siena mercadolivre.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 458 entries, 0 to 457\n",
      "Data columns (total 4 columns):\n",
      "16790                                                                                   458 non-null int64\n",
      "2008                                                                                    458 non-null int64\n",
      "78000                                                                                   458 non-null int64\n",
      "https://carro.mercadolivre.com.br/MLB-1186158464-fiat-siena-10-fire-flex-4p-2008-_JM    458 non-null object\n",
      "dtypes: int64(3), object(1)\n",
      "memory usage: 14.4+ KB\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>16790</th>\n",
       "      <th>2008</th>\n",
       "      <th>78000</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>458.000000</td>\n",
       "      <td>458.000000</td>\n",
       "      <td>458.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>21794.379913</td>\n",
       "      <td>2010.032751</td>\n",
       "      <td>107128.133188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6194.725596</td>\n",
       "      <td>3.202334</td>\n",
       "      <td>43336.588033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>7900.000000</td>\n",
       "      <td>1998.000000</td>\n",
       "      <td>10000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>17890.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>78000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>20750.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>100000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>25847.000000</td>\n",
       "      <td>2012.000000</td>\n",
       "      <td>130405.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>44000.000000</td>\n",
       "      <td>2016.000000</td>\n",
       "      <td>333000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              16790         2008          78000\n",
       "count    458.000000   458.000000     458.000000\n",
       "mean   21794.379913  2010.032751  107128.133188\n",
       "std     6194.725596     3.202334   43336.588033\n",
       "min     7900.000000  1998.000000   10000.000000\n",
       "25%    17890.000000  2008.000000   78000.000000\n",
       "50%    20750.000000  2010.000000  100000.000000\n",
       "75%    25847.000000  2012.000000  130405.000000\n",
       "max    44000.000000  2016.000000  333000.000000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#dados coletados pelo script de webscraping\n",
    "data = pd.read_csv('carros.csv')\n",
    "data.info()\n",
    "data.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Preço R$')"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "preco = data.iloc[:,0]\n",
    "ano = data.iloc[:,1]\n",
    "kms = data.iloc[:,2]\n",
    "plt.scatter(kms,preco, color='red')\n",
    "plt.xlabel('KMs')\n",
    "plt.ylabel('Preço R$')\n",
    "#dados dispersos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'KMs')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(ano, kms, color='blue')\n",
    "plt.xlabel('Ano')\n",
    "plt.ylabel('KMs')\n",
    "#igualmente dispersos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Preço R$')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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QjWsa2da7bVi8YXoDWy/YWlQZMZnZZndvGnW9QkklFHId8ArwTuBJd/9KuNR0u7sviVbbElJSEalcMb5Ix5sUYtQhRlKpWVWDM3xdw9i7cm9RZcRUbFIZ7fLX54AucpedvhZi84G/HV/1RESGizFEynjH7kpKKCPFsxLjzv5yGDGpuPur7r7O3a9w9z0h1gM8VJLaicikEuOLtFrG7mpvbmda/bRBsWn101Ld2V8Oo/X+OtbMPm1m7wrPP2hm/wQUf2upiEiRYnyRTtRf+EO1LG5h2WHL3urKXGu1LDtsWUmH3x+LgknFzP4Xucb4TwEbzewbwL8B95Dr1isiElXL4hY6TumgYXoDhtEwvSF1I/2e/j2p4kNVykCOnd2drH9w/Vs3XfZ7P+sfXF+WCcPSGGmSrpOBI9z9DTObQW5IlA+4+9aS1ExEJqWWxS3j+jX+21d+myo+1NS6qYlzlkytK+39ISO1DVXy2cpIqfcNd38DwN1fBB5XQhGRajf0i3y0eFYmatvQSGcq7zGz/DvUF+Q/d/dTs6uWiEh5zJ8+P7GnV6nbZCqlHmmNlFSGDiP/d1lWRESkErQ3t3P2v57Nnr1vt8HU19Sn6ixgWMF7TEpZj3IomFTc/eelrIiICEDbxjY6NnfQ7/3UWi2tR7WWfIiUpPlUyiE3pVTh55WosuelFJFJpW1jG+u61g3q8bSuax1tG9tKVodzN5w77CzDcc7dUPyMizOnzkwVT7Ji0wre7H9zUOzN/jeLvomzXJRURKRixJgga7ySen6NFM/KRG2oLzqpmNn+ZrZ/lpURkcmtWibIeuH1F1LFk0zUmzhHTSpmttjM7gceAbaY2WYz+0D2VRORyaYSJsiKcfNjjIRQlcO0BJcDF7p7g7vPB/4SKN25qIhMGpUwQda5RyW3nRSKJ2lvbqeuZnA/qLqaulQJIcboAuUwUpfiAfu5++0DT9z9DjPbL8M6icgk9fOtyZ1OC8WT1FgNe3340PDFnmnEqMOd2+9M7EF25/Y7UyWF8Y4uUA7FHOUnzex/mFljeHwNeDLrionI5LPluS2p4kkKDadS7DArMepQCR0OyqWYpPI5YA7wY+BHwOwQExGpOJUwzEq1dDgYi2Iuf70CLPcwRaTl7r4pZjsRkZKrhOFNaq02MYGUssNBuRRzpvILIL8r8TuAO8zsvWZ2aKGNzOwgM7vdzLaY2SNmtjzE/8bMnjGzB8LjpLxtLjazHjN7zMw+nhdfGmI9ZnZRXnyBmd0T4teFqY5FZIJaNHtRqniS9uZ26mvqB8VKPbxJJXQ4KJdikspUd//PgSfu/jLQSG6elQ0jbNcH/KW7LwKOAc43s4FPxqXufnh43AQQXjsDeD+wFFhrZrVmVgt8FzgRWAScmVfOt0JZBwMvAucU86ZFJBsfveaj2Cp76/HRaz6aavuvfuSrqeKF5I+XlfR8JM0LmlPFk6w9ee2w9ZsXNJd8uJlyKCapvGpmhw08MbMjgKfd/dvADYU2cved7v6rsPyfwKPAgSPs5zTgWnff7e5PAT3A0eHR4+5PuvubwLXAaeEy3PHAD8P264HTi3g/IpKBj17zUTY9tWlQbNNTm1IlluU3L08VT/LZf/lsqvhQd++4O1U8SWd3J3ftuGtQ7K4dd1X8BFsxFJNULgB+ZGa/MLN/B64Hzgdw978qZidm1ggcQW7WSIAvmtlDZnZlmAAMcgnn6bzNdoRYofgs4CV37xsST9p/q5l1mVnXrl27iqmyiKQ0NKGMFk/y/OvPp4on6fPkwR8LxYeKMUzLSBNsVbtRk4q73wf8F6ANOA9Y5O6bi91BGNrlR8AF4dLZOuC9wOHATkowpL67d7h7k7s3zZkzJ+vdicgkl9RRYKR4NSlmmJZpwFfI9QB7GGg0s08UU7iZ1ZNLKJ3u/mMAd/+du/e7+17ge+QubwE8AxyUt/m8ECsUfx44wMzqhsRFZIKaNXVWqngWYgzTUgnDzZRLMUfpKuBN4Njw/BngG6NtFNo8rgAedfe/z4vPzVvtk8DDYflG4Awz28fMFgALgXuB+4CFoafXFHKN+TeGLs63A58O2y9jhDYeEclWjAbuy068LFU8yXh7kMUYpiXWfSptG9uoW12HrTLqVteVdAqAsSomqbw3NMrvAXD316Co6cuWAJ8Bjh/SffjbZtZtZg8BfwJ8KZT7CLn2mi3AT4HzwxlNH/BF4BZyjf3Xh3UhdwZ1oZn1kGtjuaKody0iFenL//blVPEkc98xN1U8Cw3TG1LFk1TC3DJjYeGexsIrmP0SaAbudPcjzey9wA/c/egRN6xQTU1N3tXVVe5qiFQdW1X4t6avHPl7ppLKqF1dW3DssP5LijvT6OzupHVD66DG+mn101INCFm3uq7gDZR9l5R+Jkoz2+zuTaOtV8yZykpyZw4HmVknsAko/meDiMgEkpRQRooniTHC8EQd6mXE4VZCu8ivgf9K7gZGI9dg/1wJ6iYiMmGNd4ThiTrUy4hnKqEx/CZ3f97dN7r7T5RQRCQrB+xzQKp4kvF2GNivPnlmj0LxrEzUoV6Kufz1KzP7UOY1EZEx6+zupHFNIzWramhc0zimO7fHO8SKFei/UyieZPq+01PFk9x21m3Denotmr2I2866rajtLz/l8mFnA7VWy+WnXF50HWJYe/Jazms676261Fot5zWdV/FDvRSTVD4M3G1mT4S74Ad6bolIBRhoFN7Wuw3H2da7jdYNrakSS4whVpzkRvBC8SQxbhrs7O5ka+/WQbGtvVuLPh4ti1tY/8n1g9pD1n9yfVkmy1p78lr6LunDVzp9l/RVfEKB4np/JfaBc/cJeWuoen9JtWlc05j4pdswvYGtF2wtqoxK6HUVq4wYx0OGK7b3V8GGejPbF/gCcDDQDVyRN86WiFSI7b3bU8WrnY5HeY10+Ws90EQuoZxICcboEpH0Ck0+VcpJqSqJjkd5jZRUFrn7X7j75eSGQvmjEtVJRFJob24fNi5VjdWUdFIqgKm1BeaGLxDPSntzO9Pqpw2KTauflup4xOj4MFmNlFTemtVGl71EKtdV91817Ma8vb6Xq+6/qugyYnSjfb3/9VTxrIz3xsMYHR8ms5GSymFm9nJ4/CfwwYFlM3u5VBUUkZHFmMfk9b4CCaFAPCu1FBjdt0A8C5N5LpQYCjbUu3tl37YpItHEGJokSj0oUI8C8SRDx90aONMAijpbUUP/+BQ/QYCIVK1Kmf8jRiP7eM801NA/PkoqImU23kbhGPOYVMqQIO3N7dTX1A+K1dfUp2pkH++ZRoyG/slMSUVkHMabEGI0Cp99xNmp4kmWzF+SKp6lPXv3jPh8NDOnzkwVHyrGCMOT2ah31Fcb3VEvscSYMyPG3d/7/8/9eXXPq8Pi+9XvxytffaVkZcS4G37fb+zL7v7dw+L71O7DG197o6gyZn97Ns+//vyw+Kyps3juyxoPd6xizqciIgli9BKK0SiclAxGimdVRgxJCWWkeJKkhDJSXOJSUhEZoxgJQY3C8VVKp4PJKrOkYmYHmdntZrbFzB4xs+UhPtPMbjWzx8PfGSFuZvYdM+sJoyEfmVfWsrD+42a2LC9+VBg1uSdsW/wY2yLjFCMhxGgUHno3/WjxajdRZ0ysFll+6vqAv3T3ReRmjTzfzBYBFwGb3H0huamJLwrrnwgsDI9WYB3kkhC5KY0/DBwNrBxIRGGdz+dttzTD9yMySIyE0LK4hWWHLRs0Z8ayw5alahQ+96hzU8WzUgkTbEGuPSpNXOLKLKm4+053/1VY/k/gUeBA4DRyg1US/p4elk8DrvGcu4EDzGwu8HHgVnd/wd1fBG4FlobX3unud4cZKq/JK0skczF6CXV2d7L+wfVv/Yru937WP7g+Ve+vq++/OlU8SYxhWl7a/VKqeJIYPdlOWnhSqrjENeIc9bGYWSNwBHAP8G533xle+g/g3WH5QODpvM12hNhI8R0JcZGSGe885CM19hdbbowxtyplmJZCnRzSHI+bHr8pVVziyvyiq5ntD/wIuMDdB40ZFs4wMu/TbGatZtZlZl27du3KenciRauUIUEqZZiWGMejUo7pZJVpUjGzenIJpdPdfxzCvwuXrgh/nw3xZ4CD8jafF2IjxeclxIdx9w53b3L3pjlz5ozvTYlEVCm9vyqlx1SM41Epx3SyyrL3lwFXAI+6+9/nvXQjMNCDaxlwQ178rNAL7BigN1wmuwU4wcxmhAb6E4Bbwmsvm9kxYV9n5ZUlMiHEGJYkhmoapkXDrJRXlmcqS4DPAMeb2QPhcRLwTeBjZvY48NHwHOAm4EmgB/ge0Abg7i8AXwfuC4/VIUZY5/thmyeAmzN8P1JlYkzEFKOM8Q5L8vv7/36qeKXzIVfEhz4fjYZZKS8N0yKTUowhVmKUUb+6nr6EOfDqrI49lxSXXGIMj1IpZcQaYqVtYxsdmzvo935qrZbWo1pZe/LaoreX4TRMi8gIYgyxEqOMpIQyUrzaxRhipW1jG+u61g3qpr2uax1tG9ui1FFGpqQik5J6GVWvjs0dqeISl5KKTErqZVS9NExLeSmpyKQUo4eQehlVpkrpHj1ZKanIpBSjh1CMMozkxu1C8SRTa6emiifZt3bfVPFKdlzjcaniEpeSikgZFeoum6YbbYxhWt7oT54Aq1A8KzGSbM8LPaniEldJxv4SqTRDuwMPTOMLjLlL8VjKkMFiJFl1oCgvnanIpFQpXYplsBjtIepAUV5KKjIpqUvxYDHmMYkhxnAx6kBRXkoqMilVSpfiGBNKxWiH+OX2X6aKZ2XJ/CXD6m0YS+YvKbqMGBOfydgpqcikdPDMg1PFsyqj943eVPEkldLYH8Pym5cnjv21/OblRZcRY+IzGTslFZmU7th6R6p4VmXEmC2xmsQYpkVtXeWlpCKTUoy7rnXndmWqprauiUhJRSalGL2MdOd2fLOmzkoVT6LeX+WlpCKTUoxeRpUysVUMi2YvShVPcl7TeaniSS478bLESbouO/GyostQ76/yUlKRSWnJ/CXU1Qy+97eupi5VL6MYKuVs56sf+Wpir6uvfuSrRZex9uS1nNd03qBeV+c1nZdqHpOWxS1cdfpVg4a+uer0q0o+fI6MnSbpkkmpcU0j23q3DYs3TG9g6wVbiyqjbnVdYvtJrdXSd0lx86EMzP0xVJov4xiTY8U4HlLdip2kS8O0yKQUozE3RkP9QOIo9yyFatyWWDK7/GVmV5rZs2b2cF7sb8zsmSFz1g+8drGZ9ZjZY2b28bz40hDrMbOL8uILzOyeEL/OzKZk9V6k+sRozI116WrtyWvpu6QPX+n0XdJXlmlv1bgtsWTZpnI1sDQhfqm7Hx4eNwGY2SLgDOD9YZu1ZlZrZrXAd4ETgUXAmWFdgG+Fsg4GXgTOyfC9SJVpb25nSu3g3yFTaqekasytpoZ6NW5LLJklFXf/BfBCkaufBlzr7rvd/SmgBzg6PHrc/Ul3fxO4FjjNzAw4Hvhh2H49cHrUNyCZ6uzupHFNIzWramhc05j6bue2jW3Ura7DVhl1q+vGNP/4m/1vjvh8NIUa9Uvd2B+j51bL4haOnXfsoNix845N3bg93n9XmfjK0fvri2b2ULg8NiPEDgSezltnR4gVis8CXnL3viFxmQAGhozf1rsNx98aMr7YL6CBxu38YTjWda1LlVjO3XBuqniSz/3r51LFs7LluS2p4knaNrax6alNg2KbntqU6piO999VqkOpk8o64L3A4cBO4O9KsVMzazWzLjPr2rVrVyl2KSMY7zAaHZs7UsWTvLrn1VTxJG/uTT6zKRSvZDGOqYZHEShxUnH337l7v7vvBb5H7vIWwDPAQXmrzguxQvHngQPMrG5IvNB+O9y9yd2b5syZE+fNyJiNt6eRhkeJL8YxVQ8ygRInFTObm/f0k8BAz7AbgTPMbB8zWwAsBO4F7gMWhp5eU8g15t/ouZtrbgc+HbZfBtxQivcg4zfenkYxel3VWPJHv1C8kk2pSe74WCieRJNjSSxZdin+AXAX8D4z22Fm5wDfNrNuM3sI+BPgSwDu/ghwPbAF+Clwfjij6QO+CNwCPApcH9YF+ApwoZn1kGtjuSKr9yJxjbenUYxeV+ceVaBNpUA8Sax3PmILAAANqElEQVSJrcbbuH3l6VemiifR5FgSS5a9v85097nuXu/u89z9Cnf/jLsvdvcPuvup7r4zb/12d3+vu7/P3W/Oi9/k7oeE19rz4k+6+9HufrC7/6m7787qvUhc4x1Go1KGWLntrNuGJZDmBc3cdtZtRZcRo3H7qvuvShVPEmuIFU2OJRPvXF8mvRWbVtC3d/AwKH17+1I1CMdomAY4ZNYhg75ED5l1SKrtYzRuD+21NVq8kPHehKnJsQSUVKQMxvvrvFKGWInRtbmaGrfV+0tASUXKYLxfPjOnzkwVTxKjYTrG2U41NW5XU4KUsVNSkZKrhC+fGA3TMc52YjRux+owMF7VlCBl7JRUpOTG++XzwuvJo/8UiieJMcTK0PlHRosniTE8SowOAzD+Xmjq/SWgpCJlcPDMg1PFh4rxi3j5zctTxZPsN2W/VPEkMYZHgVxi8ZX+1mMsCWW8vdA0OZaAJumSMhjv5FYDX4D57TLT6qel+gKLMbFVzaoanOHrGsbelXuLKiPGRF8xaJIuGU2xk3TpTEVKbrxtEZXyizjGGVOlDDlTCe1cUh0086OUXK3VFvx1XqyWxS3jSiI1VsNeH342kWaYlvbm9sQzpjRtCDGORQzzp89PPFNRI7ukpTOVCSTGHCKVoBImt0pKKCPFk8Q4Y6qEYwFqZJd4lFQmiBg32lWKGEOCjNe+tfumimdlyfwlw85Kaq225EPOVMolRZn41FA/QVRKgy7kGspXbFrB9t7tzJ8+n/bm9gn35ROjoT5GhwE1kMtEoYb6KlMpDbqa3e9tMYYlUQO5VBsllQkixrAiMWh8p7fFSAi6C12qjZLKBBGrQXe8jf2V8st6vHd/xxjaJEZCUAO5VBsllQkiRuN2jMb+oV+Ao8WzEOMSXIyhTWIkBDWQS7VRQ/0kEqOxv3Z1bcH7O/ovKU37TiU1bldDpwWRYhTbUK+bHyeRGI39Me7vGK9KuQQH478JU6Ta6PLXJBKjsb8SOgyocVukcmWWVMzsSjN71swezovNNLNbzezx8HdGiJuZfcfMeszsITM7Mm+bZWH9x81sWV78KDPrDtt8x8yKH298korR2F8Jd4C3N7dTX1M/KFZfU6/GbZEKkOWZytXA0iGxi4BN7r4Q2BSeA5wILAyPVmAd5JIQsBL4MHA0sHIgEYV1Pp+33dB9yRAxGvsr4W54gKG/Icbym2K8PchilSFSTTJtqDezRuAn7v6B8Pwx4Dh332lmc4E73P19ZnZ5WP5B/noDD3c/N8QvB+4Ij9vd/dAQPzN/vZFM5ob6ahGjoT7G3fAxyhCZKCr1jvp3u/vOsPwfwLvD8oHA03nr7QixkeI7EuKJzKzVzLrMrGvXrl3jewcTXDX8so7RUB/jJk7dCCoyXNka6j13ilSS/szu3uHuTe7eNGfOnFLssiJVyxArMRrqYySmSuqFJlIpSp1UfhcuexH+PhvizwAH5a03L8RGis9LiMsIquWXdYybDmMkJvVCExmu1EnlRmCgB9cy4Ia8+FmhF9gxQG+4THYLcIKZzQgN9CcAt4TXXjazY0Kvr7PyyoquGi4ZQfX8so5xF3qMxKQhVkSGy+zmRzP7AbmG9tlmtoNcL65vAteb2TnANuDPwuo3AScBPcBrwNkA7v6CmX0duC+st9rdXwjLbeR6mE0Fbg6P6IY2xg5cMgImXGNsNc3uN96bDge2Hc/d8DHKEKk2GqZlFJU0JMh4qbeSiIxVpfb+mnCq5ZIRaPBCEcmexv4aRTVdMgKNVSUi2dKZyijUGCsiUjwllVFU0iWjaumFJiLVSw31E4Qa2UWknNRQX2Wq5cZFEaluSioTRDX1QhOR6qWkMkFoSBARmQiUVCYI9UITkYlASWWCqKReaCIihaj3l4iIjEq9v0REpOSUVEREJBolFRERiUZJRUREolFSERGRaCZd7y8z20Vu1skks4HnSlidsVI945oo9YSJU1fVM65KqGeDu88ZbaVJl1RGYmZdxXSZKzfVM66JUk+YOHVVPeOaKPUEXf4SEZGIlFRERCQaJZXBOspdgSKpnnFNlHrCxKmr6hnXRKmn2lRERCQenamIiEg0VZNUzOxKM3vWzB7Oix1mZneZWbeZbTCzd4b4FDO7KsQfNLPjQvwdZvZA3uM5M1uTsK9GM3s9b71/SFHPg8zsdjPbYmaPmNnyEJ9pZrea2ePh74wQNzP7jpn1mNlDZnZkXlnLwvqPm9myAvtLLLdU9TSzw8O/wSMh/ucF9vdZM9uVd0z/e5mOaX9eHW4ssL99zOy6sP09ZtZY4mP6J0M+p2+Y2emxjukY6nlo+DfebWZ/NaSspWb2WHgPF5X5eCbWs1A5Cfs7zsx6847nJcXUM2Zdw2tbLffd9YCZJY6OO9JnPHPuXhUP4CPAkcDDebH7gD8Oy58Dvh6WzweuCsvvAjYDNQllbgY+khBvzN9PynrOBY4My+8AfgMsAr4NXBTiFwHfCssnATcDBhwD3BPiM4Enw98ZYXlGwv4Syy1hPQ8BFobl3wd2Agck7O+zwP8p5zENr71SxP7agH8Iy2cA15W6nnllzgReAKbFOqZjqOe7gA8B7cBf5ZVTCzwBvAeYAjwILCrj8SxUz8RyEvZ3HPCTEn1GE+saXtsKzB5lf6N+drJ6lGQnJXszQ77sgV7ebjc6CNgSlr8LfCZvvU3A0UPKOgR4emD7kfYzzjrfAHwMeAyYm/cBfCwsXw6cmbf+Y+H1M4HL8+KD1hu6/tByS1XPhHIeJCSZIfHPMsakErOuFJdUbgGODct15G5KG/Y5KcUxBVqBzgLlRzmmo9Uzb72/YfCX9bHALXnPLwYuLtfxLFTPQuUkxI9jjEklZl0pLqkU9f8xi0fVXP4q4BHgtLD8p+QSC+S+2E41szozWwAclffagIFfTIV6Miwws/vN7Odm9kdjqVw4zT8CuAd4t7vvDC/9B/DusHwgueQ2YEeIFYoPVajcUtUzv5yjyf1ifaLArj4VTtV/aGZD/z1KVdd9zazLzO5OuqQ0dHt37yP342VWies54AzgByPsalzHtMh6FlLsZ7RUxzNtOUmOtdwl85vN7P1p6hixrg78m5ltNrPWAusUe+yjq/ak8jmgzcw2kzvlfDPEryR3kLuANcAvgf4h2470n3UnMN/djwAuBP7JQntNscxsf+BHwAXu/nL+ayGRRe+WN5ZyY9XTzOYC/wic7e57E1bZADS6+weBW4H1aeoZsa4Nnrtz+b8Ba8zsvWnrUaJ6DhzTxeR+6ScZ1zEtx2d0LCIez4LlBL8i9/k4DPjfwL+Wqa5/6O5HAicC55vZR9LWI0tVnVTc/dfufoK7H0UuQTwR4n3u/iV3P9zdTwMOIHeNE8g18AN17r65QLm73f35sLw5lHtIsfUys3pyH6xOd/9xCP8ufEkMfFk8G+LPMPgsal6IFYoPVajcUtWTkHA3Aivc/e6kfbn78+6+Ozz9Prmzx6LFqqu7D/x9EriD3C/Kod7a3szqgOnA86WsZ/BnwL+4+56kfY3nmKasZyHFfkZLdTzTljOIu7/s7q+E5ZuAejObXUw9Y9Y17zP6LPAvwNEJqxV77KOr6qRiZu8Kf2uArwH/EJ5PM7P9wvLHgD5335K36ZmMcEnBzOaYWW1Yfg+wkFxDeTF1MuAK4FF3//u8l24EBnpwLSN3zXUgflbozXEM0BtOl28BTjCzGaHHyAkk/2ItVG5J6mlmU8h98K9x9x+OsL+5eU9PBR4tpp6R6zrDzPYJZc4GlgD5n4ukcj8N/GyEy6TR65m33Wif0zEd0zHUs5D7gIVmtiB8Ds4IZQxVquOZtpyh6/1eWHfgUm4NxSe/WHXdz8zeMbBM7v/9wwmrjvbZyU4pGm5K8SD3n2snsIfcpa1zgOXkzkB+A3yTtxvtG8k1XD0K3EbulDa/rCeBQ4fETgVWh+VPkWuveYDcKfEpKer5h+ROcR8K2z9ArqfGLHIdBh4PdZoZ1jdyHQueALqBpryyPgf0hMfZefHvD6xXqNxS1RP4i/Bv8kDe4/Dw2mrg1LD8t+GYPgjcPvT4l6iufxCePxj+npO3j/y67gv8czju9wLvKcO/fSO5X541Q/Yx7mM6hnr+Hrn/cy8DL4Xld4bXTiL3/+8Jcmeq5TyeifUsVE7Y5gvAF8LyF/OO593AH2T4GS1U1/eE/T8Y6pJ/TPPrWvCzk/VDd9SLiEg0VX35S0RESktJRUREolFSERGRaJRUREQkGiUVERGJRklFpITM7HQzczM7tNx1EcmCkopIaZ0J/L/wV6TqKKmIlEgY9+kPyd2Ye0aIHWdmd4QBH39tZp15d203W27Q0m7LzRe0TxmrL1IUJRWR0jkN+Km7/wZ43swGxuI6AriA3Pwa7wGWmNm+wNXAn7v7YnJDwp9X+iqLpKOkIlI6ZwLXhuVrefsS2L3uvsNzozc/QG4IlvcBT4UEBLkRhitqNFqRJHXlroDIZGBmM4HjgcVm5uRmRXRyozfvzlu1H/2/lAlMZyoipfFp4B/dvcHdG939IOApoNAEb48BjWZ2cHj+GeDnJainyLgoqYiUxpnkpgDI9yMK9AJz9zeAs4F/NrNuYC9h6gaRSqZRikVEJBqdqYiISDRKKiIiEo2SioiIRKOkIiIi0SipiIhINEoqIiISjZKKiIhEo6QiIiLR/H/SOjYV160uxAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(ano,preco , color='green')\n",
    "plt.xlabel('Ano')\n",
    "plt.ylabel('Preço R$')\n",
    "#opa, acho que temos algum padrão aqui!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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