projetoInt3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conectar no Banco"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: mysql-connector-python in c:\\programdata\\anaconda3\\lib\\site-packages (8.0.29)\n",
      "Collecting protobuf>=3.0.0\n",
      "  Downloading protobuf-3.20.1-cp39-cp39-win_amd64.whl (904 kB)\n",
      "Installing collected packages: protobuf\n",
      "Successfully installed protobuf-3.20.1\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "#pip install mysql-connector-python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting spacy\n",
      "  Downloading spacy-3.3.0-cp39-cp39-win_amd64.whl (11.6 MB)\n",
      "Requirement already satisfied: requests<3.0.0,>=2.13.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy) (2.26.0)\n",
      "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy) (4.62.3)\n",
      "Collecting thinc<8.1.0,>=8.0.14\n",
      "  Downloading thinc-8.0.16-cp39-cp39-win_amd64.whl (1.0 MB)\n",
      "Collecting cymem<2.1.0,>=2.0.2\n",
      "  Downloading cymem-2.0.6-cp39-cp39-win_amd64.whl (36 kB)\n",
      "Collecting pathy>=0.3.5\n",
      "  Downloading pathy-0.6.1-py3-none-any.whl (42 kB)\n",
      "Requirement already satisfied: jinja2 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy) (2.11.3)\n",
      "Collecting spacy-loggers<2.0.0,>=1.0.0\n",
      "  Downloading spacy_loggers-1.0.2-py3-none-any.whl (7.2 kB)\n",
      "Collecting murmurhash<1.1.0,>=0.28.0\n",
      "  Downloading murmurhash-1.0.7-cp39-cp39-win_amd64.whl (18 kB)\n",
      "Collecting spacy-legacy<3.1.0,>=3.0.9\n",
      "  Downloading spacy_legacy-3.0.9-py2.py3-none-any.whl (20 kB)\n",
      "Collecting catalogue<2.1.0,>=2.0.6\n",
      "  Downloading catalogue-2.0.7-py3-none-any.whl (17 kB)\n",
      "Requirement already satisfied: setuptools in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy) (58.0.4)\n",
      "Collecting blis<0.8.0,>=0.4.0\n",
      "  Downloading blis-0.7.7-cp39-cp39-win_amd64.whl (6.6 MB)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy) (21.0)\n",
      "Note: you may need to restart the kernel to use updated packages.Collecting preshed<3.1.0,>=3.0.2\n",
      "\n",
      "  Downloading preshed-3.0.6-cp39-cp39-win_amd64.whl (112 kB)\n",
      "Collecting wasabi<1.1.0,>=0.9.1\n",
      "  Downloading wasabi-0.9.1-py3-none-any.whl (26 kB)\n",
      "Collecting pydantic!=1.8,!=1.8.1,<1.9.0,>=1.7.4\n",
      "  Downloading pydantic-1.8.2-cp39-cp39-win_amd64.whl (1.9 MB)\n",
      "Collecting srsly<3.0.0,>=2.4.3\n",
      "  Downloading srsly-2.4.3-cp39-cp39-win_amd64.whl (448 kB)\n",
      "Collecting typer<0.5.0,>=0.3.0\n",
      "  Downloading typer-0.4.1-py3-none-any.whl (27 kB)\n",
      "Collecting langcodes<4.0.0,>=3.2.0\n",
      "  Downloading langcodes-3.3.0-py3-none-any.whl (181 kB)\n",
      "Requirement already satisfied: numpy>=1.15.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from spacy) (1.20.3)\n",
      "Requirement already satisfied: pyparsing>=2.0.2 in c:\\programdata\\anaconda3\\lib\\site-packages (from packaging>=20.0->spacy) (3.0.4)\n",
      "Collecting smart-open<6.0.0,>=5.0.0\n",
      "  Downloading smart_open-5.2.1-py3-none-any.whl (58 kB)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\programdata\\anaconda3\\lib\\site-packages (from pydantic!=1.8,!=1.8.1,<1.9.0,>=1.7.4->spacy) (3.10.0.2)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy) (1.26.7)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy) (2021.10.8)\n",
      "Requirement already satisfied: charset-normalizer~=2.0.0 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy) (2.0.4)\n",
      "Requirement already satisfied: idna<4,>=2.5 in c:\\programdata\\anaconda3\\lib\\site-packages (from requests<3.0.0,>=2.13.0->spacy) (3.2)\n",
      "Requirement already satisfied: colorama in c:\\programdata\\anaconda3\\lib\\site-packages (from tqdm<5.0.0,>=4.38.0->spacy) (0.4.4)\n",
      "Requirement already satisfied: click<9.0.0,>=7.1.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from typer<0.5.0,>=0.3.0->spacy) (8.0.3)\n",
      "Requirement already satisfied: MarkupSafe>=0.23 in c:\\programdata\\anaconda3\\lib\\site-packages (from jinja2->spacy) (1.1.1)\n",
      "Installing collected packages: murmurhash, cymem, catalogue, wasabi, typer, srsly, smart-open, pydantic, preshed, blis, thinc, spacy-loggers, spacy-legacy, pathy, langcodes, spacy\n",
      "Successfully installed blis-0.7.7 catalogue-2.0.7 cymem-2.0.6 langcodes-3.3.0 murmurhash-1.0.7 pathy-0.6.1 preshed-3.0.6 pydantic-1.8.2 smart-open-5.2.1 spacy-3.3.0 spacy-legacy-3.0.9 spacy-loggers-1.0.2 srsly-2.4.3 thinc-8.0.16 typer-0.4.1 wasabi-0.9.1\n"
     ]
    }
   ],
   "source": [
    "#pip install spacy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting textblob\n",
      "  Downloading textblob-0.17.1-py2.py3-none-any.whl (636 kB)\n",
      "Requirement already satisfied: nltk>=3.1 in c:\\programdata\\anaconda3\\lib\\site-packages (from textblob) (3.6.5)\n",
      "Requirement already satisfied: click in c:\\programdata\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n",
      "Requirement already satisfied: joblib in c:\\programdata\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.1.0)\n",
      "Requirement already satisfied: regex>=2021.8.3 in c:\\programdata\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.8.3)\n",
      "Requirement already satisfied: tqdm in c:\\programdata\\anaconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.62.3)\n",
      "Requirement already satisfied: colorama in c:\\programdata\\anaconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n",
      "Installing collected packages: textblob\n",
      "Successfully installed textblob-0.17.1\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install textblob"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting pyspellchecker\n",
      "  Downloading pyspellchecker-0.6.3-py3-none-any.whl (2.7 MB)\n",
      "Installing collected packages: pyspellchecker\n",
      "Successfully installed pyspellchecker-0.6.3\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "#pip install pyspellchecker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting langdetect\n",
      "  Downloading langdetect-1.0.9.tar.gz (981 kB)\n",
      "Requirement already satisfied: six in c:\\programdata\\anaconda3\\lib\\site-packages (from langdetect) (1.16.0)\n",
      "Building wheels for collected packages: langdetect\n",
      "  Building wheel for langdetect (setup.py): started\n",
      "  Building wheel for langdetect (setup.py): finished with status 'done'\n",
      "  Created wheel for langdetect: filename=langdetect-1.0.9-py3-none-any.whl size=993242 sha256=e4a81090b5f07f69548b20e061e2528a2b1e15e8fbbf355ba7c531b5674202c7\n",
      "  Stored in directory: c:\\users\\cd202-10\\appdata\\local\\pip\\cache\\wheels\\d1\\c1\\d9\\7e068de779d863bc8f8fc9467d85e25cfe47fa5051fff1a1bb\n",
      "Successfully built langdetect\n",
      "Installing collected packages: langdetect\n",
      "Successfully installed langdetect-1.0.9\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "#pip install langdetect"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting apyori\n",
      "  Downloading apyori-1.1.2.tar.gz (8.6 kB)\n",
      "Building wheels for collected packages: apyori\n",
      "  Building wheel for apyori (setup.py): started\n",
      "  Building wheel for apyori (setup.py): finished with status 'done'\n",
      "  Created wheel for apyori: filename=apyori-1.1.2-py3-none-any.whl size=5974 sha256=6003fd551852225583bc0167277cec2b5f2bf712aa3740fa6bdf0f07a0306bdb\n",
      "  Stored in directory: c:\\users\\cd202-10\\appdata\\local\\pip\\cache\\wheels\\32\\2a\\54\\10c595515f385f3726642b10c60bf788029e8f3a1323e3913a\n",
      "Successfully built apyori\n",
      "Installing collected packages: apyori\n",
      "Successfully installed apyori-1.1.2\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "#pip install apyori"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (Temp/ipykernel_8380/4252503982.py, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"C:\\Users\\cd202-10\\AppData\\Local\\Temp/ipykernel_8380/4252503982.py\"\u001b[1;36m, line \u001b[1;32m1\u001b[0m\n\u001b[1;33m    python -m spacy download en_core_web_sg\u001b[0m\n\u001b[1;37m              ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "# python -m spacy download en_core_web_sg\n",
    "# python -m spacy download en_core_web_sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "## bibliotecas  necessarias\n",
    "import mysql.connector\n",
    "from mysql.connector import Error\n",
    "import pandas as pd\n",
    "import re\n",
    "from datetime import datetime\n",
    "from spacy.lang.en import English\n",
    "from textblob import Word\n",
    "from textblob import TextBlob\n",
    "from spacy.lang.en.stop_words import STOP_WORDS\n",
    "import spacy\n",
    "from spacy import displacy\n",
    "from spellchecker import SpellChecker\n",
    "from langdetect import detect\n",
    "from apyori import apriori\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package wordnet to\n",
      "[nltk_data]     C:\\Users\\Pichau\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download('wordnet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "## função para conectar com o banco da locadora\n",
    "def conectaBD():\n",
    "    ## configurações para a conexão com bd\n",
    "    mysql_config = {\n",
    "        ####usuario\n",
    "            'user': 'root',\n",
    "        ####senha\n",
    "            'password': '***',\n",
    "\n",
    "            'host': 'localhost',\n",
    "            'port': '***',\n",
    "            'ssl_disabled': True,\n",
    "        ### nome do bd\n",
    "            'database':'mysq'\n",
    "        }\n",
    "    mydb = mysql.connector.connect(**mysql_config)     \n",
    "    return mydb \n",
    "\n",
    "## função para conectar com o banco do historico de pesquisa\n",
    "def worldBD():\n",
    "        \n",
    "        ##config do bd\n",
    "        mysql_config = {\n",
    "        ####usuario\n",
    "            'user': 'root',\n",
    "        ####senha\n",
    "            'password': '***',\n",
    "            'host': 'localhost',\n",
    "            'port': '***',\n",
    "            'ssl_disabled': True,\n",
    "        ### nome do bd\n",
    "            'database':'world_x'\n",
    "        }\n",
    "    ### para conectar    \n",
    "        worldXBD = mysql.connector.connect(**mysql_config)\n",
    "        return worldXBD  \n",
    "    \n",
    "def historicoBD():\n",
    "        \n",
    "        ##config do bd\n",
    "        mysql_config = {\n",
    "        ####usuario\n",
    "            'user': 'root',\n",
    "        ####senha\n",
    "            'password': '***',\n",
    "            'host': 'localhost',\n",
    "            'port': '***',\n",
    "            'ssl_disabled': True,\n",
    "        ### nome do bd\n",
    "            'database':'historico'\n",
    "        }\n",
    "    ### para conectar    \n",
    "        mydb_hist = mysql.connector.connect(**mysql_config)\n",
    "        return mydb_hist \n",
    "    \n",
    "def tvBD():\n",
    "    ## configurações para a conexão com bd\n",
    "    mysql_config = {\n",
    "        ####usuario\n",
    "            'user': 'root',\n",
    "        ####senha\n",
    "            'password': '***',\n",
    "\n",
    "            'host': 'localhost',\n",
    "            'port': '***',\n",
    "            'ssl_disabled': True,\n",
    "        ### nome do bd\n",
    "            'database':'tv'\n",
    "        }\n",
    "    mydb_tv = mysql.connector.connect(**mysql_config)\n",
    "        \n",
    "            \n",
    "    return mydb_tv "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "aluguel\n"
     ]
    },
    {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>aluguel_id</th>\n",
       "      <th>data_de_aluguel</th>\n",
       "      <th>inventario_id</th>\n",
       "      <th>cliente_id</th>\n",
       "      <th>data_de_devolucao</th>\n",
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       "      <td>2</td>\n",
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       "      <td>2079</td>\n",
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       "      <td>1</td>\n",
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       "      <td>1</td>\n",
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       "      <td>74</td>\n",
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       "      <td>2</td>\n",
       "      <td>2006-02-15 21:30:53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16041</th>\n",
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       "      <td>2</td>\n",
       "      <td>2006-02-15 21:30:53</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16044 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       aluguel_id     data_de_aluguel  inventario_id  cliente_id  \\\n",
       "0               1 2005-05-24 22:53:30            367         130   \n",
       "1               2 2005-05-24 22:54:33           1525         459   \n",
       "2               3 2005-05-24 23:03:39           1711         408   \n",
       "3               4 2005-05-24 23:04:41           2452         333   \n",
       "4               5 2005-05-24 23:05:21           2079         222   \n",
       "...           ...                 ...            ...         ...   \n",
       "16039       16045 2005-08-23 22:25:26            772          14   \n",
       "16040       16046 2005-08-23 22:26:47           4364          74   \n",
       "16041       16047 2005-08-23 22:42:48           2088         114   \n",
       "16042       16048 2005-08-23 22:43:07           2019         103   \n",
       "16043       16049 2005-08-23 22:50:12           2666         393   \n",
       "\n",
       "        data_de_devolucao  funcionario_id  ultima_atualizacao  \n",
       "0     2005-05-26 22:04:30               1 2006-02-15 21:30:53  \n",
       "1     2005-05-28 19:40:33               1 2006-02-15 21:30:53  \n",
       "2     2005-06-01 22:12:39               1 2006-02-15 21:30:53  \n",
       "3     2005-06-03 01:43:41               2 2006-02-15 21:30:53  \n",
       "4     2005-06-02 04:33:21               1 2006-02-15 21:30:53  \n",
       "...                   ...             ...                 ...  \n",
       "16039 2005-08-25 23:54:26               1 2006-02-15 21:30:53  \n",
       "16040 2005-08-27 18:02:47               2 2006-02-15 21:30:53  \n",
       "16041 2005-08-25 02:48:48               2 2006-02-15 21:30:53  \n",
       "16042 2005-08-31 21:33:07               1 2006-02-15 21:30:53  \n",
       "16043 2005-08-30 01:01:12               2 2006-02-15 21:30:53  \n",
       "\n",
       "[16044 rows x 7 columns]"
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       "      <th>195</th>\n",
       "      <td>196</td>\n",
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       "      <th>197</th>\n",
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       "<p>200 rows × 4 columns</p>\n",
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       "     ator_id primeiro_nome   ultimo_nome  ultima_atualizacao\n",
       "0          1      PENELOPE       GUINESS 2006-02-15 04:34:33\n",
       "1          2          NICK      WAHLBERG 2006-02-15 04:34:33\n",
       "2          3            ED         CHASE 2006-02-15 04:34:33\n",
       "3          4      JENNIFER         DAVIS 2006-02-15 04:34:33\n",
       "4          5        JOHNNY  LOLLOBRIGIDA 2006-02-15 04:34:33\n",
       "..       ...           ...           ...                 ...\n",
       "195      196          BELA        WALKEN 2006-02-15 04:34:33\n",
       "196      197         REESE          WEST 2006-02-15 04:34:33\n",
       "197      198          MARY        KEITEL 2006-02-15 04:34:33\n",
       "198      199         JULIA       FAWCETT 2006-02-15 04:34:33\n",
       "199      200         THORA        TEMPLE 2006-02-15 04:34:33\n",
       "\n",
       "[200 rows x 4 columns]"
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       "      <td>2006-02-15 04:46:27</td>\n",
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       "      <th>14</th>\n",
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       "</div>"
      ],
      "text/plain": [
       "    categoria_id         nome  ultima_atualizacao\n",
       "0              1       Action 2006-02-15 04:46:27\n",
       "1              2    Animation 2006-02-15 04:46:27\n",
       "2              3     Children 2006-02-15 04:46:27\n",
       "3              4     Classics 2006-02-15 04:46:27\n",
       "4              5       Comedy 2006-02-15 04:46:27\n",
       "5              6  Documentary 2006-02-15 04:46:27\n",
       "6              7        Drama 2006-02-15 04:46:27\n",
       "7              8       Family 2006-02-15 04:46:27\n",
       "8              9      Foreign 2006-02-15 04:46:27\n",
       "9             10        Games 2006-02-15 04:46:27\n",
       "10            11       Horror 2006-02-15 04:46:27\n",
       "11            12        Music 2006-02-15 04:46:27\n",
       "12            13          New 2006-02-15 04:46:27\n",
       "13            14       Sci-Fi 2006-02-15 04:46:27\n",
       "14            15       Sports 2006-02-15 04:46:27\n",
       "15            16       Travel 2006-02-15 04:46:27"
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      "cidade\n"
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>A Corua (La Corua)</td>\n",
       "      <td>87</td>\n",
       "      <td>2006-02-15 04:45:25</td>\n",
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       "      <th>1</th>\n",
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       "      <td>Abha</td>\n",
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       "      <th>595</th>\n",
       "      <td>596</td>\n",
       "      <td>Zaria</td>\n",
       "      <td>69</td>\n",
       "      <td>2006-02-15 04:45:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>596</th>\n",
       "      <td>597</td>\n",
       "      <td>Zeleznogorsk</td>\n",
       "      <td>80</td>\n",
       "      <td>2006-02-15 04:45:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>597</th>\n",
       "      <td>598</td>\n",
       "      <td>Zhezqazghan</td>\n",
       "      <td>51</td>\n",
       "      <td>2006-02-15 04:45:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>598</th>\n",
       "      <td>599</td>\n",
       "      <td>Zhoushan</td>\n",
       "      <td>23</td>\n",
       "      <td>2006-02-15 04:45:25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>599</th>\n",
       "      <td>600</td>\n",
       "      <td>Ziguinchor</td>\n",
       "      <td>83</td>\n",
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       "  </tbody>\n",
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       "<p>600 rows × 4 columns</p>\n",
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       "     cidade_id              cidade  pais_id  ultima_atualizacao\n",
       "0            1  A Corua (La Corua)       87 2006-02-15 04:45:25\n",
       "1            2                Abha       82 2006-02-15 04:45:25\n",
       "2            3           Abu Dhabi      101 2006-02-15 04:45:25\n",
       "3            4                Acua       60 2006-02-15 04:45:25\n",
       "4            5               Adana       97 2006-02-15 04:45:25\n",
       "..         ...                 ...      ...                 ...\n",
       "595        596               Zaria       69 2006-02-15 04:45:25\n",
       "596        597        Zeleznogorsk       80 2006-02-15 04:45:25\n",
       "597        598         Zhezqazghan       51 2006-02-15 04:45:25\n",
       "598        599            Zhoushan       23 2006-02-15 04:45:25\n",
       "599        600          Ziguinchor       83 2006-02-15 04:45:25\n",
       "\n",
       "[600 rows x 4 columns]"
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      "cliente\n"
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       "      <td>SMITH</td>\n",
       "      <td>MARY.SMITH@sakilacustomer.org</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:36</td>\n",
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       "      <td>PATRICIA</td>\n",
       "      <td>JOHNSON</td>\n",
       "      <td>PATRICIA.JOHNSON@sakilacustomer.org</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:36</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>LINDA</td>\n",
       "      <td>WILLIAMS</td>\n",
       "      <td>LINDA.WILLIAMS@sakilacustomer.org</td>\n",
       "      <td>7</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:36</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2</td>\n",
       "      <td>BARBARA</td>\n",
       "      <td>JONES</td>\n",
       "      <td>BARBARA.JONES@sakilacustomer.org</td>\n",
       "      <td>8</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:36</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>ELIZABETH</td>\n",
       "      <td>BROWN</td>\n",
       "      <td>ELIZABETH.BROWN@sakilacustomer.org</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:36</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>594</th>\n",
       "      <td>595</td>\n",
       "      <td>1</td>\n",
       "      <td>TERRENCE</td>\n",
       "      <td>GUNDERSON</td>\n",
       "      <td>TERRENCE.GUNDERSON@sakilacustomer.org</td>\n",
       "      <td>601</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:37</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>595</th>\n",
       "      <td>596</td>\n",
       "      <td>1</td>\n",
       "      <td>ENRIQUE</td>\n",
       "      <td>FORSYTHE</td>\n",
       "      <td>ENRIQUE.FORSYTHE@sakilacustomer.org</td>\n",
       "      <td>602</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:37</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>596</th>\n",
       "      <td>597</td>\n",
       "      <td>1</td>\n",
       "      <td>FREDDIE</td>\n",
       "      <td>DUGGAN</td>\n",
       "      <td>FREDDIE.DUGGAN@sakilacustomer.org</td>\n",
       "      <td>603</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:37</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>597</th>\n",
       "      <td>598</td>\n",
       "      <td>1</td>\n",
       "      <td>WADE</td>\n",
       "      <td>DELVALLE</td>\n",
       "      <td>WADE.DELVALLE@sakilacustomer.org</td>\n",
       "      <td>604</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:37</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>598</th>\n",
       "      <td>599</td>\n",
       "      <td>2</td>\n",
       "      <td>AUSTIN</td>\n",
       "      <td>CINTRON</td>\n",
       "      <td>AUSTIN.CINTRON@sakilacustomer.org</td>\n",
       "      <td>605</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-14 22:04:37</td>\n",
       "      <td>2006-02-15 04:57:20</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>599 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     cliente_id  loja_id primeiro_nome ultimo_nome  \\\n",
       "0             1        1          MARY       SMITH   \n",
       "1             2        1      PATRICIA     JOHNSON   \n",
       "2             3        1         LINDA    WILLIAMS   \n",
       "3             4        2       BARBARA       JONES   \n",
       "4             5        1     ELIZABETH       BROWN   \n",
       "..          ...      ...           ...         ...   \n",
       "594         595        1      TERRENCE   GUNDERSON   \n",
       "595         596        1       ENRIQUE    FORSYTHE   \n",
       "596         597        1       FREDDIE      DUGGAN   \n",
       "597         598        1          WADE    DELVALLE   \n",
       "598         599        2        AUSTIN     CINTRON   \n",
       "\n",
       "                                     email  endereco_id  ativo  \\\n",
       "0            MARY.SMITH@sakilacustomer.org            5      1   \n",
       "1      PATRICIA.JOHNSON@sakilacustomer.org            6      1   \n",
       "2        LINDA.WILLIAMS@sakilacustomer.org            7      1   \n",
       "3         BARBARA.JONES@sakilacustomer.org            8      1   \n",
       "4       ELIZABETH.BROWN@sakilacustomer.org            9      1   \n",
       "..                                     ...          ...    ...   \n",
       "594  TERRENCE.GUNDERSON@sakilacustomer.org          601      1   \n",
       "595    ENRIQUE.FORSYTHE@sakilacustomer.org          602      1   \n",
       "596      FREDDIE.DUGGAN@sakilacustomer.org          603      1   \n",
       "597       WADE.DELVALLE@sakilacustomer.org          604      1   \n",
       "598      AUSTIN.CINTRON@sakilacustomer.org          605      1   \n",
       "\n",
       "           data_criacao  ultima_atualizacao  \n",
       "0   2006-02-14 22:04:36 2006-02-15 04:57:20  \n",
       "1   2006-02-14 22:04:36 2006-02-15 04:57:20  \n",
       "2   2006-02-14 22:04:36 2006-02-15 04:57:20  \n",
       "3   2006-02-14 22:04:36 2006-02-15 04:57:20  \n",
       "4   2006-02-14 22:04:36 2006-02-15 04:57:20  \n",
       "..                  ...                 ...  \n",
       "594 2006-02-14 22:04:37 2006-02-15 04:57:20  \n",
       "595 2006-02-14 22:04:37 2006-02-15 04:57:20  \n",
       "596 2006-02-14 22:04:37 2006-02-15 04:57:20  \n",
       "597 2006-02-14 22:04:37 2006-02-15 04:57:20  \n",
       "598 2006-02-14 22:04:37 2006-02-15 04:57:20  \n",
       "\n",
       "[599 rows x 9 columns]"
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      "endereco\n"
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       "      <td>28 MySQL Boulevard</td>\n",
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       "      <td>401</td>\n",
       "      <td>97661</td>\n",
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       "      <td>2006-02-15 04:45:30</td>\n",
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       "      <th>600</th>\n",
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       "      <td>1103 Quilmes Boulevard</td>\n",
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       "      <td>Piura</td>\n",
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       "      <td>604</td>\n",
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       "      <td>605</td>\n",
       "      <td>1325 Fukuyama Street</td>\n",
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       "      <td>Heilongjiang</td>\n",
       "      <td>537</td>\n",
       "      <td>27107</td>\n",
       "      <td>288241215394</td>\n",
       "      <td>2006-02-15 04:45:30</td>\n",
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       "<p>603 rows × 8 columns</p>\n",
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      "text/plain": [
       "     endereco_id                  endereco endereco2        bairro  cidade_id  \\\n",
       "0              1         47 MySakila Drive      None       Alberta        300   \n",
       "1              2        28 MySQL Boulevard      None           QLD        576   \n",
       "2              3         23 Workhaven Lane      None       Alberta        300   \n",
       "3              4      1411 Lillydale Drive      None           QLD        576   \n",
       "4              5            1913 Hanoi Way                Nagasaki        463   \n",
       "..           ...                       ...       ...           ...        ...   \n",
       "598          601       844 Bucuresti Place                Liaoning        242   \n",
       "599          602  1101 Bucuresti Boulevard             West Greece        401   \n",
       "600          603    1103 Quilmes Boulevard                   Piura        503   \n",
       "601          604       1331 Usak Boulevard                    Vaud        296   \n",
       "602          605      1325 Fukuyama Street            Heilongjiang        537   \n",
       "\n",
       "       cep      telefone  ultima_atualizacao  \n",
       "0                        2006-02-15 04:45:30  \n",
       "1                        2006-02-15 04:45:30  \n",
       "2            14033335568 2006-02-15 04:45:30  \n",
       "3             6172235589 2006-02-15 04:45:30  \n",
       "4    35200   28303384290 2006-02-15 04:45:30  \n",
       "..     ...           ...                 ...  \n",
       "598  36603  935952366111 2006-02-15 04:45:30  \n",
       "599  97661  199514580428 2006-02-15 04:45:30  \n",
       "600  52137  644021380889 2006-02-15 04:45:30  \n",
       "601  61960  145308717464 2006-02-15 04:45:30  \n",
       "602  27107  288241215394 2006-02-15 04:45:30  \n",
       "\n",
       "[603 rows x 8 columns]"
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>ACADEMY DINOSAUR</td>\n",
       "      <td>A Epic Drama of a Feminist And a Mad Scientist...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>6</td>\n",
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       "      <td>86</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>ACE GOLDFINGER</td>\n",
       "      <td>A Astounding Epistle of a Database Administrat...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>3</td>\n",
       "      <td>4.99</td>\n",
       "      <td>48</td>\n",
       "      <td>12.99</td>\n",
       "      <td>G</td>\n",
       "      <td>{Trailers, Deleted Scenes}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>ADAPTATION HOLES</td>\n",
       "      <td>A Astounding Reflection of a Lumberjack And a ...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>7</td>\n",
       "      <td>2.99</td>\n",
       "      <td>50</td>\n",
       "      <td>18.99</td>\n",
       "      <td>NC-17</td>\n",
       "      <td>{Trailers, Deleted Scenes}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>AFFAIR PREJUDICE</td>\n",
       "      <td>A Fanciful Documentary of a Frisbee And a Lumb...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>5</td>\n",
       "      <td>2.99</td>\n",
       "      <td>117</td>\n",
       "      <td>26.99</td>\n",
       "      <td>G</td>\n",
       "      <td>{Commentaries, Behind the Scenes}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>AFRICAN EGG</td>\n",
       "      <td>A Fast-Paced Documentary of a Pastry Chef And ...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>6</td>\n",
       "      <td>2.99</td>\n",
       "      <td>130</td>\n",
       "      <td>22.99</td>\n",
       "      <td>G</td>\n",
       "      <td>{Deleted Scenes}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>996</td>\n",
       "      <td>YOUNG LANGUAGE</td>\n",
       "      <td>A Unbelieveable Yarn of a Boat And a Database ...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>6</td>\n",
       "      <td>0.99</td>\n",
       "      <td>183</td>\n",
       "      <td>9.99</td>\n",
       "      <td>G</td>\n",
       "      <td>{Behind the Scenes, Trailers}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>997</td>\n",
       "      <td>YOUTH KICK</td>\n",
       "      <td>A Touching Drama of a Teacher And a Cat who mu...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>4</td>\n",
       "      <td>0.99</td>\n",
       "      <td>179</td>\n",
       "      <td>14.99</td>\n",
       "      <td>NC-17</td>\n",
       "      <td>{Behind the Scenes, Trailers}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>998</td>\n",
       "      <td>ZHIVAGO CORE</td>\n",
       "      <td>A Fateful Yarn of a Composer And a Man who mus...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>6</td>\n",
       "      <td>0.99</td>\n",
       "      <td>105</td>\n",
       "      <td>10.99</td>\n",
       "      <td>NC-17</td>\n",
       "      <td>{Deleted Scenes}</td>\n",
       "      <td>2006-02-15 05:03:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>999</td>\n",
       "      <td>ZOOLANDER FICTION</td>\n",
       "      <td>A Fateful Reflection of a Waitress And a Boat ...</td>\n",
       "      <td>2006</td>\n",
       "      <td>1</td>\n",
       "      <td>None</td>\n",
       "      <td>5</td>\n",
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       "     filme_id             titulo  \\\n",
       "0           1   ACADEMY DINOSAUR   \n",
       "1           2     ACE GOLDFINGER   \n",
       "2           3   ADAPTATION HOLES   \n",
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       "\n",
       "                                             descricao  ano_de_lancamento  \\\n",
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       "\n",
       "     duracao_do_filme  custo_de_substituicao classificacao  \\\n",
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       "\n",
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       "999  {Commentaries, Trailers, Behind the Scenes} 2006-02-15 05:03:42  \n",
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       "<table border=\"1\" class=\"dataframe\">\n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>inventario_id</th>\n",
       "      <th>filme_id</th>\n",
       "      <th>loja_id</th>\n",
       "      <th>ultima_atualizacao</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
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       "      <td>1</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
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       "      <th>3</th>\n",
       "      <td>4</td>\n",
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       "      <td>1</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>4576</th>\n",
       "      <td>4577</td>\n",
       "      <td>1000</td>\n",
       "      <td>1</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4577</th>\n",
       "      <td>4578</td>\n",
       "      <td>1000</td>\n",
       "      <td>2</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4578</th>\n",
       "      <td>4579</td>\n",
       "      <td>1000</td>\n",
       "      <td>2</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4579</th>\n",
       "      <td>4580</td>\n",
       "      <td>1000</td>\n",
       "      <td>2</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4580</th>\n",
       "      <td>4581</td>\n",
       "      <td>1000</td>\n",
       "      <td>2</td>\n",
       "      <td>2006-02-15 05:09:17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4581 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      inventario_id  filme_id  loja_id  ultima_atualizacao\n",
       "0                 1         1        1 2006-02-15 05:09:17\n",
       "1                 2         1        1 2006-02-15 05:09:17\n",
       "2                 3         1        1 2006-02-15 05:09:17\n",
       "3                 4         1        1 2006-02-15 05:09:17\n",
       "4                 5         1        2 2006-02-15 05:09:17\n",
       "...             ...       ...      ...                 ...\n",
       "4576           4577      1000        1 2006-02-15 05:09:17\n",
       "4577           4578      1000        2 2006-02-15 05:09:17\n",
       "4578           4579      1000        2 2006-02-15 05:09:17\n",
       "4579           4580      1000        2 2006-02-15 05:09:17\n",
       "4580           4581      1000        2 2006-02-15 05:09:17\n",
       "\n",
       "[4581 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loja\n"
     ]
    },
    {
     "data": {
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       "      <th>endereco_id</th>\n",
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      "text/plain": [
       "   loja_id  gerente_id  endereco_id  ultima_atualizacao\n",
       "0        1           1            1 2006-02-15 04:57:12\n",
       "1        2           2            2 2006-02-15 04:57:12"
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     "text": [
      "pagamento\n"
     ]
    },
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     "data": {
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       "      <th></th>\n",
       "      <th>pagamento_id</th>\n",
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       "      <th>funcionario_id</th>\n",
       "      <th>aluguel_id</th>\n",
       "      <th>valor</th>\n",
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       "      <td>2005-06-15 00:54:12</td>\n",
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       "      <td>14719.0</td>\n",
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       "      <td>2005-08-21 21:41:57</td>\n",
       "      <td>2006-02-15 22:24:12</td>\n",
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       "      <td>15590.0</td>\n",
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       "      <td>2006-02-15 22:24:12</td>\n",
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       "      <td>2005-08-23 11:25:00</td>\n",
       "      <td>2006-02-15 22:24:13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>16049 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       pagamento_id  cliente_id  funcionario_id  aluguel_id  valor  \\\n",
       "0                 1           1               1        76.0   2.99   \n",
       "1                 2           1               1       573.0   0.99   \n",
       "2                 3           1               1      1185.0   5.99   \n",
       "3                 4           1               2      1422.0   0.99   \n",
       "4                 5           1               2      1476.0   9.99   \n",
       "...             ...         ...             ...         ...    ...   \n",
       "16044         16045         599               1     14599.0   4.99   \n",
       "16045         16046         599               1     14719.0   1.99   \n",
       "16046         16047         599               2     15590.0   8.99   \n",
       "16047         16048         599               2     15719.0   2.99   \n",
       "16048         16049         599               2     15725.0   2.99   \n",
       "\n",
       "        data_de_pagamento  ultima_atualizacao  \n",
       "0     2005-05-25 11:30:37 2006-02-15 22:12:30  \n",
       "1     2005-05-28 10:35:23 2006-02-15 22:12:30  \n",
       "2     2005-06-15 00:54:12 2006-02-15 22:12:30  \n",
       "3     2005-06-15 18:02:53 2006-02-15 22:12:30  \n",
       "4     2005-06-15 21:08:46 2006-02-15 22:12:30  \n",
       "...                   ...                 ...  \n",
       "16044 2005-08-21 17:43:42 2006-02-15 22:24:12  \n",
       "16045 2005-08-21 21:41:57 2006-02-15 22:24:12  \n",
       "16046 2005-08-23 06:09:44 2006-02-15 22:24:12  \n",
       "16047 2005-08-23 11:08:46 2006-02-15 22:24:13  \n",
       "16048 2005-08-23 11:25:00 2006-02-15 22:24:13  \n",
       "\n",
       "[16049 rows x 7 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pais\n"
     ]
    },
    {
     "data": {
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Algeria</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>American Samoa</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Angola</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Anguilla</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <th>104</th>\n",
       "      <td>105</td>\n",
       "      <td>Vietnam</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>106</td>\n",
       "      <td>Virgin Islands, U.S.</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>107</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>108</td>\n",
       "      <td>Yugoslavia</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>109</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>2006-02-15 04:44:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>109 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     pais_id                  pais  ultima_atualizacao\n",
       "0          1           Afghanistan 2006-02-15 04:44:00\n",
       "1          2               Algeria 2006-02-15 04:44:00\n",
       "2          3        American Samoa 2006-02-15 04:44:00\n",
       "3          4                Angola 2006-02-15 04:44:00\n",
       "4          5              Anguilla 2006-02-15 04:44:00\n",
       "..       ...                   ...                 ...\n",
       "104      105               Vietnam 2006-02-15 04:44:00\n",
       "105      106  Virgin Islands, U.S. 2006-02-15 04:44:00\n",
       "106      107                 Yemen 2006-02-15 04:44:00\n",
       "107      108            Yugoslavia 2006-02-15 04:44:00\n",
       "108      109                Zambia 2006-02-15 04:44:00\n",
       "\n",
       "[109 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## mostra todas as tabelas \n",
    "tabelas = ['aluguel','ator','categoria','cidade','cliente','endereco','filme','filme_ator','filme_categoria','filme_texto','funcionario','idioma','inventario','loja','pagamento','pais']\n",
    "\n",
    "for x in tabelas:\n",
    "    print(x)\n",
    "    df = pd.read_sql(\"SELECT * FROM {}\".format(x),conectaBD())\n",
    "    display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "city\n"
     ]
    },
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>cities</th>\n",
       "      <th>CountryCode</th>\n",
       "      <th>District</th>\n",
       "      <th>Info</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Kabul</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Kabol</td>\n",
       "      <td>{\"Population\": 1780000}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Qandahar</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Qandahar</td>\n",
       "      <td>{\"Population\": 237500}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Herat</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Herat</td>\n",
       "      <td>{\"Population\": 186800}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Mazar-e-Sharif</td>\n",
       "      <td>AFG</td>\n",
       "      <td>Balkh</td>\n",
       "      <td>{\"Population\": 127800}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Amsterdam</td>\n",
       "      <td>NLD</td>\n",
       "      <td>Noord-Holland</td>\n",
       "      <td>{\"Population\": 731200}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4074</th>\n",
       "      <td>4075</td>\n",
       "      <td>Khan Yunis</td>\n",
       "      <td>PSE</td>\n",
       "      <td>Khan Yunis</td>\n",
       "      <td>{\"Population\": 123175}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4075</th>\n",
       "      <td>4076</td>\n",
       "      <td>Hebron</td>\n",
       "      <td>PSE</td>\n",
       "      <td>Hebron</td>\n",
       "      <td>{\"Population\": 119401}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4076</th>\n",
       "      <td>4077</td>\n",
       "      <td>Jabaliya</td>\n",
       "      <td>PSE</td>\n",
       "      <td>North Gaza</td>\n",
       "      <td>{\"Population\": 113901}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4077</th>\n",
       "      <td>4078</td>\n",
       "      <td>Nablus</td>\n",
       "      <td>PSE</td>\n",
       "      <td>Nablus</td>\n",
       "      <td>{\"Population\": 100231}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4078</th>\n",
       "      <td>4079</td>\n",
       "      <td>Rafah</td>\n",
       "      <td>PSE</td>\n",
       "      <td>Rafah</td>\n",
       "      <td>{\"Population\": 92020}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4079 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        ID          cities CountryCode       District                     Info\n",
       "0        1           Kabul         AFG          Kabol  {\"Population\": 1780000}\n",
       "1        2        Qandahar         AFG       Qandahar   {\"Population\": 237500}\n",
       "2        3           Herat         AFG          Herat   {\"Population\": 186800}\n",
       "3        4  Mazar-e-Sharif         AFG          Balkh   {\"Population\": 127800}\n",
       "4        5       Amsterdam         NLD  Noord-Holland   {\"Population\": 731200}\n",
       "...    ...             ...         ...            ...                      ...\n",
       "4074  4075      Khan Yunis         PSE     Khan Yunis   {\"Population\": 123175}\n",
       "4075  4076          Hebron         PSE         Hebron   {\"Population\": 119401}\n",
       "4076  4077        Jabaliya         PSE     North Gaza   {\"Population\": 113901}\n",
       "4077  4078          Nablus         PSE         Nablus   {\"Population\": 100231}\n",
       "4078  4079           Rafah         PSE          Rafah    {\"Population\": 92020}\n",
       "\n",
       "[4079 rows x 5 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "country\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Code</th>\n",
       "      <th>nomec</th>\n",
       "      <th>Capital</th>\n",
       "      <th>Code2</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABW</td>\n",
       "      <td>Aruba</td>\n",
       "      <td>129.0</td>\n",
       "      <td>AW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>1.0</td>\n",
       "      <td>AF</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AGO</td>\n",
       "      <td>Angola</td>\n",
       "      <td>56.0</td>\n",
       "      <td>AO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AIA</td>\n",
       "      <td>Anguilla</td>\n",
       "      <td>62.0</td>\n",
       "      <td>AI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ALB</td>\n",
       "      <td>Albania</td>\n",
       "      <td>34.0</td>\n",
       "      <td>AL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>YEM</td>\n",
       "      <td>Yemen</td>\n",
       "      <td>1780.0</td>\n",
       "      <td>YE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>YUG</td>\n",
       "      <td>Yugoslavia</td>\n",
       "      <td>1792.0</td>\n",
       "      <td>YU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>ZAF</td>\n",
       "      <td>South Africa</td>\n",
       "      <td>716.0</td>\n",
       "      <td>ZA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>ZMB</td>\n",
       "      <td>Zambia</td>\n",
       "      <td>3162.0</td>\n",
       "      <td>ZM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Zimbabwe</td>\n",
       "      <td>4068.0</td>\n",
       "      <td>ZW</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>239 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Code         nomec  Capital Code2\n",
       "0    ABW         Aruba    129.0    AW\n",
       "1    AFG   Afghanistan      1.0    AF\n",
       "2    AGO        Angola     56.0    AO\n",
       "3    AIA      Anguilla     62.0    AI\n",
       "4    ALB       Albania     34.0    AL\n",
       "..   ...           ...      ...   ...\n",
       "234  YEM         Yemen   1780.0    YE\n",
       "235  YUG    Yugoslavia   1792.0    YU\n",
       "236  ZAF  South Africa    716.0    ZA\n",
       "237  ZMB        Zambia   3162.0    ZM\n",
       "238  ZWE      Zimbabwe   4068.0    ZW\n",
       "\n",
       "[239 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "countryinfo\n"
     ]
    },
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>{\"GNP\": 828, \"_id\": \"00005de917d80000000000000...</td>\n",
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       "      <td>{\"type\": \"object\"}</td>\n",
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       "      <th>1</th>\n",
       "      <td>{\"GNP\": 5976, \"_id\": \"00005de917d8000000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>{\"GNP\": 6648, \"_id\": \"00005de917d8000000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>{\"GNP\": 63.20000076293945, \"_id\": \"00005de917d...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>{\"GNP\": 3205, \"_id\": \"00005de917d8000000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>{\"GNP\": 6041, \"_id\": \"00005de917d8000000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>{\"GNP\": 17000, \"_id\": \"00005de917d800000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>{\"GNP\": 116729, \"_id\": \"00005de917d80000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
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       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>{\"GNP\": 3377, \"_id\": \"00005de917d8000000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>{\"GNP\": 5951, \"_id\": \"00005de917d8000000000000...</td>\n",
       "      <td>[48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...</td>\n",
       "      <td>{\"type\": \"object\"}</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>239 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   doc  \\\n",
       "0    {\"GNP\": 828, \"_id\": \"00005de917d80000000000000...   \n",
       "1    {\"GNP\": 5976, \"_id\": \"00005de917d8000000000000...   \n",
       "2    {\"GNP\": 6648, \"_id\": \"00005de917d8000000000000...   \n",
       "3    {\"GNP\": 63.20000076293945, \"_id\": \"00005de917d...   \n",
       "4    {\"GNP\": 3205, \"_id\": \"00005de917d8000000000000...   \n",
       "..                                                 ...   \n",
       "234  {\"GNP\": 6041, \"_id\": \"00005de917d8000000000000...   \n",
       "235  {\"GNP\": 17000, \"_id\": \"00005de917d800000000000...   \n",
       "236  {\"GNP\": 116729, \"_id\": \"00005de917d80000000000...   \n",
       "237  {\"GNP\": 3377, \"_id\": \"00005de917d8000000000000...   \n",
       "238  {\"GNP\": 5951, \"_id\": \"00005de917d8000000000000...   \n",
       "\n",
       "                                                   _id        _json_schema  \n",
       "0    [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "1    [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "2    [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "3    [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "4    [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "..                                                 ...                 ...  \n",
       "234  [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "235  [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "236  [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "237  [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "238  [48, 48, 48, 48, 53, 100, 101, 57, 49, 55, 100...  {\"type\": \"object\"}  \n",
       "\n",
       "[239 rows x 3 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "countrylanguage\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>CountryCode</th>\n",
       "      <th>Language</th>\n",
       "      <th>IsOfficial</th>\n",
       "      <th>Percentage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ABW</td>\n",
       "      <td>Dutch</td>\n",
       "      <td>T</td>\n",
       "      <td>5.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABW</td>\n",
       "      <td>English</td>\n",
       "      <td>F</td>\n",
       "      <td>9.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABW</td>\n",
       "      <td>Papiamento</td>\n",
       "      <td>F</td>\n",
       "      <td>76.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ABW</td>\n",
       "      <td>Spanish</td>\n",
       "      <td>F</td>\n",
       "      <td>7.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AFG</td>\n",
       "      <td>Balochi</td>\n",
       "      <td>F</td>\n",
       "      <td>0.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>ZMB</td>\n",
       "      <td>Tongan</td>\n",
       "      <td>F</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>English</td>\n",
       "      <td>T</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Ndebele</td>\n",
       "      <td>F</td>\n",
       "      <td>16.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Nyanja</td>\n",
       "      <td>F</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>ZWE</td>\n",
       "      <td>Shona</td>\n",
       "      <td>F</td>\n",
       "      <td>72.1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>984 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    CountryCode    Language IsOfficial  Percentage\n",
       "0           ABW       Dutch          T         5.3\n",
       "1           ABW     English          F         9.5\n",
       "2           ABW  Papiamento          F        76.7\n",
       "3           ABW     Spanish          F         7.4\n",
       "4           AFG     Balochi          F         0.9\n",
       "..          ...         ...        ...         ...\n",
       "979         ZMB      Tongan          F        11.0\n",
       "980         ZWE     English          T         2.2\n",
       "981         ZWE     Ndebele          F        16.2\n",
       "982         ZWE      Nyanja          F         2.2\n",
       "983         ZWE       Shona          F        72.1\n",
       "\n",
       "[984 rows x 4 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## mostra todas as tabelas \n",
    "tabelas = ['city','country','countryinfo','countrylanguage']\n",
    "\n",
    "for x in tabelas:\n",
    "    print(x)\n",
    "    df = pd.read_sql(\"SELECT * FROM {}\".format(x),worldBD())\n",
    "    display(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>marca_tv</th>\n",
       "      <th>resolucao_tv</th>\n",
       "      <th>tamanho_tv</th>\n",
       "      <th>precoV_tv</th>\n",
       "      <th>precoO_tv</th>\n",
       "      <th>so_tv</th>\n",
       "      <th>rate_tv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>TOSHIBA</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>37999</td>\n",
       "      <td>54990</td>\n",
       "      <td>VIDAA</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>TCL</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>52999</td>\n",
       "      <td>129990</td>\n",
       "      <td>Android</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>realme</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>13999</td>\n",
       "      <td>17999</td>\n",
       "      <td>Android</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Mi</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>14999</td>\n",
       "      <td>19999</td>\n",
       "      <td>Android</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>realme</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>12999</td>\n",
       "      <td>21999</td>\n",
       "      <td>Android</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>907</th>\n",
       "      <td>SONY</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>44999</td>\n",
       "      <td>57900</td>\n",
       "      <td>Linux</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>908</th>\n",
       "      <td>SONY</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>40</td>\n",
       "      <td>41499</td>\n",
       "      <td>51900</td>\n",
       "      <td>Linux</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>909</th>\n",
       "      <td>SONY</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>149990</td>\n",
       "      <td>184990</td>\n",
       "      <td>Linux</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>910</th>\n",
       "      <td>SONY</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>32900</td>\n",
       "      <td>32900</td>\n",
       "      <td>Linux</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>911</th>\n",
       "      <td>SONY</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>56900</td>\n",
       "      <td>56900</td>\n",
       "      <td>Linux</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>912 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    marca_tv   resolucao_tv  tamanho_tv  precoV_tv  precoO_tv    so_tv  \\\n",
       "0    TOSHIBA   Ultra HD LED          55      37999      54990    VIDAA   \n",
       "1       TCL   QLED Ultra HD          55      52999     129990  Android   \n",
       "2    realme          HD LED          32      13999      17999  Android   \n",
       "3        Mi          HD LED          32      14999      19999  Android   \n",
       "4    realme          HD LED          32      12999      21999  Android   \n",
       "..       ...            ...         ...        ...        ...      ...   \n",
       "907    SONY     Full HD LED          43      44999      57900    Linux   \n",
       "908    SONY     Full HD LED          40      41499      51900    Linux   \n",
       "909    SONY    Ultra HD LED          65     149990     184990    Linux   \n",
       "910    SONY          HD LED          32      32900      32900    Linux   \n",
       "911    SONY     Full HD LED          43      56900      56900    Linux   \n",
       "\n",
       "     rate_tv  \n",
       "0        4.3  \n",
       "1        4.4  \n",
       "2        4.3  \n",
       "3        4.4  \n",
       "4        4.3  \n",
       "..       ...  \n",
       "907      4.4  \n",
       "908      4.6  \n",
       "909      4.3  \n",
       "910      4.4  \n",
       "911      4.6  \n",
       "\n",
       "[912 rows x 7 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_sql(\"SELECT * FROM tvs\",tvBD())\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "### função de filtro que separa as palavras e remove conectores\n",
    "def filtered(search):\n",
    "   \n",
    "    ## recebe from textblob biblioteca para reformulação da palavras\n",
    "     #############################\n",
    "    #lista\n",
    "    lem = []\n",
    "    ##separa as palavras e reformula ela\n",
    "    for i in search.split():\n",
    "        word1 = Word(i).lemmatize(\"n\")\n",
    "        word2 = Word(word1).lemmatize(\"v\")\n",
    "        word3 = Word(word2).lemmatize(\"a\")\n",
    "        lem.append(Word(word3).lemmatize())\n",
    "    #############################\n",
    "    ##usa spacy para retirar os conectores\n",
    "     ##filtro para ingles\n",
    "    nlp = English()\n",
    "    ##lista para guardar o que foi filtrado\n",
    "    filtered_sentence =[] \n",
    "    ##remove os conectores\n",
    "    for word in lem:\n",
    "        lexeme = nlp.vocab[word]\n",
    "        if lexeme.is_stop == False:\n",
    "            filtered_sentence.append(word) \n",
    "    ##retorna as palavras filtradas\n",
    "    return filtered_sentence\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "##Classifica as palavras com base na biblioteca do Spacy\n",
    "##função\n",
    "def ner(search):\n",
    "    ##lista vazia\n",
    "    entities = []\n",
    "    ##carrega a biblioteca do NER do spacy***ingles\n",
    "    NER = spacy.load(\"en_core_web_sm\")\n",
    "    ##repetição que interage com cada palvra da função de filtragem \n",
    "    for i in filtered(search):\n",
    "        ##classifica a palavra com a biblioteca ner\n",
    "        text1= NER(i)\n",
    "        ##interage com cada palvra e guarda a classicificação na lista entities\n",
    "        for word in text1.ents:\n",
    "             entities.append(word.label_)\n",
    "    ##retorna a lista                \n",
    "    return entities  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "## função\n",
    "def historico(search):\n",
    "    ## pega a data de hoje\n",
    "    now = datetime.now()\n",
    "    ## mapeia a data\n",
    "    d1 = now.strftime(\"%Y-%m-%d %H:%M:%S\")\n",
    "    ## codigo sql para adicionar no bd\n",
    "    insert = \"INSERT INTO hist (hist_texto, hist_data) VALUES (%s, %s)\"\n",
    "    ## variavel contendo o texto da pesquisa e a data de agora\n",
    "    val = (search,d1)\n",
    "    ## armazena o bd em uma variavel\n",
    "    bd=historicoBD()\n",
    "    ##adiciona um cursor localmente\n",
    "    cursor = bd.cursor()\n",
    "    ##adiciona no bd\n",
    "    cursor.execute(insert, val)\n",
    "    bd.commit()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "##verificador de texto\n",
    "def verificadorTexto(search):\n",
    "    ## mostra o texto antes das palavras corrigidas\n",
    "    print(\"Voce quis dizer\",end = ' ')\n",
    "    ##interage com cada palavvra que foi separada da função filtro\n",
    "    for word in filtered(search):\n",
    "        ##detecta o idioma\n",
    "        lang = detect(search)\n",
    "        ## pega o idioma e corrigi de acordo com ele\n",
    "        ## se ele for diferente de portugues, ingles e espanhol ele corrige em portugues\n",
    "        if str(lang) !='pt' or  str(lang) !='en' or str(lang) !='es':\n",
    "            ##mostra a palavra corrigida em portugues para idiomas diferentes de pt, en e es\n",
    "            print(str(SpellChecker(language='pt').correction(word)),end = ' ')  \n",
    "        else:\n",
    "            print(str(SpellChecker(language=str(lang)).correction(word)),end = ' ')\n",
    "    return\n",
    "  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "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>Palavra 1</th>\n",
       "      <th>Palavra 2</th>\n",
       "      <th>Support</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>action</td>\n",
       "      <td>movie</td>\n",
       "      <td>0.044944</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Palavra 1 Palavra 2   Support\n",
       "6    action     movie  0.044944"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "search = 'action'\n",
    "##função da pesquisa relacionadas\n",
    "def pesquisaRelacionadas(search):\n",
    "    ##codigo sql para chamar o historico\n",
    "    sql = 'SELECT * FROM hist '\n",
    "    ## le a tabela do historico  de pesquisa\n",
    "    df = pd.read_sql(sql,historicoBD())\n",
    "    ###variavel vazia onde ira conter as palavras no historico separadas\n",
    "    df2=[]\n",
    "    ##repetição para interagir com cada linha do historico e usar a função do filtro que radicalizar as palavras\n",
    "    for index, row in df.iterrows():\n",
    "        word=np.array(filtered(row['hist_texto']))\n",
    "        df2.append(word)\n",
    "    #### passa df2 para tipo dataframe\n",
    "    df2=pd.DataFrame(df2)\n",
    "    ###lista de palavras\n",
    "    listaDePalavra = []\n",
    "    ##tem que transformar cada posição do df2 em string\n",
    "    for i in range(0, len(df2)):\n",
    "        listaDePalavra.append([str(df2.values[i,j]) for j in range(0, len(df. columns)+1)])\n",
    "    ###metodo Regra de Associação\n",
    "    rules = apriori(transactions = listaDePalavra, min_support = 0.003, min_confidence = 0.2, min_lift = 3, min_length = 2, max_length = 2)\n",
    "    ###resultado\n",
    "    results = list(rules)\n",
    "    ##função que retorna os resultados em dicionario\n",
    "    def inspect(results):\n",
    "        lhs         = [tuple(result[2][0][0])[0] for result in results]\n",
    "        rhs         = [tuple(result[2][0][1])[0] for result in results]\n",
    "        supports    = [result[1] for result in results]\n",
    "        return list(zip(lhs, rhs, supports))\n",
    "    ###transforma em dataframe\n",
    "    resultsinDataFrame = pd.DataFrame(inspect(results), columns = ['Palavra 1', 'Palavra 2', 'Support'])\n",
    "    ##transforma em dataframe e mostra por ordem de maior suporte\n",
    "    resultados=resultsinDataFrame.nlargest(n = 10, columns = 'Support')\n",
    "    ###localiza as linhas que contem as palavras pesquisadas\n",
    "    resultados=resultados[resultados['Palavra 1'].str.contains(search) | resultados['Palavra 2'].str.contains(search)]\n",
    "    ###mostra os resultados\n",
    "    return resultados \n",
    "\n",
    "pesquisaRelacionadas(search)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Metodo de pesquisa 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# original(dataframe pandas na saida)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pesquise na biblioteca: tv samsung\n",
      "Voce quis dizer tv samsung "
     ]
    },
    {
     "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>Marca</th>\n",
       "      <th>Resolução</th>\n",
       "      <th>Polegadas</th>\n",
       "      <th>Preço</th>\n",
       "      <th>Sistema Operacional</th>\n",
       "      <th>Rate</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>38990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>18490</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>51990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>16290</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>76999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>55990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>20880</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>50</td>\n",
       "      <td>84999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>50</td>\n",
       "      <td>68999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>32999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36580</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>50</td>\n",
       "      <td>73990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>43</td>\n",
       "      <td>59990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>41900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>21600</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>121990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>128999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>57989</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>84990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>45400</td>\n",
       "      <td>Linux</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>29900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>59990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>159500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>55790</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>89390</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>85990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>318700</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>44870</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>38999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>64299</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>224999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>104900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>144990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>163738</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>295900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>53200</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>148990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>49990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>294900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>38990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>159500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>49</td>\n",
       "      <td>74990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>75</td>\n",
       "      <td>169990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>84999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>179900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>62900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>470900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>61890</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>199990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>204900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>314900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>64499</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>89990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>43</td>\n",
       "      <td>59700</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>75</td>\n",
       "      <td>239999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>241900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>122299</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>258999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>62980</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>118900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>129900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>18490</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>89990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>125900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>51990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>274900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>50</td>\n",
       "      <td>69990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>45785</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>121999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>48</td>\n",
       "      <td>49990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>75</td>\n",
       "      <td>159990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>44990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>162900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>145900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>89850</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>139990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>167199</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>105990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>154900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>65999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>144900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>122290</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>284900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>103990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>24</td>\n",
       "      <td>15200</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>45700</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>146900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>19599</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>65</td>\n",
       "      <td>219990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>89990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>50</td>\n",
       "      <td>69744</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>23000</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>149900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>129900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>136500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>49</td>\n",
       "      <td>84990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>48900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>94990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>2.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>49</td>\n",
       "      <td>64990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>QLED Ultra HD</td>\n",
       "      <td>55</td>\n",
       "      <td>105990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>17999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>26900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>52890</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>229900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>67990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>49</td>\n",
       "      <td>92500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>31990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36890</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>39999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>51999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>34999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>43751</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36514</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>11999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>36106</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>24726</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>15210</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>43</td>\n",
       "      <td>35999</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>17499</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>40</td>\n",
       "      <td>19929</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>Samsung</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>50</td>\n",
       "      <td>36900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>40</td>\n",
       "      <td>33000</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>20126</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>15990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>13990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>46</td>\n",
       "      <td>87500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>178900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>46</td>\n",
       "      <td>145500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>60</td>\n",
       "      <td>210900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>160500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Samsung</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>46</td>\n",
       "      <td>139990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Samsung</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>189900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>267000</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>218900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Samsung</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>249990</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>Samsung</td>\n",
       "      <td>HD Plasma</td>\n",
       "      <td>43</td>\n",
       "      <td>45000</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>246900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Ultra HD LED</td>\n",
       "      <td>55</td>\n",
       "      <td>178500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Samsung</td>\n",
       "      <td>HD Plasma</td>\n",
       "      <td>49</td>\n",
       "      <td>68000</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>32</td>\n",
       "      <td>35700</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>3.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>65</td>\n",
       "      <td>385500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>Full HD LED</td>\n",
       "      <td>75</td>\n",
       "      <td>419900</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>SAMSUNG</td>\n",
       "      <td>HD LED</td>\n",
       "      <td>48</td>\n",
       "      <td>70500</td>\n",
       "      <td>Tizen</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Marca      Resolução  Polegadas   Preço Sistema Operacional  Rate\n",
       "0    SAMSUNG   Ultra HD LED         43   38990               Tizen   4.3\n",
       "1    SAMSUNG         HD LED         32   18490               Tizen   4.3\n",
       "2    SAMSUNG   Ultra HD LED         50   51990               Tizen   4.3\n",
       "3    SAMSUNG         HD LED         32   16290               Tizen   4.3\n",
       "4    SAMSUNG  QLED Ultra HD         55   76999               Tizen   4.5\n",
       "5    SAMSUNG   Ultra HD LED         55   55990               Tizen   4.3\n",
       "6    SAMSUNG    Full HD LED         32   20880               Tizen   4.2\n",
       "7    SAMSUNG  QLED Ultra HD         50   84999               Tizen   4.8\n",
       "8    SAMSUNG  QLED Ultra HD         50   68999               Tizen   4.5\n",
       "9    SAMSUNG    Full HD LED         43   32999               Tizen   4.4\n",
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   "source": [
    "## barra de pesquisa\n",
    "search = input('pesquise na biblioteca: ')\n",
    "## guarda o que foi pesquisado no bd historico\n",
    "historico(search)\n",
    "##verificador de texto se ele tiver errado\n",
    "verificadorTexto(search)    \n",
    "##########################################\n",
    "## função \n",
    "def pesquisa(search):\n",
    "    ##variaveis usadas\n",
    "    df = pd.DataFrame()\n",
    "    veriMovie= False\n",
    "    veriMovieCat = False\n",
    "    veriCounty= False\n",
    "    numberVeri= False\n",
    "    veriTV = False\n",
    "    menorPrecoCheck = False\n",
    "    maiorPrecoCheck = False\n",
    "    menortmhCheck = False\n",
    "    maiortmhCheck = False\n",
    "    categorias=['action','horror','animation','children','classics','comedy','documentary','drama','family','foreign','games','horror','music','new','sci-fi','sports','travel']\n",
    "    #########\n",
    "    \n",
    "    pd.set_option('display.max_rows', None)\n",
    "    ### chama função filtered para separar as palavras e remover os conectores\n",
    "    res = filtered(search)        \n",
    "     ###faz a pesquisa no banco\n",
    "    ##verifica se o texto esta em branco\n",
    "    if search:\n",
    "        ##named entity classification(ner)\n",
    "        ner(search)\n",
    "        ##anda pelos ner\n",
    "        for x in ner(search):\n",
    "            ##se for gpe(cidade, estdos e paises)\n",
    "            if x =='GPE':\n",
    "                ##variavel booleana do pais como verdade\n",
    "                veriCounty = True\n",
    "            ### se for numero, variavel booleana de numero true\n",
    "            elif x =='CARDINAL':\n",
    "                numberVeri =True\n",
    "        ##anda pela lista\n",
    "        for x in res:\n",
    "            ##se um item da lista for igual\n",
    "            if x =='movie' or x =='filme' or x =='Movie' or x =='Filme' :\n",
    "                ##bool verdadeira\n",
    "                veriMovie = True\n",
    "                ##remove a palavra\n",
    "                res.remove(x)\n",
    "                for x in res:\n",
    "                    for i in categorias:\n",
    "                        if x.lower()==i:\n",
    "                            veriMovieCat=True\n",
    "          ### ler as palavras da pesquisa\n",
    "        for x in res:\n",
    "            ### se for tv\n",
    "            if x.upper() =='TV':\n",
    "                ##bool da tv True\n",
    "                veriTV = True\n",
    "                res.remove(x)\n",
    "        if veriTV == True:  \n",
    "            ### verifica se tem uma das palvras é preço\n",
    "            for x in res:\n",
    "                if x=='price' or x=='preço' or x =='preco':\n",
    "                    res.remove(x)\n",
    "                    ##### verifica se tem uma das palvras é menor\n",
    "                    for x in res:\n",
    "                        if x =='menor' or x =='low' or x =='lowest':\n",
    "\n",
    "                            menorPrecoCheck = True\n",
    "                            maiorPrecoCheck=False\n",
    "                        ### verifica se tem uma das palvras é maior\n",
    "                        elif x =='maior' or x =='high' or x =='highest':\n",
    "\n",
    "                            maiorPrecoCheck=True\n",
    "                            menorPrecoCheck = False\n",
    "                ### verifica se tem uma das palvras é tamanho da tv\n",
    "                elif x=='tamanho' or x=='size' or x=='polegada' or x=='polegadas':\n",
    "                    res.remove(x)\n",
    "                    for x in res:\n",
    "                        ### verifica se tem uma das palvras é menor\n",
    "                        if x =='menor' or x =='low' or x =='lowest':\n",
    "\n",
    "                            menortmhCheck = True\n",
    "                            maiortmhCheck=False\n",
    "                         ### verifica se tem uma das palvras é   \n",
    "                        elif x =='maior' or x =='high' or x =='highest':\n",
    "\n",
    "                            maiortmhCheck=True\n",
    "                            menortmhCheck = False\n",
    "                            \n",
    "                \n",
    "        if  veriMovie == True:\n",
    "            if veriMovieCat==False:\n",
    "                for x in res:\n",
    "\n",
    "                    ##verifica se o item da lista é numero inteiro e pesquisa no banco\n",
    "                    if type(x)==int:\n",
    "                        ##codigo sql\n",
    "                        sql = '''\n",
    "            SELECT * \n",
    "            FROM filme \n",
    "            Inner JOIN idioma ON filme.idioma_id = idioma.idioma_id \n",
    "            Inner JOIN filme_ator ON filme.filme_id = filme_ator.filme_id \n",
    "            Inner JOIN ator ON filme_ator.ator_id =ator.ator_id \n",
    "            Inner JOIN filme_categoria ON filme.filme_id =filme_categoria.filme_id \n",
    "            Inner JOIN categoria ON filme_categoria.categoria_id = categoria.categoria_id   \n",
    "            WHERE concat(ano_de_lancamento,duracao_do_filme) \n",
    "            LIKE '%{}%' \n",
    "\n",
    "            '''\n",
    "                        ## pesquisa no banco e faz o JOIN com a tabela de idiomas mostrando o idioma do filme\n",
    "                        dflocal = pd.read_sql(sql.format(x),conectaBD())\n",
    "                        df = df.append(dflocal)\n",
    "                    ####se for string pesquisa no banco em tabelas onde os dados são string\n",
    "                    else:\n",
    "                        ##codigo sql \n",
    "                        sqlLike = '''\n",
    "            SELECT * \n",
    "            FROM filme \n",
    "            Inner JOIN idioma ON filme.idioma_id = idioma.idioma_id \n",
    "            Inner JOIN filme_ator ON filme.filme_id = filme_ator.filme_id \n",
    "            Inner JOIN ator ON filme_ator.ator_id =ator.ator_id \n",
    "            Inner JOIN filme_categoria ON filme.filme_id =filme_categoria.filme_id \n",
    "            Inner JOIN categoria ON filme_categoria.categoria_id = categoria.categoria_id   \n",
    "            WHERE concat(titulo,classificacao,primeiro_nome,ultimo_nome) \n",
    "            LIKE '%{}%'\n",
    "\n",
    "\n",
    "            '''\n",
    "\n",
    "                        ## pesquisa no banco e faz o JOIN com a tabela de idiomas mostrando o idioma do filme\n",
    "                        dflocal = pd.read_sql(sqlLike.format(x.upper()),conectaBD())\n",
    "\n",
    "                        df = df.append(dflocal)\n",
    "            else:\n",
    "                for x in res:\n",
    "                    sql='''\n",
    "                    select filme.titulo,filme.descricao,categoria.nome\n",
    "                    from categoria\n",
    "                    inner join filme_categoria on categoria.categoria_id=filme_categoria.categoria_id\n",
    "                    inner join filme on filme.filme_id=filme_categoria.filme_id\n",
    "                    where concat(nome) like '%{}%'\n",
    "                    '''\n",
    "                    dflocal = pd.read_sql(sql.format(x.upper()),conectaBD())\n",
    "\n",
    "                    df = df.append(dflocal)\n",
    "         ##se bool de filme for falsa pesquisa na base de paises           \n",
    "        ##se a variavel do pais for true entra aqui\n",
    "        elif veriCounty ==True:\n",
    "            ##bool de pais true\n",
    "            \n",
    "            ##anda pelas as palavras para pesquisa-las\n",
    "            for x in res:        \n",
    "#                 ##sql das cidades para palvras completamente igual\n",
    "                sql = '''\n",
    "            SELECT * \n",
    "            FROM city \n",
    "            RIGHT JOIN country ON city.CountryCode = country.Code\n",
    "            RIGHT JOIN countrylanguage ON city.CountryCode = countrylanguage.CountryCode\n",
    "            WHERE concat(cities) \n",
    "            = '{}' \n",
    "           \n",
    "\n",
    "            '''\n",
    "                ## pesquisa no banco e faz o JOIN \n",
    "                dflocal = pd.read_sql(sql.format(x.upper()),worldBD())\n",
    "            ## se não encontrar nada pesquisa com like\n",
    "                if dflocal.empty==True:\n",
    "                    ##codigo sql para like\n",
    "                    sql = '''\n",
    "            SELECT * \n",
    "            FROM city \n",
    "            Inner JOIN country ON city.CountryCode = country.Code\n",
    "            Inner JOIN countrylanguage ON city.CountryCode = countrylanguage.CountryCode\n",
    "            WHERE concat(cities) \n",
    "            like '%{}%' \n",
    "           \n",
    "\n",
    "            '''\n",
    "                    ## pesquisa no banco e faz o JOIN \n",
    "                    dflocal = pd.read_sql(sql.format(x.upper()),worldBD())\n",
    "                    ##retorno\n",
    "                    df = df.append(dflocal)\n",
    "                else:\n",
    "                    ##retorno\n",
    "                    df = df.append(dflocal)\n",
    "        ### verifica a boleana tv\n",
    "        elif veriTV ==True:\n",
    "            ### pesquisa geral da tv sem filtro\n",
    "            if veriTV ==True and menorPrecoCheck==False and maiorPrecoCheck==False and  menortmhCheck==False \\\n",
    "            and maiortmhCheck==False:\n",
    "                for x in res:\n",
    "                    sqlTV = \"select * from tvs where concat(marca_tv) LIKE '%{}%'\"\n",
    "                    dflocal = pd.read_sql(sqlTV.format(x.upper()),tvBD())\n",
    "                    df = df.append(dflocal)\n",
    "            ### se quer preço menor\n",
    "            elif veriTV ==True and menorPrecoCheck==True and maiorPrecoCheck==False :\n",
    "\n",
    "                for x in res:\n",
    "                    sqlTV = '''\n",
    "                    select * from tvs where concat(marca_tv,resolucao_tv,so_tv) LIKE '%{}%' group by  \n",
    "                    precoV_tv order by precoV_tv ASC'''\n",
    "                    dflocal = pd.read_sql(sqlTV.format(x.upper()),tvBD())\n",
    "                    df = df.append(dflocal)\n",
    "            ### se quer maior preço\n",
    "            elif veriTV ==True and maiorPrecoCheck==True and menorPrecoCheck==False:\n",
    "\n",
    "                for x in res:\n",
    "                    sqlTV = '''\n",
    "                    select * from tvs where concat(marca_tv,resolucao_tv,so_tv) LIKE '%{}%' group by  \n",
    "                    precoV_tv order by precoV_tv DESC'''\n",
    "                    dflocal = pd.read_sql(sqlTV.format(x.upper()),tvBD())\n",
    "                    df = df.append(dflocal)\n",
    "\n",
    "            ############################################################\n",
    "            ### se quer menor tamanho\n",
    "            elif veriTV ==True and menortmhCheck==True and maiortmhCheck==False :\n",
    "                for x in res:\n",
    "                    sqlTV = '''\n",
    "                    select * from tvs where concat(marca_tv,resolucao_tv,so_tv) LIKE '%{}%' group by  tamanho_tv \n",
    "                    order by tamanho_tv ASC'''\n",
    "                    dflocal = pd.read_sql(sqlTV.format(x.upper()),tvBD())\n",
    "                    df = df.append(dflocal)\n",
    "            ### se quer maior tamanho\n",
    "            elif veriTV ==True and menortmhCheck==False and maiortmhCheck==True:\n",
    "                for x in res:\n",
    "                    sqlTV = '''\n",
    "                    select * from tvs where concat(marca_tv,resolucao_tv,so_tv) LIKE '%{}%' group by  \n",
    "                    tamanho_tv order by tamanho_tv DESC'''\n",
    "                    dflocal = pd.read_sql(sqlTV.format(x.upper()),tvBD())\n",
    "                    df = df.append(dflocal)\n",
    "        ####################################################################\n",
    "        ### se nenhuma das variaveis classificatorias derem verdade, ele faz uma pesquisa geral em todos os bancos\n",
    "        else:\n",
    "            for x in res:\n",
    "                \n",
    "                sqlcities = '''\n",
    "                SELECT * \n",
    "                FROM city \n",
    "                Inner JOIN country ON city.CountryCode = country.Code\n",
    "                Inner JOIN countrylanguage ON city.CountryCode = countrylanguage.CountryCode\n",
    "                WHERE concat(cities) \n",
    "                LIKE '%{}%' \n",
    "\n",
    "\n",
    "                '''\n",
    "                sqlmovie = '''\n",
    "            SELECT * \n",
    "            FROM filme \n",
    "            Inner JOIN idioma ON filme.idioma_id = idioma.idioma_id \n",
    "            Inner JOIN filme_ator ON filme.filme_id = filme_ator.filme_id \n",
    "            Inner JOIN ator ON filme_ator.ator_id =ator.ator_id \n",
    "            Inner JOIN filme_categoria ON filme.filme_id =filme_categoria.filme_id \n",
    "            Inner JOIN categoria ON filme_categoria.categoria_id = categoria.categoria_id   \n",
    "            WHERE concat(titulo,classificacao,primeiro_nome,ultimo_nome) \n",
    "            LIKE '%{}%'\n",
    "\n",
    "\n",
    "            '''\n",
    "                sqlTV = \"select * from tvs where concat(marca_tv,resolucao_tv,so_tv) LIKE '%{}%'\"\n",
    "               \n",
    "            ##pesquisas gerais   \n",
    "                dfcities = pd.read_sql(sqlcities.format(x.upper()),worldBD())\n",
    "                if dfcities.empty==False:\n",
    "                    display(dfcities)\n",
    "                \n",
    "                dfmovie= pd.read_sql(sqlmovie.format(x.upper()),conectaBD())\n",
    "                if dfmovie.empty==False:\n",
    "                    display(dfmovie)\n",
    "                \n",
    "                dftv = pd.read_sql(sqlTV.format(x.upper()),tvBD())\n",
    "                if dftv.empty==False:\n",
    "                    display(dftv)\n",
    "            \n",
    "        \n",
    "        \n",
    "################################\n",
    "    #limpeza nas tabelas\n",
    "    if veriMovie ==True and veriMovieCat==False:\n",
    "        ### junta o primeiro e ultimo nome do ator para formar uma coluna\n",
    "        df[\"Ator\"] = df[\"primeiro_nome\"] +' '+ df[\"ultimo_nome\"]\n",
    "         ### tira algumas colunas\n",
    "        df.drop(columns=['filme_id','idioma_id','idioma_original_id', 'ultima_atualizacao','custo_de_substituicao','ator_id','categoria_id','primeiro_nome','ultimo_nome'],inplace=True)\n",
    "        ### remove os duplicados\n",
    "        df.drop_duplicates(subset=['titulo'],inplace=True)\n",
    "        ### ele modifica os nomes de colunas iguais,isso facilita o renomear\n",
    "        cols=pd.Series(df.columns)\n",
    "        for dup in cols[cols.duplicated()].unique(): \n",
    "            cols[cols[cols == dup].index.values.tolist()] = [dup + '.' + str(i) if i != 0 else dup for i in range(sum(cols == dup))]\n",
    "        df.columns=cols\n",
    "        ### renomeia colunas com nomes iguais\n",
    "        df.rename(columns = {'nome':'Idioma','nome.1':'Categoria'}, inplace = True)\n",
    "        ## reseta o index\n",
    "        df = df.reset_index(drop=True)\n",
    "        ### mostra o resultado/os\n",
    "    elif veriCounty==True:\n",
    "\n",
    "\n",
    "#     #         ### junta o primeiro e ultimo nome do ator para formar uma coluna\n",
    "#             df[\"Ator\"] = df[\"primeiro_nome\"] +' '+ df[\"ultimo_nome\"]\n",
    "#          ### tira algumas colunas\n",
    "        df.drop(columns=['ID','CountryCode','Code', 'Code2'],inplace=True)\n",
    "#         ### remove os duplicados\n",
    "#          df.drop_duplicates(subset=['titulo'],inplace=True)\n",
    "#         ### ele modifica os nomes de colunas iguais,isso facilita o renomear\n",
    "        cols=pd.Series(df.columns)\n",
    "        for dup in cols[cols.duplicated()].unique(): \n",
    "            cols[cols[cols == dup].index.values.tolist()] = [dup + '.' + str(i) if i != 0 else dup for i in range(sum(cols == dup))]\n",
    "        df.columns=cols\n",
    "#         ### renomeia colunas com nomes iguais\n",
    "        df.rename(columns = {'Name':'Cidade','nomec':'País','Info':'População','Language':'Lingua','Percentage':'Porcentual'}, inplace = True)\n",
    "         \n",
    "    #         ## reseta o index\n",
    "        df = df.reset_index(drop=True)\n",
    "    #         ### mostra o resultado/os\n",
    "    elif veriTV ==True:\n",
    "        df.rename(columns = {'marca_tv':'Marca','resolucao_tv':'Resolução','tamanho_tv':'Polegadas','precoV_tv':'Preço','so_tv':'Sistema Operacional','rate_tv':'Rate'}, inplace = True)\n",
    "        df.drop(columns=['precoO_tv'],inplace=True)\n",
    "        df = df.reset_index(drop=True)\n",
    "    if df.empty==False:\n",
    "        display(df)\n",
    "    \n",
    "\n",
    "\n",
    "\n",
    " \n",
    "    return\n",
    "#################################################\n",
    "\n",
    "\n",
    "## chama a função =  o botão devera chamar\n",
    "pesquisa(search)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Guardar Historico de pesquisa e visualizar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>hist_texto</th>\n",
       "      <th>hist_data</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pesquisa pesquisa e pesquisa</td>\n",
       "      <td>2022-03-21 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>pesquisa pesquisa e pesquisa</td>\n",
       "      <td>2022-03-21 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>pesquisa pesquisa e pesquisa</td>\n",
       "      <td>2022-03-21 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-22 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-22 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-25 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-28 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-28 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-28 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>aaansjdnajnsjdnajsnd</td>\n",
       "      <td>2022-03-28 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>test 1</td>\n",
       "      <td>2022-03-28 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>kabul</td>\n",
       "      <td>2022-04-04 00:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>movie youth</td>\n",
       "      <td>2022-04-04 15:18:32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>tv lg</td>\n",
       "      <td>2022-05-19 19:24:42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>television lg</td>\n",
       "      <td>2022-05-19 19:25:44</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      hist_texto           hist_data\n",
       "0   pesquisa pesquisa e pesquisa 2022-03-21 00:00:00\n",
       "1   pesquisa pesquisa e pesquisa 2022-03-21 00:00:00\n",
       "2   pesquisa pesquisa e pesquisa 2022-03-21 00:00:00\n",
       "3           aaansjdnajnsjdnajsnd 2022-03-22 00:00:00\n",
       "4           aaansjdnajnsjdnajsnd 2022-03-22 00:00:00\n",
       "5           aaansjdnajnsjdnajsnd 2022-03-25 00:00:00\n",
       "6           aaansjdnajnsjdnajsnd 2022-03-28 00:00:00\n",
       "7           aaansjdnajnsjdnajsnd 2022-03-28 00:00:00\n",
       "8           aaansjdnajnsjdnajsnd 2022-03-28 00:00:00\n",
       "9           aaansjdnajnsjdnajsnd 2022-03-28 00:00:00\n",
       "10                        test 1 2022-03-28 00:00:00\n",
       "11                         kabul 2022-04-04 00:00:00\n",
       "12                   movie youth 2022-04-04 15:18:32\n",
       "13                         tv lg 2022-05-19 19:24:42\n",
       "14                 television lg 2022-05-19 19:25:44"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def historicoView():\n",
    "    \n",
    "    ##codigo sql   \n",
    "    sql = '''\n",
    "                SELECT * \n",
    "                FROM hist \n",
    "\n",
    "\n",
    "     '''\n",
    "    ## le a tabela do historico  de pesquisa\n",
    "    df = pd.read_sql(sql,historicoBD())\n",
    "    #mostra\n",
    "    display(df)\n",
    "historicoView()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ## codigo para criar o banco do historico\n",
    "# create database historico;\n",
    "# use historico;\n",
    "# create table hist(\n",
    "# hist_id int NOT NULL AUTO_INCREMENT,\n",
    "# hist_texto varchar (400),\n",
    "# hist_data datetime NOT NULL,\n",
    "# primary key(hist_id)\n",
    "# )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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