Exercises/draft/Exercicios_Revisao_A2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exercícios de Revisão A2\n",
    "--\n",
    "Professor: Renato Rocha Souza  \n",
    "--"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [],
   "source": [
    "import itertools\n",
    "import random\n",
    "from collections import Counter\n",
    "import re\n",
    "import string\n",
    "\n",
    "import pymysql\n",
    "import sqlite3\n",
    "import getpass\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import pandas.io.sql as psql\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parte I - Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Para o Dataframe abaixo, resolva as seguintes tarefas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "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>animal</th>\n",
       "      <th>hair</th>\n",
       "      <th>feathers</th>\n",
       "      <th>eggs</th>\n",
       "      <th>milk</th>\n",
       "      <th>airborne</th>\n",
       "      <th>aquatic</th>\n",
       "      <th>predator</th>\n",
       "      <th>toothed</th>\n",
       "      <th>backbone</th>\n",
       "      <th>breathes</th>\n",
       "      <th>venomous</th>\n",
       "      <th>fins</th>\n",
       "      <th>legs</th>\n",
       "      <th>tail</th>\n",
       "      <th>domestic</th>\n",
       "      <th>catsize</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardvark</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>antelope</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>bass</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>fish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>bear</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>boar</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     animal   hair  feathers   eggs   milk  airborne  aquatic  predator  \\\n",
       "0  aardvark   True     False  False   True     False    False      True   \n",
       "1  antelope   True     False  False   True     False    False     False   \n",
       "2      bass  False     False   True  False     False     True      True   \n",
       "3      bear   True     False  False   True     False    False      True   \n",
       "4      boar   True     False  False   True     False    False      True   \n",
       "\n",
       "   toothed  backbone  breathes  venomous   fins  legs   tail  domestic  \\\n",
       "0     True      True      True     False  False     4  False     False   \n",
       "1     True      True      True     False  False     4   True     False   \n",
       "2     True      True     False     False   True     0   True     False   \n",
       "3     True      True      True     False  False     4  False     False   \n",
       "4     True      True      True     False  False     4   True     False   \n",
       "\n",
       "   catsize    type  \n",
       "0     True  mammal  \n",
       "1     True  mammal  \n",
       "2    False    fish  \n",
       "3     True  mammal  \n",
       "4     True  mammal  "
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zoo = pd.read_csv('../Dados/zoo.csv')\n",
    "df_zoo.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "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>animal</th>\n",
       "      <th>hair</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardvark</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>antelope</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>bass</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     animal   hair\n",
       "0  aardvark   True\n",
       "1  antelope   True\n",
       "2      bass  False"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zoo.loc[:2,['animal','hair']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "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>animal</th>\n",
       "      <th>hair</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardvark</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>antelope</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     animal  hair\n",
       "0  aardvark  True\n",
       "1  antelope  True"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zoo.iloc[0:2,0:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1 - Crie uma série somente com os nomes dos animais (primeira coluna)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df_zoo.animal)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2 - Transforme os campos booleanos True/False em strings \"True\"/\"False\"  \n",
    "Veja as dicas [aqui](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.apply.html) e [aqui](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.applymap.html)  \n",
    "\n",
    "Obs: O Pandas já inferiu que as variáveis originais são de tipo booleano, mas como você faria se não o fossem; se fossem strings, por exemplo?  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 101 entries, 0 to 100\n",
      "Data columns (total 18 columns):\n",
      "animal      101 non-null object\n",
      "hair        101 non-null bool\n",
      "feathers    101 non-null bool\n",
      "eggs        101 non-null bool\n",
      "milk        101 non-null bool\n",
      "airborne    101 non-null bool\n",
      "aquatic     101 non-null bool\n",
      "predator    101 non-null bool\n",
      "toothed     101 non-null bool\n",
      "backbone    101 non-null bool\n",
      "breathes    101 non-null bool\n",
      "venomous    101 non-null bool\n",
      "fins        101 non-null bool\n",
      "legs        101 non-null int64\n",
      "tail        101 non-null bool\n",
      "domestic    101 non-null bool\n",
      "catsize     101 non-null bool\n",
      "type        101 non-null object\n",
      "dtypes: bool(15), int64(1), object(2)\n",
      "memory usage: 3.9+ KB\n"
     ]
    }
   ],
   "source": [
    "df_zoo.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.bool_"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(df_zoo.hair[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 101 entries, 0 to 100\n",
      "Data columns (total 18 columns):\n",
      "animal      101 non-null object\n",
      "hair        101 non-null object\n",
      "feathers    101 non-null bool\n",
      "eggs        101 non-null bool\n",
      "milk        101 non-null bool\n",
      "airborne    101 non-null bool\n",
      "aquatic     101 non-null bool\n",
      "predator    101 non-null bool\n",
      "toothed     101 non-null bool\n",
      "backbone    101 non-null bool\n",
      "breathes    101 non-null bool\n",
      "venomous    101 non-null bool\n",
      "fins        101 non-null bool\n",
      "legs        101 non-null int64\n",
      "tail        101 non-null bool\n",
      "domestic    101 non-null bool\n",
      "catsize     101 non-null bool\n",
      "type        101 non-null object\n",
      "dtypes: bool(14), int64(1), object(3)\n",
      "memory usage: 4.6+ KB\n"
     ]
    }
   ],
   "source": [
    "df_zoo.hair = df_zoo.hair.apply(lambda x:str(x))\n",
    "df_zoo.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 101 entries, 0 to 100\n",
      "Data columns (total 18 columns):\n",
      "animal      101 non-null object\n",
      "hair        101 non-null object\n",
      "feathers    101 non-null object\n",
      "eggs        101 non-null bool\n",
      "milk        101 non-null bool\n",
      "airborne    101 non-null bool\n",
      "aquatic     101 non-null bool\n",
      "predator    101 non-null bool\n",
      "toothed     101 non-null bool\n",
      "backbone    101 non-null bool\n",
      "breathes    101 non-null bool\n",
      "venomous    101 non-null bool\n",
      "fins        101 non-null bool\n",
      "legs        101 non-null int64\n",
      "tail        101 non-null bool\n",
      "domestic    101 non-null bool\n",
      "catsize     101 non-null bool\n",
      "type        101 non-null object\n",
      "dtypes: bool(13), int64(1), object(4)\n",
      "memory usage: 5.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_zoo.feathers = df_zoo.feathers.map({True:'Verdadeiro', False:'Falso'})\n",
    "df_zoo.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['eggs', 'milk', 'airborne', 'aquatic', 'predator', 'toothed',\n",
       "       'backbone', 'breathes', 'venomous', 'fins', 'tail', 'domestic',\n",
       "       'catsize'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zoo.loc[:, df_zoo.dtypes == bool].columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>eggs</th>\n",
       "      <th>milk</th>\n",
       "      <th>airborne</th>\n",
       "      <th>aquatic</th>\n",
       "      <th>predator</th>\n",
       "      <th>toothed</th>\n",
       "      <th>backbone</th>\n",
       "      <th>breathes</th>\n",
       "      <th>venomous</th>\n",
       "      <th>fins</th>\n",
       "      <th>tail</th>\n",
       "      <th>domestic</th>\n",
       "      <th>catsize</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    eggs   milk  airborne  aquatic  predator  toothed  backbone  breathes  \\\n",
       "0  False   True     False    False      True     True      True      True   \n",
       "1  False   True     False    False     False     True      True      True   \n",
       "2   True  False     False     True      True     True      True     False   \n",
       "3  False   True     False    False      True     True      True      True   \n",
       "4  False   True     False    False      True     True      True      True   \n",
       "\n",
       "   venomous   fins   tail  domestic  catsize  \n",
       "0     False  False  False     False     True  \n",
       "1     False  False   True     False     True  \n",
       "2     False   True   True     False    False  \n",
       "3     False  False  False     False     True  \n",
       "4     False  False   True     False     True  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "booleanas = df_zoo.loc[:, df_zoo.dtypes == bool].columns\n",
    "df_zoo[booleanas].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 101 entries, 0 to 100\n",
      "Data columns (total 18 columns):\n",
      "animal      101 non-null object\n",
      "hair        101 non-null object\n",
      "feathers    101 non-null object\n",
      "eggs        101 non-null int64\n",
      "milk        101 non-null int64\n",
      "airborne    101 non-null int64\n",
      "aquatic     101 non-null int64\n",
      "predator    101 non-null int64\n",
      "toothed     101 non-null int64\n",
      "backbone    101 non-null int64\n",
      "breathes    101 non-null int64\n",
      "venomous    101 non-null int64\n",
      "fins        101 non-null int64\n",
      "legs        101 non-null int64\n",
      "tail        101 non-null int64\n",
      "domestic    101 non-null int64\n",
      "catsize     101 non-null int64\n",
      "type        101 non-null object\n",
      "dtypes: int64(14), object(4)\n",
      "memory usage: 14.3+ KB\n"
     ]
    }
   ],
   "source": [
    "df_zoo[booleanas] = df_zoo[booleanas].applymap(lambda x:int(x))\n",
    "df_zoo.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3 - Crie um novo dataframe somente com os Mamíferos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>animal</th>\n",
       "      <th>hair</th>\n",
       "      <th>feathers</th>\n",
       "      <th>eggs</th>\n",
       "      <th>milk</th>\n",
       "      <th>airborne</th>\n",
       "      <th>aquatic</th>\n",
       "      <th>predator</th>\n",
       "      <th>toothed</th>\n",
       "      <th>backbone</th>\n",
       "      <th>breathes</th>\n",
       "      <th>venomous</th>\n",
       "      <th>fins</th>\n",
       "      <th>legs</th>\n",
       "      <th>tail</th>\n",
       "      <th>domestic</th>\n",
       "      <th>catsize</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>aardvark</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>antelope</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>bear</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>boar</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>buffalo</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>calf</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>cavy</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>cheetah</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>deer</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>dolphin</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>elephant</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>fruitbat</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>giraffe</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>girl</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>goat</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>gorilla</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>hamster</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>hare</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>leopard</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>lion</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>lynx</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>mink</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>mole</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>mongoose</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>opossum</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>oryx</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>platypus</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>polecat</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>pony</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>porpoise</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>puma</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>pussycat</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>raccoon</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>reindeer</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>seal</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>sealion</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>squirrel</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>vampire</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>vole</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>wallaby</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>2</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>wolf</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>4</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      animal   hair  feathers   eggs  milk  airborne  aquatic  predator  \\\n",
       "0   aardvark   True     False  False  True     False    False      True   \n",
       "1   antelope   True     False  False  True     False    False     False   \n",
       "3       bear   True     False  False  True     False    False      True   \n",
       "4       boar   True     False  False  True     False    False      True   \n",
       "5    buffalo   True     False  False  True     False    False     False   \n",
       "6       calf   True     False  False  True     False    False     False   \n",
       "9       cavy   True     False  False  True     False    False     False   \n",
       "10   cheetah   True     False  False  True     False    False      True   \n",
       "17      deer   True     False  False  True     False    False     False   \n",
       "19   dolphin  False     False  False  True     False     True      True   \n",
       "22  elephant   True     False  False  True     False    False     False   \n",
       "27  fruitbat   True     False  False  True      True    False     False   \n",
       "28   giraffe   True     False  False  True     False    False     False   \n",
       "29      girl   True     False  False  True     False    False      True   \n",
       "31      goat   True     False  False  True     False    False     False   \n",
       "32   gorilla   True     False  False  True     False    False     False   \n",
       "35   hamster   True     False  False  True     False    False     False   \n",
       "36      hare   True     False  False  True     False    False     False   \n",
       "44   leopard   True     False  False  True     False    False      True   \n",
       "45      lion   True     False  False  True     False    False      True   \n",
       "47      lynx   True     False  False  True     False    False      True   \n",
       "48      mink   True     False  False  True     False     True      True   \n",
       "49      mole   True     False  False  True     False    False      True   \n",
       "50  mongoose   True     False  False  True     False    False      True   \n",
       "54   opossum   True     False  False  True     False    False      True   \n",
       "55      oryx   True     False  False  True     False    False     False   \n",
       "63  platypus   True     False   True  True     False     True      True   \n",
       "64   polecat   True     False  False  True     False    False      True   \n",
       "65      pony   True     False  False  True     False    False     False   \n",
       "66  porpoise  False     False  False  True     False     True      True   \n",
       "67      puma   True     False  False  True     False    False      True   \n",
       "68  pussycat   True     False  False  True     False    False      True   \n",
       "69   raccoon   True     False  False  True     False    False      True   \n",
       "70  reindeer   True     False  False  True     False    False     False   \n",
       "74      seal   True     False  False  True     False     True      True   \n",
       "75   sealion   True     False  False  True     False     True      True   \n",
       "84  squirrel   True     False  False  True     False    False     False   \n",
       "93   vampire   True     False  False  True      True    False     False   \n",
       "94      vole   True     False  False  True     False    False     False   \n",
       "96   wallaby   True     False  False  True     False    False     False   \n",
       "98      wolf   True     False  False  True     False    False      True   \n",
       "\n",
       "    toothed  backbone  breathes  venomous   fins  legs   tail  domestic  \\\n",
       "0      True      True      True     False  False     4  False     False   \n",
       "1      True      True      True     False  False     4   True     False   \n",
       "3      True      True      True     False  False     4  False     False   \n",
       "4      True      True      True     False  False     4   True     False   \n",
       "5      True      True      True     False  False     4   True     False   \n",
       "6      True      True      True     False  False     4   True      True   \n",
       "9      True      True      True     False  False     4  False      True   \n",
       "10     True      True      True     False  False     4   True     False   \n",
       "17     True      True      True     False  False     4   True     False   \n",
       "19     True      True      True     False   True     0   True     False   \n",
       "22     True      True      True     False  False     4   True     False   \n",
       "27     True      True      True     False  False     2   True     False   \n",
       "28     True      True      True     False  False     4   True     False   \n",
       "29     True      True      True     False  False     2  False      True   \n",
       "31     True      True      True     False  False     4   True      True   \n",
       "32     True      True      True     False  False     2  False     False   \n",
       "35     True      True      True     False  False     4   True      True   \n",
       "36     True      True      True     False  False     4   True     False   \n",
       "44     True      True      True     False  False     4   True     False   \n",
       "45     True      True      True     False  False     4   True     False   \n",
       "47     True      True      True     False  False     4   True     False   \n",
       "48     True      True      True     False  False     4   True     False   \n",
       "49     True      True      True     False  False     4   True     False   \n",
       "50     True      True      True     False  False     4   True     False   \n",
       "54     True      True      True     False  False     4   True     False   \n",
       "55     True      True      True     False  False     4   True     False   \n",
       "63    False      True      True     False  False     4   True     False   \n",
       "64     True      True      True     False  False     4   True     False   \n",
       "65     True      True      True     False  False     4   True      True   \n",
       "66     True      True      True     False   True     0   True     False   \n",
       "67     True      True      True     False  False     4   True     False   \n",
       "68     True      True      True     False  False     4   True      True   \n",
       "69     True      True      True     False  False     4   True     False   \n",
       "70     True      True      True     False  False     4   True      True   \n",
       "74     True      True      True     False   True     0  False     False   \n",
       "75     True      True      True     False   True     2   True     False   \n",
       "84     True      True      True     False  False     2   True     False   \n",
       "93     True      True      True     False  False     2   True     False   \n",
       "94     True      True      True     False  False     4   True     False   \n",
       "96     True      True      True     False  False     2   True     False   \n",
       "98     True      True      True     False  False     4   True     False   \n",
       "\n",
       "    catsize    type  \n",
       "0      True  mammal  \n",
       "1      True  mammal  \n",
       "3      True  mammal  \n",
       "4      True  mammal  \n",
       "5      True  mammal  \n",
       "6      True  mammal  \n",
       "9     False  mammal  \n",
       "10     True  mammal  \n",
       "17     True  mammal  \n",
       "19     True  mammal  \n",
       "22     True  mammal  \n",
       "27    False  mammal  \n",
       "28     True  mammal  \n",
       "29     True  mammal  \n",
       "31     True  mammal  \n",
       "32     True  mammal  \n",
       "35    False  mammal  \n",
       "36    False  mammal  \n",
       "44     True  mammal  \n",
       "45     True  mammal  \n",
       "47     True  mammal  \n",
       "48     True  mammal  \n",
       "49    False  mammal  \n",
       "50     True  mammal  \n",
       "54    False  mammal  \n",
       "55     True  mammal  \n",
       "63     True  mammal  \n",
       "64     True  mammal  \n",
       "65     True  mammal  \n",
       "66     True  mammal  \n",
       "67     True  mammal  \n",
       "68     True  mammal  \n",
       "69     True  mammal  \n",
       "70     True  mammal  \n",
       "74     True  mammal  \n",
       "75     True  mammal  \n",
       "84    False  mammal  \n",
       "93    False  mammal  \n",
       "94    False  mammal  \n",
       "96     True  mammal  \n",
       "98     True  mammal  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zoo[df_zoo.type == 'mammal']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4 - Crie um gráfico com os números de patas por animais  \n",
    "Veja as dicas [aqui](https://pandas.pydata.org/pandas-docs/version/0.22/generated/pandas.DataFrame.plot.html)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7faafeb58550>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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7EV6Q5bjVcsAgpKU7AO4lJzy1/otn4YeYekF8LM+8W0g4bp2xbBrilHeLRDru9RuhOpj7bIck0l2tfVfkZOzt9EEpcLBYP8+tpSohhHwHwARAAMCnlJqmCmCe6mjoRvK21XjcPcdiXsYyVIlAuQDtB3fyhltNlbCfi7uM8JcW47ireVycVtkdOHHnn/HUy6tKhE49Xeh40hQ8IQGHqUo2MwA790Mc7zvsxb2i4GSyXpjDtk5UkQO+mlJ6trWRbCDGMw+7A2dldS241ng0cOItmyVQENrn4RMxpkra9Vj8MC0H5IE/SmmcTSlSJ2xRqs83mQtUydCpRPXE/PjQTQz3zJNSJTpj2TSI5Qc2WVWSrAUXT51ftPtdkVPB18t46gMXtPqVpdgeV2INiKkSx15ZPW6+PVxmy7YWqsRKe9yUJkaEjUk03MX3MqFKmMc99QJtOWbMjw/c2GuazHypHFBnLJsGP67U2F1VCaUUf33v2cKqf4wqsSOqZEXByZ3VODo60DXcFMBnCCG3E0Jukn2AEHITIeQMIeTM/v5+cyPsMMYzFuTqO/nGAG1gIQRkgPoyqEUmONn2VtMPKFxHVJXku6gv/DDujlNmhBOqhPHUgP5iio3+MDl2PPXyqhJOlWyZskRMee+qquTLDz6Fn/3gbfjyg08pPxM7MYPl4j06iKlFvl46oOXWNdyvoJS+EMAbAbyDEPLK7AcopTdTSk9TSk/v7e01OsiuIvG4k61/m+A87Gi4XOJBVlWyCo/bsWRGUeS1g/i6ymin8czD0LUZ3z+sVmgqUaQ4wrF5qqRny5sabzrEErt2R6kSTn0UvYwXfhitBRbvaXPtzf0AjkWSomYd0HJrGW5K6fej/z8O4M8AvKjNQW0KJlEiR9+1c1v/NsCNy268xa83gbgxuvB4D4S070F4AY1LugIiDZHmtflOoszL5fcdgEB36N2LJDjJdNwAcO68jOPeTqokbmrhdLdWyTR6oRetJ05t7Q4ceAFt9QW78BM+HehGoalSw00IOU4I2eU/A3g9gDvaHljXIcrKVrXI51mqpKbBnXsBCGHGiaW9tx2czHjcTt6bnfshdiMPuJTjjmqNAEi8Zs3dh8iP8xfgk4fMw+u7Asft6tE2mwYx5d3qKMd9fsENt/rex3LAJWlDHcz9EH3XFqi19VMlOqqSSwD8WRT9dwD8J0rpp1od1QZgIiSBcGHH3A+x2+J3zv0AJyMlBVB/snLvkhCytLRQB4zjVnuzvLED94BLqZKouh+AZDHpctwzDxYBjvccWBbBwLWwf7BIjYv9vOVUid1hjzsy3KqXZhCyhsc8OAmw53rxaNDKePhLwrEtHO/ZnQhOlhpuSun9AJ63grFsFMaxrCwpMNX2Ip97YazjZmOob7h5IHA0dFv3IBZBCDeTOQnkKwKOKnjcFx7vpY7RfYmNpx52B24soxwNXOxP5mxcR4AqEXtOdrU6IKdKVAF/vt56UXASAM61OIdFGm13BY6ODowcsCYmgqws9s5algTyCbSz5JaNBTnZmHcHTvs67mxZ14w3Gxtu7nGXcNzc+IrH6HvcCT8OMMO/f8ANd54q2TZVyUJIee+qx11GlfCXqRjvadOYMs04mxssa3n9VIkx3DXBH95uiuNu2eOOtKuubeHYEls2sWkAo0palgOG6ezDXsab5f/ni7DsPk5mCVVyvOfAIvr1VniBKY7RwMFZ7nG7R4EqSVLeWa2S7l3fzCumSuLGzq6FE0MuB23T4w7iObsKalEHxnDXhCgrE9Oj28Q8kkABy00gceu3bN0THYgabSChIfjCXGQ97gJ6glKaCk5ace9IfR03jxEA7GWReNxHgCqJDLXd4Xrc56PEMqXHHe2Cmshp0EF6vRjDvdHgE0WkStpWICxyBre+jjve+q0iOBlmqgOqqJLIGBfdx5kXwgto2muukD03znrcQzfFmXL0VrSLWjW8kEkzCSGw7W6qSqYLds9VcsBFkFAlYnCyLYgOE6MWDVWysRBrXqxaDggs63EnBZVGQ7f1UpWM41Z7s9yDGmlQJeJOh6NKoanxNPHW2bHJeaQp71vGcXt+UvCrqx731OPt5OT3fhZ73Bb6joWebbXKO3OKEqg219qEMdw1kcjKbCE42d4i55K5JLpd/82f2voNnFZLVVJK4YVhOgEnpyphBlwnc1JMoOGoUmhqIglOxuOSyAG3rSa3uPvhqpK2M36rYloanOQctw1CSOsB9txOd+av/Z4Zw10TXNlACFkJxy0GZIDluLas5w60xxEGIQWlyNXj5uMQ/3+854CQYnXOOSGBhkNXohWEFJO5n6JKdhUeN6MT2lcKrRpiiV1uwLvmdMeqEmVwMqFKgGpUWR2kHR0XQUjjMa4LxnDXBC8wBawmkBUb7ga2bGJBpWXrnpRB1A1z5KiS6P8D147rvqggdr/h0L0XBwK9JR4bj0tQlRBCSseyiRClmXZkuP2OFZqalei4k7WQ7BpbDU4KcsCk3MR6eW5juGtClJWtIpDFjVuvgS3bQmiM23b9hbg2hiXhuDlV4iXBwV5JUwoxKMzB70UZkpKu5VQJ+z3fqWfTIfO4u8Zzl+q4vXQwuW2lRzomVC1voC0Yw10TLO2aLfpVJODMvayXwbZs0xrfmaJKhu16EElX8cTjdmwLFslTJX3HKm0DNxEyVjlGAxZgLTNAcm9dTpXw8WybHJCpStgcSjzubhnuOHPSl48roUqS3We7Ou40VQKsv0KgMdw1wbvfAPJqd00jS5XEGWM1KA7RgxBrUrcBTyjcL4J5s2mqpM+pkoIgr9gIgYMb4oOSxZskTWl63JKmxpsOPwhjTzv2uDvWMFg7OCkE6tvWcYvePWA87o2FKCvLJpS0gUWW11tiyyb1INqiSoTC/SL6rpVLwOHyrnmBkmM89dGzrZSR1S00JTX6osftHgWqJJFm2tH/u+txl2dOAu1SJYmaKykRAay/QqAx3DXB0q6ZAXCiNlCr4LjFzEmgnqcsUiVtT0SxcL8IMfCXokocu9TjHg2duFclkNyLcyX3gt+rE4rgZC+zK2B8+5ZRJUGInp3xuDtkuCmlQj3u4iJTCVXiYOaFrThO+UDocrXwm4Ix3DUQy8qGIj/a7iLPqUpqctOU0pQute1SlZ6E4wbS3qx4bazxcjHHne2wPdKsVxHz4xKaxbZIrpv7qppArxJi3ZguqkpYJyn2s1pVkpcDAu0YUxktA6y/fZkx3DVwIDEAbUvHspO1ah3q5DzpbSY7V3tbTU+oRidCfNHxxg6uXS7BY/r5dDViXbqH//vOIP3CzVIv6TF2x6g1AS+gOY67Q3Y7pY9WUiXe6oxp7N1H1TS5ZHVjgpOEEJsQ8hVCyCfaHNAmYBxn76UVCW0GsuLJuiRVkvXcgXZLVSaqEnXgT2zsUMYriwWmOHTvxXjqY6fvxJ4mgDjzTm64t4/j9gU5YBc9blElVRSc7EXzBWhX6ZF1mIBu1OSu4nG/C8BdbQ1kkyCTlfVWRJVwz7Wul5HVgwPtFpryQt5xpZgq4S8SpipR30feoFlEEqgtUZXMvFQwMjneRVYKqDOWTYTY/9PuIMc9FUovqIpMzf0AfcERaFPpoXR0NoEqIYRcAeDHAXyw3eFsBpK+hWugSpbcsmW3mQCb+G3ruIsCf2K9455jFQaZxIxVjp2+nqQxW2CKYzRwcooSgN3r7es5mXDcTgd13LwyoGORQlWJ+LxGS0hjyyBdLx0oNKXTcxIAfhvArwGttlTEu/7zV+KHRQjwCy+7Gi+6+sLUZz7ytw/i1nv2S8/16h+6GD9z+unKf7/9u0/iQ198IA6EXP+0Xbz7dc/SGqesQl02kDXzAvzbz3wLv/za61IFkXTx+5+/D6++/mJc/zR2y7NBEvb9Lj55x6N48MnzAICf/uEr8Nq/d0nqPJ+581EEIcUbn3up+jwDB/ftH2iP7f79A/zWX347Vozs7fbxvjc/O0VBcHhBshBF9F0Lh4dRFTihsUOWnqCU4l9/8u74Gn9wuMh53I7Nmh5//GsP457HJspxf/nBH+CaUzu5v4+GrjSRqe9YePjcFP/0j24HADzn8hN4x6uvVZ5/GUwXAd738TukL9CeY+FXf+x6XHHBsfhvlFL85qe+he8+cVh4XkKAf/zSq/CSay4CwIx04nGze94lj5vX4h4N3cLMyawHDLA184mvP5z6rEUI/umrnonnXH5C+Z1/cuZ7uOLkEC+79lT+uzJqLj62MgVT2yg13ISQnwDwOKX0dkLIqwo+dxOAmwDgyiuvrDWYB84exnUK7ts/xImhmzPcH/zC/Xh8PMelJ9WNQR9+aoYHzh4WGu4//+rD+NQdj+Lai3fw5OECn7zjUbzzNddJjU8WfHId72U4boEq+er3nsIffOEBvPjqi/C6Gy7JnaMIcz/Av/7k3XjqvIf3vPGH2N8kb/43//3L8MV793Hf/gG++8R5zLwgZ7hvvvV+LIJQMNzprDOAcXZVJuLn7n4c/8/XHsa1F+/gcO7jkXMz/OLLr8bVp47nPhsbbklwMu7VGQiGO6MqGU99/B+33o+93T4uOObi2ot38HLJAvvJ51+GM995svAFdOHxHl7/7Pyz+PHnXoonok7vIn70WXv4xkPncN/+Ac4eLPBXdz3emuH+5iNj/MmZh3D5ySGO95Nn4wcU9589xEuuuQhve1Gyrs4vAvz+5+/DqZ0+LjyudgweOHuIgWvHhtsLwlia2UmPO1r/J4ZuoapEXAd7O3386LP28Mi5ae753/PYAZ5+4bFCw/1bn70Hz7vipMJw56mS4z0bDz811b+oFqDjcb8cwE8SQt4EYABgRAj5I0rpPxQ/RCm9GcDNAHD69OlaM+Hjv/SK+OdX/ObnpNTD3A9x47Mvwft/5vnK87zzI1/Bnd8/V/hdcy/ExbsDfOZXfhQf+uID+Jef+CYOZj5OHCv3jrOBQiBtiIBk216nLCjf8onyJn4ecQL9z2++If75Z//gS1JvbTzzUlzhQqIq4WVRKaUpfbQK/Ln8xS//A9x6zz7+u/94RinF4lRJLgFH5Li9DMct3sfovL/2Y9fjvyl4Ef8vP/Xc0nGr8NYXyR2NNz/vMrz5eZcBAH7vlnvxv336W5h5AQZung9fFvxl9W9/5nmxkQWAJw8XeOG//GyONuD36J2vuRY//7KrlOd9w2/fmpoXfpBPeQ+6FJxc8BK/Lh49JzeOYq0dgDkFH/5vXyT97HPe9+lSums89TCZy+evLCaUXevrQCnHTSl9L6X0CkrpVQDeCuBzWaPdBlScsRjIqnps+jxC4ZiK0jrZWzj7nXyx1AlYciMoBkBEyZwMqgDjZOan+Dg5VVKt7ok4ljI9OVcs5FPek8Cf+CyyVAnfCci46VWi7Zousuci/p6dRzK1gwysjkfy/FmRqbQc0O9QynvK4y7kuPVenmX5FX4Q4nARKJ+rbKeb3V2vA53VcfcU8jqxJKn62HKFR7aPHFDFcOcXTVYOyM9VRyLIDba44ETJnAyqZgLjqRd70/w8fLzJsdWCO/OohyQhRCgLK793C5XH7aYzJxOOm3kzfLyypJl1oOrLvSqyFe844sqTmXkk2/XJkJV6+mG+rGu3OO7EcBeqSkpsAEeZE3cwZ/dGNX9lL9QuJGZVMtyU0v+PUvoTbQ1GhOpNKS7ywmNLDKZYOKZq2rf0LSzhZvn3VAWfRFlPuWinsSuJdHNvYhGEAi0h06VW33EkyQ/FLz11yrtCDphpSiHTzK8DbVeFk8UeAOYVi5UUk89zeWix55nVHHu+wHHb3eO4eYxrNHAK63HrGu5eaUJXZLgVHnc2AQfQsy9to7Met4xHopRqGm67sFARwNsRZbrAVDBc2RRpFTdbhwsby6iSEi9jNHBxuAhiQwmkt/Xc4PAxDqRyqgqG203qRLBjFVSJMuU9nTkpqkrEccrqi6wDulrxusgWEePgSUlZI6ZPlaQr53lh4rB0U1WSpkpk9eZFFVIZ+o6NRcHuO15rU0/+XardtaFK5GB1mdOTlW+dyvit7HZbBtEQnhhWM1yLID9xsm92TnPUecCxFyB63F6Y20aLkNXrSBnuWdpwi55aHaqIX//xngOLqI/lCTg5HbdjwQsogpCmgk1JU4ogGlPCIBgXAAAgAElEQVRXqJK2PW419cGyTNPzSBZkliHbDNqXpLx3yeOeegFcm+BYj81P2djE5r1lKKM1+PP0FTEeKVXiWAgpUk7SqtFdwy3Z4uh6GTo9IGWlTXUDTzKenXHczVAl3OhPUh53sZchuwbRmI4zwdJ0AoNekSbZWCyLYLegkD3vG5iXA0bNeP0wlzkJJHQUvxc766ZKVhacVGRwKqiSMgM2GrgIKXC4YHEOxnF3W1UydO04mC3TclehSsrru8sdHfG72HkEqmQFPWbL0HHDnY2ky7eT+WPT220ZRAnaTi2OV9YtRRKcXIIqmXpBonUu8TJkPLXoHcZUiYSf361KlWQSIIoK2ct6TorfHxvuWFWS4bgl9UXWgbpFvXRR5JTIaqboOjFiaQQvzmLtsMe9CDDsJYZbRjVmMyeLUEZrqNZL/F0SNZeOfWkbHTbceVWJrpeh07xXlKDZFsFOX7/QkhjYFMfrhzTmCxNVSX2qBBApl+LJOpLQPTKPW6YHr1r3RLx3QHGtE24s3Gxw0k2ekUi9iJ44vwZZfZFVY+jacCzSHlUieaFySJ0YbVVJMi/8ML376aSqxAtwrOfA5S92mcftVaBKNKpNxj9L5rBMzZWl89aB7hpuCTcVKyJKJmt2uy1Ddrs1Gji1OF5xvEBicBIdd32Pm/2cnEeHKpEdC+Q9bvHFU7XuSe7eFVQX5DygLAGHn0uuKgnica9bww0gkj62V4wrW/FOhKyFWhWqBGDzMa6NHnPc7F53Sse98DF07biIlEwSKIsxqVDKcafWiJwqkZUkBupJfZtCdw33MlSJq0GVZOiO0VC/cMzcy3u/WS8/q+KoApUapGiRJnrq/LGASN2w4E+WemBGqQrHLdy7Qo+bXX/2+/j9mkV0kKjj5t/Bx73uwCTHaCDXyjeBItXQMlSJqLNPXqKRx213z+OeehFV4rCxeZnr1lWWcZRRJZNZmccd5MQQhiopgEx/qetl8DdkIVWSCTDuVliUco47eZiU0lwwsArGUy/2iGPPvSTxSKan5mNwbZLaAcju326VHYcXpDz2wuBkVNQo60nya+FjFDMn+TgBdv3r1nBzyLTyTaHIGMlaqOk6MeJOLKatOlwd8PwiwDGR485QJV5AQWm5soyjNDg59eO5LHNcZNJDHSq2bXTWcDP9ZVrSx6mSIlkckKctZMjy1FVqUkupEmH7dH4RxF5MXR33FSeH8c/8PEWTdbfvgJA8PbI7cHBC2E2oPLsqpSqzW1VGlagTcLLJN0Cy8Pj15VUlQfzvXaBKgHbrMGcDviLExsri54HytZAkl3lCwa9M5mSBbHbVmC5YLZieIjipu9Pg6DlWYb2g1FqTBScltIxRlRQgVh0IN11fVVJ8Y4OQyaJyVEmNzEEOMWCRlfFVxXjq4/IL0pNJxrWJsOIAa3INvD8jy55LSqjKFnslqiRbVnPgYjL3pVtusXC/iNjjjsbLxyRTlXQhOAm0W4e5iLctlsaWZ04CbC5wzzou6xrtgoI16pGzmHqRx+3I5YBxHkJTcsCph1M7ffRsS06VSF6o2QD6OtB5wy1O2Gx3Z/WxxRyUtELeQF9VspBSJcl4xQlQJ4AxmXm4PONxZ5UcMmR3DeMZ87jF7DnVlpzxt1UyJ0WPmxkHXvdBhCe0yhKR3Z7KMicppZh0yeMuoISWRZZ+EiHjuBd+WFh0jKPnWBi6NsYzL1d+wO5gyjvXcas9bj3njYNz3KpkvEnUmENV60e27gxVUoA4wOhJPG5tVYn8xqr6yE1m8rTX/PGS4GQcEA1iI+lYpPLD5fVFnnZiAIuIHHd5QCbL03NFButwI1Il+RcfC85WkAPKap1IvFE/oDkNN5Dc+0lMlUSGW1CVHC4ChHT9dUo4qsQBqqKo4p1YSTH1eYUKJQuu+llkgpNOB+WAXMfdiz3u9NiSWjv6HHdI1S8nHvxW7aZkjk48R42qJA/ZW02X3xqUcFDyCnlOlGFWbmjnXqCWCAke96mdfmWqhBveE5HBjT3loLycbVYZM46okpFAlSwUevBKwUmJqoR9X/54L1Rw3NHxk9jjTnPcCz+Mr6UzqpKhi/OLQNmZZRkUqkpk0tgSlZEIvhPL1ka3OxicnHrFmZOVPe4SW8Cdm10FVSi7z4n4wRjuHGRUiX4CTjFVouojB+hlD0o9bmG83Bid2u1VfrhxW7SBGxlTlqq8UFAcIkQDza9lNHRSmY1qqoQV9ZmVJAzJxiKTInL4AZVSAFmOW6YqkTVlXieqlgaogiJViUoOqGu8+E4sm4DjdKzI1MIP4Yc0UpWwl4qMIgLKd90c8XySzOswpJjM/RydKEJa3kLYXa8LHTbcEqpEUpJUfmwxB6XqIwfopTQXygG9xFM8tdOvnDnJjQKbTMyD1qWIsuqOCd8GCoFXlaemW4tDNpYkyUPicQdhrt+keHyW4xbrT8uaMq8TyT1qni4pVJUoMid1jRd//kkWK3se/LF0xePmRZ54QhhQ5HHrUyXicSJY/RbEu1LZc8122yk756rQYcMto0r0DJiq+HzuPLLtvgbPW5Q5OfeD2BjVoUpiemDoxlvcKlly3EBzb2IUeRMzL4zqgqjkgHq1OJLqgsk54uqKEqPvBTRXYEq8ltjjjn63LQLXJqlYQbar+7rQajfxAg9arKSYfL4iVSLIAbligxACxyKdKTLF25Yd6zkFVEk1OWARVRJXnoyCk7pUyUZkThJCBoSQvyWEfI0Qcich5DdWMbAiqqRIFseOjeQ6Bc1Gxe8AkgBYmTcVhBReQNUPM+Jm+44V0w9VIFIlPNJdpfYyL+F5wL2JiCvn16by1HSpomS3Iql1IgtOhmGxHDATnGQ/M2qA9wHc7YjH3WahqTKqBEgrLKpQJdwo+ZmUd4C9KLvmcQ97lrLIVEJz6nrcalpDjKGog5MyVclmUCVzAK+hlD4PwPMBvIEQ8pJ2hyVPopn7Qa6BgQylHrckeUGXKlFxbD3RcM98jIZurRZHMT0wdOJMPd1ki9HQBaXAwcJPTUqxiJRKD67bKEBW8H+nrzZoYnNaEVmOW2zswKmBhCrpiMddsW57FRQVERMDtuLndbXMXDHlZVQlADPiQUdqlZxfsOc9dIs87mo6bpWsEEie425EJ84lMR7ZC5VlAndcx00ZeM97N/qv9SctCzDqdr4Qt9syzIO88Snr5BIfq/B+xSAI10/3o6ytsIJHk7TqStQgldOboz6T7DxO6u9KOaC2x50fi2NbyuqKCwXHTQiJkh7YMWJjh16UNCEurC6gasOJKpDlBnBkC28B+msBYM/WC2g8J0R5Zpc87lnscSdywEVWDtgSVbKrCDzLqBLWlWi9fSe1rp4QYhNCvgrgcQCfpZTe1u6w5Bx3papgkkg8h2y7pVuTWpUElKVKRgO3lLKRYTzzQQhLYR8NGfXBub9yOWDy8klx5YLBUXl22sFJxVZVlcDjKxJw2DmsRMed87iZqmTo2treVdtoV1VSXGSKfUZwYjTkoRx8XjxxOAeQ8bhtqzOqkvMxx50k4CiDk5VVJfk1OJmlqRLxb4BcQSWet/OGm1IaUEqfD+AKAC8ihDwn+xlCyE2EkDOEkDP7+/tLD0yuKtGfrLJIfHweiaqk51gYuPK01/Sxcu+3L6NKagQxxlMPO30HlkXiyXQ2WnBlk3VXmHxiyy+xtKfKU9Plb2X3jn+3lCoJ5Qk4/BwzWePlKNutSwWmANamjZDmqZKyinfSQH1J0TER/Pk/ecjGLdZG75LHzR0UpuNmcybPcVdPwAFKOO6hK6UKi14SRfZlFajkylBKnwJwC4A3SP7tZkrpaUrp6b29vaUHJtvi6KR9x8cX1ChQGV+dlGb+sLJeICGEFbTxw0iG50i3uGUQy5hyo3V2MpeON4skEcZPKTLE4OFC4anpNgpQ3jtFTW5PwXGzc9jyn6OiSl0qMAVEbdr6zReaKqt4l5TATZd/0K2Qx+/hk5EDIL5IO6UqEagSx7ZgkXYTcMYKOjH/Xfn73CuwL6uAjqpkjxByMvp5COBGAHe3PTCVHFD/gRVQJYoHolNoSuYhimPmQbXR0K2VYcWP5eMBgP0Dbrh1qRIvvQ3kC/f8AkFIpWPXbRSgvHcKj5vVKlF43E56xyP+nVFO3SkwxVGlbrsuynhbWX35KmuBv7ifPFwA6C7HLXrcAKN0sjSjLDhehDJVCc/SlMUvitvJrZfj1lkVlwL4MCHEBjP0f0Ip/US7w0qrNDiqaFdlNYzj8yg66egUmkq2T7KmrnbMze4OnFoZVpPoWDaeyHBX9riT4OTOwIFjEVhEOI9i16LTKECVBDUauvj24we5z6vKugLJM842dug7NqYeSy2/8HivcDyrRjY7tQmUKSVk9eUryQE55XawSJ0P4B53Nwy3yHEDbJyyIlM6yjKOIrqSF5gCIA1OFreTK27Q0DZKDTel9OsAXrCCsaQQT1YvQ5VU2CKVe9x5nvYH5xeF5y17C4+nHhZ+GAUn81vcMoxnflwZkE8qbnAHJTTRjqCMmcy8VEH60dAVXgDyl59OowD1vZPXOvEURaaA5OUnC/Q+NV3gYObjGRcdLxzPqtFGoamy7b+UNqwQ7+HziM9t0eh1yuMWMicBnnhUP9UfKM5yFGnJIqpEWrKhhtS3SXQjXC+BY1twLIJFkJFAVeC4VTpLVSIPq6Kn6XErHubZiNYQg5OVVCVRfRFA9JT0qBLXtnCsZ0fByXTLr92BI5xH4XFrNApQqWp4AkO2uqIfquuIJ6VcM4HeqMciqyd+BKiSkoCbSsetnfLOg5ORxy3KMx3L6oyOe7oIYJHkel3bgudn5YD6+nUgcQ6kOm5hd3usZ8O2iIIqke2uO85xrxPZm1PWTCB9bBHHHUgbs6oKzaSOLcjc6tlW7NWOBk6hFEkFmRfAz6kzYTnXLG4D+d/LzqPTKEAVaVdVVyz0uDP1STh6toWZH3QuOAm0U5O71OPOyAHDkGIR6K+FQSSpnMx5K7u0x92VDjjTqMM7X5euQ3JOTxX9OlDcxlCMJxFCclRpUUGrvmPH+SDrQLcNdybAqEoekR5bINdRaTN5cK6oJrdKDsfHmxhut7KqJAwpDuaJl8mpD12Om10Dm3zMm0iMnmi4VfewiqpGpsgB8iUDvAKOW+lxOzbOnWdFkbpSYIqD7Uqa9bjLKt4lPC2799yY6XrcQKJBt0i6cbPdMY57IMSOepLgZBUbACRZjjInbpLblaYLTRXurp18jfRVotuGO2N8q2wP+XZbBlWQc3fgwAtoISddFNXuO0km4GjoFPJrMoj1RQC2qET5mc6E5XrqrCJDpEFULwAd/lalKkkSmNKG31e0LhPPkeO4XSsl1eoSdgduXA+mKZQVEcty3FXrdQDJizUb1OsSxz2L2pZxMKokH5ys4nEXZTmOs7vSDFVY9Fz6rt3tlPd1InvDdWpSJ8cWZ06qalIDxUkohQ8zlUKfZE7qGm5Z4wDRcOlRJUwZkqUZRO9bqSrRaBSgqpuSJDCk7x0rMlXicStqm/MxdQmjgQNKEdMOTaBUDpiZR/OgWto3AOxG99HNlB/oko77/MKPpYCAKjip77xx9B075x1TSqNm2uldaSo4WVBGet1ywI4bbjvHcTeVOVmc9l1uuOXNAdLNh7Nb3DKIBaayY8pK5lTgdA9vFBz/XTTcSqqkPKV77gfSscii8pRSZVlXIDHYqrov4pi6gjYKTZV50NmchiKZmgr8Pko97q4EJ70Qw4zHLdNxV9lpAHIjO/UC+CHNrZGxhCqRqbl6m5Q5uWpkb06VNN9ewRtR2UwgmtznCrTchXJAN+txV6NKxKQZ8Tzs+/RrL5+beil1CpB+GahVJXovLnl1wXytk7iruOKFo6RKOu1x69V0qQJtHXdksItyCVTg487ufhy7Oxz3NOtxS1Ul1eSAgFy6N5nJnKR0HkPZ7tqoShTIvikrcdwlKe+q4CRQQpWUZE4CbPs5cK3qVEnM6wqGO5pYVWovP3Xegx/S3DYwHqcyAae8UQDbrahfeuK9i+s/15ADysbdBagooWVQRpVYFokSykKtz8vAx52NN9iW1RmOe5rluB1ZcLIaxw3Ik2XktGSGKinM2diAIlPrAq9ZAbAMPD/MNzBQHuvY6kYKCs89Ke1a4nFKpIT8OwH2AiCESGuKF0HW8WU39rj1HpXKWItcuToBp9woqYtU5SkEL+JOy1LeVYXq2TV0jCqp0JtUFzoV78S8hKr1OgAxOCnjuLthuM8vAgx6osdNpI0UalElGScuKZ+clsweLgL4QToIrOqZWrVkc5PotuEW3moLSQ3t4mNZuUpfYrznigI9YpEmFYrLb0ZZitFkKNKQyjCWUiXRuSqmNwNyrrzoXDr8raq0blJdMbl3XBGgCk7ycWSpF1mDi65AZ45UhU7FO7bdz3LcFaiSODjZYVXJIsCx0uBkULnMb1/iuSfxpPx64XRJsaqkenJdk+i44c5PVt2HVlQVrJynLfa4y4JI/DzZLW4Z+GRKeQHDihx3JulG9nMZx13ucRfpwAWqJORUST2Ou2dblbfFbUMs5NUUdDxo0YlRVagsAncAchx3l1QlXpALTkpVJRXnhKySn9xJSs//RUHsoSoN2jS6tSoyEDlu3Ya5ybHqG7tQqEr6jsW6shRxvAWZW/zvaVpCP4jB64uInHAcnKyY3pwdh1ZwUlNVUiQnFO9d3CpLlYDDVSUKqmQ0dKSU1DrB27Q1GZzUqXgnXwsV5IAKqqRLHvf5Rd5wy4pM1ZIDZjluSXAyW2hKpaBi56y2m24aHTfcthBJr9iyqODGqt7ahJDSJJRFUNAbMNrmZQOBVaiSbDCOT6aqJTyBzDZQQw6o0yigyOPJ3jsvCk66TgnHnZMD8hdgt2gSgAVaj/fshoOT5RXvekKmXpFMTQVuoLLf0RWOOwhZt5msjjvXusyrljkJyOWAsuBklirU2V2vS1nSbcMtGL2ytGDZsYD8xhY9kLIiQnMvKC2alDWSVagS0QPg4+Hn0YHKWPOfCVEHC3UaBRTeu0xUnscX1Cnv6sxJdr5uBSY5mi40pSNxE8s/qAp9FYE//55MVdIBHTevDHgsFZxshiqR1eYfz7wcFZelSoqei6zs9CrRbcPdElVSpAcvq0mtCmzy8QLp7VeRnjwLmcc9qqgqUVElO4LnXkQ/lL64CiYzS/4RqZLI4y5TlSgScLoWmORQNY2oCx1jlIr31JIDRlSJ1U2PO9tEAWDzRjTcQUgrKcs4ZHVFuJMkrgWxZytQRotWr7XfJDptuHtOfe1qkaKjiCcr6wKj09Q1GwjUzZyczPycsYp13Jo7DZFaEQv28LonpV10ShoFzD11Wc1sw2A/LPG4lRx3fufSJWQTNZZF0T3lSDkxS9UqyXjcdjc47thw9xJnI8txV911c8iokmyBKSAfnC900grED6tA6R0ghDydEHILIeSbhJA7CSHvWsXAADYxuaSvapqvSkOdNGZVa5nrcrz8O7PBSV3JkFgfOBlPNaqEl/CU8cO7A6f0/pVx/MUcNwtO8uqKcXCy5EWnokq6VmCKQ9UYuS50Kt6JQW4d3XcWux1XlcT9JjMctx/SWCtdZ6fBPi+jSvKNqHd4jEcITpYJEbrMcfsA/hml9AYALwHwDkLIDe0Oi4HfnEUQVk7zVVElZXpwHY9TVw7Ix6H7cMdTGVVSLTjJjnFzXDkfV9liL6NKimpFjIZO6lnFVIky5X1TqZLyFndVoEeVJAllsRxQsx43kDQKyGdOdsPjPr9g9zNbHRBIErnKSgOoICbycbCSEOn5ZVkEO30nE5wsdjrWpePWaV32CIBHop8nhJC7AFwO4Jstjy31VmtKVVImpdLieBXGryfZ4vddC4cFleS+/dgk7gWYLTMJJB53Jc3u0JHSDKOBW1j5j3/m7MECf3PfEwCAy04OUu3DCuWAQlbhwLVLU97jBJzMtSX3sZse92jo4geHyT1S4cLjPVz/tN3S8+lI3NIcN8tDsDSKjnHwRgFVVCXjmQc/oIV9P6eLAF976CnwEvaXnhjgqlN67ebCkOKrDz2FuRfim4+MASBXjxtInIU6FBH7fJLlyO/ZeObFLQJFjAYu7j97iL+57wnsT+apF0n2nEC6gNy9j09wburjh59xQaXx1UGllUEIuQqs/+Rtkn+7CcBNAHDllVc2MLTEu577YeW3rUpVUka5jAZO9H3y7WvRW/ji3QEA4DJhQvQdC08eyo3luamHN/zOF1IL55LRIPWZnmPh4t0+9nb60nPIcPnJodRwX37BEAq6Wfj+Ps4ezPG2P/gSAGC37+Drv/76OIhTdP0iR3jxaBB7SqoEnIt2+rAIsLebvrbRwEHPsVL3sUu4ZDTAZO7H90gFQoC//eevy11fFlpUiVBfXocTl+HyC4Y4lTHCRbVKfv3jd+J7T57Hn/73L1Oe8/duuRf/7pZ74993+g6+IcyXItzyrcfx9g+fSf3t1E4yPn6NfOc2q0mV9ISd+8Bi93kioUoANv9vvWcft96zDwB4/Q2XSM85kHDcH/rid/DZbz6KM//ixkrjqwNtw00I2QHwXwC8m1I6zv47pfRmADcDwOnTpxvZe4lec2WOu5QqUTfMBdiD7e+oDLf82OdcfgJf+LVX4+kXHkuNQxXAeOJgjiCkeOdrrsXLnnkKjk3wvCtO5j73iXe+ohJt8Ltve4F04fzGW55d2l/wna+5Dq981h4oBT7x9Yfxx7c9GLeUAoqvP6l1wnYYPOVdtaW//OQQn//VV+OKC9IGenfg4pb/4VW4pMTgrQtvf8XVOP2MC1DEMPzdd57E+z97D84ezEsNt06d+WzmZJ2M0g//4otSHi0A2BaU9Ta+/4MpHn5qVnjOx8YznNrp4Xff9kL8v994GH/0pQdxuAjiRKXiY1lHpg/83Atx8lgPuwMH112S7FBiqiRas3H1zIoUmthCkF+/jCoBgN//Rz+M+x4/jH//e5fKd0wy+yJThbUFLcNNCHHBjPYfU0o/1u6QEog3p6hxp/xYBVXC60IoVSVJSvMpiZdbtshEo83HoZIMcQP3gitP4qXPvEh5zoszXngZTh6Tb211JtWwZ+Ml17CxPHCWTeDx1MexngM/CBGEtDA+wD7PFlhZyjuQv18csm1sVzBwbbz4GvXzAoAw4g509N5zPyw1dFmqpI7hvkgyn7nHTSnNvezHM790/OOZh4uO9/HSZ16E7z7B54unZbh5gPdHr9+LHQMRnI/n/LSsJIQO0rbAxcwLMPdDKRV38e4g3jnrnxPR+Ly4YUXb0FGVEAAfAnAXpfT97Q8pQZrjrpiAoxDIl3LcJUWEqno7sjoJHLLsrS4hW8K07BmcGGY87pIEnG1GlWJUOhXvuKSNUpZhWKUWdxF4x3eZ0z2eepjM/UKdt5g0plPrJnt+xyIpJYkIkeIQz1t1vWRtQVKLu/666wm2iYM1L1lNXEZnRb0cwD8C8BpCyFej/97U8rgAiNlJQeX6DLIby85VTJUUFZpKpIT6hkimIeVoYgK1iWwD4HkJ9ZH9vF+SgLPNSCrN6Xjc5RXveo4FShnfW5cqkYHX4fAlkkA+9oOC4PpkntADVZtM8LwFFR/ey1AlsvoiOkhiZUH0vcs7TEqqZEVrWUdV8kUAa1l54puyzGjkj5VnNhX1kQOKmwl4AQWl+pJEgKfbqqiSfE3gLiHmrKeJrhVQX39S6yHtcavKum4zZPXJVdCVA7LPBrWpEhm4x531qsOQxn01x1MPJxQGaTz1ce0emyfJfNH0uCV5CyJijttP0051PW7eBLzuC0BET0qVdMvjXhu4gVjEKo/idG0Rrk1ASD4Bp2y7X9RMoE4CAC+Az5NSRHSfKslkkpUEiPuOBdcm8ec9DY57W5EN1BZBSw4oJJTVaSagQuJxp+fnwcKPJX5F1IfoZdahSormfkKVBPF5e5mMYB1kqRK+7pYpYsY18esKTnbbcGdUJVUMJiFESlPoUiUyr6FOOc2+YyGk+YUBsAdtW0SpFV03ssHGMkUO0wonOni/pKzrNsO1LRzr2Xoet0bFu/TuU62lr4rY486ojcRxq5KNKKWpptSjzA6tDLK8BRFurOPmHnc9jzZOlvGX48pl5+XnnHkBFn64Mqqk0ysqS5VUDcjIpHhlXvPxng2LyHm6qoWuxM/KeG4ezOhazWmOrNeoI8kUC00lCTjdvL62wRpLaHrc2lRJ2ChVYkfGMetYiONW8fTnFwGCkMbGd3egjg/JIKsXIqIXlQMW5YB1jG1SV4Rz3MtTJUBa6ROf01AlQlAhypyskuILyKV4ZZ10CCHKQlNlUkLpGOJEoDzPPZ56naw5zcHrnohlLoHi6xcLTS2OMMcNlNd9AfQr3qV2n369BBwZVBx3yuNWvHySGE2S3ZttX1eE8VSeBMPhCpmTfBx15HZJwbk0VbK8x50oxrL3om10ekVlJ2vlqmBuXopXtt0H1IWm6lIl4rEiyraKXcBo4ArBSZ17J1IlXFXS6WnWGsoqTQL6Fe/ETGCdTEtdqFQlovFV0T1x38ZM3fcqwUkdjjtWlUy9Wh5tNsuxKYpSrPMta/TdJjq9olJUSa3uzhKqpERVAqgLTRX1oCsaA6Aw3CXBmS5gNHTyHnchVZI0YvDDEIRA2vrpKECnGJVuwDtFlVSM9xRBz+NWGO5Z3ljpvKwAZozPL4JCTjj2uAUddy2qJM6cjIKckae/LEXJ+slmqRLjcae6TNTRroo3lkMnkUflNdThuGWyIY5VRqHrQrwXOg2bxc97AT2SgUkOHSOmW4Mnm9PQvI47Y7hn5cFJafsvzcqJOpxwL0OVTGruUPMJOM2sO9ahKxPwNMFJgZuKIrbVWxapVSVFfLmqUH5dOSAgr9tbdyKuEqNhEmDToYrEz3tBeCSTbzh0gpO6Fe/EedRs5iQ7b9bj5uM+tdNXBhtlCWTs+Zd73Dp1R7JFpuruULO73qYoyhTHXa4sUCAAABTcSURBVDMdvy46bbhjSV9QV1UiM9wBnJLGrKpC+XXKShbV7e16cBJIB9jKEnAAVk1wGr1o/SAsvM/bDh4rkWn4OWpRJW1kTkrkgMd6Ni463iulSkRjtVtSzz45Pzd05VSJF4RJfZEaHm1WVdIURSl2j29KYqiLzq8q/lar1SRUynGXn6eUKqmlKkmPww9CHC6CDaFK2CJbaHrcAPOovJAebY976MIPadzdRQbdgDf/98OFj5BWL22qgpLjjuiE3QLqI0lkETjukg5S4vn551UQi0wtI7fLUi5lGZu6ELtbjaerzcnovuGOIrd1vAxZv0cdz300dHC4COIEkuTYJaiSDMfdlJa0baSDkzqGO9F++0F4JAtMcRSVT+DQ2cWwf7eic7Fn0ZiqxFaoSqIAXhFPP575GLhWaiz880W7DHZ+fapkEYQxtVJnh2pZJIp3CVx5Uxy3J55zdTkZnV9VXItdS1Xi2pKU9/IXAH+o2eI6TSbgrDoKXRejgYuFn2xVgeLrF7MtvYDCdY6yx11eaEq3zjy/55yGaDxzMstxz1kqO9Ply1880oa7AzcqhFXcaUmnwBoPbHtBuHR9kTQf3UwxKHFHv8oCU8DGGO6wVtKBKuW97DzZ4krxsRpSQtkY2PemPe6uF5ji4FvTyczH3AtASHG1P7ERhReER1pVEheaKmm+DOhTJdxTrZqMpoJSVRKllxd63JIEGt1CUzrz37IIHIsww71k0kwvcgCbpCjFBD8Wr1rdWu78quK95mpTJZLMyVKPW1Esp0mOW2er2AWI94LHGYq2g2INbz+gRzbdHdCr3aHbICQ23NGcbMrjtqNnme2Cwz1IHu+RFkmTeJm6habGUw+EsM7qRXBtVqRtWbkdd+KapChFx3DcEP2ii+4bbteqnzkp6bC+CMopl2xxpfjYiqVlxc9mPf9VR6HrQrwXRW3LZJ/3w/DIZk0CekZM1xlwbAu2ReKXQFMct2OrPG7mQe4OHIQUOFzISzbkqRJmEM+VaLnHMx+7fae04XHPseAFNDa4db1aHitLzrP8uhObpDSlDddF51dVz7YS7WrFydpTyAHLPW55Sc65H8IukRJmkS3iztFETeBVQLwXOgX/RWO1COiRlgPqdMGpUme+Zyd1Y5qTA+Z13GLVv6LGIrwRgoiiz4vQ5YRdmyk3lqVKuFBBR82if04mB6SUpjoBrQKlT58Q8oeEkMcJIXesYkBZ9F07LuhehypZBOla2HOv3HMfKbjJunQNkK8L3kRN4FVAbAigQzOJ1RX9IIR7RNPdAT2+twr91net2GNszOOWcNxTL4Af0pgqAeR0j0xWF9NDJVpuxo+Xz/2eTWKqZBm5Hac1mqQoxZLN7F50y+P+DwDe0PI4lOg7Vvz2rpM5CaRpiqrbfRF1tOSORWARGVXigxCWsNJliO2o5kH59RNC4kJTR53jzlZXlCEJeJcbpNRaaIrjjlUlQkMAoXhUtu8oR+xlSlQl7BwaHreG18uokjAOltaV2/Ha2U1SlPwZnJ8HrO5Klww3pfRWAE+uYCxS9B0r0a7WqMcNZA13ude8o/Aa6kgSWfZnPhGId8Iu4/jWDXHh6l4/LzTlHXGOG0gnMMlQpeJk30kaMzSdgCN63GLxKFULtrkfYhGEOXqgSnBSlyphcsDl5HY8VtYkRcnXwtnDeWPn1EVjq4oQchMh5Awh5Mz+/n5Tp0XfWY4qAdL8so7XbFsEu30nx9PV7TzChPr5BJyuByYBYOjacCwSBSf1rp8rEVitkiNuuIf5eSSimuG2hLXQbFlXkeMWk11EOagIlefadyz0bEup/U6+Q2/+c1XJZFZcu7sMWaqkCVqDP7P9SWS4u+Rx64JSejOl9DSl9PTe3l5Tp0XfteLed7UNt6As0fca855S3apsMj15U2m3bYNRH05KDliGUVTrxQ9o7NEdVZTV7uABXx0KYJm1oALPbBVrlSRUiaP0oFVFleL5okGV6Mz/nmNhEdCl64vwXW+TFCV3YrjhNjpuAeIErc5xy6kSnUQeWfcSHX5cOg4FVdJ1DTcHr/ine/27Ubad8bjLa3dUqa0t3vumOuDwlPdASpW4ygBrka5abF8nQxhSHMzzihQZerYFL+KmlzHcPAGnSYqSP4/Y4zaZkwnEyVq9kUI9qgSQF5rSNfpZ8EkjYtWC/WXA7wVraqtx74ZRcPKIF5kCymtyV3EGlnFiVJBy3IL0ru/YLM6UpUoK5HllL6vJnHWQ1wlOug5JgpNLcMg85b1JipJLOM8edJAqIYR8BMDfALieEPIQIeTt7Q8rQW+JySo2YuBYaCbyiJ1cUsfWpUokmZNd13Bz8Hux0Cw7wDsIef7RLusKlAcnq8yp1FpoqB63VFWSSXbhL2IR/DMnJHO47GVVRZLXi3Tcyya4xBx3gxRllipZ5Xou/SZK6dtWMRAVUl5G5czJtIbaD0KtxqwAW3B3zyapv839EDs1uDGx/CPHqjOtlsFo4OLx8YG2dzgaOjiY++g7lvG4S4OT+rkBK/O4Z17U+Jc9a1mhqUmBrG40cPHIuZnyO6sUWHNtC9NFgMNFsFRAkWVOBo1SlDFVcmCokhzSk3U5OWDSKFiT485SJTXkgHwcoscdhhSTud9I9tYqkAQn9VQlfIE9NfWOdFlXgBmneVRdUYYqxdP43LMIGgv6ylQlWX22zIMuaoRQFpyskr3oOhaePFxE42hAVdIgVcLtyNmDuVbdlSbR+VUlbgnrq0qC6P/6hns0dDGZ+6niO0vJAQWO+2ARcXybEpwciMFJHaqETeAgpCY4qZDTcVTp7MTvfd+xG6v7HKtKMh63aCR3JfGe8cyDa5O4g7qIpqmSJ89HhntJqoRS4AeHi8YoDW4Lzk4WK8/J6PyqWsbjHmQyJ5P0Yj2qhFJmZDmakgMuW3dh1RgNXZxfsOwwXSklh6FKihNSdAO+QGIomsqaBFQed5rGGw3y8R7+GdkLZDRwMIvqC8kwrkCV9OxEArlUAg5PljmYN+hxN39OXWyW4a5RHRAQDbd+Pe2kCH7WcC8vB9yU7jccogetq8jhOMop70C6ZIAMVZwBPvea4rcBgeMOxAScdLKLrAGwrMCU+Hn2GVWT4SQzswxiI46lEnDcZGfRFEXJnwOv67JKbIDhboAqiQx2lQ42slTfKt5Rdhxi5uSmFJjiEMepx3EnC+Ooc9xlhabqyAGbypoEWLMCQrKqknQAjytjxGJtReqM+JoVLyvOj+sE+kWqbVmqJD5PY8HJ5JyrTqbr/KoSDUX1DjiRxx1x2/z/upI2IGO4a9QEBzjHnZdbbRJVwqFjNE4In28qUWRTUUqVVIib8Hvf9D11LJLRcacDeLsDB4sgzNF9qvlbVmhqPPNwvGdrSUV7KYNb3zimztMUVSJQroYqyaAvPNyq7ZqyOu46VAk3skFI4YcUPbu6t9OzbTnHvWFUCVDtpQc0p37YVJQ1DJ57YWqOF6EXe9zNLluLEARUHZyMXz6CIR7P1AkxZS+rKpI8cc03wXGz8zSz7tJjMx53CtwbcSo2MABEw80M9sKvoCoZpHm6+NgGVCVFGtguIu1xl1//jkiVHHVVSUnD4EWgv4vrt2S4HYsgiDjumRdg4Ye54CSQpj6K8hDKeP0q2YucKllWbpemNZpZd67NaCbAeNw5LBOQsS0CNyrEDlRTlWS5ySreehb9qP0SlxbyBbCzQTpuDp3rty0S85dHXVUydG3WcqxQVaLJcXNVSYMcN8CeF6dKkuQYicctXIOsUTBHGa9fJXuRO1/Lyu1SHndDRpaVbLaicxqPO4XYy6iZ4isqOqoY36RDtx8dqx/YlI0BSBKAxlMPx3r2xmicq3LcQDKRN+Ua2wIhJKrd0aCqpEE5IMB2RUHsVOQ11qOMIV74IaaeunFAKVVSobY2nz/LGlvxnjVJa/BnYlQlGSwrgRI7vVepfdxzLAzdpHB9leQd2RjEcyxb6WzV2Ok58ZZQ12jwiXzUOW5AnZBCKa1ouNuhSkSPW5ZjkO2dOZEYdxG8fZ3qZcW72eigF+3YljWM/RaCk+J5DVWSQbI9XMJwZ1Qlut47qzPBPe4gNZ5KY4gTgdg5JgWBnS7CihpLAPrPgU/ko+5xA0nmaRZxCYYamZNNwrFILAeU5RhkddlleQiEEKn2m2NSy+Nebr2I96xJ6R5f2yY4mcGyk5UVl6lOlQBJQwB27PJUCT/HpnncQLJ4tamSaCIf9QQcIKquKOF7q+wAgcTAt+pxz/I5BllljE7fRl4hMgtKaaV6IZzjXjagyO/ZMU0Zov55eSEu43GnsCyvV5cqAdLNFJYNTornKArsdBV84ejfO+Nxc+z25VRJVfotife0oCqJqZJ8jsHAtVj7uugaigpMcagKTZ1fBAhCqj3/Y497SY829owbNrD9hl4sVdH5VcXfuFU13OLx2VolugkMYvuyKsk7sjEAwEzkuDekwBQH36rq71aMqoSDedx575O/yHXnVLIW2lOVjCXp6Jz64IZY9pksxN2qiKLOOTI0FZzsNfQCyJ3Xaee8ZdCaMYSQNxBCvkUIuZcQ8p62ByXCtggciyznccccd7RQNF8CcqpkGY87UZVsP1XCg5Od9w1ah8qIVaXf2vO4rVjHPZ56cCyCYYZ3FwtN6RRJU72sZB59EeLg37LBSbcdSqOzwUlCiA3g9wC8EcANAN5GCLmh7YGJ6DtWfY7bseMg0DxgEXzdkpjp4GQDckA/BKV044KTQDIxtVUl0ecNx51UV/QzzTSqJISxz7XPcfPiUdk1IgYbk+BkMcctC05WKTAFNBmcbOYFkD8veyZdrFXyIgD3Ukrvp5QuAPxnAG9pd1hp9F27GTlghcasQFKHmMm2mlGVTL0Afkg3psAUx25FqoR/vi7FtU3g9yKrLJlXzMZtTVViJ6oSVXKMyFmPZx4swmR/Kqi628uCn0XgVNuyHq1jEVikeQPbd6zGA5460LmKywF8T/j9IQAvbmc4cjCPu6bhdi3c8+gBbnz/5/HYeIZehUk/GrjwQ4obf+vW2FOoY4j42P/5x74Rt4PatOBkbarEGO7Y6PzXH/jrlK59GlN3VTMnm/e4b3vgSdz4/s/j4aemuHrveO4zo4GLv/vOD3Dj+z+P/YM5dvpO4c6Vt6+78f2fT/2dv7yqZk4uu15YlqPdvOF2mz+nDhr7RkLITQBuAoArr7yyqdMCAH7lxmfhGRceq3XsW38kGct1l+zg9DMu1D729c++BHc9MoYfeSN7O31cfnJYeQzXXryDt73oSpybsk4ef/+KE3jV9RdXPs868ZbnX4aBa2FY4GWJeMV1p/BPXnkNbrh01PLIuo9XXHcKP/WCy1P1ajhees1FeN7TT2idZ2+nj3e/7jrceMMljY7vF152FT5956MA2Bp5/Q1Py33mZ198ZZyEdd0lO3jhlRcUnvNNz70U9+0fpsrFcpza6eOqi/IvBxmefdkJ/JNXXoOXX3dK6/NFeM8bfwgvuPLk0ucR8XMvvhL/oIGxVQURa+xKP0DISwH8OqX0x6Lf3wsAlNL/VXXM6dOn6ZkzZ5ocp4GBgcFWgxByO6X0tM5ndfZcfwfgOkLI1YSQHoC3Avj4MgM0MDAwMKiPUqqEUuoTQn4JwKcB2AD+kFJ6Z+sjMzAwMDCQQovjppT+BYC/aHksBgYGBgYaMCF/AwMDgw2DMdwGBgYGGwZjuA0MDAw2DMZwGxgYGGwYjOE2MDAw2DCUJuDUOikh+wC+W/PwUwDONjicTYC55u3HUbtewFxzVTyDUrqn88FWDPcyIISc0c0e2haYa95+HLXrBcw1twlDlRgYGBhsGIzhNjAwMNgwdNFw37zuAawB5pq3H0ftegFzza2hcxy3gYGBgUExuuhxGxgYGBgUoDOGe50NiVcFQsjTCSG3EEK+SQi5kxDyrujvFxJCPksI+Xb0/+Iq9RsIQohNCPkKIeQT0e9XE0Jui573/xWVDN4aEEJOEkI+Sgi5mxByFyHkpdv+nAkhvxLN6zsIIR8hhAy27TkTQv6QEPI4IeQO4W/S50oY/vfo2r9OCHlhU+PohOHuQkPiFcEH8M8opTcAeAmAd0TX+R4Af0UpvQ7AX0W/bxveBeAu4fffBPBblNJrAfwAwNvXMqr28DsAPkUp/SEAzwO79q19zoSQywH8MoDTlNLngJWAfiu27zn/BwBvyPxN9VzfCOC66L+bAHygqUF0wnCjAw2JVwFK6SOU0i9HP0/AFvPlYNf64ehjHwbwX61nhO2AEHIFgB8H8MHodwLgNQA+Gn1kq66ZEHICwCsBfAgAKKULSulT2PLnDFYmekgIcQAcA/AItuw5U0pvBfBk5s+q5/oWAP+RMnwJwElCyKVNjKMrhlvWkPjyNY1lJSCEXAXgBQBuA3AJpfSR6J8eBdBsU8H147cB/BoA3oDwIgBPUUp5G/Bte95XA9gH8O8jeuiDhJDj2OLnTCn9PoB/A+BBMIN9DsDt2O7nzKF6rq3Zta4Y7iMFQsgOgP8C4N2U0rH4b5TJfLZG6kMI+QkAj1NKb1/3WFYIB8ALAXyAUvoCAIfI0CJb+JwvAPMwrwZwGYDjyFMKW49VPdeuGO7vA3i68PsV0d+2DoQQF8xo/zGl9GPRnx/jW6jo/4+va3wt4OUAfpIQ8h0wCuw1YPzvyWhLDWzf834IwEOU0tui3z8KZsi3+Tm/DsADlNJ9SqkH4GNgz36bnzOH6rm2Zte6YriPREPiiNv9EIC7KKXvF/7p4wB+Pvr55wH8+arH1hYope+llF5BKb0K7Ll+jlL6cwBuAfDT0ce27ZofBfA9Qsj10Z9eC+Cb2OLnDEaRvIQQciya5/yat/Y5C1A9148D+MeRuuQlAM4JlMpyoJR24j8AbwJwD4D7APyP6x5PS9f4CrBt1NcBfDX6701gnO9fAfg2gL8EcOG6x9rS9b8KwCein68B8LcA7gXwpwD66x5fw9f6fABnomf9fwO4YNufM4DfAHA3gDsA/J8A+tv2nAF8BIzD98B2Vm9XPVcABEwtdx+Ab4ApbhoZh8mcNDAwMNgwdIUqMTAwMDDQhDHcBgYGBhsGY7gNDAwMNgzGcBsYGBhsGIzhNjAwMNgwGMNtYGBgsGEwhtvAwMBgw2AMt4GBgcGG4f8HKj5bih3sFRcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_zoo.legs.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7faafca67b00>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_zoo.legs.plot(kind='hist')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>animal</th>\n",
       "      <th>hair</th>\n",
       "      <th>feathers</th>\n",
       "      <th>eggs</th>\n",
       "      <th>milk</th>\n",
       "      <th>airborne</th>\n",
       "      <th>aquatic</th>\n",
       "      <th>predator</th>\n",
       "      <th>toothed</th>\n",
       "      <th>backbone</th>\n",
       "      <th>breathes</th>\n",
       "      <th>venomous</th>\n",
       "      <th>fins</th>\n",
       "      <th>legs</th>\n",
       "      <th>tail</th>\n",
       "      <th>domestic</th>\n",
       "      <th>catsize</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>starfish</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>True</td>\n",
       "      <td>True</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>5</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>False</td>\n",
       "      <td>invertebrate</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      animal   hair  feathers  eggs   milk  airborne  aquatic  predator  \\\n",
       "85  starfish  False     False  True  False     False     True      True   \n",
       "\n",
       "    toothed  backbone  breathes  venomous   fins  legs   tail  domestic  \\\n",
       "85    False     False     False     False  False     5  False     False   \n",
       "\n",
       "    catsize          type  \n",
       "85    False  invertebrate  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_zoo[df_zoo.legs == 5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5 - crie uma tabela no banco alunos a partir do dataframe  \n",
    "ver referência [aqui](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_sql.html)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#como seria com um banco MySQL\n",
    "\n",
    "p = getpass.getpass()\n",
    "conn = pymysql.connect(host='127.0.0.1', #localhost\n",
    "                       port=3306, \n",
    "                       user='aluno', \n",
    "                       passwd=p, \n",
    "                       db='alunos')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = sqlite3.connect('tabela_zoo')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_zoo.to_sql('tabela_zoo', con=conn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('table', 'tabela_zoo', 'tabela_zoo', 2, 'CREATE TABLE \"tabela_zoo\" (\\n\"index\" INTEGER,\\n  \"animal\" TEXT,\\n  \"hair\" INTEGER,\\n  \"feathers\" INTEGER,\\n  \"eggs\" INTEGER,\\n  \"milk\" INTEGER,\\n  \"airborne\" INTEGER,\\n  \"aquatic\" INTEGER,\\n  \"predator\" INTEGER,\\n  \"toothed\" INTEGER,\\n  \"backbone\" INTEGER,\\n  \"breathes\" INTEGER,\\n  \"venomous\" INTEGER,\\n  \"fins\" INTEGER,\\n  \"legs\" INTEGER,\\n  \"tail\" INTEGER,\\n  \"domestic\" INTEGER,\\n  \"catsize\" INTEGER,\\n  \"type\" TEXT\\n)')\n",
      "('index', 'ix_tabela_zoo_index', 'tabela_zoo', 3, 'CREATE INDEX \"ix_tabela_zoo_index\"ON \"tabela_zoo\" (\"index\")')\n"
     ]
    }
   ],
   "source": [
    "cur.execute(\"SELECT * FROM sqlite_master;\")\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[('tabela_zoo',)]\n"
     ]
    }
   ],
   "source": [
    "cur.execute(\"SELECT name FROM sqlite_master WHERE type='table';\")\n",
    "print(cur.fetchall())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 'aardvark', 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 4, 0, 0, 1, 'mammal')\n",
      "(1, 'antelope', 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 4, 1, 0, 1, 'mammal')\n",
      "(2, 'bass', 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 'fish')\n",
      "(3, 'bear', 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 4, 0, 0, 1, 'mammal')\n",
      "(4, 'boar', 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 4, 1, 0, 1, 'mammal')\n",
      "(5, 'buffalo', 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 4, 1, 0, 1, 'mammal')\n",
      "(6, 'calf', 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 4, 1, 1, 1, 'mammal')\n",
      "(7, 'carp', 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1, 0, 'fish')\n",
      "(8, 'catfish', 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 0, 1, 0, 0, 'fish')\n",
      "(9, 'cavy', 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 4, 0, 1, 0, 'mammal')\n",
      "(10, 'cheetah', 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 0, 0, 4, 1, 0, 1, 'mammal')\n",
      "(11, 'chicken', 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 0, 2, 1, 1, 0, 'bird')\n"
     ]
    }
   ],
   "source": [
    "cur.execute(\"SELECT * FROM tabela_zoo;\")\n",
    "for r in cur.fetchmany(12):\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "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>index</th>\n",
       "      <th>animal</th>\n",
       "      <th>hair</th>\n",
       "      <th>feathers</th>\n",
       "      <th>eggs</th>\n",
       "      <th>milk</th>\n",
       "      <th>airborne</th>\n",
       "      <th>aquatic</th>\n",
       "      <th>predator</th>\n",
       "      <th>toothed</th>\n",
       "      <th>backbone</th>\n",
       "      <th>breathes</th>\n",
       "      <th>venomous</th>\n",
       "      <th>fins</th>\n",
       "      <th>legs</th>\n",
       "      <th>tail</th>\n",
       "      <th>domestic</th>\n",
       "      <th>catsize</th>\n",
       "      <th>type</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>aardvark</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>antelope</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>bass</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>fish</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>bear</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>boar</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>mammal</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index    animal  hair  feathers  eggs  milk  airborne  aquatic  predator  \\\n",
       "0      0  aardvark     1         0     0     1         0        0         1   \n",
       "1      1  antelope     1         0     0     1         0        0         0   \n",
       "2      2      bass     0         0     1     0         0        1         1   \n",
       "3      3      bear     1         0     0     1         0        0         1   \n",
       "4      4      boar     1         0     0     1         0        0         1   \n",
       "\n",
       "   toothed  backbone  breathes  venomous  fins  legs  tail  domestic  catsize  \\\n",
       "0        1         1         1         0     0     4     0         0        1   \n",
       "1        1         1         1         0     0     4     1         0        1   \n",
       "2        1         1         0         0     1     0     1         0        0   \n",
       "3        1         1         1         0     0     4     0         0        1   \n",
       "4        1         1         1         0     0     4     1         0        1   \n",
       "\n",
       "     type  \n",
       "0  mammal  \n",
       "1  mammal  \n",
       "2    fish  \n",
       "3  mammal  \n",
       "4  mammal  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df = pd.read_sql_query(\"SELECT * FROM tabela_zoo;\", conn)\n",
    "new_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parte 2 - Shell Linux"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Usando comandos do Shell, abra o arquivo ../Dados/DomCasmurroMachadoAssis.txt e resolva as seguintes tarefas:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1 - [Ordene as palavras do texto nas formas abaixo](https://jupyterhub.namd.mat.br/user/rsouza/notebooks/FGV_Programming_Languages/Bash/Unix4Poets.ipynb):\n",
    "+ ordem ascii\n",
    "+ ordem alfabética\n",
    "+ ordem de \"rima\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "      3 dada\n",
      "      1 assobradada\n",
      "      1 mandada\n",
      "      1 prendada\n",
      "      2 guardada\n",
      "      1 mudada\n",
      "      1 lisongeada\n",
      "      1 creada\n",
      "      3 fada\n",
      "      1 almofada\n",
      "      2 socegada\n",
      "      2 chegada\n",
      "      1 obrigada\n",
      "      2 castigada\n",
      "      1 zangada\n",
      "      1 engasgada\n",
      "      3 madrugada\n",
      "      1 trabalhada\n",
      "      1 palhada\n",
      "      1 atrapalhada\n",
      "      1 enxovalhada\n"
     ]
    }
   ],
   "source": [
    "! cat ../Dados/DomCasmurroMachadoAssis.txt | tr -sc '[A-Z][a-z]' '[\\012*]' | rev | sort | rev | uniq -c | sed -n '110,130p'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2 - Quantas palavras maiúsculas distintas há no texto?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3 - Quantas palavras há com apenas uma; com apenas duas; e com apenas 3 vogais?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4 - Qual a sequência de comandos para criar um arquivo com os bigramas e suas contagens?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parte 3 - Expressões Regulares"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1 - Repita os exercícios 1 a 4 da parte 2 utilizando [Python](https://docs.python.org/3/library/re.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "﻿The Project Gutenberg EBook of Dom Casmurro, by Machado de Assis\n",
      "\n",
      "This eBook is for the use of anyone anywhere in the United States and most\n",
      "other parts of the world at no cost and with almost no restrictions\n",
      "whatsoever.  You may copy it, give it away or re-use it under the terms of\n",
      "the Project Gutenberg License included with this eBook or online at\n",
      "www.gutenberg.org.  If you are not located in the United States, you'll have\n",
      "to check the laws of the country where you are located before using th\n"
     ]
    }
   ],
   "source": [
    "with open('../Dados/DomCasmurroMachadoAssis.txt', 'r') as f:\n",
    "    texto = f.read()\n",
    "print(texto[0:500])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['\\ufeffThe',\n",
       " 'Project',\n",
       " 'Gutenberg',\n",
       " 'EBook',\n",
       " 'of',\n",
       " 'Dom',\n",
       " 'Casmurro',\n",
       " 'by',\n",
       " 'Machado',\n",
       " 'de']"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "palavras = texto.split()\n",
    "palavras = [p.strip(string.punctuation) for p in palavras]\n",
    "palavras[0:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[' Project',\n",
       " ' Gutenberg',\n",
       " ' E',\n",
       " ' Dom',\n",
       " ' Casmurro',\n",
       " ' Machado',\n",
       " ' Assis',\n",
       " '\\nThis',\n",
       " ' United',\n",
       " ' States',\n",
       " ' You',\n",
       " ' Project',\n",
       " ' Gutenberg',\n",
       " ' License',\n",
       " ' If',\n",
       " ' United',\n",
       " ' States',\n",
       " '\\nTitle',\n",
       " ' Dom',\n",
       " ' Casmurro',\n",
       " '\\nAuthor',\n",
       " ' Machado',\n",
       " ' Assis',\n",
       " '\\nRelease',\n",
       " ' Date',\n",
       " ' October',\n",
       " '\\nLanguage',\n",
       " ' Portuguese',\n",
       " ' S',\n",
       " ' O',\n",
       " ' T',\n",
       " ' P',\n",
       " ' G',\n",
       " ' E',\n",
       " ' D',\n",
       " ' C',\n",
       " '\\nProduced',\n",
       " ' Laura',\n",
       " ' Natal',\n",
       " ' Rodriguez',\n",
       " ' Marc',\n",
       " ' D',\n",
       " ' Free',\n",
       " '\\nLiterature',\n",
       " ' M',\n",
       " ' Bibliotheca',\n",
       " ' Nacional',\n",
       " ' Digital',\n",
       " ' Brasil',\n",
       " '\\nD',\n",
       " ' C',\n",
       " '\\nP',\n",
       " '\\nM',\n",
       " ' D',\n",
       " ' A',\n",
       " '\\nD',\n",
       " ' A',\n",
       " ' B',\n",
       " '\\nH',\n",
       " ' G',\n",
       " ' L',\n",
       " '\\nR',\n",
       " ' M',\n",
       " ' C',\n",
       " '\\nR',\n",
       " ' D',\n",
       " ' J',\n",
       " ' R',\n",
       " ' D',\n",
       " ' S',\n",
       " '\\nP',\n",
       " '\\nI',\n",
       " '\\nDo',\n",
       " '\\nUma',\n",
       " ' Engenho',\n",
       " ' Novo',\n",
       " ' Central',\n",
       " ' Comprimentou',\n",
       " ' A',\n",
       " ' Succedeu',\n",
       " '\\nVi',\n",
       " ' No',\n",
       " ' Casmurro',\n",
       " ' Os',\n",
       " ' Nem',\n",
       " ' Contei',\n",
       " '\\nCasmurro',\n",
       " ' Petropolis',\n",
       " ' Dom',\n",
       " '\\nCasmurro',\n",
       " ' Rhenania',\n",
       " '\\nEngenho',\n",
       " ' Novo',\n",
       " ' Dom',\n",
       " '\\nCasmurro',\n",
       " '\\nN',\n",
       " '\\nTudo',\n",
       " ' Tambem',\n",
       " ' O',\n",
       " '\\nE',\n",
       " ' Ha',\n",
       " '\\nI',\n",
       " '\\nDo',\n",
       " '\\nAgora',\n",
       " ' Antes',\n",
       " '\\nVivo',\n",
       " ' A',\n",
       " ' Um',\n",
       " ' Engenho',\n",
       " ' Novo',\n",
       " '\\nMatacavallos',\n",
       " ' Constructor',\n",
       " ' Na',\n",
       " ' Nos',\n",
       " ' Cesar',\n",
       " ' Augusto',\n",
       " ' Nero',\n",
       " ' Massinissa',\n",
       " ' N',\n",
       " ' Quando',\n",
       " ' Matacavallos',\n",
       " ' Naturalmente',\n",
       " ' O',\n",
       " ' Tenho',\n",
       " ' Uso',\n",
       " ' Emfim',\n",
       " '\\nO',\n",
       " ' Pois',\n",
       " ' Em',\n",
       " '\\nSe',\n",
       " ' O',\n",
       " ' Uma',\n",
       " ' Os',\n",
       " ' Quanto',\n",
       " ' Duas',\n",
       " '\\nEntretanto',\n",
       " '\\nA',\n",
       " ' Em',\n",
       " ' Distrac',\n",
       " '\\nO',\n",
       " '\\nOra',\n",
       " '\\nQuiz',\n",
       " ' Jurisprudencia',\n",
       " ' Depois',\n",
       " ' Suburbios',\n",
       " ' Luiz',\n",
       " ' Gon',\n",
       " ' Santos',\n",
       " ' Foi',\n",
       " ' Talvez',\n",
       " ' Ahi',\n",
       " '\\nFiquei',\n",
       " ' Sim',\n",
       " ' Nero',\n",
       " ' Augusto',\n",
       " ' Massinissa',\n",
       " ' Cesar',\n",
       " ' Deste',\n",
       " ' Eia',\n",
       " ' Novembro',\n",
       " '\\nTive',\n",
       " '\\nI',\n",
       " '\\nA',\n",
       " '\\nIa',\n",
       " ' A',\n",
       " ' Matacavallos',\n",
       " '\\nNovembro',\n",
       " ' Gloria',\n",
       " ' Bentinho',\n",
       " '\\nMinha',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Padua',\n",
       " ' Padua',\n",
       " ' N',\n",
       " ' Bentinho',\n",
       " ' Mettidos',\n",
       " ' Em',\n",
       " ' Bentinho',\n",
       " ' A',\n",
       " ' Comprehendo',\n",
       " ' Sr',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Basta',\n",
       " ' Bentinho',\n",
       " '\\nCapit',\n",
       " ' N',\n",
       " ' Padua',\n",
       " ' Pois',\n",
       " ' Mano',\n",
       " ' Cosme',\n",
       " '\\nTio',\n",
       " ' Cosme',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Oxal',\n",
       " ' Bentinho',\n",
       " ' E',\n",
       " ' N',\n",
       " ' Constituinte',\n",
       " ' Feij',\n",
       " ' Cosme',\n",
       " ' O',\n",
       " ' Brasil',\n",
       " ' Quanto',\n",
       " ' Mas',\n",
       " ' Gloria',\n",
       " '\\nCreio',\n",
       " ' Voc',\n",
       " ' Justina',\n",
       " ' Cosme',\n",
       " ' Deus',\n",
       " ' Comtudo',\n",
       " ' Mas',\n",
       " ' Gloria',\n",
       " ' Est',\n",
       " ' Ora',\n",
       " ' Pois',\n",
       " '\\nMinha',\n",
       " ' Prima',\n",
       " ' Justina',\n",
       " ' Seguiu',\n",
       " ' N',\n",
       " ' Cosme',\n",
       " ' Prima',\n",
       " ' Justina',\n",
       " ' Gloria',\n",
       " ' Gloria',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " '\\nI',\n",
       " '\\nUm',\n",
       " '\\nJos',\n",
       " ' Dias',\n",
       " ' Era',\n",
       " ' Levantou',\n",
       " ' Cosi',\n",
       " ' Foi',\n",
       " ' Rio',\n",
       " ' Janeiro',\n",
       " ' Trazia',\n",
       " ' A',\n",
       " ' O',\n",
       " ' Era',\n",
       " ' Levantou',\n",
       " ' Um',\n",
       " '\\nV',\n",
       " '\\nO',\n",
       " '\\nNem',\n",
       " ' Tambem',\n",
       " ' Outrosim',\n",
       " ' Nos',\n",
       " '\\nEra',\n",
       " ' Itaguahy',\n",
       " ' Um',\n",
       " ' Havia',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Ent',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' V',\n",
       " '\\nVoltou',\n",
       " ' Quando',\n",
       " ' Rio',\n",
       " ' Janeiro',\n",
       " ' Um',\n",
       " ' Itaguahy',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Tom',\n",
       " ' Elles',\n",
       " ' Deus',\n",
       " ' Eu',\n",
       " ' N',\n",
       " '\\nN',\n",
       " '\\nTinha',\n",
       " ' Quando',\n",
       " ' Minha',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " '\\nTeve',\n",
       " ' Copiou',\n",
       " ' Com',\n",
       " ' Ao',\n",
       " ' E',\n",
       " ' A',\n",
       " ' Era',\n",
       " ' Robespierre',\n",
       " ' Contava',\n",
       " ' Europa',\n",
       " ' Lisboa',\n",
       " ' Deus',\n",
       " ' Cosme',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " '\\nE',\n",
       " ' Deus',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Minha',\n",
       " ' Tio',\n",
       " ' Cosme',\n",
       " '\\nV',\n",
       " '\\nTio',\n",
       " ' Cosme',\n",
       " '\\nTio',\n",
       " ' Cosme',\n",
       " ' J',\n",
       " ' Justina',\n",
       " '\\nA',\n",
       " ' Formado',\n",
       " ' Cosme',\n",
       " '\\nTinha',\n",
       " ' Violas',\n",
       " ' Aljube',\n",
       " ' Trabalhava',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Cosme',\n",
       " ' Era',\n",
       " ' Em',\n",
       " ' Tio',\n",
       " ' Cosme',\n",
       " '\\nEra',\n",
       " '\\nUma',\n",
       " '\\nO',\n",
       " ' Depois',\n",
       " ' Emfim',\n",
       " ' Cosme',\n",
       " ' Raramente',\n",
       " ' Tio',\n",
       " ' Cosme',\n",
       " '\\nTambem',\n",
       " ' Posto',\n",
       " ' Tio',\n",
       " ' Cosme',\n",
       " ' Quando',\n",
       " ' Ella',\n",
       " ' Gloria',\n",
       " ' Padre',\n",
       " ' Gloria',\n",
       " ' Ora',\n",
       " '\\nA',\n",
       " ' N',\n",
       " ' Cosme',\n",
       " ' Nelle',\n",
       " '\\nJ',\n",
       " ' Contam',\n",
       " ' Agora',\n",
       " ' Nas',\n",
       " ' Uma',\n",
       " '\\nV',\n",
       " '\\nD',\n",
       " ' Gloria',\n",
       " '\\nMinha',\n",
       " ' Quando',\n",
       " ' Pedro',\n",
       " '\\nAlbuquerque',\n",
       " ' Santiago',\n",
       " ' Itaguahy',\n",
       " ' N',\n",
       " ' Vendeu',\n",
       " ' Matacavallos',\n",
       " ' Era',\n",
       " ' Fernandes',\n",
       " '\\nOra',\n",
       " ' D',\n",
       " ' Maria',\n",
       " ' Gloria',\n",
       " ' Fernandes',\n",
       " '\\nSantiago',\n",
       " ' Era',\n",
       " ' Vivia',\n",
       " ' Os',\n",
       " ' Lidava',\n",
       " '\\nTenho',\n",
       " ' A',\n",
       " ' N',\n",
       " ' O',\n",
       " ' O',\n",
       " ' Contava',\n",
       " ' No',\n",
       " ' O',\n",
       " '\\nConcluo',\n",
       " ' Nenhum',\n",
       " ' Pandora',\n",
       " '\\nAqui',\n",
       " ' Quando',\n",
       " ' Pandora',\n",
       " '\\nS',\n",
       " ' O',\n",
       " ' O',\n",
       " ' Se',\n",
       " ' Depois',\n",
       " '\\nS',\n",
       " '\\nV',\n",
       " '\\nMas',\n",
       " ' Novembro',\n",
       " '\\nVerdadeiramente',\n",
       " '\\nAgora',\n",
       " ' E',\n",
       " ' Talvez',\n",
       " '\\nI',\n",
       " '\\nA',\n",
       " '\\nJ',\n",
       " ' Sempre',\n",
       " '\\nEuropa',\n",
       " ' Trazia',\n",
       " ' Quando',\n",
       " ' Babylonia',\n",
       " ' Vinha',\n",
       " ' Uma',\n",
       " ' Chianti',\n",
       " ' O',\n",
       " ' Ha',\n",
       " ' Marcolini',\n",
       " '\\nE',\n",
       " '\\nDeus',\n",
       " ' A',\n",
       " ' Satanaz',\n",
       " ' Rival',\n",
       " ' Miguel',\n",
       " ' Raphael',\n",
       " '\\nGabriel',\n",
       " ' P',\n",
       " ' Tramou',\n",
       " ' Tudo',\n",
       " ' Deus',\n",
       " ' Satanaz',\n",
       " '\\nCom',\n",
       " ' Padre',\n",
       " ' Eterno',\n",
       " ' Aqui',\n",
       " ' Senhor',\n",
       " ' Senhor',\n",
       " '\\nSatanaz',\n",
       " ' Deus',\n",
       " ' Creou',\n",
       " ' Basta',\n",
       " '\\nFoi',\n",
       " ' Com',\n",
       " ' N',\n",
       " ' Eden',\n",
       " ' Abel',\n",
       " ' N',\n",
       " ' Certos',\n",
       " ' Tambem',\n",
       " '\\nAs',\n",
       " ' Tal',\n",
       " '\\nOs',\n",
       " ' Um',\n",
       " ' J',\n",
       " '\\nJuram',\n",
       " ' O',\n",
       " ' Windsor',\n",
       " ' Este',\n",
       " ' Dizem',\n",
       " ' Satanaz',\n",
       " '\\nShakespeare',\n",
       " ' Chegam',\n",
       " ' O',\n",
       " ' Poeta',\n",
       " ' Escriptura',\n",
       " ' Deus',\n",
       " ' Satanaz',\n",
       " ' Caro',\n",
       " '\\nSantiago',\n",
       " ' Isto',\n",
       " ' Um',\n",
       " ' Tudo',\n",
       " ' No',\n",
       " ' Este',\n",
       " ' N',\n",
       " ' Tambem',\n",
       " '\\nX',\n",
       " '\\nAcceito',\n",
       " '\\nQue',\n",
       " '\\nEu',\n",
       " ' Marcolini',\n",
       " ' Cantei',\n",
       " ' Mas',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' A',\n",
       " '\\nX',\n",
       " '\\nA',\n",
       " '\\nT',\n",
       " ' N',\n",
       " ' A',\n",
       " '\\nOs',\n",
       " ' Tendo',\n",
       " ' Deus',\n",
       " ' Talvez',\n",
       " ' N',\n",
       " ' Viuva',\n",
       " ' Deus',\n",
       " ' Unicamente',\n",
       " ' Cabral',\n",
       " ' Cosme',\n",
       " '\\nPrazos',\n",
       " '\\nMinha',\n",
       " ' Entretanto',\n",
       " '\\nQuando',\n",
       " ' Em',\n",
       " ' Arranjavamos',\n",
       " '\\nCapit',\n",
       " ' Ella',\n",
       " ' No',\n",
       " ' Eu',\n",
       " ' Voltava',\n",
       " ' Isto',\n",
       " ' N',\n",
       " '\\nUltimamente',\n",
       " ' Quinze',\n",
       " ' S',\n",
       " ' Jos',\n",
       " ' Minha',\n",
       " '\\nX',\n",
       " '\\nNa',\n",
       " '\\nParei',\n",
       " ' N',\n",
       " ' Comecei',\n",
       " ' Vozes',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " '\\nTijolos',\n",
       " ' E',\n",
       " '\\nUm',\n",
       " '\\nEra',\n",
       " ' Passaros',\n",
       " '\\nCom',\n",
       " ' Capit',\n",
       " ' Capit',\n",
       " ' Realmente',\n",
       " ' Antes',\n",
       " ' Entretanto',\n",
       " ' Capit',\n",
       " ' E',\n",
       " '\\nEu',\n",
       " ' Ent',\n",
       " ' Capit',\n",
       " ' Quando',\n",
       " ' Corcovado',\n",
       " ' Em',\n",
       " ' Os',\n",
       " ' Tambem',\n",
       " '\\nCapit',\n",
       " ' Fez',\n",
       " '\\nPois',\n",
       " ' A',\n",
       " ' Os',\n",
       " ' Tambem',\n",
       " ' Capit',\n",
       " ' Se',\n",
       " ' Cheguei',\n",
       " '\\nTudo',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Naquelle',\n",
       " ' Verdade',\n",
       " '\\nBondade',\n",
       " ' Virtudes',\n",
       " ' Em',\n",
       " ' Capit',\n",
       " ' Capit',\n",
       " ' E',\n",
       " ' Esse',\n",
       " ' Naturalmente',\n",
       " ' Naturalmente',\n",
       " '\\nX',\n",
       " '\\nCapit',\n",
       " '\\nDe',\n",
       " '\\nE',\n",
       " '\\nE',\n",
       " '\\nN',\n",
       " ' As',\n",
       " ' Era',\n",
       " ' Que',\n",
       " ' As',\n",
       " ' Havia',\n",
       " ' Capit',\n",
       " ' A',\n",
       " ' Era',\n",
       " '\\nEm',\n",
       " ' Quando',\n",
       " ' Capit',\n",
       " ' Entrava',\n",
       " ' Jo',\n",
       " ' Costa',\n",
       " ' Capit',\n",
       " ' Ent',\n",
       " '\\nA',\n",
       " ' Quiz',\n",
       " ' Afinal',\n",
       " ' Capit',\n",
       " ' O',\n",
       " '\\nCaminhei',\n",
       " ' Nada',\n",
       " '\\nQuiz',\n",
       " ' Todo',\n",
       " ' N',\n",
       " '\\nOs',\n",
       " ' Morena',\n",
       " '\\nAs',\n",
       " ' Cal',\n",
       " '\\nE',\n",
       " '\\nPensei',\n",
       " ' Se',\n",
       " ' Mas',\n",
       " '\\nNisto',\n",
       " ' Vi',\n",
       " ' Ent',\n",
       " ' Capit',\n",
       " ' Foi',\n",
       " '\\nX',\n",
       " '\\nA',\n",
       " '\\nTudo',\n",
       " '\\nO',\n",
       " ' Dei',\n",
       " '\\nB',\n",
       " ' C',\n",
       " '\\nVoltei',\n",
       " ' Capit',\n",
       " ' Ergueu',\n",
       " ' Confiss',\n",
       " ' Em',\n",
       " ' N',\n",
       " ' N',\n",
       " ' Devia',\n",
       " '\\nConhecia',\n",
       " '\\nN',\n",
       " ' Os',\n",
       " ' Padre',\n",
       " ' Epistola',\n",
       " ' Evangelho',\n",
       " ' A',\n",
       " '\\nFaltava',\n",
       " ' N',\n",
       " ' Estavamos',\n",
       " ' As',\n",
       " ' Os',\n",
       " '\\nX',\n",
       " '\\nOutra',\n",
       " '\\nOutra',\n",
       " '\\nEra',\n",
       " ' Capit',\n",
       " '\\nSolt',\n",
       " ' Capit',\n",
       " '\\nCapit',\n",
       " ' Padua',\n",
       " ' De',\n",
       " ' Era',\n",
       " ' Tartaruga',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Ninguem',\n",
       " '\\nOlhei',\n",
       " ' Capit',\n",
       " ' Bentinho',\n",
       " ' Papae',\n",
       " '\\nE',\n",
       " ' O',\n",
       " ' Padua',\n",
       " ' Capit',\n",
       " ' Esta',\n",
       " ' E',\n",
       " ' Ha',\n",
       " ' E',\n",
       " ' Capit',\n",
       " ' Parece',\n",
       " ' Mam',\n",
       " ' Estou',\n",
       " '\\nVoc',\n",
       " ' Est',\n",
       " ' Ia',\n",
       " '\\nQue',\n",
       " ' Meu',\n",
       " ' Capit',\n",
       " ' Tinha',\n",
       " ' A',\n",
       " ' Trocava',\n",
       " ' Tambem',\n",
       " '\\nX',\n",
       " '\\nO',\n",
       " '\\nPadua',\n",
       " '\\nN',\n",
       " '\\nDemais',\n",
       " ' Comprou',\n",
       " ' A',\n",
       " '\\nPadua',\n",
       " ' Cabo',\n",
       " ' Europa',\n",
       " ' D',\n",
       " '\\nFortunata',\n",
       " ' Padua',\n",
       " '\\nD',\n",
       " ' Fortunata',\n",
       " ' Nem',\n",
       " ' Padua',\n",
       " ' Escutai',\n",
       " '\\nO',\n",
       " ' Padua',\n",
       " '\\nNorte',\n",
       " ' Padua',\n",
       " ' Esta',\n",
       " ' N',\n",
       " ' Viveu',\n",
       " ' Uma',\n",
       " ' Pediu',\n",
       " ' Minha',\n",
       " ' Fazer',\n",
       " ' J',\n",
       " ' N',\n",
       " ' E',\n",
       " ' Que',\n",
       " ' E',\n",
       " ' E',\n",
       " ' Sr',\n",
       " ' Padua',\n",
       " ' Deixe',\n",
       " ' Lembre',\n",
       " ' Pois',\n",
       " '\\nSeja',\n",
       " '\\nPadua',\n",
       " ' D',\n",
       " ' Fortunata',\n",
       " '\\nMas',\n",
       " ' Minha',\n",
       " ' Que',\n",
       " ' N',\n",
       " ' Padua',\n",
       " '\\nNos',\n",
       " ' N',\n",
       " ' Vieram',\n",
       " ' Padua',\n",
       " ' A',\n",
       " ' J',\n",
       " '\\nCom',\n",
       " ' Padua',\n",
       " ' A',\n",
       " '\\nOu',\n",
       " ' Ora',\n",
       " '\\nOu',\n",
       " '\\nTal',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Cabral',\n",
       " '\\nEscriptura',\n",
       " ' Padua',\n",
       " ' Eliphaz',\n",
       " '\\nJob',\n",
       " ' Senhor',\n",
       " '\\nX',\n",
       " '\\nOs',\n",
       " ' Quando',\n",
       " ' Achilles',\n",
       " ' Cheguei',\n",
       " ' Catei',\n",
       " '\\nN',\n",
       " ' Os',\n",
       " ' Talvez',\n",
       " '\\nX',\n",
       " '\\nUm',\n",
       " '\\nPae',\n",
       " ' Capit',\n",
       " ' Com',\n",
       " ' Capit',\n",
       " ' Quando',\n",
       " '\\nCapit',\n",
       " ' Recolheu',\n",
       " ' Ent',\n",
       " ' Naquelle',\n",
       " ' Jurei',\n",
       " ' Que',\n",
       " ' Capit',\n",
       " ' Quiz',\n",
       " ' Essa',\n",
       " ' Emfim',\n",
       " '\\nFiquei',\n",
       " ' Capit',\n",
       " ' Que',\n",
       " ' Tambem',\n",
       " ' Quiz',\n",
       " ' Capit',\n",
       " ' Nunca',\n",
       " ' Cerrava',\n",
       " '\\nEu',\n",
       " ' Voc',\n",
       " '\\nCalou',\n",
       " ' Quando',\n",
       " ' Capit',\n",
       " ' Estava',\n",
       " ' Quiz',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Quando',\n",
       " ' Mam',\n",
       " ' Parece',\n",
       " ' Dias',\n",
       " ' Elle',\n",
       " ' Mas',\n",
       " '\\nDisse',\n",
       " ' Ao',\n",
       " ' Este',\n",
       " ' Aos',\n",
       " '\\nCapit',\n",
       " ' A',\n",
       " ' Pediu',\n",
       " ' Como',\n",
       " ' A',\n",
       " ' Capit',\n",
       " '\\nEm',\n",
       " ' Deus',\n",
       " ' Fiquei',\n",
       " ' Capit',\n",
       " ' Tinhamos',\n",
       " ' Capit',\n",
       " '\\nComprei',\n",
       " ' Capit',\n",
       " ' Vi',\n",
       " ' Ao',\n",
       " ' Chora',\n",
       " ' Chora',\n",
       " ' Vintem',\n",
       " ' Da',\n",
       " ' Creio',\n",
       " ' Europa',\n",
       " '\\nDito',\n",
       " ' Com',\n",
       " '\\nComo',\n",
       " ' Capit',\n",
       " ' Supponde',\n",
       " '\\nAssim',\n",
       " ' Europa',\n",
       " ' Capit',\n",
       " ' Lage',\n",
       " ' Bord',\n",
       " ' Tal',\n",
       " ' Rejeitou',\n",
       " ' Cosme',\n",
       " ' Prima',\n",
       " '\\nJustina',\n",
       " ' Cabral',\n",
       " '\\nJos',\n",
       " ' Dias',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Capit',\n",
       " ' Elle',\n",
       " ' N',\n",
       " ' Tudo',\n",
       " '\\nD',\n",
       " ' Fa',\n",
       " ' D',\n",
       " ' Gloria',\n",
       " ' Capit',\n",
       " ' Experimentemos',\n",
       " ' D',\n",
       " ' Gloria',\n",
       " ' Cabral',\n",
       " ' Voc',\n",
       " ' D',\n",
       " ' Gloria',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Ande',\n",
       " ' Olhe',\n",
       " ' S',\n",
       " ' Paulo',\n",
       " '\\nEstremeci',\n",
       " ' S',\n",
       " ' Paulo',\n",
       " ' Prometti',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Capit',\n",
       " ' E',\n",
       " ' Conto',\n",
       " ' Genesis',\n",
       " '\\nX',\n",
       " '\\nSem',\n",
       " '\\nQuando',\n",
       " ' Vim',\n",
       " ' Formulei',\n",
       " ' Na',\n",
       " ' Capit',\n",
       " ' Proferi',\n",
       " ' Repeti',\n",
       " ' Cuidei',\n",
       " '\\nAfinal',\n",
       " ' E',\n",
       " ' Bastava',\n",
       " ' Capit',\n",
       " ' Geitoso',\n",
       " '\\nX',\n",
       " '\\nMil',\n",
       " '\\nLevantei',\n",
       " ' Era',\n",
       " ' E',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " '\\nA',\n",
       " ' A',\n",
       " ' A',\n",
       " ' Santa',\n",
       " ' Theresa',\n",
       " '\\nN',\n",
       " ' Desde',\n",
       " ' Disse',\n",
       " ' Assim',\n",
       " ' Entrei',\n",
       " ' Era',\n",
       " '\\nMas',\n",
       " ' O',\n",
       " '\\nAfinal',\n",
       " '\\nRealmente',\n",
       " ' Mil',\n",
       " '\\nEra',\n",
       " ' Deus',\n",
       " ' Homem',\n",
       " ' Sublimes',\n",
       " '\\nCogitei',\n",
       " ' N',\n",
       " ' Mandar',\n",
       " ' Gloria',\n",
       " ' Terra',\n",
       " '\\nEra',\n",
       " '\\nA',\n",
       " ' Terra',\n",
       " ' As',\n",
       " '\\nX',\n",
       " '\\nPrima',\n",
       " ' Justina',\n",
       " '\\nNa',\n",
       " ' Justina',\n",
       " ' Veiu',\n",
       " ' D',\n",
       " ' Fortunata',\n",
       " ' Mam',\n",
       " '\\nA',\n",
       " ' N',\n",
       " ' Justina',\n",
       " ' Pedro',\n",
       " ' Paulo',\n",
       " ' Paulo',\n",
       " ' Pedro',\n",
       " ' Era',\n",
       " ' Vivia',\n",
       " '\\nPasse',\n",
       " ' Quiz',\n",
       " ' Respondi',\n",
       " ' Gloria',\n",
       " ' Quem',\n",
       " ' Primo',\n",
       " ' Cosme',\n",
       " ' Dias',\n",
       " '\\nEnruguei',\n",
       " ' Prima',\n",
       " '\\nJustina',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Gloria',\n",
       " ' E',\n",
       " '\\nNote',\n",
       " ' Pois',\n",
       " ' Voc',\n",
       " ' Hoje',\n",
       " '\\nN',\n",
       " ' Novamente',\n",
       " ' Jos',\n",
       " ' Dias',\n",
       " ' Eu',\n",
       " ' Justina',\n",
       " ' Supponha',\n",
       " ' Gloria',\n",
       " ' Voc',\n",
       " ' L',\n",
       " ' Se',\n",
       " ' Justina',\n",
       " '\\nGloria',\n",
       " ' E',\n",
       " ' Agora',\n",
       " '\\nX',\n",
       " '\\nSensa',\n",
       " '\\nN',\n",
       " ' Capit',\n",
       " ' Ent',\n",
       " ' Justina',\n",
       " ' Concei',\n",
       " '\\nCapit',\n",
       " ' N',\n",
       " ' Eu',\n",
       " '\\nEntretanto',\n",
       " ' Justina',\n",
       " ' Quando',\n",
       " ' N',\n",
       " '\\nJos',\n",
       " ' Dias',\n",
       " ...]"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "maiusculas = re.findall(r'\\s[$A-Z]{1}[a-z]*', texto)\n",
    "maiusculas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Parte 4 - Bancos de dados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "········\n"
     ]
    }
   ],
   "source": [
    "p = getpass.getpass()\n",
    "conn = pymysql.connect(host='127.0.0.1', #localhost\n",
    "                       port=3306, \n",
    "                       user='aluno', \n",
    "                       passwd=p, \n",
    "                       db='SQLExample1')\n",
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('account',)\n",
      "('branch',)\n",
      "('business',)\n",
      "('customer',)\n",
      "('department',)\n",
      "('employee',)\n",
      "('individual',)\n",
      "('officer',)\n",
      "('product',)\n",
      "('product_type',)\n",
      "('transaction',)\n"
     ]
    }
   ],
   "source": [
    "cur.execute('use SQLExample1;')\n",
    "cur.execute('show tables;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('account_id', 'int(10) unsigned', 'NO', 'PRI', None, 'auto_increment')\n",
      "('product_cd', 'varchar(10)', 'NO', 'MUL', None, '')\n",
      "('cust_id', 'int(10) unsigned', 'NO', 'MUL', None, '')\n",
      "('open_date', 'date', 'NO', '', None, '')\n",
      "('close_date', 'date', 'YES', '', None, '')\n",
      "('last_activity_date', 'date', 'YES', '', None, '')\n",
      "('status', \"enum('ACTIVE','CLOSED','FROZEN')\", 'YES', '', None, '')\n",
      "('open_branch_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n",
      "('open_emp_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n",
      "('avail_balance', 'float(10,2)', 'YES', '', None, '')\n",
      "('pending_balance', 'float(10,2)', 'YES', '', None, '')\n"
     ]
    }
   ],
   "source": [
    "cur.execute('describe account;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 'CHK', 1, datetime.date(2000, 1, 15), None, datetime.date(2005, 1, 4), 'ACTIVE', 2, 10, 1057.75, 1057.75)\n",
      "(2, 'SAV', 1, datetime.date(2000, 1, 15), None, datetime.date(2004, 12, 19), 'ACTIVE', 2, 10, 500.0, 500.0)\n",
      "(3, 'CD', 1, datetime.date(2004, 6, 30), None, datetime.date(2004, 6, 30), 'ACTIVE', 2, 10, 3000.0, 3000.0)\n",
      "(4, 'CHK', 2, datetime.date(2001, 3, 12), None, datetime.date(2004, 12, 27), 'ACTIVE', 2, 10, 2258.02, 2258.02)\n",
      "(5, 'SAV', 2, datetime.date(2001, 3, 12), None, datetime.date(2004, 12, 11), 'ACTIVE', 2, 10, 200.0, 200.0)\n"
     ]
    }
   ],
   "source": [
    "cur.execute('select * from account limit 5;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('product_cd', 'varchar(10)', 'NO', 'PRI', None, '')\n",
      "('name', 'varchar(50)', 'NO', '', None, '')\n",
      "('product_type_cd', 'varchar(10)', 'NO', 'MUL', None, '')\n",
      "('date_offered', 'date', 'YES', '', None, '')\n",
      "('date_retired', 'date', 'YES', '', None, '')\n"
     ]
    }
   ],
   "source": [
    "cur.execute('describe product;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('AUT', 'auto loan', 'LOAN', datetime.date(2000, 1, 1), None)\n",
      "('BUS', 'business line of credit', 'LOAN', datetime.date(2000, 1, 1), None)\n",
      "('CD', 'certificate of deposit', 'ACCOUNT', datetime.date(2000, 1, 1), None)\n",
      "('CHK', 'checking account', 'ACCOUNT', datetime.date(2000, 1, 1), None)\n",
      "('MM', 'money market account', 'ACCOUNT', datetime.date(2000, 1, 1), None)\n",
      "('MRT', 'home mortgage', 'LOAN', datetime.date(2000, 1, 1), None)\n",
      "('SAV', 'savings account', 'ACCOUNT', datetime.date(2000, 1, 1), None)\n",
      "('SBL', 'small business loan', 'LOAN', datetime.date(2000, 1, 1), None)\n"
     ]
    }
   ],
   "source": [
    "cur.execute('select * from product;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('product_type_cd', 'varchar(10)', 'NO', 'PRI', None, '')\n",
      "('name', 'varchar(50)', 'NO', '', None, '')\n"
     ]
    }
   ],
   "source": [
    "cur.execute('describe product_type;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('ACCOUNT', 'Customer Accounts')\n",
      "('INSURANCE', 'Insurance Offerings')\n",
      "('LOAN', 'Individual and Business Loans')\n"
     ]
    }
   ],
   "source": [
    "cur.execute('select * from product_type;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('emp_id', 'smallint(5) unsigned', 'NO', 'PRI', None, 'auto_increment')\n",
      "('fname', 'varchar(20)', 'NO', '', None, '')\n",
      "('lname', 'varchar(20)', 'NO', '', None, '')\n",
      "('start_date', 'date', 'NO', '', None, '')\n",
      "('end_date', 'date', 'YES', '', None, '')\n",
      "('superior_emp_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n",
      "('dept_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n",
      "('title', 'varchar(20)', 'YES', '', None, '')\n",
      "('assigned_branch_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n"
     ]
    }
   ],
   "source": [
    "cur.execute('describe employee;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 'Michael', 'Smith', datetime.date(2001, 6, 22), None, None, 3, 'President', 1)\n",
      "(2, 'Susan', 'Barker', datetime.date(2002, 9, 12), None, 1, 3, 'Vice President', 1)\n",
      "(3, 'Robert', 'Tyler', datetime.date(2000, 2, 9), None, 1, 3, 'Treasurer', 1)\n",
      "(4, 'Susan', 'Hawthorne', datetime.date(2002, 4, 24), None, 3, 1, 'Operations Manager', 1)\n",
      "(5, 'John', 'Gooding', datetime.date(2003, 11, 14), None, 4, 2, 'Loan Manager', 1)\n",
      "(6, 'Helen', 'Fleming', datetime.date(2004, 3, 17), None, 4, 1, 'Head Teller', 1)\n",
      "(7, 'Chris', 'Tucker', datetime.date(2004, 9, 15), None, 6, 1, 'Teller', 1)\n",
      "(8, 'Sarah', 'Parker', datetime.date(2002, 12, 2), None, 6, 1, 'Teller', 1)\n",
      "(9, 'Jane', 'Grossman', datetime.date(2002, 5, 3), None, 6, 1, 'Teller', 1)\n",
      "(10, 'Paula', 'Roberts', datetime.date(2002, 7, 27), None, 4, 1, 'Head Teller', 2)\n"
     ]
    }
   ],
   "source": [
    "cur.execute('select * from employee limit 10;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1 - Na tabela \"account\", quais os valores médio, mínimo e máximo de \"avail_balance\"?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2 - Quais registros na tabela \"account\" estão acima da média de \"avail_balance\"?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3 - Na tabela \"account\", quais as 3 datas mais recentes e as 3 datas mais antigas (\"open_date\")?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4 - Para cada elemento na tabela \"product\", exiba o nome completo do \"product_type_cd\" (tabela \"product_type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cur.execute('use SQLExample1;')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('auto loan', 'Individual and Business Loans')\n",
      "('business line of credit', 'Individual and Business Loans')\n",
      "('certificate of deposit', 'Customer Accounts')\n",
      "('checking account', 'Customer Accounts')\n",
      "('money market account', 'Customer Accounts')\n",
      "('home mortgage', 'Individual and Business Loans')\n",
      "('savings account', 'Customer Accounts')\n",
      "('small business loan', 'Individual and Business Loans')\n"
     ]
    }
   ],
   "source": [
    "q = '''\n",
    "SELECT p.name, t.name FROM product AS p \n",
    "JOIN product_type AS t\n",
    "ON p.product_type_cd = t.product_type_cd\n",
    ";\n",
    "'''\n",
    "\n",
    "cur.execute(q)\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5 - Quantos empregados (\"employees\") possuem a letra \"e\" em seus nomes? E quantos tem sobrenomes que terminam com \"r\"? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6 - Quais são os títulos (\"title\") possíveis para os empregados (\"employees\")? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7 - Quantos empregados (\"employees\") estão a exatamente dois níveis abaixo do presidente? "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cur.execute('use SQLExample1;')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('emp_id', 'smallint(5) unsigned', 'NO', 'PRI', None, 'auto_increment')\n",
      "('fname', 'varchar(20)', 'NO', '', None, '')\n",
      "('lname', 'varchar(20)', 'NO', '', None, '')\n",
      "('start_date', 'date', 'NO', '', None, '')\n",
      "('end_date', 'date', 'YES', '', None, '')\n",
      "('superior_emp_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n",
      "('dept_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n",
      "('title', 'varchar(20)', 'YES', '', None, '')\n",
      "('assigned_branch_id', 'smallint(5) unsigned', 'YES', 'MUL', None, '')\n"
     ]
    }
   ],
   "source": [
    "cur.execute('describe employee;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2, 'Susan', 'Barker', datetime.date(2002, 9, 12), None, 1, 3, 'Vice President', 1)\n",
      "(3, 'Robert', 'Tyler', datetime.date(2000, 2, 9), None, 1, 3, 'Treasurer', 1)\n",
      "(4, 'Susan', 'Hawthorne', datetime.date(2002, 4, 24), None, 3, 1, 'Operations Manager', 1)\n"
     ]
    }
   ],
   "source": [
    "q = '''\n",
    "SELECT * FROM employee WHERE superior_emp_id IN \n",
    "(SELECT emp_id FROM employee WHERE superior_emp_id = 1)\n",
    "OR \n",
    "superior_emp_id = 1\n",
    ";\n",
    "'''\n",
    "\n",
    "cur.execute(q)\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "8 - Na tabela \"account\", quais os valores médio, mínimo e máximo de \"avail_balance\" por tipo de 'product_cd' ?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "9 - Na tabela \"transaction\", há quantos registros por ano (\"txn_date\")?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "10 - Você é dono de uma loja de automóveis. Crie tabelas no banco \"alunos\" para representar os carros de seu pátio, os modelos de automóveis, os clientes e as compras realizadas. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "cur.execute('use alunos;')\n",
    "cur.execute('show tables;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/pymysql/cursors.py:166: Warning: (1050, \"Table 'carros' already exists\")\n",
      "  result = self._query(query)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "q = '''CREATE TABLE IF NOT EXISTS carros\n",
    "       (text VARCHAR(200) DEFAULT NULL,\n",
    "        number INT DEFAULT NULL)\n",
    "        ENGINE=MyISAM DEFAULT CHARSET='utf8';'''\n",
    "\n",
    "cur.execute(q)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('carros',)\n"
     ]
    }
   ],
   "source": [
    "cur.execute('show tables;')\n",
    "for r in cur.fetchall():\n",
    "    print(r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "11 - Crie uma lista no Python com todos os nomes e sobrenomes em strings únicas, a partir da tabela \"individual\"  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "12 - A partir da tabela \"individual\", crie um dicionário no Python tendo os nomes e sobrenomes em strings únicas como chaves e os anos das datas como valores."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "13 - Utilizando Python, crie um banco de dados no sqlite que guarde a seguinte estrutura, demonstrada no dataframe do Pandas:  \n",
    "Use os tipos de dados mais adequados.  \n",
    "\n",
    "Veja:  \n",
    "https://sqlite.org/datatype3.html    \n",
    "https://sqlite.org/autoinc.html  \n",
    "https://www.tutorialspoint.com/sqlite/sqlite_update_query.htm  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>Gender</th>\n",
       "      <th>Age</th>\n",
       "      <th>Salary before Stern</th>\n",
       "      <th>Expected salary</th>\n",
       "      <th>Candidate</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Male</td>\n",
       "      <td>27</td>\n",
       "      <td>60000</td>\n",
       "      <td>110000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Male</td>\n",
       "      <td>30</td>\n",
       "      <td>125000</td>\n",
       "      <td>125000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Male</td>\n",
       "      <td>27</td>\n",
       "      <td>50000</td>\n",
       "      <td>120000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Male</td>\n",
       "      <td>26</td>\n",
       "      <td>56000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Male</td>\n",
       "      <td>27</td>\n",
       "      <td>82000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Male</td>\n",
       "      <td>32</td>\n",
       "      <td>150000</td>\n",
       "      <td>150000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Female</td>\n",
       "      <td>24</td>\n",
       "      <td>55000</td>\n",
       "      <td>100000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Male</td>\n",
       "      <td>30</td>\n",
       "      <td>110000</td>\n",
       "      <td>150000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Male</td>\n",
       "      <td>26</td>\n",
       "      <td>48000</td>\n",
       "      <td>80000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Male</td>\n",
       "      <td>26</td>\n",
       "      <td>120000</td>\n",
       "      <td>80000</td>\n",
       "      <td>Bush</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Gender  Age  Salary before Stern  Expected salary Candidate\n",
       "id                                                             \n",
       "0     Male   27                60000           110000      Bush\n",
       "1     Male   30               125000           125000      Bush\n",
       "2     Male   27                50000           120000      Bush\n",
       "3     Male   26                56000           100000      Bush\n",
       "4     Male   27                82000           100000      Bush\n",
       "5     Male   32               150000           150000      Bush\n",
       "6   Female   24                55000           100000      Bush\n",
       "7     Male   30               110000           150000      Bush\n",
       "8     Male   26                48000            80000      Bush\n",
       "9     Male   26               120000            80000      Bush"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_tf = pd.read_excel('../Dados/votesurvey.xls')\n",
    "df_tf.index.name = 'id'\n",
    "df_tf.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "14 - Conecte ao banco SQLite \"iris_database.sqlite\"e responda, demonstrando os comandos SQL apropriados:  \n",
    "\n",
    "a) Há quantas \"Species\" diferentes na tabela \"iris\"?  \n",
    "b) Quantos registros totais há na tabela \"iris\"?  \n",
    "\n",
    "Considerando a superfície das pétalas e sépalas como retangular, responda:  \n",
    "\n",
    "c) Qual espécie (\"Species\") contém, em média, a maior área de pétalas?  \n",
    "d) Qual espécie (\"Species\") contém, em média, a maior área total (pétalas e sépalas)?  \n",
    "\n",
    "(Por curiosidade, as espécies de Iris contém 3 pétalas e 3 sépalas)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = sqlite3.connect('../Dados/iris_database.sqlite')\n",
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "15 - Conecte ao banco Python/Dados/chinook.sqlite e responda:\n",
    "\n",
    "a) Utilizando um comando SQL e as tabelas \"invoices\", \"invoice_items\", \"customers\" e \"tracks\", mostre quais as faixas compradas por clientes que têm o primeiro nome começando com a letra \"M\".  \n",
    "b) Quais clientes contêm a letra \"o\" tanto no nome como no sobrenome?  \n",
    "c) Crie um histograma de faixas (\"tracks\") mais compradas, usando o matplotlib.  \n",
    "d) Qual o cliente (\"customers\") que teve gasto médio em compras (\"invoices\") o valor mais próximo do valor médio do total de compras de todos os clientes?  \n",
    "e) Escreva um script em Python + SQL para construir um dicionário tendo os nomes dos artistas (\"artists\") como chaves e uma lista dos álbuns (\"albuns\") respectivos como valores."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "conn = sqlite3.connect('../Dados/chinook.sqlite')\n",
    "cur = conn.cursor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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