intro.ipynb 24.2 KB
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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# yf_dianping 说明\n",
    "0. **下载地址:** [百度网盘](https://pan.baidu.com/s/1yMNvHLl6QYsGbjT7u51Nfg)\n",
    "1. **数据概览:** 24 万家餐馆,54 万用户,440 万条评论/评分数据\n",
    "2. **推荐实验:** 推荐系统、情感/观点/评论 倾向性分析\n",
    "2. **数据来源:** [大众点评](http://www.dianping.com/)\n",
    "3. **原数据集:** [Dianping Review Dataset](http://yongfeng.me/dataset/),Yongfeng Zhang 教授为 WWW 2013, SIGIR 2013, SIGIR 2014 会议论文而搜集的数据\n",
    "4. **加工处理:**\n",
    "    1. 只保留原数据集中的评论、评分等信息,去除其他无用信息\n",
    "    2. 整理成与 [MovieLens](https://grouplens.org/datasets/movielens/) 兼容的格式\n",
    "    3. 进行脱敏操作,以保护用户隐私"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = 'yf_dianping_文件夹_所在_路径'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. restaurants.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "餐馆数目(有名称):209132\n",
      "餐馆数目(没有名称):34115\n",
      "餐馆数目(总计):243247\n"
     ]
    }
   ],
   "source": [
    "restaurants = pd.read_csv(path + 'restaurants.csv')\n",
    "\n",
    "print('餐馆数目(有名称):%d' % restaurants[~pd.isnull(restaurants.name)].shape[0])\n",
    "print('餐馆数目(没有名称):%d' % restaurants[pd.isnull(restaurants.name)].shape[0])\n",
    "print('餐馆数目(总计):%d' % restaurants.shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 字段说明\n",
    "\n",
    "| 字段 | 说明 |\n",
    "| ---- | ---- |\n",
    "| restId | 餐馆 id (从 0 开始,连续编号) |\n",
    "| name | 餐馆名称 |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "        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>restId</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>210902</th>\n",
       "      <td>210902</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124832</th>\n",
       "      <td>124832</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26766</th>\n",
       "      <td>26766</td>\n",
       "      <td>香锅制造(新苏天地店)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91754</th>\n",
       "      <td>91754</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204465</th>\n",
       "      <td>204465</td>\n",
       "      <td>西部牛扒城(湖塘店)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36475</th>\n",
       "      <td>36475</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231861</th>\n",
       "      <td>231861</td>\n",
       "      <td>四季火锅</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79816</th>\n",
       "      <td>79816</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140694</th>\n",
       "      <td>140694</td>\n",
       "      <td>彝家牛汤锅</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169641</th>\n",
       "      <td>169641</td>\n",
       "      <td>春秋</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33809</th>\n",
       "      <td>33809</td>\n",
       "      <td>九头鸟酒家(永定门店)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236919</th>\n",
       "      <td>236919</td>\n",
       "      <td>老上海城隍庙小吃(人民大学店)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182387</th>\n",
       "      <td>182387</td>\n",
       "      <td>河源三家村酒楼</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140475</th>\n",
       "      <td>140475</td>\n",
       "      <td>荣记麻辣烫</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194224</th>\n",
       "      <td>194224</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152406</th>\n",
       "      <td>152406</td>\n",
       "      <td>鼎丰真(东四马路店)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11701</th>\n",
       "      <td>11701</td>\n",
       "      <td>南亚餐厅</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58805</th>\n",
       "      <td>58805</td>\n",
       "      <td>益丰坊(虎泉店)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15641</th>\n",
       "      <td>15641</td>\n",
       "      <td>万达艾美酒店大堂吧</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43424</th>\n",
       "      <td>43424</td>\n",
       "      <td>新美心绿姿生活</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        restId             name\n",
       "210902  210902              NaN\n",
       "124832  124832              NaN\n",
       "26766    26766      香锅制造(新苏天地店)\n",
       "91754    91754              NaN\n",
       "204465  204465       西部牛扒城(湖塘店)\n",
       "36475    36475              NaN\n",
       "231861  231861             四季火锅\n",
       "79816    79816              NaN\n",
       "140694  140694            彝家牛汤锅\n",
       "169641  169641               春秋\n",
       "33809    33809      九头鸟酒家(永定门店)\n",
       "236919  236919  老上海城隍庙小吃(人民大学店)\n",
       "182387  182387          河源三家村酒楼\n",
       "140475  140475            荣记麻辣烫\n",
       "194224  194224              NaN\n",
       "152406  152406       鼎丰真(东四马路店)\n",
       "11701    11701             南亚餐厅\n",
       "58805    58805         益丰坊(虎泉店)\n",
       "15641    15641        万达艾美酒店大堂吧\n",
       "43424    43424          新美心绿姿生活"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "restaurants.sample(20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. ratings.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "用户 数目:542706\n",
      "评分/评论 数目(总计):4422473\n",
      "\n",
      "总体 评分 数目([1,5]):3293878\n",
      "环境 评分 数目([1,5]):4076220\n",
      "口味 评分 数目([1,5]):4093819\n",
      "服务 评分 数目([1,5]):4076220\n",
      "评论 数目:4107409\n"
     ]
    }
   ],
   "source": [
    "pd_ratings = pd.read_csv(path+'ratings.csv')\n",
    "\n",
    "print('用户 数目:%d' % pd_ratings.userId.unique().shape[0])\n",
    "print('评分/评论 数目(总计):%d\\n' % pd_ratings.shape[0])\n",
    "\n",
    "print('总体 评分 数目([1,5]):%d' % pd_ratings[(pd_ratings.rating>=1) & (pd_ratings.rating<=5)].shape[0])\n",
    "print('环境 评分 数目([1,5]):%d' % pd_ratings[(pd_ratings.rating_env>=1) & (pd_ratings.rating_env<=5)].shape[0])\n",
    "print('口味 评分 数目([1,5]):%d' % pd_ratings[(pd_ratings.rating_flavor>=1) & (pd_ratings.rating_flavor<=5)].shape[0])\n",
    "print('服务 评分 数目([1,5]):%d' % pd_ratings[(pd_ratings.rating_service>=1) & (pd_ratings.rating_service<=5)].shape[0])\n",
    "print('评论 数目:%d' % pd_ratings[~pd_ratings.comment.isna()].shape[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 字段说明\n",
    "\n",
    "| 字段 | 说明 |\n",
    "| ---- | ---- |\n",
    "| userId | 用户 id (从 0 开始,连续编号) |\n",
    "| restId | 即 restaurants.csv 中的 restId |\n",
    "| rating | 总体评分,[0,5] 之间的整数 |\n",
    "| rating_env | 环境评分,[1,5] 之间的整数 |\n",
    "| rating_flavor | 口味评分,[1,5] 之间的整数 |\n",
    "| rating_service | 服务评分,[1,5] 之间的整数 |\n",
    "| timestamp | 评分时间戳 |\n",
    "| comment |  评论内容 |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>userId</th>\n",
       "      <th>restId</th>\n",
       "      <th>rating</th>\n",
       "      <th>rating_env</th>\n",
       "      <th>rating_flavor</th>\n",
       "      <th>rating_service</th>\n",
       "      <th>timestamp</th>\n",
       "      <th>comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3331708</th>\n",
       "      <td>6802</td>\n",
       "      <td>183728</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1315673880000</td>\n",
       "      <td>环境不错,停车方便,交通也比较方便,东西齐全,应有尽有,吃、喝、玩、乐样样齐全,还有个五星级...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3332473</th>\n",
       "      <td>3106</td>\n",
       "      <td>183750</td>\n",
       "      <td>5.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1260155880000</td>\n",
       "      <td>去过两次,都是由日本朋友带着去的,很喜欢那种在小巷子深处的店,总觉得那样的店料理会很好吃。最...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291609</th>\n",
       "      <td>39590</td>\n",
       "      <td>13570</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1324792500000</td>\n",
       "      <td>朋友请客,两个人中午去吃的,虽然不是节假日,但人还是非常的多,等了很长时间才上餐,价位偏高,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>749582</th>\n",
       "      <td>59192</td>\n",
       "      <td>38519</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1321430760000</td>\n",
       "      <td>十一长假之前,我们的房子终于有了好消息,这个月底就可以拿到钥匙,真是不容易,盼星星盼月亮的,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>719908</th>\n",
       "      <td>241643</td>\n",
       "      <td>36382</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1271862180000</td>\n",
       "      <td>很差的一家店!公司聚餐居然选在这里,真是个大大的失策!\\n点的菜迟迟不上,不知道是故意不上还...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3127953</th>\n",
       "      <td>12481</td>\n",
       "      <td>173459</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1300407540000</td>\n",
       "      <td>这家是离家最近的一家城市超市了,所以自然要进去随便逛逛啦。\\n因为附近是居民区,自然光顾的主...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2068253</th>\n",
       "      <td>13070</td>\n",
       "      <td>115853</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1308671820000</td>\n",
       "      <td>以前觉得还行,但有了85度之后就不行了。要了个提拉米苏,不行,太甜了。\\n辣松的味道倒不错,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>640356</th>\n",
       "      <td>168006</td>\n",
       "      <td>33263</td>\n",
       "      <td>NaN</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1224868560000</td>\n",
       "      <td>算比较地道的川菜了 味道辣的很正 强力推荐 据说还是标点美食的... 香辣鸡翅每去必点~!不...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1222261</th>\n",
       "      <td>76280</td>\n",
       "      <td>65171</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1302136740000</td>\n",
       "      <td>为什么这么多人说好吃啊?为什么这么多人说肉多啊?难道是我人品有问题?\\n这个也是慕名而去的~...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101366</th>\n",
       "      <td>67372</td>\n",
       "      <td>2853</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1283741400000</td>\n",
       "      <td>两年前经常去这家吃卤煮,感觉特别好吃,可是最近吃了一次,让我大失所望。。。\\n卤煮的汤和食材...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         userId  restId  rating  rating_env  rating_flavor  rating_service  \\\n",
       "3331708    6802  183728     3.0         3.0            4.0             3.0   \n",
       "3332473    3106  183750     5.0         4.0            4.0             4.0   \n",
       "291609    39590   13570     3.0         3.0            2.0             3.0   \n",
       "749582    59192   38519     4.0         2.0            3.0             2.0   \n",
       "719908   241643   36382     1.0         2.0            1.0             1.0   \n",
       "3127953   12481  173459     4.0         3.0            3.0             3.0   \n",
       "2068253   13070  115853     3.0         3.0            3.0             2.0   \n",
       "640356   168006   33263     NaN         3.0            5.0             3.0   \n",
       "1222261   76280   65171     3.0         2.0            2.0             2.0   \n",
       "101366    67372    2853     1.0         1.0            1.0             1.0   \n",
       "\n",
       "             timestamp                                            comment  \n",
       "3331708  1315673880000  环境不错,停车方便,交通也比较方便,东西齐全,应有尽有,吃、喝、玩、乐样样齐全,还有个五星级...  \n",
       "3332473  1260155880000  去过两次,都是由日本朋友带着去的,很喜欢那种在小巷子深处的店,总觉得那样的店料理会很好吃。最...  \n",
       "291609   1324792500000  朋友请客,两个人中午去吃的,虽然不是节假日,但人还是非常的多,等了很长时间才上餐,价位偏高,...  \n",
       "749582   1321430760000  十一长假之前,我们的房子终于有了好消息,这个月底就可以拿到钥匙,真是不容易,盼星星盼月亮的,...  \n",
       "719908   1271862180000  很差的一家店!公司聚餐居然选在这里,真是个大大的失策!\\n点的菜迟迟不上,不知道是故意不上还...  \n",
       "3127953  1300407540000  这家是离家最近的一家城市超市了,所以自然要进去随便逛逛啦。\\n因为附近是居民区,自然光顾的主...  \n",
       "2068253  1308671820000  以前觉得还行,但有了85度之后就不行了。要了个提拉米苏,不行,太甜了。\\n辣松的味道倒不错,...  \n",
       "640356   1224868560000  算比较地道的川菜了 味道辣的很正 强力推荐 据说还是标点美食的... 香辣鸡翅每去必点~!不...  \n",
       "1222261  1302136740000  为什么这么多人说好吃啊?为什么这么多人说肉多啊?难道是我人品有问题?\\n这个也是慕名而去的~...  \n",
       "101366   1283741400000  两年前经常去这家吃卤煮,感觉特别好吃,可是最近吃了一次,让我大失所望。。。\\n卤煮的汤和食材...  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_ratings.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. links.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 加载数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "links = pd.read_csv(path + 'links.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 字段说明\n",
    "\n",
    "| 字段 | 说明 |\n",
    "| ---- | ---- |\n",
    "| restId | 即 restaurants.csv 和 ratings.csv 中的 restId |\n",
    "| dianpingId | 大众点评网的餐馆编号 |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>8528</th>\n",
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       "      <td>130597</td>\n",
       "      <td>2632129</td>\n",
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       "      <th>186956</th>\n",
       "      <td>186956</td>\n",
       "      <td>2233513</td>\n",
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       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        restId  dianpingId\n",
       "138492  138492     3566359\n",
       "158007  158007     2484433\n",
       "16170    16170     3651451\n",
       "116637  116637     5143029\n",
       "191554  191554     2734621\n",
       "192481  192481     3000367\n",
       "40978    40978     3168181\n",
       "196832  196832     3523291\n",
       "6048      6048     2435827\n",
       "200405  200405     4130573\n",
       "69792    69792     2853502\n",
       "153075  153075     2000257\n",
       "8528      8528     2651221\n",
       "196930  196930     3534673\n",
       "224063  224063     3138160\n",
       "3434      3434     2185753\n",
       "125490  125490     2112511\n",
       "230533  230533     4122445\n",
       "130597  130597     2632129\n",
       "186956  186956     2233513"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "links.sample(20)"
   ]
  }
 ],
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