machine_learning_projects/3.宝可梦数据集分析/平时作业/message.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import re\n",
    "import jieba"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 数据预处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def data_process(file='message80W1.csv'):\n",
    "    data = pd.read_csv(file, header=None, index_col=0)  #把数据读取进来\n",
    "    #处理数据\n",
    "    # data.shape#数据的结构\n",
    "    # data.head()   #看一下前5行，发现头部多了无关标题，用header=None去掉，3列第1列不需要用index_col=0，使第一列为行索引\n",
    "\n",
    "    # 欠抽样操作\n",
    "    data.columns = ['label', 'message']  #列名赋值->标签 内容\n",
    "    n = 5000\n",
    "    a = data[data['label'] == 0].sample(n)  #反例正常\n",
    "    b = data[data['label'] == 1].sample(n)  #正例垃圾\n",
    "    data_new = pd.concat([a, b], axis=0) #纵向拼接\n",
    "    #data['label'].value_counts()\n",
    "\n",
    "    data_dup = data_new['message'].drop_duplicates() #短信去重\n",
    "    data_qumin = data_dup.apply(lambda x: re.sub('x', '', x)) #对敏感字符x替换成空\n",
    "\n",
    "    jieba.load_userdict('newdic1.txt')     #将自定义的词典加入\n",
    "    data_cut = data_qumin.apply(lambda x: jieba.lcut(x))  #data去敏的句子进行分词操作，返回列表\n",
    "\n",
    "    #去除停用词\n",
    "    stopWords = pd.read_csv('stopword.txt', encoding='GB18030', sep='hahaha', header=None,engine='python')     #导入停用词,编码，设置分隔符号\n",
    "    stopWords = ['≮', '≯', '≠', '≮', ' ', '会', '月', '日', '–'] + list(stopWords.iloc[:, 0])  #增加的分词与以列表为形式的原有分词拼接起来\n",
    "\n",
    "    data_after_stop = data_cut.apply(lambda x: [i for i in x if i not in stopWords])   #将短信中的停用词去掉\n",
    "\n",
    "    #数据预处理函数封装\n",
    "    labels = data_new.loc[data_after_stop.index, 'label']   #标签\n",
    "    adata = data_after_stop.apply(lambda x: ' '.join(x))   #将列表进行拼接\n",
    "    #' '.join(data_after_stop[236042 ]\n",
    "\n",
    "    return adata, data_after_stop, labels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 绘制词云"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Building prefix dict from the default dictionary ...\n",
      "Loading model from cache C:\\Users\\asus\\AppData\\Local\\Temp\\jieba.cache\n",
      "Loading model cost 0.972 seconds.\n",
      "Prefix dict has been built successfully.\n"
     ]
    }
   ],
   "source": [
    "from wordcloud import WordCloud\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.colors as colors \n",
    "import numpy\n",
    "from PIL import Image\n",
    "\n",
    "adata, data_after_stop, labels = data_process()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0\n",
       "122508                                           有个 公司 招聘员工\n",
       "735473                               有利于 欧美 发达国家 殖民主义 轨道 发展\n",
       "698427                                    买 防晒霜 兔熊 想 买 奶茶 熊\n",
       "42275                                      拐弯 地方 设计 突起 挂 衣服\n",
       "66295                                            已用 iPhone6\n",
       "                                ...                        \n",
       "786389    欧派 家居 集团 总部 号 舟山 欧派 旗舰店 举办 鉴证 欧派 力量 大型 专场 活动 进...\n",
       "412632    新 羊 年 姚 司机 祝您 生意兴隆 万事如意 深圳 大浪 面包车 承接 货运 送客 期待 ...\n",
       "231086                              经理 您好 正 规 「 发 嘌 先 验证 付款\n",
       "112371    三八妇女节 东易 日盛 装饰 感恩 回馈 凡到 店 咨询 女业主 瑰 翠柏 护手霜 礼盒 一...\n",
       "740203    紧急通知 泗阳 学府 众兴 壹品 双 学区 房 元宵节 特价 房元 平方米 抢 挣 机不可失...\n",
       "Name: message, Length: 9975, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0\n",
       "122508    0\n",
       "735473    0\n",
       "698427    0\n",
       "42275     0\n",
       "66295     0\n",
       "         ..\n",
       "786389    1\n",
       "412632    1\n",
       "231086    1\n",
       "112371    1\n",
       "740203    1\n",
       "Name: label, Length: 9975, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0\n",
       "122508                                       [有个, 公司, 招聘员工]\n",
       "735473                        [有利于, 欧美, 发达国家, 殖民主义, 轨道, 发展]\n",
       "698427                            [买, 防晒霜, 兔熊, 想, 买, 奶茶, 熊]\n",
       "42275                               [拐弯, 地方, 设计, 突起, 挂, 衣服]\n",
       "66295                                         [已用, iPhone6]\n",
       "                                ...                        \n",
       "786389    [欧派, 家居, 集团, 总部, 号, 舟山, 欧派, 旗舰店, 举办, 鉴证, 欧派, 力...\n",
       "412632    [新, 羊, 年, 姚, 司机, 祝您, 生意兴隆, 万事如意, 深圳, 大浪, 面包车, ...\n",
       "231086                   [经理, 您好, 正, 规, 「, 发, 嘌, 先, 验证, 付款]\n",
       "112371    [三八妇女节, 东易, 日盛, 装饰, 感恩, 回馈, 凡到, 店, 咨询, 女业主, 瑰,...\n",
       "740203    [紧急通知, 泗阳, 学府, 众兴, 壹品, 双, 学区, 房, 元宵节, 特价, 房元, ...\n",
       "Name: message, Length: 9975, dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_after_stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "word_fre = {}\n",
    "for i in data_after_stop[labels == 0]:\n",
    "    for j in i:\n",
    "        if j not in word_fre.keys():\n",
    "            word_fre[j] = 1\n",
    "        else:\n",
    "            word_fre[j] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'有个': 2,\n",
       " '公司': 72,\n",
       " '招聘员工': 3,\n",
       " '有利于': 1,\n",
       " '欧美': 22,\n",
       " '发达国家': 1,\n",
       " '殖民主义': 1,\n",
       " '轨道': 2,\n",
       " '发展': 19,\n",
       " '买': 42,\n",
       " '防晒霜': 7,\n",
       " '兔熊': 1,\n",
       " '想': 84,\n",
       " '奶茶': 3,\n",
       " '熊': 3,\n",
       " '拐弯': 1,\n",
       " '地方': 21,\n",
       " '设计': 85,\n",
       " '突起': 1,\n",
       " '挂': 8,\n",
       " '衣服': 5,\n",
       " '已用': 1,\n",
       " 'iPhone6': 1,\n",
       " '浙江': 98,\n",
       " '哈雷': 1,\n",
       " '编队': 1,\n",
       " '犹如': 2,\n",
       " '挣开': 1,\n",
       " '缰绳': 1,\n",
       " '野马': 1,\n",
       " '扬州': 25,\n",
       " '商城': 5,\n",
       " '篮球场': 1,\n",
       " '东边': 1,\n",
       " '街心花园': 1,\n",
       " '昆山': 10,\n",
       " '我要': 7,\n",
       " '走': 33,\n",
       " '离开': 11,\n",
       " '令': 2,\n",
       " '伤心': 1,\n",
       " '失望': 2,\n",
       " '是非之地': 1,\n",
       " '发现': 44,\n",
       " '襟': 1,\n",
       " '副翼': 1,\n",
       " 'MH': 2,\n",
       " '客机': 3,\n",
       " '手扶': 2,\n",
       " '电梯': 57,\n",
       " '遇': 2,\n",
       " '紧急情况': 1,\n",
       " '三种': 4,\n",
       " '方法': 12,\n",
       " '急停': 1,\n",
       " '螺蛳': 1,\n",
       " '湾': 3,\n",
       " '国际': 20,\n",
       " '商贸城': 3,\n",
       " '社区': 13,\n",
       " '知识产权': 2,\n",
       " '工作站': 2,\n",
       " '标志': 3,\n",
       " '标牌': 1,\n",
       " '规章制度': 1,\n",
       " '悬挂': 2,\n",
       " '粘贴': 1,\n",
       " 'sephora': 1,\n",
       " '顺便': 5,\n",
       " '摸': 2,\n",
       " '一把': 6,\n",
       " '学生': 17,\n",
       " '留置': 1,\n",
       " '宿舍': 2,\n",
       " '电脑': 115,\n",
       " '现金': 6,\n",
       " '遭窃': 1,\n",
       " '登陆': 9,\n",
       " 'qq': 3,\n",
       " '早就': 2,\n",
       " '手机': 199,\n",
       " '绑定': 3,\n",
       " '装修': 34,\n",
       " '房子': 12,\n",
       " '制服': 3,\n",
       " '巨蟹座': 1,\n",
       " '把握': 2,\n",
       " '样样': 1,\n",
       " '顺利': 3,\n",
       " '生活': 31,\n",
       " '强奸': 16,\n",
       " '桑那': 1,\n",
       " '回去': 2,\n",
       " '男子': 18,\n",
       " '车': 15,\n",
       " '赌': 2,\n",
       " '小区': 9,\n",
       " '大门': 3,\n",
       " '局长': 2,\n",
       " '报警': 10,\n",
       " '没用': 5,\n",
       " 'biang': 1,\n",
       " '旅游': 60,\n",
       " '一点': 7,\n",
       " '素质': 1,\n",
       " '2015': 88,\n",
       " '年': 186,\n",
       " '28': 12,\n",
       " '富平': 1,\n",
       " '法院': 59,\n",
       " '办公楼': 3,\n",
       " '审判': 8,\n",
       " '区域': 6,\n",
       " '办公': 4,\n",
       " '实行': 2,\n",
       " '分离': 1,\n",
       " 'HAPO': 1,\n",
       " '提供': 17,\n",
       " '北海道': 1,\n",
       " '生产': 11,\n",
       " '食材': 1,\n",
       " '三点': 4,\n",
       " '尾盘': 2,\n",
       " '十分钟': 2,\n",
       " '买股': 1,\n",
       " '几天': 8,\n",
       " '上午': 12,\n",
       " '卫视': 25,\n",
       " '放爱': 1,\n",
       " '反感': 3,\n",
       " '感觉': 32,\n",
       " '相比': 1,\n",
       " '每月': 2,\n",
       " '无锡': 36,\n",
       " '绍兴': 2,\n",
       " '节奏': 5,\n",
       " '武汉': 7,\n",
       " '活动': 44,\n",
       " '两块钱': 1,\n",
       " '微信': 14,\n",
       " '红包': 12,\n",
       " '进到': 1,\n",
       " '45': 9,\n",
       " '分钟': 19,\n",
       " '微软': 44,\n",
       " '研究院': 4,\n",
       " '教育': 12,\n",
       " '峰会': 1,\n",
       " '人工智能': 3,\n",
       " '研讨会': 2,\n",
       " '录像': 2,\n",
       " '四十种': 1,\n",
       " '成份': 3,\n",
       " '维生素': 10,\n",
       " '抗衰老': 1,\n",
       " '物质': 3,\n",
       " '矿物质': 1,\n",
       " '补充剂': 1,\n",
       " '外': 5,\n",
       " '上海': 39,\n",
       " '你好': 4,\n",
       " '再见': 2,\n",
       " '南京': 146,\n",
       " '免费': 28,\n",
       " '分享': 41,\n",
       " '河北': 5,\n",
       " '保定': 1,\n",
       " '份小偿': 1,\n",
       " '弹簧': 1,\n",
       " '草球球': 1,\n",
       " '原文': 9,\n",
       " '9bigbang': 2,\n",
       " '演唱会': 8,\n",
       " '看台': 1,\n",
       " '1280': 2,\n",
       " '1580': 2,\n",
       " '两张': 4,\n",
       " '200': 18,\n",
       " '重点项目': 3,\n",
       " '预计': 12,\n",
       " '投资': 50,\n",
       " '2100': 1,\n",
       " '亿元': 8,\n",
       " '华为': 40,\n",
       " '系统': 34,\n",
       " '判定': 2,\n",
       " '蓝牙': 3,\n",
       " '连上来': 1,\n",
       " '音频': 1,\n",
       " '输出设备': 1,\n",
       " '带不带': 1,\n",
       " '输入': 7,\n",
       " '小偷': 23,\n",
       " '18': 17,\n",
       " '楼': 12,\n",
       " '绑': 1,\n",
       " '绳子': 1,\n",
       " '17': 14,\n",
       " '家里': 20,\n",
       " '偷东西': 1,\n",
       " '遭': 10,\n",
       " '憋死': 2,\n",
       " '恐怖': 2,\n",
       " '医院': 69,\n",
       " 'RT': 1,\n",
       " 'COM': 1,\n",
       " '德国': 10,\n",
       " '顶尖': 1,\n",
       " '互动': 3,\n",
       " '德累斯顿': 1,\n",
       " '卫生': 2,\n",
       " '博物馆': 9,\n",
       " '中': 90,\n",
       " '举办': 14,\n",
       " 'Work': 1,\n",
       " 'RVclipping': 1,\n",
       " '剩下': 5,\n",
       " '30%': 4,\n",
       " '系统优化': 1,\n",
       " '解决': 13,\n",
       " '好吃': 3,\n",
       " '小龙虾': 1,\n",
       " '每日': 6,\n",
       " '黄金': 3,\n",
       " '外汇': 1,\n",
       " '白银': 2,\n",
       " '原油': 3,\n",
       " '实时': 2,\n",
       " '解盘': 1,\n",
       " '视频教程': 2,\n",
       " '技术': 15,\n",
       " '分析': 12,\n",
       " '我弟': 1,\n",
       " '阿里巴巴': 27,\n",
       " '实习': 1,\n",
       " '昨天': 24,\n",
       " 'Windows10': 5,\n",
       " '正式': 23,\n",
       " '发布': 27,\n",
       " 'WorldSquare': 1,\n",
       " 'LVMH': 1,\n",
       " '集团': 30,\n",
       " '总营收': 1,\n",
       " '上涨': 3,\n",
       " '19': 13,\n",
       " '南': 7,\n",
       " '徐州': 24,\n",
       " '东': 3,\n",
       " '张': 8,\n",
       " '下车': 3,\n",
       " '前': 35,\n",
       " '打开': 17,\n",
       " '缴纳': 2,\n",
       " '停': 8,\n",
       " '东站': 1,\n",
       " '地下': 3,\n",
       " '停车场': 6,\n",
       " '轿车': 4,\n",
       " '停车费': 1,\n",
       " '医生': 54,\n",
       " '注重': 1,\n",
       " '健康': 13,\n",
       " '建议': 12,\n",
       " '体内': 3,\n",
       " '足够': 6,\n",
       " '酵素': 4,\n",
       " '数量': 9,\n",
       " '中场': 2,\n",
       " '休息': 4,\n",
       " '火箭': 10,\n",
       " '4976': 1,\n",
       " '星空': 3,\n",
       " '元素': 1,\n",
       " '图案': 1,\n",
       " '另类': 1,\n",
       " '达': 7,\n",
       " '中国': 112,\n",
       " '主发': 1,\n",
       " 'babylily': 1,\n",
       " '诺丽果': 1,\n",
       " '阳光': 7,\n",
       " '隔离': 3,\n",
       " '乳为': 1,\n",
       " '挡住': 1,\n",
       " '恶毒': 1,\n",
       " '特别': 16,\n",
       " '名企': 1,\n",
       " '齐聚': 1,\n",
       " '环湖': 1,\n",
       " 'CBD': 3,\n",
       " '板块': 8,\n",
       " '腐败': 17,\n",
       " '官员': 11,\n",
       " '留下': 4,\n",
       " '违法': 20,\n",
       " '罪证': 1,\n",
       " '推': 4,\n",
       " '暑假': 7,\n",
       " '陪': 16,\n",
       " '妈妈': 9,\n",
       " '过个': 1,\n",
       " '生日': 4,\n",
       " '仙剑': 1,\n",
       " '上市': 4,\n",
       " '火爆': 9,\n",
       " '激活': 3,\n",
       " '难': 5,\n",
       " '官方': 7,\n",
       " '重启': 2,\n",
       " '终于': 23,\n",
       " '质疑': 43,\n",
       " '信誓旦旦': 1,\n",
       " '东西': 25,\n",
       " '累到': 2,\n",
       " '再也': 7,\n",
       " '懒得': 2,\n",
       " '追求': 2,\n",
       " '越来越': 6,\n",
       " '真实': 5,\n",
       " '温暖': 3,\n",
       " '奢望': 1,\n",
       " '有种': 6,\n",
       " '想要': 16,\n",
       " '大哭': 1,\n",
       " '念头': 3,\n",
       " '拍够': 1,\n",
       " 'Lisa': 1,\n",
       " '横店': 1,\n",
       " '念念不忘': 1,\n",
       " '结论': 1,\n",
       " '东革': 1,\n",
       " '阿里': 21,\n",
       " '痛风病': 1,\n",
       " '疗效': 2,\n",
       " 'Pepper': 1,\n",
       " '欢迎词': 1,\n",
       " '模仿': 2,\n",
       " '单口相声': 1,\n",
       " '语气': 3,\n",
       " '瑞穗': 1,\n",
       " '银行': 14,\n",
       " '咨询': 27,\n",
       " '存款': 1,\n",
       " '理财': 15,\n",
       " '月初': 4,\n",
       " '检查': 13,\n",
       " '肺癌': 1,\n",
       " '晚期': 1,\n",
       " '说': 119,\n",
       " '小伙子': 1,\n",
       " '进水': 2,\n",
       " '医疗': 15,\n",
       " '行业': 11,\n",
       " '网民': 3,\n",
       " '搜索': 6,\n",
       " '调研': 6,\n",
       " '报名': 6,\n",
       " '时间': 31,\n",
       " '年月日': 9,\n",
       " '附件': 1,\n",
       " '下载': 25,\n",
       " '地址': 13,\n",
       " '周末': 5,\n",
       " '感冒': 7,\n",
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       " '完': 18,\n",
       " '噢': 1,\n",
       " '高校': 5,\n",
       " '联谊': 1,\n",
       " '车才': 1,\n",
       " '40rmb': 1,\n",
       " '恶心': 6,\n",
       " '事情': 17,\n",
       " '演': 3,\n",
       " '仿真': 2,\n",
       " '日本首相': 1,\n",
       " '安倍': 3,\n",
       " '不停': 2,\n",
       " '参观者': 1,\n",
       " '鞠躬': 1,\n",
       " '道歉': 3,\n",
       " '青歌赛': 1,\n",
       " '冠军': 4,\n",
       " '真不知道': 2,\n",
       " '资格': 4,\n",
       " '哈尔滨': 2,\n",
       " '多个': 5,\n",
       " '小时': 39,\n",
       " '辛辛苦苦': 1,\n",
       " '薄': 1,\n",
       " '非要': 3,\n",
       " '卡个': 1,\n",
       " ...}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "word_fre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1f8b61e2520>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "colormaps = colors.ListedColormap(['#FF0000','#FF7F50','#FFE4C4'])\n",
    "wc = WordCloud(\n",
    "        colormap=colormaps, \n",
    "        background_color='white', \n",
    "        font_path='simsun.ttc'\n",
    ")\n",
    "wc.fit_words(word_fre)\n",
    "plt.imshow(wc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 模型构建与性能评估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import GaussianNB   #导入高斯朴素贝叶斯\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer #导入文本特征提取模块  转换成词频  向量转换成TF-IDF权重矩阵\n",
    "\n",
    "adata, data_after_stop, lables = data_process()\n",
    "\n",
    "data_tr, data_te, labels_tr, labels_te = train_test_split(adata, lables, test_size=0.2)\n",
    "\n",
    "countVectorizer = CountVectorizer()   #使训练集与测试集的列数相同\n",
    "data_tr = countVectorizer.fit_transform(data_tr)\n",
    "X_tr = TfidfTransformer().fit_transform(data_tr.toarray()).toarray() #训练集TF-IDF权值\n",
    "\n",
    "data_te = CountVectorizer(vocabulary=countVectorizer.vocabulary_).fit_transform(data_te)\n",
    "X_te = TfidfTransformer().fit_transform(data_te.toarray()).toarray()    #测试集TF-IDF权值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.906813627254509"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = GaussianNB()\n",
    "model.fit(X_tr, labels_tr)\n",
    "model.score(X_te, labels_te)"
   ]
  }
 ],
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