文章主题和LDA模型 词云.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "import sqlite3\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer as TFIDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "cx = sqlite3.connect(r'D:\\Python\\获取网络信息用于文本分析\\data.db')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = pd.read_sql_query('select * from junshi',cx)\n",
    "df1 = pd.read_sql_query('select * from NBA',cx)\n",
    "df0 = pd.read_sql_query('select * from gaokao',cx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df0 = df0.dropna(axis=1, how='any')\n",
    "df1 = df1.dropna(axis=1, how='any')\n",
    "df2 = df2.dropna(axis=1, how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "junshi = df2.to_dict(orient='records') \n",
    "nba = df1.to_dict(orient='records')\n",
    "gaokao = df0.to_dict(orient='records')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'acticle'"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1 = []\n",
    "data2 = []\n",
    "data3 = []\n",
    "for w in junshi[3]:\n",
    "        data1.append(junshi[3][w])\n",
    "for w in gaokao[3]:\n",
    "        data2.append(gaokao[3][w])\n",
    "for w in nba[3]:\n",
    "        data3.append(nba[3][w])\n",
    "data1.pop(0)\n",
    "data2.pop(0)\n",
    "data3.pop(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "li = []\n",
    "for i in range(len(data2)):\n",
    "    reg = \"[^\\u4e00-\\u9fa5]\"\n",
    "    li.append(re.sub(reg,'',data2[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'调查问答样式不使用默认样式配置或者不传此参数调查结果样式不使用默认样式配置或者不传此参数通过来源设置图片宽高手浪默认月日上午国务院联防联控机制举办新闻发布会介绍积极鼓励吸纳高校毕业生农民工就业的相关政策高考会不会推迟教育部回应组织专家评估针对疫情对今年高考安排可能产生的影响教育部副部长翁铁慧在今天的发布会上说教育部目前正密切关注疫情发展变化的情况综合研判各方面因素对考试组织工作的影响翁铁慧表示教育部将重点做好三项工作与有关部门及地区会商研判疫情发展情况研判疫情走势正在组织专家评估疫情对考试组织考场防疫交通出行的影响今年高考考生人数预计过一千万他们的出行情况是否有可行的方案有待评估此外命题制卷也需要考虑将命题老师集聚在一起的防疫措施安排等各方面因素无论出台什么样的方案都必须要全力保障广大考生和涉考工作人员的生命安全和身体健康这是必须要做到的事情最近也了解到高三的学生以及家长特别关切高考方案的问题教育部将稳妥审慎研究今年的高考实施方案相关工作安排将及时向社会公布今年硕士研究生招生规模预计增加万人向这些专业倾斜翁铁慧介绍今年将着力扩大硕士研究生招生和专升本规模预计同比增加万万人翁铁慧介绍教育部将科学确定分校招生方案综合考虑经济社会发展需求财政支持情况高校办学条件等因素目前全国有万左右研究生导师万个硕士研究生学位授予点近几年新增多个硕士点经过认真研究过科学确定招生规模将重点向中西部地区和东北地区倾斜经测算预计硕士研究生扩大规模同比增加万人同时扩大普通高校专升本同比争取增加万人她表示扩大招生将向服务国家战略和社会民生急需的领域倾斜其中硕士研究生扩招向临床医学公共卫生人工智能等专业倾斜以专业学位培养为主专升本计划增量向职教本科应用型本科倾斜包括预防医学应急管理养老服务管理电子商务等领域倾斜教育部即日起推出全天候网上校园招聘今年全国普通高校毕业生万人受疫情影响毕业生就业压力增大据了解目前教育部已与有关行业主管部门举办了场网上大型招聘活动最近还将举办场同时教育部要求各省市各高校大力增加紧贴区域经济社会发展需求专业匹配度高的网络招聘会接下来教育部将寻求与社会招聘网站合作已遴选了家规模大岗位与毕业生匹配度高的企业前程无忧智联招聘直聘中华英才网猎聘网开辟校园招聘专区免费提供优质服务考虑到毕业生对用人单位可信度的关切教育部将要求合作企业严格审核岗位信息确保真实准确从今天日起教育部正式推出全天候网上校园招聘服务每天小时全年天服务不打烊不见面也能招聘也可签约认定人社部疫情一旦解除将密集推出现场招聘人力资源和社会保障部副部长游钧表示一旦疫情解除迅速组织动员全国各级各类公共就业服务机构市场服务机构密集推出行业化特色化的现场招聘游钧说今年疫情突发对高校毕业生的求职带来非常大的影响当前正值春季招聘的黄金季节疫情导致了整个市场的招聘需求下滑线下的招聘活动停止众多的毕业生求职受阻实习中断不少毕业生感到焦虑对此我们感同身受十分牵挂他表示为此人社部将加快完善落实就业创业政策鼓励企业吸纳一批引导基层就业一批支持创业带动一批并协同做好机关事业单位的招聘考录工作千方百计挖掘提供充分的就业机会同时加大线上招聘启动路同行职等你来网络招聘活动推出线上指导组织百名职业指导师开设就业指导的云课堂提早谋划一旦疫情解除迅速组织动员全国各级各类公共就业服务机构市场服务机构密集推出行业化特色化的现场招聘见习规模也将扩大游钧介绍今明两年将组织百万毕业生见习丰富他们的实践经验提升他们的就业能力增强他们的市场竞争能力对企业开放见习岗位的给予个月的政策补贴对离校未就业的毕业生游钧表示将尽早与教育部门对接信息开展实名服务重点关注建档立卡贫困家庭零就业家庭的毕业生实行一对一的帮扶举措政策服务全兜底与此同时也将始终关注湖北高校和湖北籍的毕业生积极会同有关方面采取有针对性的援助措施给他们提供平等的就业机会来源微信公众号经济日报原标题今年高考会不会推迟教育部回应'"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "li[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Loading model from cache C:\\Users\\14982\\AppData\\Local\\Temp\\jieba.cache\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "调查问答样式不使用默认样式配置或者不传此参数调查结果样式不使用默认样式配置或者不传此参数通过来源设置图片宽高手浪默认月日上午国务院联防联控机制举办新闻发布会介绍积极鼓励吸纳高校毕业生农民工就业的相关政策高考会不会推迟教育部回应组织专家评估针对疫情对今年高考安排可能产生的影响教育部副部长翁铁慧在今天的发布会上说教育部目前正密切关注疫情发展变化的情况综合研判各方面因素对考试组织工作的影响翁铁慧表示教育部将重点做好三项工作与有关部门及地区会商研判疫情发展情况研判疫情走势正在组织专家评估疫情对考试组织考场防疫交通出行的影响今年高考考生人数预计过一千万他们的出行情况是否有可行的方案有待评估此外命题制卷也需要考虑将命题老师集聚在一起的防疫措施安排等各方面因素无论出台什么样的方案都必须要全力保障广大考生和涉考工作人员的生命安全和身体健康这是必须要做到的事情最近也了解到高三的学生以及家长特别关切高考方案的问题教育部将稳妥审慎研究今年的高考实施方案相关工作安排将及时向社会公布今年硕士研究生招生规模预计增加万人向这些专业倾斜翁铁慧介绍今年将着力扩大硕士研究生招生和专升本规模预计同比增加万万人翁铁慧介绍教育部将科学确定分校招生方案综合考虑经济社会发展需求财政支持情况高校办学条件等因素目前全国有万左右研究生导师万个硕士研究生学位授予点近几年新增多个硕士点经过认真研究过科学确定招生规模将重点向中西部地区和东北地区倾斜经测算预计硕士研究生扩大规模同比增加万人同时扩大普通高校专升本同比争取增加万人她表示扩大招生将向服务国家战略和社会民生急需的领域倾斜其中硕士研究生扩招向临床医学公共卫生人工智能等专业倾斜以专业学位培养为主专升本计划增量向职教本科应用型本科倾斜包括预防医学应急管理养老服务管理电子商务等领域倾斜教育部即日起推出全天候网上校园招聘今年全国普通高校毕业生万人受疫情影响毕业生就业压力增大据了解目前教育部已与有关行业主管部门举办了场网上大型招聘活动最近还将举办场同时教育部要求各省市各高校大力增加紧贴区域经济社会发展需求专业匹配度高的网络招聘会接下来教育部将寻求与社会招聘网站合作已遴选了家规模大岗位与毕业生匹配度高的企业前程无忧智联招聘直聘中华英才网猎聘网开辟校园招聘专区免费提供优质服务考虑到毕业生对用人单位可信度的关切教育部将要求合作企业严格审核岗位信息确保真实准确从今天日起教育部正式推出全天候网上校园招聘服务每天小时全年天服务不打烊不见面也能招聘也可签约认定人社部疫情一旦解除将密集推出现场招聘人力资源和社会保障部副部长游钧表示一旦疫情解除迅速组织动员全国各级各类公共就业服务机构市场服务机构密集推出行业化特色化的现场招聘游钧说今年疫情突发对高校毕业生的求职带来非常大的影响当前正值春季招聘的黄金季节疫情导致了整个市场的招聘需求下滑线下的招聘活动停止众多的毕业生求职受阻实习中断不少毕业生感到焦虑对此我们感同身受十分牵挂他表示为此人社部将加快完善落实就业创业政策鼓励企业吸纳一批引导基层就业一批支持创业带动一批并协同做好机关事业单位的招聘考录工作千方百计挖掘提供充分的就业机会同时加大线上招聘启动路同行职等你来网络招聘活动推出线上指导组织百名职业指导师开设就业指导的云课堂提早谋划一旦疫情解除迅速组织动员全国各级各类公共就业服务机构市场服务机构密集推出行业化特色化的现场招聘见习规模也将扩大游钧介绍今明两年将组织百万毕业生见习丰富他们的实践经验提升他们的就业能力增强他们的市场竞争能力对企业开放见习岗位的给予个月的政策补贴对离校未就业的毕业生游钧表示将尽早与教育部门对接信息开展实名服务重点关注建档立卡贫困家庭零就业家庭的毕业生实行一对一的帮扶举措政策服务全兜底与此同时也将始终关注湖北高校和湖北籍的毕业生积极会同有关方面采取有针对性的援助措施给他们提供平等的就业机会来源微信公众号经济日报原标题今年高考会不会推迟教育部回应\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading model cost 0.939 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "招聘  教育部  毕业生  疫情  就业\n"
     ]
    }
   ],
   "source": [
    "import jieba.analyse\n",
    "index = 1\n",
    "print (li[index])\n",
    "content_S_str = \"\".join(li[index])  \n",
    "print (\"  \".join(jieba.analyse.extract_tags(content_S_str, topK=5, withWeight=False)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba\n",
    "data1 = []\n",
    "for  w  in range(len(li)):\n",
    "    data1.append(jieba.lcut(li[w]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data =[]\n",
    "for  i in range(len(data1)):\n",
    "          data.extend(data1[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "stopwords=pd.read_csv(\"stopwords.txt\",index_col=False,sep=\"\\t\",quoting=3,names=['stopword'], encoding='utf-8')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "stopwords = stopwords.stopword.values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       " 'Δ',\n",
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       " 'В',\n",
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       " '↑',\n",
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       " '∈［',\n",
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       " '不仅...而且',\n",
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       " '不仅仅是',\n",
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       " '宣布',\n",
       " '容易',\n",
       " '密切',\n",
       " '对',\n",
       " '对于',\n",
       " '对应',\n",
       " '对待',\n",
       " '对方',\n",
       " '对比',\n",
       " '将',\n",
       " '将才',\n",
       " '将要',\n",
       " '将近',\n",
       " '小',\n",
       " '少数',\n",
       " '尔',\n",
       " '尔后',\n",
       " '尔尔',\n",
       " '尔等',\n",
       " '尚且',\n",
       " '尤其',\n",
       " '就',\n",
       " '就地',\n",
       " '就是',\n",
       " '就是了',\n",
       " '就是说',\n",
       " '就此',\n",
       " '就算',\n",
       " '就要',\n",
       " '尽',\n",
       " '尽可能',\n",
       " '尽如人意',\n",
       " '尽心尽力',\n",
       " '尽心竭力',\n",
       " '尽快',\n",
       " '尽早',\n",
       " '尽然',\n",
       " '尽管',\n",
       " '尽管如此',\n",
       " '尽量',\n",
       " '局外',\n",
       " '居然',\n",
       " '届时',\n",
       " '属于',\n",
       " '屡',\n",
       " '屡屡',\n",
       " '屡次',\n",
       " '屡次三番',\n",
       " '岂',\n",
       " '岂但',\n",
       " '岂止',\n",
       " '岂非',\n",
       " '川流不息',\n",
       " '左右',\n",
       " '巨大',\n",
       " '巩固',\n",
       " '差一点',\n",
       " '差不多',\n",
       " '己',\n",
       " '已',\n",
       " '已矣',\n",
       " '已经',\n",
       " '巴',\n",
       " '巴巴',\n",
       " '带',\n",
       " '帮助',\n",
       " '常',\n",
       " '常常',\n",
       " '常言说',\n",
       " '常言说得好',\n",
       " '常言道',\n",
       " '平素',\n",
       " '年复一年',\n",
       " '并',\n",
       " '并不',\n",
       " '并不是',\n",
       " '并且',\n",
       " '并排',\n",
       " '并无',\n",
       " '并没',\n",
       " '并没有',\n",
       " '并肩',\n",
       " '并非',\n",
       " '广大',\n",
       " '广泛',\n",
       " '应当',\n",
       " '应用',\n",
       " '应该',\n",
       " '庶乎',\n",
       " '庶几',\n",
       " '开外',\n",
       " '开始',\n",
       " '开展',\n",
       " '引起',\n",
       " '弗',\n",
       " '弹指之间',\n",
       " '强烈',\n",
       " '强调',\n",
       " '归',\n",
       " '归根到底',\n",
       " '归根结底',\n",
       " '归齐',\n",
       " ...]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stopwords"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_words = []\n",
    "for i in  range(len(data)):\n",
    "            if  data[i] in stopwords:\n",
    "                continue\n",
    "            all_words.append(data[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>归类</td>\n",
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       "      <td>关注</td>\n",
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       "    <tr>\n",
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       "      <td>察言</td>\n",
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       "    <tr>\n",
       "      <th>110495</th>\n",
       "      <td>观数</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110496</th>\n",
       "      <td>撰文</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110497</th>\n",
       "      <td>余洋</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110498 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       all_words\n",
       "0             问答\n",
       "1             不传\n",
       "2             不传\n",
       "3              宽\n",
       "4             高手\n",
       "5              受\n",
       "6             疫情\n",
       "7             影响\n",
       "8             国内\n",
       "9             学校\n",
       "10            推迟\n",
       "11            开学\n",
       "12            多项\n",
       "13            考试\n",
       "14            取消\n",
       "15            推迟\n",
       "16            备受\n",
       "17            关注\n",
       "18            高考\n",
       "19            方案\n",
       "20            昨天\n",
       "21           国务院\n",
       "22            联防\n",
       "23            联控\n",
       "24            机制\n",
       "25            举办\n",
       "26            新闻\n",
       "27           发布会\n",
       "28           教育部\n",
       "29           负责人\n",
       "...          ...\n",
       "110468        院校\n",
       "110469        案例\n",
       "110470        素材\n",
       "110471        代表\n",
       "110472        个体\n",
       "110473        情况\n",
       "110474        本次\n",
       "110475       数据量\n",
       "110476        较大\n",
       "110477        归类\n",
       "110478        过程\n",
       "110479        接受\n",
       "110480        误差\n",
       "110481        较大\n",
       "110482        影响\n",
       "110483        未来\n",
       "110484        关注\n",
       "110485        申请\n",
       "110486       考核制\n",
       "110487        博士\n",
       "110488        入学\n",
       "110489        生源\n",
       "110490        结构\n",
       "110491        分析\n",
       "110492        敬请\n",
       "110493        关注\n",
       "110494        察言\n",
       "110495        观数\n",
       "110496        撰文\n",
       "110497        余洋\n",
       "\n",
       "[110498 rows x 1 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_all_words=pd.DataFrame({'all_words':all_words})\n",
    "df_all_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\14982\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: FutureWarning: using a dict on a Series for aggregation\n",
      "is deprecated and will be removed in a future version\n",
      "  \n"
     ]
    },
    {
     "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>all_words</th>\n",
       "      <th>count</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>479</th>\n",
       "      <td>专业</td>\n",
       "      <td>1260</td>\n",
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       "    <tr>\n",
       "      <th>10663</th>\n",
       "      <td>考试</td>\n",
       "      <td>1207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10654</th>\n",
       "      <td>考生</td>\n",
       "      <td>1117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13334</th>\n",
       "      <td>高校</td>\n",
       "      <td>1102</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6649</th>\n",
       "      <td>招生</td>\n",
       "      <td>987</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      all_words  count\n",
       "479          专业   1260\n",
       "10663        考试   1207\n",
       "10654        考生   1117\n",
       "13334        高校   1102\n",
       "6649         招生    987"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy\n",
    "words_count=df_all_words.groupby(by=['all_words'])['all_words'].agg({\"count\":numpy.size})\n",
    "words_count=words_count.reset_index().sort_values(by=[\"count\"],ascending=False)\n",
    "words_count.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x23dbc619ba8>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import matplotlib\n",
    "matplotlib.rcParams['figure.figsize'] = (10.0, 5.0)\n",
    "\n",
    "wordcloud=WordCloud(font_path=\"./data/simhei.ttf\",background_color=\"white\",max_font_size=80)\n",
    "word_frequence = {x[0]:x[1] for x in words_count.head(100).values}\n",
    "wordcloud=wordcloud.fit_words(word_frequence)\n",
    "plt.imshow(wordcloud)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gensim import corpora, models, similarities\n",
    "import gensim\n",
    "#http://radimrehurek.com/gensim/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "data4 = data1+data2+data3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "l = []\n",
    "for i in range(len(data2)):\n",
    "    reg = \"[^\\u4e00-\\u9fa5]\"\n",
    "    l.append(re.sub(reg,'',data2[i]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba\n",
    "data5 = []\n",
    "for  w  in range(len(l)):\n",
    "    data5.append(jieba.lcut(l[w]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "contents_clean = []\n",
    "all_words = []\n",
    "for line in data5:\n",
    "    line_clean = []\n",
    "    for word in line:\n",
    "        if word in stopwords:\n",
    "            continue\n",
    "        line_clean.append(word)\n",
    "        all_words.append(str(word))\n",
    "    contents_clean.append(line_clean)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#做映射，相当于词袋\n",
    "dictionary = corpora.Dictionary(data5)\n",
    "corpus = [dictionary.doc2bow(sentence) for sentence in data5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "lda = gensim.models.ldamodel.LdaModel(corpus=corpus, id2word=dictionary, num_topics=2)#类似Kmeans自己指定K值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.032*\"的\" + 0.013*\"和\" + 0.008*\"在\" + 0.007*\"考生\" + 0.007*\"样式\" + 0.006*\"不\" + 0.006*\"专业\" + 0.006*\"学生\" + 0.006*\"默认\" + 0.006*\"等\" + 0.005*\"高校\" + 0.005*\"考试\" + 0.005*\"招生\" + 0.005*\"工作\" + 0.005*\"大学\" + 0.005*\"使用\" + 0.005*\"了\" + 0.005*\"疫情\" + 0.005*\"为\" + 0.004*\"高考\"\n"
     ]
    }
   ],
   "source": [
    "print (lda.print_topic(1, topn=20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.039*\"的\" + 0.011*\"和\" + 0.008*\"在\" + 0.008*\"考试\" + 0.008*\"专业\" + 0.007*\"高校\" + 0.007*\"样式\" + 0.006*\"年\" + 0.006*\"招生\" + 0.005*\"学院\" + 0.005*\"考生\" + 0.005*\"不\" + 0.005*\"高考\" + 0.005*\"是\" + 0.004*\"学生\" + 0.004*\"了\" + 0.004*\"为\" + 0.004*\"设置\" + 0.004*\"默认\" + 0.004*\"学校\"\n"
     ]
    }
   ],
   "source": [
    "print (lda.print_topic(0, topn=20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.057*\"的\" + 0.012*\"了\" + 0.012*\"在\" + 0.009*\"是\" + 0.008*\"和\" + 0.006*\"科比\" + 0.006*\"他\" + 0.005*\"也\" + 0.005*\"湖人\" + 0.004*\"不\" + 0.004*\"我\" + 0.003*\"都\" + 0.003*\"月\" + 0.003*\"这\" + 0.003*\"与\" + 0.003*\"上\" + 0.003*\"对\" + 0.003*\"分\" + 0.003*\"詹姆斯\" + 0.003*\"中\"\n"
     ]
    }
   ],
   "source": [
    "print (lda.print_topic(0, topn=20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}