM/1XU3ADehoY35bHopHx+LQkLc/yiXPLyisHbtWq1evVrh4eFaunSpWrRoIUn69ttv9eCDD2revHkaNmyY2rZtK8MwlJCQoOLiYs2aNUuxsbGSpIKCAo0fP15r1qzRoEGDNGTIEOfrz5kzR3a7XXFxcUpMTJSPj48qKyv1/PPPa/Xq1ZozZ45eeuklZ/2GDRu0atUqderUSe+9954zRCQnJ2vatGmaOnWqVq9eLYvFUrt3DAAASPJwjMLHH38sSXr22WedIUGSIiIiNHz4cFVXVys9PV2SlJ6eLrvdrujoaGdIkKTmzZtr2rRpkqQlS5Y4txcVFSklJUVBQUGaMmWK87aEn5+fpk2bpqZNmyo1NVWlpaXOfRYvXixJmjp1qsuVhjFjxqhfv36y2+3KyMi4vHcCAAC48SgozJ07V2vWrNGvf/1rt7aSkhJJkq+vryRp27ZtkqSBAwe61UZFRSkkJER79uxRcXGxJGn37t0qKytTnz593MYiBAYGqm/fviorK9Pu3bslnQ8WX331lZo1a6aePXu6HcNx3K1bt3pyagAA4CI8CgoNGzaUzWZTw4YNXbZv3rxZn332maxWq/MXdGZmpiTJZrPV+Frh4eGqrq5WVlaWS31ERESN9e3atZMk2e12SVJWVpYMw1D79u1rHBTpqD9y5IgnpwYAAC7C41kPDmVlZUpISFBmZqaysrLUqlUrzZo1y3lL4sSJE5Kk0NDQGvd3bD916pQk6eTJkx7V5+fne1QfFhbmUg8AAGrvstdR+PHHH7V+/XrnFQHpP3/tS9LZs2clSQEBATXu79juGHPg+NqoUaOrUu/v7+9SBwAAau+yryjcfPPN2rlzp3x8fLR9+3a98sormjFjhkpLS/XYY485bweYzThwzMZ0fL3W9bVlNk0EqA9CQxtfugioA3w2bzyXHRSsVqusVqskaejQoWrZsqXGjBmjBQsWaNy4cc62srKyGvcvLy93vs7Pv16q3nEF4VL1FRUVLvW1daOvowDvxlx11Eeso+C9LraOwhUv4Xz77bfr1ltvVXFxsXJzc51jBBxjEC504RiDq11/qTESAADAc5cMCoZhaNasWXrqqadUWVlZY41jNkRlZaVz9oJjNsOFr5WdnS1fX1+1b99eki5aL8k5FiIyMlKS1KFDB/n4+LiMkfi57OxsSeazLgAAgOcuGRQsFos2bdqktWvXOhdV+rnc3Fzl5OTIarUqPDxc/fv3lyRt2rTJrXbv3r0qKChQVFSUc82EXr16KSAgQDt27HAbgFhSUqIdO3bIarUqKipKkpzf5+fna+/evW7HSEtLkyTFxMRc6tQAAMAleHTrIS4uTpI0c+ZMHT9+3Lk9Ly9PTz/9tCorKxUfHy9/f39FR0crIiJC6enpWrlypbO2oKBAiYmJkqQJEyY4t1utVo0YMUKFhYVKTEx0XrWorKzU9OnTVVRUpNGjR7ssxhQfHy9JSkxMVEFBgXP7ihUrtH37dnXq1Em9e/e+7DcDAAC48uihUOfOndMf//hHbdmyRVarVT169FBVVZW+/vprlZaWKiYmRvPmzXPegti/f7/GjRun0tJSdevWTWFhYdq1a5cKCwsVFxenGTNmuLz+mTNnNGbMGOXk5KhNmzbq2LGjDh06pNzcXHXs2FFLly5VYGCgyz5PPvmk1q1bp6ZNmyo6Olp5eXnav3+/mjRpouXLl5su4OSpG30wIw+F8l48FAr1FYMZvdfFBjN6/PTIqqoqLV++XKtWrVJWVpZ8fHxks9k0cuRIxcXFua2SmJmZqblz5yojI0MVFRW67bbbNGbMGI0aNcq53PPPnTlzRvPmzVNaWpry8/PVsmVLDRo0SJMmTXJ7cqR0/orD0qVLlZqaqqNHjyo4OFg9e/bU5MmT1bZtW09O6aIICqivCAqorwgK3uuqBIVfGoIC6iuCAuorgoL3uqbTIwEAwI2LoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEz5eVpYVVWlDz74QB9++KGys7NVVVWlNm3a6J577tHEiRPl7+/vUp+Tk6OkpCTt2bNHZ86c0a233qrRo0crPj5ePj7u+aSoqEgLFixQWlqajh07phYtWmjw4MF6/PHHFRQUVGN/UlJSlJycrKNHjyogIEB9+vTR5MmTFR4eXou3AgAAXMhiGIZxqaKqqir94Q9/0BdffCGr1apu3brJz89PX3/9tYqKitStWze99957atSokSTp8OHDeuihh1RcXKwePXooJCREGRkZKioq0vDhw/XGG2+4vH5xcbHi4+Nlt9sVHh4um82mgwcP6vvvv1eHDh2UnJysxo0bu+zz3HPPadWqVQoODlavXr107NgxHThwQFarVcuWLVPHjh2v6I3Jzy9WdfUl3xqvFBraWMOfWV3X3UAtrXkzVidP/lTX3QDchIY25rPppXx8LAoJcf+jXPLw1kNKSoq++OILRUZG6rPPPtO7776rhQsXav369erevbu+/vprvf3225IkwzCUkJCg4uJizZo1Sx988IHmzZun9evXKzIyUmvWrNH69etdXn/OnDmy2+2Ki4vT2rVrNXfuXK1fv16xsbHKzMzUnDlzXOo3bNigVatWqVOnTtq4caOSkpKUmpqqxMRElZaWaurUqfIg/wAAgEvwKCh8+OGHkqTnn39eN910k3N78+bN9fLLL0uSPv30U0lSenq67Ha7oqOjFRsb61I7bdo0SdKSJUuc24uKipSSkqKgoCBNmTLFeVvCz89P06ZNU9OmTZWamqrS0lLnPosXL5YkTZ061eVKw5gxY9SvXz/Z7XZlZGR4/i4AAIAaeRQUgoOD1a5dO3Xt2tWtrW3btpKkEydOSJK2bdsmSRo4cKBbbVRUlEJCQrRnzx4VFxdLknbv3q2ysjL16dPHbSxCYGCg+vbtq7KyMu3evVvS+WDx1VdfqVmzZurZs6fbMRzH3bp1qyenBgAALsKjoDB//nytW7dOVqvVre3AgQOSpJtvvlmSlJmZKUmy2Ww1vlZ4eLiqq6uVlZXlUh8REVFjfbt27SRJdrtdkpSVlSXDMNS+ffsaB0U66o8cOeLJqQEAgIu4oumRhmFo7ty5kqTBgwdL+s+VhdDQ0Br3cWw/deqUJOnkyZMe1efn53tUHxYW5lIPAABq74qCwt/+9jft2rVLLVq00MSJEyVJZ8+elSQFBATUuI9ju2PMgeOrY8bEldY7pmn+fEwDAACoHY/XUbjQW2+9pX/84x9q2LCh5syZo+bNm0uS83aAxWKpcT/HbATH12tdX1tm00SA+iA0tPGli4A6wGfzxnPZQaGyslLTp0/XihUr5O/vr6SkJPXq1cvZ7hjHUFZWVuP+5eXlLnWe1juuIFyqvqKiwqW+tm70dRTg3ZirjvqIdRS81xWvo+BQUlKiSZMmacWKFWrSpIkWLVqkmJgYlxrHGAHHGIQLXTjG4GrXX2qMBAAA8JzHQaGwsFBjx47Vtm3b1LJlSy1btszlSoKDY/aCYzbDzxmGoezsbPn6+qp9+/aXrJfknB0RGRkpSerQoYN8fHyc2y+UnZ0tyXzWBQAA8JxHQaGiokKPPfaYDh486FxS2ewXcf/+/SVJmzZtcmvbu3evCgoKFBUV5VwzoVevXgoICNCOHTvcBiCWlJRox44dslqtioqKkiTn9/n5+dq7d6/bMdLS0iTJ7UoHAAC4fB4Fhblz5+qrr75Sy5YttWTJEueaCTWJjo5WRESE0tPTtXLlSuf2goICJSYmSpImTJjg3G61WjVixAgVFhYqMTFRlZWVkv4zFqKoqEijR492WYwpPj5ekpSYmKiCggLn9hUrVmj79u3q1KmTevfu7cmpAQCAi7jkQ6HOnDmjmJgYlZWVqVOnTs4FjWrieNjT/v37NW7cOJWWlqpbt24KCwvTrl27VFhYqLi4OM2YMcPtGGPGjFFOTo7atGmjjh076tChQ8rNzVXHjh21dOlSBQYGuuzz5JNPat26dWratKmio6OVl5en/fv3q0mTJlq+fLnpAk6eutEHM/JQKO/FQ6FQXzGY0XtdbDDjJYPC1q1b9dvf/tajAzlWT5TOjzmYO3euMjIyVFFRodtuu01jxozRqFGj5Ovr67bvmTNnNG/ePKWlpSk/P18tW7bUoEGDNGnSJLcnR0rnrzgsXbpUqampOnr0qIKDg9WzZ09NnjzZuaz0lSAooL4iKKC+Iih4rysKCr9UBAXUVwQF1FcEBe911aZHAgCAXxaCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMFXroLBq1SpFRkbqX//6V43tOTk5evrppxUTE6Nu3bpp+PDhWrp0qaqrq2usLyoq0l//+lcNGTJEXbt21YABA/SXv/xFxcXFNdZXVVUpOTlZI0aMUPfu3dW3b1899dRTysnJqe0pAQCAC9QqKOzbt08zZswwbT98+LAeeOABffrpp2rVqpX69++v48ePa8aMGUpISHCrLy4u1sMPP6yFCxfKYrHozjvvlMVi0TvvvKPRo0frp59+ctvnxRdf1LRp03T8+HHdcccdat26tdauXauRI0fq0KFDtTktAABwgcsOChs2bNCjjz6q0tLSGtsNw1BCQoKKi4s1a9YsffDBB5o3b57Wr1+vyMhIrVmzRuvXr3fZZ86cObLb7YqLi9PatWs1d+5crV+/XrGxscrMzNScOXPc+rBq1Sp16tRJGzduVFJSklJTU5WYmKjS0lJNnTpVhmFc7qkBAIALeBwUjh8/roSEBD3xxBOqrq5WixYtaqxLT0+X3W5XdHS0YmNjndubN2+uadOmSZKWLFni3F5UVKSUlBQFBQVpypQp8vE53yU/Pz9NmzZNTZs2VWpqqkswWbx4sSRp6tSpaty4sXP7mDFj1K9fP9ntdmVkZHh6agAAwITHQWHOnDlavXq1OnfurBUrVqhdu3Y11m3btk2SNHDgQLe2qKgohYSEaM+ePc6xB7t371ZZWZn69OmjoKAgl/rAwED17dtXZWVl2r17t6TzweKrr75Ss2bN1LNnT7djOI67detWT08NAACY8DgotGvXTq+//rpSUlIUGRlpWpeZmSlJstlsNbaHh4erurpaWVlZLvURERGmx5Uku90uScrKypJhGGrfvr3z6kNN9UeOHPHktAAAwEX4eVr42GOPeVR34sQJSVJoaGiN7Y7tp06dkiSdPHnSo/r8/HyP6sPCwlzqAQBA7V31dRTOnj0rSQoICKix3bHdMebA8bVRo0ZXpd7f39+lDgAA1J7HVxQ85bgdYLFYamx3zEZwfL3W9bUVEhJ06SKgjoSGNr50EVAH+GzeeK56ULBarZKksrKyGtvLy8td6jytd1xBuFR9RUWFS31t5ecXq7r6xpxiyQ+y9zt50n1tEaCuhYY25rPppXx8LKZ/IF/1Ww+OMQKOMQgXunCMwdWuv9QYCQAA4LmrHhQcsxccsxl+zjAMZWdny9fXV+3bt79kvSTn7AjHTIsOHTrIx8fHuf1C2dnZksxnXQAAAM9d9aDQv39/SdKmTZvc2vbu3auCggJFRUU510zo1auXAgICtGPHDrcBiCUlJdqxY4esVquioqIkyfl9fn6+9u7d63aMtLQ0SVJMTMxVPS8AAH6JrnpQiI6OVkREhNLT07Vy5Urn9oKCAiUmJkqSJkyY4NxutVo1YsQIFRYWKjExUZWVlZKkyspKTZ8+XUVFRRo9erTLYkzx8fGSpMTERBUUFDi3r1ixQtu3b1enTp3Uu3fvq31qAAD84lyTWQ+vvvqqxo0bp5deekmpqakKCwvTrl27VFhYqLi4OA0YMMBln6eeekoZGRn66KOPtGfPHnXs2FGHDh1Sbm6uOnbsqCeeeMKl/p577tGGDRu0bt06/eY3v1F0dLTy8vK0f/9+NWnSRK+//vrVPi0AAH6RrvoVBUnq2rWrUlJSNGTIEB09elTp6elq1aqVEhMT9fLLL7vVN2vWTMnJyRo7dqwqKyu1efNm+fj4aOLEiXr//fcVGBjots8bb7yh5557TmFhYdqyZYvy8vI0bNgwpaSkmK7yCAAALo/F4DGLNbrRp0cOf2Z1XXcDtbTmzVimoKFeYnqk97qu0yMBAMCNg6AAAABMERQAAIApggIAADBFUAAAAKYICgAAwBRBAQAAmCIoAAAAU1d9CWcAQM0aN2mkAP8b+/92Q0Mb13UXrpmy8kr9VHS2rrtx3d3Yn1gAqEcC/P1YFdWLrXkzVr/EdSe59QAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGCKoAAAAEwRFAAAgCmCAgAAMEVQAAAApggKAADAFEEBAACYIigAAABTBAUAAGDK64PC9u3b9cgjj6h3797q0aOHxo4dq23bttV1twAAuCF4dVBYtWqVJkyYoH379qlr167q3r279u3bp4kTJ2rFihV13T0AALyeX113oLZOnDihadOmqXHjxlq+fLlsNpskaf/+/ZowYYJeeeUV3XnnnbrpppvquKcAAHgvr72isHTpUlVUVGj8+PHOkCBJXbt21cSJE1VeXs5VBQAArpDXBgXHOISBAwe6tQ0aNEiStHXr1uvaJwAAbjReGRQMw1BmZqZ8fHzUrl07t/a2bdvKx8dHmZmZMgyjDnoIAMCNwSuDQmFhoSoqKtSsWTM1bNjQrd3Pz0/BwcE6e/asSkpK6qCHAADcGLxyMOPZs2clSY0aNTKtCQgIkCSVlJQoKCjoso/h42OpXee8RFiw+XuH+u9G/3zeyPjZ82436s/exc7LK4OCj8+lL4Rc6S2H4ODAK9q/vlv04uC67gKuQEjI5Ydf1A/87Hm3X+LPnlfeerBarZKk8vJy0xpH28WuOgAAgIvzyqAQFBQkq9Wq06dPq7Ky0q29srJSp0+flr+/v5o0aVIHPQQA4MbglUHBYrGoQ4cOqqqq0nfffefWnpOTo+rqapf1FQAAwOXzyqAgSf3795ckpaWlubU5tsXExFzXPgEAcKPx2qAwcuRI+fv765///Kf+/e9/O7cfOHBACxcuVEBAgOLj4+uwhwAAeD+L4cUrEi1btkzTp09XgwYN1KdPHxmGoYyMDFVWVur1119XbGxsXXcRAACv5tVBQZI2b96shQsX6tChQ2rYsKEiIyP1+9//Xn379q3rrgEA4PW8PigAAIBrx2vHKAAAgGuPoAAAAEwRFAAAgCmCAgAAMEVQAAAAprzy6ZHAz5WUlKi0tFSGYchqtdbqseIAgJoRFOB1Tpw4oZUrV2rr1q369ttvVVZW5tLu7+8vm82mmJgYPfjgg2revHkd9RQAvB/rKMCrpKSk6JVXXlF5ebkMw5CPj4+Cg4Pl7+8v6fzjxU+fPq3q6mpJ5x8zPmPGDN1777112W0A8FoEBXiNL7/8UhMnTlRQUJAmTpyoQYMGqW3btvL19XWpq6qqUk5OjjZu3KhFixaptLRU77zzjnr37l1HPQcA70VQgNd45JFHtG/fPn3wwQfq3LmzR/scOHBADz74oHr16qV33nnnGvcQAG48jFGA1zh48KB69+7tcUiQpC5duqhPnz4uTxgFcPn27t17Rfv36NHjKvUE1xtBAV6jQYMGbrcZPGGxWFRRUXENegT8csTHx8tisdRqX4vFokOHDl3lHuF6ISjAa9hsNu3cuVNZWVlq3769R/scPHhQO3bsUPfu3a9x74Ab26uvvqqZM2eqtLRULVq0UHh4eF13CdcJYxTgNbZv367//u//VpMmTTR+/Hjdfffdat++vfz8XPNudXW1cnJytGnTJv3zn/9UcXGx5s+fr5iYmDrqOXBj2LdvnyZOnKjq6mqtXLlSERERdd0lXAcEBXiVVatW6eWXX9a5c+ckST4+PmrWrJkCAgJksVhUVlamM2fOqKqqSoZhyN/fX1OmTFF8fHwd9xy4MWzYsEGTJ09W165dtXLlyrruDq4DggK8zsmTJ7VkyRJ9+eWXyszMdBt/YLVa1aFDB/Xv318jR45U69at66inwI0pISFBa9as0V/+8hfFxsbWdXdwjREU4PUKCwt19uxZWSwWBQYGsoQzcI3l5eVpzpw5ateunX7729/WdXdwjREUAACAKZ4eCQAATBEUAACAKYICAAAwRVAAAACmCAoAAMDU/wc069y1O8vllgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df['category_D'].value_counts().plot.bar()\n",
    "plt.title('category_D')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'category_E')"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df['category_E'].value_counts().plot.bar()\n",
    "plt.title('category_E')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'category_F')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_df['category_F'].value_counts().plot.bar()\n",
    "plt.title('category_F')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据清洗"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "from bs4 import BeautifulSoup\n",
    "def beautifulSoup(html):\n",
    "    soup = BeautifulSoup(html,'html.parser')\n",
    "    return soup.get_text()\n",
    "\n",
    "df['Question Sentence'] = df['Question Sentence'].apply(beautifulSoup) # applymap()则作用于DataFrame中的每一个元素"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "def htmlClean(text):\n",
    "    re_tag = re.compile('im=new Image;im.src.*\";')  # HTML标签\n",
    "    new_text = re.sub(re_tag, '', text)\n",
    "    return new_text\n",
    " \n",
    "        \n",
    "\n",
    "df['Question Sentence'] = df['Question Sentence'].apply(htmlClean) # applymap()则作用于DataFrame中的每一个元素"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 替换中英文字符\n",
    "import re\n",
    "def replace_punctuation(example):\n",
    "    example = list(example)\n",
    "    pre = ''\n",
    "    cur = ''\n",
    "    for i in range(len(example)):\n",
    "        if i == 0:\n",
    "            pre = example[i]\n",
    "            continue\n",
    "        pre = example[i-1]\n",
    "        cur = example[i]\n",
    "        if re.match(\"[\\w]\", pre): # pre是中文、数字、字母\n",
    "            if re.match(\"[\\w]\", cur): # cur是中文、数字、字母\n",
    "                continue\n",
    "            elif cur == ',':\n",
    "                example[i] = '，'\n",
    "            elif cur == '.':\n",
    "                example[i] = '。'\n",
    "            elif cur == '?':\n",
    "                example[i] = '？'\n",
    "            elif cur == ':':\n",
    "                example[i] = '：'\n",
    "            elif cur == ';':\n",
    "                example[i] = '；'\n",
    "            elif cur == '!':\n",
    "                example[i] = '！'\n",
    "            elif cur == '\"':\n",
    "                example[i] = '”'\n",
    "            elif cur == \"'\":\n",
    "                example[i] = \"’\"\n",
    "        else: # pre非中文、数字、字母\n",
    "            if not re.match(\"[\\w]\", cur): # cur非中文、数字、字母\n",
    "                example[i] = ''\n",
    "    return ''.join(example)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "df['Question Sentence'] = df['Question Sentence'].apply(replace_punctuation) # applymap()则作用于DataFrame中的每一个元素"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "r1 = \"[a-zA-Z'!\\\"#$%&'()*+,-./:;<=>?@★[\\\\]^_`{|}~]+\"\n",
    "comment = []\n",
    "for com_str in df['Question Sentence']:\n",
    "    com_str = re.sub(r1,'',com_str) # 非法字符替换为空\n",
    "    com_str = com_str.replace(\"病情描述：\",\"\")\n",
    "    com_str = com_str.strip()\n",
    "    if not com_str:\n",
    "        com_str = '无'\n",
    "    comment.append(com_str)\n",
    "    \n",
    "df['Question Sentence'] = comment\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Question Sentence_len'] = df['Question Sentence'].astype(str).apply(len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df = df[:len(train_df)]\n",
    "test_df = df[len(train_df):]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Question Sentence_len', ylabel='Density'>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(df['Question Sentence_len'])\n",
    "#plt.title('weibo_len')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Question Sentence_len', ylabel='Density'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.kdeplot(train_df['Question Sentence_len'])\n",
    "sns.kdeplot(test_df['Question Sentence_len'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='Question Sentence_len', ylabel='Density'>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x396 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = df.loc[df[\"Question Sentence_len\"]<500]\n",
    "sns.kdeplot(x['Question Sentence_len'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>category_A</th>\n",
       "      <th>category_B</th>\n",
       "      <th>category_C</th>\n",
       "      <th>category_D</th>\n",
       "      <th>category_E</th>\n",
       "      <th>category_F</th>\n",
       "      <th>Question Sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>QCT1000000001</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>乙肝抗体多久打一次乙肝抗体多久打一次，戊型肝炎的传播途径是怎样的，伴侣中有一个是乙肝携带，不...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>QCT1000000002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>十日观察法我没被狗咬伤，我想问问，狂犬病不是有十日观察法吗，那如果说狗咬人时狗得了狂犬病，可...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>QCT1000000003</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>我的乙肝大三阳十年了，现在能治的好了吗沈阳肝病携带者能治好，我的乙肝大三阳十年了，现在能治的...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>QCT1000000004</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>治疗丙肝哪里治疗最好丙肝的预防与治疗，治疗丙肝哪里治疗最好，丙肝表现症状是什么呢？丙肝有哪些...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>QCT1000000005</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>婚检乙肝上千倍婚检乙肝上千倍，我父亲肝硬化失代偿期，有单个结节癌变。有乙肝病史已经射频手术，...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              ID  category_A  category_B  category_C  category_D  category_E  \\\n",
       "0  QCT1000000001         NaN         NaN         NaN         NaN         NaN   \n",
       "1  QCT1000000002         NaN         NaN         NaN         NaN         NaN   \n",
       "2  QCT1000000003         NaN         NaN         NaN         NaN         NaN   \n",
       "3  QCT1000000004         NaN         NaN         NaN         NaN         NaN   \n",
       "4  QCT1000000005         NaN         NaN         NaN         NaN         NaN   \n",
       "\n",
       "   category_F                                  Question Sentence  \n",
       "0         NaN  乙肝抗体多久打一次乙肝抗体多久打一次，戊型肝炎的传播途径是怎样的，伴侣中有一个是乙肝携带，不...  \n",
       "1         NaN  十日观察法我没被狗咬伤，我想问问，狂犬病不是有十日观察法吗，那如果说狗咬人时狗得了狂犬病，可...  \n",
       "2         NaN  我的乙肝大三阳十年了，现在能治的好了吗沈阳肝病携带者能治好，我的乙肝大三阳十年了，现在能治的...  \n",
       "3         NaN  治疗丙肝哪里治疗最好丙肝的预防与治疗，治疗丙肝哪里治疗最好，丙肝表现症状是什么呢？丙肝有哪些...  \n",
       "4         NaN  婚检乙肝上千倍婚检乙肝上千倍，我父亲肝硬化失代偿期，有单个结节癌变。有乙肝病史已经射频手术，...  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_df.to_csv(\"train_clean.csv\",index=False)\n",
    "test_df.to_csv(\"test_clean.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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