NumPy.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "do3kUOLbltjE"
      },
      "source": [
        "# <font color=green> PYTHON PARA DATA SCIENCE - NUMPY\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "umSz9TLxltjG"
      },
      "source": [
        "# <font color=green> 1. INTRODUÇÃO AO PYTHON\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "gSnX12-sltjH"
      },
      "source": [
        "# 1.1 Introdução"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "SRG_k55kltjI"
      },
      "source": [
        "> Python é uma linguagem de programação de alto nível com suporte a múltiplos paradigmas de programação. É um projeto *open source* e desde seu surgimento, em 1991, vem se tornando uma das linguagens de programação interpretadas mais populares. \n",
        ">\n",
        "> Nos últimos anos Python desenvolveu uma comunidade ativa de processamento científico e análise de dados e vem se destacando como uma das linguagens mais relevantes quando o assunto é ciência de dados e machine learning, tanto no ambiente acadêmico como também no mercado."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "2oZuKvWkltjJ"
      },
      "source": [
        "# 1.2 Instalação e ambiente de desenvolvimento"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "v4P8bMEIltjK"
      },
      "source": [
        "### Instalação Local\n",
        "\n",
        "### https://www.python.org/downloads/\n",
        "### ou\n",
        "### https://www.anaconda.com/distribution/"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "FZtu5tjrltjL"
      },
      "source": [
        "### Google Colaboratory\n",
        "\n",
        "### https://colab.research.google.com"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "C6vbfq8DltjM"
      },
      "source": [
        "### Verificando versão"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "jeuAt-4NltjM",
        "outputId": "10db37fd-b395-4601-8b7e-a71de7f9c040"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Python 3.6.8\n"
          ]
        }
      ],
      "source": [
        "!python -V"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "v86aEyR2ltjR"
      },
      "source": [
        "# 1.3 Trabalhando com arrays Numpy"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "OFaxgUptltjW",
        "scrolled": true
      },
      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "FXjYowRDltjZ"
      },
      "outputs": [],
      "source": [
        "km = np.loadtxt('carros-km.txt')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 901
        },
        "colab_type": "code",
        "id": "f_d2Ya-vltjb",
        "outputId": "654adef7-b5b8-403a-916a-2fe0f797f5b3"
      },
      "outputs": [
        {
          "data": {
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              "       0.00000e+00, 5.79500e+03, 0.00000e+00, 5.88480e+04, 9.43810e+04,\n",
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              "       1.18236e+05, 1.13808e+05, 6.10000e+02, 0.00000e+00, 0.00000e+00,\n",
              "       1.28870e+04, 7.96070e+04, 9.09240e+04, 4.27330e+04, 0.00000e+00,\n",
              "       0.00000e+00, 1.17714e+05, 1.13885e+05, 0.00000e+00, 3.05110e+04,\n",
              "       7.48670e+04, 1.19760e+05, 8.35600e+03, 6.42470e+04, 8.86610e+04,\n",
              "       4.53900e+03, 1.10116e+05, 3.32150e+04, 9.20010e+04, 0.00000e+00,\n",
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              "       5.25960e+04, 4.75030e+04, 8.90560e+04, 2.88340e+04, 1.10564e+05,\n",
              "       5.66380e+04, 1.73570e+04, 7.40150e+04, 1.51960e+04, 0.00000e+00,\n",
              "       1.08210e+04, 0.00000e+00, 0.00000e+00, 9.59500e+03, 9.90520e+04,\n",
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              "       7.95770e+04, 1.08201e+05, 7.64530e+04, 5.76830e+04, 9.66100e+04,\n",
              "       1.09001e+05, 2.62120e+04, 4.59710e+04, 4.91820e+04, 4.99070e+04,\n",
              "       3.86200e+04, 6.09960e+04, 7.39140e+04, 1.07392e+05, 9.14600e+03,\n",
              "       0.00000e+00, 1.79240e+04, 0.00000e+00, 1.16949e+05, 2.04760e+04,\n",
              "       5.28040e+04, 8.84900e+03, 9.17240e+04, 3.20560e+04, 7.48860e+04,\n",
              "       0.00000e+00, 0.00000e+00, 5.21890e+04, 8.35590e+04, 0.00000e+00,\n",
              "       2.03280e+04, 0.00000e+00, 7.55770e+04, 3.36590e+04, 1.04341e+05,\n",
              "       2.55100e+04, 1.89650e+04, 8.71610e+04, 6.65200e+03, 5.57380e+04,\n",
              "       0.00000e+00, 0.00000e+00, 0.00000e+00, 6.43200e+04, 0.00000e+00,\n",
              "       6.86780e+04, 7.16970e+04, 0.00000e+00, 3.47830e+04, 3.37720e+04,\n",
              "       8.51270e+04, 1.36060e+04, 3.56470e+04, 9.51280e+04, 1.40460e+04,\n",
              "       4.11940e+04, 0.00000e+00, 9.61000e+04, 1.03900e+05, 4.38140e+04,\n",
              "       2.46380e+04, 0.00000e+00, 1.10966e+05, 1.59870e+04, 5.33690e+04,\n",
              "       1.00770e+04, 7.15440e+04, 1.07000e+02, 8.39400e+03, 4.14980e+04,\n",
              "       1.16002e+05, 1.00858e+05, 6.74750e+04, 8.49700e+03, 4.42000e+03,\n",
              "       0.00000e+00, 5.85370e+04, 0.00000e+00, 0.00000e+00, 1.12016e+05,\n",
              "       9.18400e+04, 1.12787e+05, 0.00000e+00, 0.00000e+00, 9.29300e+03,\n",
              "       0.00000e+00, 5.50830e+04, 4.87960e+04, 0.00000e+00, 8.96850e+04,\n",
              "       8.53840e+04, 9.81080e+04, 7.12800e+04, 2.75050e+04, 2.99810e+04,\n",
              "       5.26370e+04, 7.68500e+03, 5.01880e+04])"
            ]
          },
          "execution_count": 7,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "hxLZatdeltje"
      },
      "outputs": [],
      "source": [
        "anos = np.loadtxt('carros-anos.txt', dtype = int)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "colab_type": "code",
        "id": "GLsHBNakltjg",
        "outputId": "1949314f-2aa7-41a1-ae39-88acf7a352a5"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([2003, 1991, 1990, 2019, 2006, 2012, 2019, 2009, 2010, 2011, 2002,\n",
              "       2007, 2001, 2019, 2009, 2016, 2012, 2019, 2016, 2017, 2002, 2019,\n",
              "       1994, 1991, 2019, 2019, 2016, 2019, 2002, 1991, 1997, 1995, 2018,\n",
              "       1991, 2014, 1995, 2019, 2019, 2009, 2019, 2013, 2003, 2019, 2002,\n",
              "       2019, 2002, 2004, 2001, 2019, 2003, 2009, 2006, 2000, 2006, 2010,\n",
              "       1994, 2007, 2019, 2019, 2019, 2019, 2019, 2017, 2011, 2001, 1996,\n",
              "       2019, 1994, 2019, 2007, 1994, 2007, 1997, 2006, 2013, 1994, 2008,\n",
              "       2008, 2019, 2019, 1999, 2007, 1993, 1995, 2019, 2019, 2016, 2011,\n",
              "       2019, 2002, 2013, 2017, 2016, 2008, 2018, 2003, 2003, 2004, 2010,\n",
              "       2019, 2006, 2001, 2019, 2015, 2018, 2017, 1992, 2001, 1993, 1995,\n",
              "       2003, 2014, 2008, 2013, 2019, 2017, 2019, 2019, 2006, 2015, 2007,\n",
              "       2005, 2017, 1998, 2019, 1999, 2019, 2009, 2003, 1994, 2019, 1994,\n",
              "       2019, 2015, 1996, 1997, 1993, 2019, 1992, 1995, 2019, 1990, 2019,\n",
              "       2019, 1991, 1990, 2012, 2007, 2013, 2000, 2002, 1996, 1996, 2015,\n",
              "       1993, 2013, 2013, 2009, 2019, 2019, 2002, 1997, 1998, 2004, 1996,\n",
              "       2015, 2016, 2005, 1999, 1995, 1993, 2004, 2013, 1998, 2018, 2019,\n",
              "       2018, 2019, 1990, 2009, 1990, 2006, 2002, 1991, 1992, 2019, 2019,\n",
              "       2005, 2010, 2019, 2016, 2019, 2010, 1994, 2001, 2014, 1996, 1993,\n",
              "       1993, 2001, 2019, 2019, 2019, 2007, 2019, 2016, 2014, 2019, 2015,\n",
              "       2015, 1996, 2002, 2005, 1995, 1999, 2005, 2019, 1997, 1990, 2001,\n",
              "       2013, 2019, 2017, 2011, 2005, 2007, 1993, 1991, 1991, 1997, 2000,\n",
              "       2007, 2006, 2015, 2008, 2019, 1996, 2019, 2019, 2014, 2004, 2008,\n",
              "       2019, 2019, 2012, 2019, 1996, 2011, 2019, 2010, 2007, 1994, 2007,\n",
              "       2014, 1991, 2002, 1996, 1992])"
            ]
          },
          "execution_count": 9,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "anos"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "wMdUsAq4ltjs"
      },
      "source": [
        "### Obtendo a quilometragem média por ano"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "colab_type": "code",
        "id": "cD2M3s3Fltjt",
        "outputId": "9a754639-9669-4a28-a73c-853c05a5a99b"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: RuntimeWarning: invalid value encountered in true_divide\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ],
      "source": [
        "km_media = km / (2019 - anos)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "colab_type": "code",
        "id": "65IyPzKKltjv",
        "outputId": "5ef0bef8-189e-45b9-acc1-59a0178ed3a8"
      },
      "outputs": [
        {
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              "                  nan, 4.36818182e+03, 3.58275862e+03, 2.43411111e+03,\n",
              "       4.10633333e+03,            nan, 5.54830000e+04, 1.99837500e+03,\n",
              "       3.81207143e+03, 8.39750000e+02, 2.75169231e+03, 3.82142857e+00,\n",
              "       2.99785714e+02, 1.88627273e+03, 6.10536842e+03, 8.40483333e+03,\n",
              "       5.19038462e+03, 2.12425000e+03, 4.01818182e+02,            nan,\n",
              "       2.54508696e+03,            nan,            nan, 2.24032000e+04,\n",
              "       6.12266667e+03, 1.02533636e+04,            nan,            nan,\n",
              "       1.32757143e+03,            nan, 2.39491304e+03, 6.09950000e+03,\n",
              "                  nan, 9.96500000e+03, 7.11533333e+03, 3.92432000e+03,\n",
              "       5.94000000e+03, 5.50100000e+03, 1.07075000e+03, 3.09629412e+03,\n",
              "       3.34130435e+02, 1.85881481e+03])"
            ]
          },
          "execution_count": 11,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km_media"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "Z0JCmAWvltjy",
        "outputId": "cfda0665-ac65-4073-84b0-eb204f2fffd6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "execution_count": 12,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(km_media)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "KdG5NmmGltj0"
      },
      "source": [
        "# <font color=green> 2. CARACTERÍSTICAS BÁSICAS DA LINGUAGEM\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "X1K5kisFltj1"
      },
      "source": [
        "# 2.1 Operações matemáticas\n",
        "\n",
        "### Operadores aritméticos: $+$, $-$, $*$, $/$, $**$, $\\%$, $//$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "8YCDVpbYltj1"
      },
      "source": [
        "### Adição ($+$)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "h6DsMqhaltj2",
        "outputId": "b0317bf0-24f0-4d9b-d829-271ba5cfce3b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "4"
            ]
          },
          "execution_count": 13,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "2 + 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "WeJG-WJBltj8"
      },
      "source": [
        "### Subtração ($-$)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "zoB7_OcRltj9",
        "outputId": "4213c523-33da-43dd-afa6-3cc29801fab1"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "execution_count": 14,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "2 - 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "zuv8N7fjltkC"
      },
      "source": [
        "### Multiplicação ($*$)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "TAWG7xSTltkD",
        "outputId": "40174276-b103-4cd6-f917-c28b77885c7e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "6"
            ]
          },
          "execution_count": 15,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "2 * 3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "dMp7BsnwltkF"
      },
      "source": [
        "### Divisão ($/$) e ($//$)\n",
        "A operação divisão sempre retorna um número de ponto flutuante"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "DD5kx3H3ltkF",
        "outputId": "724d22b1-1510-490e-e705-cc046d7fb2c8"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "3.3333333333333335"
            ]
          },
          "execution_count": 16,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "10 / 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "ji0CYH3UltkI",
        "outputId": "b436553f-ad70-4fcd-e4da-7578a373c2be"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "execution_count": 17,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "10 // 3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "3DSO7TcvltkL"
      },
      "source": [
        "### Exponenciação ($**$)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "tBKvl2TWltkM",
        "outputId": "2e51e963-5afe-412e-9895-5a2bc5e689e9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "execution_count": 18,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "2 ** 3"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "MhD56p-9ltkQ"
      },
      "source": [
        "### Resto da divisão ($\\%$)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "bfa7phO6ltkR",
        "outputId": "ddbc98b0-7a39-4ad6-b503-03f26c55b5dd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1"
            ]
          },
          "execution_count": 19,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "10 % 3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "khIEx6olltkT",
        "outputId": "dceb7020-95e5-4816-9ee9-079509471cda"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "0"
            ]
          },
          "execution_count": 20,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "10 % 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "8pVVp5fsltkV"
      },
      "source": [
        "### Expressões matemáticas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "jlQTk4gNltkW",
        "outputId": "abd58817-1e82-4b18-9fb0-be5a499d688b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "execution_count": 21,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "5 * 2 + 3 * 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "kkCb6Crgltka",
        "outputId": "61eeae14-ff2e-4dac-b3a1-4240b255c9ca"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "execution_count": 22,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "(5 * 2) + (3 * 2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "UD12tlgAltkd",
        "outputId": "c71e4ffe-b760-4655-b4a1-957c5f05cceb"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "50"
            ]
          },
          "execution_count": 23,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "5 * (2 + 3) * 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "a5tKQ5Beltkf"
      },
      "source": [
        "### A variável _\n",
        "\n",
        "No modo interativo, o último resultado impresso é atribuído à variável _"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "VkHEx516ltkg",
        "outputId": "043d4bd8-6f3b-44de-a2fc-6ce09b42518a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "10"
            ]
          },
          "execution_count": 24,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "5 * 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "dFShsobXltki",
        "outputId": "8ca0f3da-55c5-4e06-b4aa-493b3ba6238d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "16"
            ]
          },
          "execution_count": 25,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "_ + 3 * 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "hJIpR3KUltkk",
        "outputId": "581a22a8-2997-43be-d896-2a5e5e4da109"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "8.0"
            ]
          },
          "execution_count": 26,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "_ / 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "MUrQAf6Mltkm"
      },
      "source": [
        "# 2.2 Variáveis "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "qaVLKIeultkn"
      },
      "source": [
        "### Nomes de variáveis\n",
        "\n",
        "- Nomes de variáveis pode começar com letras (a - z, A - Z) ou o caractere *underscore* (_):\n",
        "\n",
        "    > Altura\n",
        "    >\n",
        "    > _peso\n",
        "    \n",
        "- O restante do nome pode conter letras, números e o caractere \"_\":\n",
        "\n",
        "    > nome_da_variavel\n",
        "    >\n",
        "    > _valor\n",
        "    >\n",
        "    > dia_28_11_\n",
        "    \n",
        "\n",
        "- O nomes são *case sensitive*:\n",
        "\n",
        "    > Nome_Da_Variável $\\ne$ nome_da_variavel $\\ne$ NOME_DA_VARIAVEL\n",
        "    \n",
        "### <font color=red>Observações:\n",
        "- Existem algumas palavras reservadas da linguagem que não podem ser utilizadas como nomes de variável:\n",
        "\n",
        "| |Lista de palavras <br>reservadas em Python| |\n",
        "|:-------------:|:------------:|:-------------:|\n",
        "| and           | as           | not           | \n",
        "| assert        | finally      | or            | \n",
        "| break         | for          | pass          | \n",
        "| class         | from         | nonlocal      | \n",
        "| continue      | global       | raise         | \n",
        "| def           | if           | return        | \n",
        "| del           | import       | try           | \n",
        "| elif          | in           | while         | \n",
        "| else          | is           | with          | \n",
        "| except        | lambda       | yield         | \n",
        "| False         | True         | None          | "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "3frWjfAtltkn"
      },
      "source": [
        "### Declaração de variáveis\n",
        "\n",
        "### Operadores de atribuição: $=$, $+=$, $-=$, $*=$, $/=$, $**=$, $\\%=$, $//=$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "7VIcrXNHltko"
      },
      "outputs": [],
      "source": [
        "ano_atual = 2019\n",
        "ano_fabricacao = 2003\n",
        "km_total = 44410.0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "atVoqp6bltkq",
        "outputId": "ed2b4e61-5d17-48d9-fd11-e2d2aa2c913e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2019"
            ]
          },
          "execution_count": 28,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_atual"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "_t82qXrOltkt",
        "outputId": "0e21ae36-9808-4266-9630-c231c0ad0f85"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2003"
            ]
          },
          "execution_count": 29,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_fabricacao"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "1anwuDHiltkv",
        "outputId": "e199bf88-a3c6-4ac3-b11f-14f9e10ad4ff"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "44410.0"
            ]
          },
          "execution_count": 30,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km_total"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "gCBkfq_8ltky"
      },
      "source": [
        "# $$km_{média} = \\frac {km_{total}}{(Ano_{atual} - Ano_{fabricação})}$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "zswWS4hNltky"
      },
      "source": [
        "### Operações com variáveis"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "HxxU0rnfltkz",
        "outputId": "f3a56ba9-50ae-4d03-fa16-b3e51531e263"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2775.625"
            ]
          },
          "execution_count": 31,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km_media = km_total / (ano_atual - ano_fabricacao)\n",
        "km_media"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "_2Qhb32jltk1",
        "outputId": "64d6c010-9f12-4233-bb56-da89ad4fe558"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2775.625"
            ]
          },
          "execution_count": 32,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_atual = 2019\n",
        "ano_fabricacao = 2003\n",
        "km_total = 44410.0\n",
        "km_media = km_total / (ano_atual - ano_fabricacao)\n",
        "km_media"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "nCJzA7dyltk3",
        "outputId": "855a0c22-c99a-41cc-b3ac-9370601fe2d6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "47185.625"
            ]
          },
          "execution_count": 33,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_atual = 2019\n",
        "ano_fabricacao = 2003\n",
        "km_total = 44410.0\n",
        "km_media = km_total / (ano_atual - ano_fabricacao)\n",
        "\n",
        "km_total = km_total + km_media\n",
        "km_total"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "ifRwQ0vEltk9",
        "outputId": "649bb85f-75b4-4edd-e686-db4ee5fa34b9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "47185.625"
            ]
          },
          "execution_count": 34,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_atual = 2019\n",
        "ano_fabricacao = 2003\n",
        "km_total = 44410.0\n",
        "km_media = km_total / (ano_atual - ano_fabricacao)\n",
        "\n",
        "km_total += km_media\n",
        "km_total"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "fDBrHWSBltlB"
      },
      "source": [
        "### Conclusão:\n",
        "```\n",
        "\"valor = valor + 1\" é equivalente a \"valor += 1\"\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "uVAyJbmAltlC"
      },
      "source": [
        "### Declaração múltipla"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "oMWEzjPOltlC"
      },
      "outputs": [],
      "source": [
        "ano_atual, ano_fabricacao, km_total = 2019, 2003, 44410.0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 36,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "9ZKlHkLultlE",
        "outputId": "9677e531-b75b-418c-ac4c-a5d99a45b73c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2019"
            ]
          },
          "execution_count": 36,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_atual"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 37,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "-mcMuW9nltlG",
        "outputId": "3e4a92bf-b3e3-46a9-8a21-846a5c02a66c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2003"
            ]
          },
          "execution_count": 37,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_fabricacao"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 38,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "WFFavLIvltlL",
        "outputId": "ba455478-18c9-4ee7-cf36-a2337fd9f458"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "44410.0"
            ]
          },
          "execution_count": 38,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km_total"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 39,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "iFawOJe6ltlO",
        "outputId": "1bee6477-1f2c-466b-989e-59093a749b00"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2775.625"
            ]
          },
          "execution_count": 39,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "ano_atual, ano_fabricacao, km_total = 2019, 2003, 44410.0\n",
        "km_media = km_total / (ano_atual - ano_fabricacao)\n",
        "km_media"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "uoRXMeRDltlQ"
      },
      "source": [
        "# 2.3 Tipos de dados"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "sW_G6EjWltlQ"
      },
      "source": [
        "Os tipos de dados especificam como números e caracteres serão armazenados e manipulados dentro de um programa. Os tipos de dados básicos do Python são:\n",
        "\n",
        "1. **Números**\n",
        "    1. ***int*** - Inteiros\n",
        "    - ***float*** - Ponto flutuante\n",
        "- **Booleanos** - Assume os valores True ou False. Essencial quando começarmos a trabalhar com declarações condicionais\n",
        "- ***Strings*** - Sequência de um ou mais caracteres que pode incluir letras, números e outros tipos de caracteres. Representa um texto.\n",
        "- **None** - Representa a ausência de valor"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "-HRRxQOtltlQ"
      },
      "source": [
        "### Números"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "5PKIcIuUltlR"
      },
      "outputs": [],
      "source": [
        "ano_atual = 2019"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 41,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "G32Yd1g0ltlT",
        "outputId": "63c67a82-9ecd-48ad-9a2f-86dfad59d92f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "int"
            ]
          },
          "execution_count": 41,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(ano_atual)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "b9_v__dEltlV"
      },
      "outputs": [],
      "source": [
        "km_total = 44410.0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 43,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "A0nySb3LltlZ",
        "outputId": "e9e0e9a1-e4d4-4aff-9a86-5e04198ad435"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "float"
            ]
          },
          "execution_count": 43,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(km_total)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "7X9iheAnltld"
      },
      "source": [
        "### Booleanos"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "liUYdchPltle"
      },
      "outputs": [],
      "source": [
        "zero_km = True"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 45,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "oZIQAghaltlh",
        "outputId": "e1207fde-4be1-4e38-8893-60f4831825e8"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "bool"
            ]
          },
          "execution_count": 45,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(zero_km)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "XCAYApe3ltlj"
      },
      "outputs": [],
      "source": [
        "zero_km = False"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 47,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "mJ0nGEV7ltll",
        "outputId": "559fdea4-ccce-4dab-f76f-e40c14f66688"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "bool"
            ]
          },
          "execution_count": 47,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(zero_km)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Ipjq4eiSltlp"
      },
      "source": [
        "### Strings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 48,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "OeW_GQzOltlr",
        "outputId": "debd835d-abf2-49dc-b507-b0aec7eb788a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Jetta Variant'"
            ]
          },
          "execution_count": 48,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nome = 'Jetta Variant'\n",
        "nome"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 49,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "xF1Bi-Rkltlu",
        "outputId": "98e21c44-bb61-42df-909e-772447004ca6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Jetta Variant'"
            ]
          },
          "execution_count": 49,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nome = \"Jetta Variant\"\n",
        "nome"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 50,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "QlobSFUtltlw",
        "outputId": "02061ee6-c50e-45c5-c912-62c5dad75920"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Jetta \"Variant\"'"
            ]
          },
          "execution_count": 50,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nome = 'Jetta \"Variant\"'\n",
        "nome"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 51,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "8LBWzzfbltly",
        "outputId": "82a8efdd-825e-4511-fd9f-8d29361da3b0"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "\"Jetta 'Variant'\""
            ]
          },
          "execution_count": 51,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "nome = \"Jetta 'Variant'\"\n",
        "nome"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "ycEhoxtUltl0"
      },
      "outputs": [],
      "source": [
        "carro = '''\n",
        "  Nome\n",
        "  Idade\n",
        "  Nota\n",
        "'''"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 53,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "bjZQzpuUltl2",
        "outputId": "7bbe2675-cacf-4b59-d4e2-0d861c1ad958"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "execution_count": 53,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(carro)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "w6bJU-R9ltl5"
      },
      "source": [
        "### None"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "RgeVhXGxltl5"
      },
      "outputs": [],
      "source": [
        "quilometragem = None\n",
        "quilometragem"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 55,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "MJI6PKS6ltl8",
        "outputId": "b7e0d847-ef10-43ba-e36c-c2e481b95898"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "NoneType"
            ]
          },
          "execution_count": 55,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(quilometragem)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "_ilupwV-ltl-"
      },
      "source": [
        "# 2.4 Conversão de tipos"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "D5hq5Qbvltl-"
      },
      "outputs": [],
      "source": [
        "a = 10\n",
        "b = 20\n",
        "c = 'Python é '\n",
        "d = 'legal'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 57,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "aJ0vi8_Nltl_",
        "outputId": "d473a9b7-31e3-448d-f520-3e4d583e8625"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "int"
            ]
          },
          "execution_count": 57,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(a)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 58,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "29FVH7p7ltmB",
        "outputId": "aa213039-0b1f-40e5-dbbe-94e7b7fe872d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "int"
            ]
          },
          "execution_count": 58,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(b)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 59,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "NGseTO2SltmC",
        "outputId": "50672ce2-61db-4427-81b6-e1f3c36868da"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "execution_count": 59,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(c)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 60,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "yaSBhwNWltmE",
        "outputId": "a5e2a755-4e72-4a8a-c2e4-bb68080ba459"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "execution_count": 60,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(d)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 61,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "5zMXVwLHltmF",
        "outputId": "25b74b99-108c-4d1a-e0d4-b130f9924479"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "30"
            ]
          },
          "execution_count": 61,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "a + b"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 62,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "JJrqKRZFltmJ",
        "outputId": "390b513d-3bb4-41f3-d8a4-2e9263fd2970"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Python é legal'"
            ]
          },
          "execution_count": 62,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "c + d"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "QDZzu0A813ax"
      },
      "outputs": [],
      "source": [
        "# c + a"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "dByigpENltmO"
      },
      "source": [
        "### Conversões de tipo\n",
        "\n",
        "Funções int(), float(), str()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 64,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "MtecvWlsltmP",
        "outputId": "7fa1e3fd-6377-4031-cfb0-420ca3f46df6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'10'"
            ]
          },
          "execution_count": 64,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "str(a)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 65,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "S1NuIhDVltmS",
        "outputId": "f471dbc0-3c19-4ece-cf1b-b5c942458817"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "execution_count": 65,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(str(a))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 66,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "3kCUD1X-ltmT",
        "outputId": "6e909b4d-99e0-4eed-9c18-1b01a6688b0f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Python é 10'"
            ]
          },
          "execution_count": 66,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "c + str(a)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 67,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "TTjSEVRaltmU",
        "outputId": "51f710b2-e55c-4d2a-82c4-bed7f0c593c9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "10.0"
            ]
          },
          "execution_count": 67,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "float(a)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "P1P1bXaYltmV"
      },
      "outputs": [],
      "source": [
        "var = 3.141592"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 69,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "F_8Cn0aAltmW",
        "outputId": "2a3e7efb-d332-4b10-ab2e-8936ad2d7496"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "execution_count": 69,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "int(var)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "_KA6MUgmltmY"
      },
      "outputs": [],
      "source": [
        "var = 3.99"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 71,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "7uiCxqUcltma",
        "outputId": "273cd3c3-9686-49bf-92d2-7c1363a7e095"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "3"
            ]
          },
          "execution_count": 71,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "int(var)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "gGpflJMYltmd"
      },
      "source": [
        "# 2.5 Indentação, comentários e formatação de *strings*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "XbijUgqVltmw"
      },
      "source": [
        "### Indentação\n",
        "\n",
        "Na linguagem Python os programas são estruturados por meio de indentação. Em qualquer linguagem de programação a prática da indentação é bastante útil, facilitando a leitura e também a manutenção do código. Em Python a indentação não é somente uma questão de organização e estilo, mas sim um requisito da linguagem."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 72,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "DqXANnyultmw",
        "outputId": "81632c2d-9919-4713-8099-411c48945e64"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Verdadeiro\n"
          ]
        }
      ],
      "source": [
        "ano_atual = 2019\n",
        "ano_fabricacao = 2019\n",
        "\n",
        "if (ano_atual == ano_fabricacao):\n",
        "  print('Verdadeiro')\n",
        "else:\n",
        "  print('Falso')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "dNBfv7x7ltmy"
      },
      "source": [
        "### Comentários\n",
        "\n",
        "Comentários são extremamente importantes em um programa. Consiste em um texto que descreve o que o programa ou uma parte específica do programa está fazendo. Os comentários são ignorados pelo interpretador Python. \n",
        "\n",
        "Podemos ter comentários de uma única linha ou de múltiplas linhas."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 73,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "GN3DfwiRltmy",
        "outputId": "a8194e87-0ce8-4bee-a03a-7a6cd8f5a3e3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2019"
            ]
          },
          "execution_count": 73,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Isto é um comentário\n",
        "ano_atual = 2019\n",
        "ano_atual"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 74,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "PICBiohFltm2",
        "outputId": "74fa6861-10e2-4eda-9ade-ec6bafbb537f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2019"
            ]
          },
          "execution_count": 74,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Isto\n",
        "# é um \n",
        "# comentário\n",
        "ano_atual = 2019\n",
        "ano_atual"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 75,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "PTkJ4Vjultm4",
        "outputId": "1b125254-516d-499e-9e7f-e04988b875a2"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "2019"
            ]
          },
          "execution_count": 75,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "'''Isto é um\n",
        "comentário'''\n",
        "ano_atual = 2019\n",
        "ano_atual"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 76,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "SYEGdALxltm5",
        "outputId": "9d205531-813f-41d4-bdf5-264759f5f2d5"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Verdadeiro\n"
          ]
        }
      ],
      "source": [
        "# Definindo variáveis\n",
        "ano_atual = 2019\n",
        "ano_fabricacao = 2019\n",
        "\n",
        "'''\n",
        "Estrutura condicional que vamos \n",
        "aprender na próxima aula\n",
        "'''\n",
        "if (ano_atual == ano_fabricacao):   # Testando se condição é verdadeira\n",
        "  print('Verdadeiro')\n",
        "else:                               # Testando se condição é falsa\n",
        "  print('Falso')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "8--bcJ01ltm8"
      },
      "source": [
        "### Formatação de *strings*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "CMovhJZ_ltnG"
      },
      "source": [
        "## *str.format()*\n",
        "\n",
        "https://docs.python.org/3.6/library/stdtypes.html#str.format"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 77,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "N12xmMehltnG",
        "outputId": "38bbc20b-52e8-4a89-b09f-570577ab012f"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Olá, Rodrigo!\n"
          ]
        }
      ],
      "source": [
        "print('Olá, {}!'.format('Rodrigo'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 78,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "mRBmU9G1ltnJ",
        "outputId": "6a615c5f-5ee5-4160-b013-91522183072b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Olá, Rodrigo! Este é seu acesso de número 32\n"
          ]
        }
      ],
      "source": [
        "print('Olá, {}! Este é seu acesso de número {}'.format('Rodrigo', 32))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 79,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "wpqEsTwnltnL",
        "outputId": "26a1dcbc-ae20-429e-ff06-c96d04c99381"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Olá, Rodrigo! Este é seu acesso de número 32\n"
          ]
        }
      ],
      "source": [
        "print('Olá, {nome}! Este é seu acesso de número {acessos}'.format(nome = 'Rodrigo', acessos = 32))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "V-wPNUN9ltnN"
      },
      "source": [
        "## *f-Strings*\n",
        "\n",
        "https://docs.python.org/3.6/reference/lexical_analysis.html#f-strings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "7Fq_WPv0ltnO"
      },
      "outputs": [],
      "source": [
        "nome = 'Rodrigo'\n",
        "acessos = 32"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 81,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "bE3qbd6WltnR",
        "outputId": "fbf2be99-cee1-4498-e901-7ef82cfa42df"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Olá, Rodrigo! Este é seu acesso de número 32\n"
          ]
        }
      ],
      "source": [
        "print(f'Olá, {nome}! Este é seu acesso de número {acessos}')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "_IZuNE48ltnS"
      },
      "source": [
        "# <font color=green> 3. TRABALHANDO COM LISTAS\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "zhS89xysltnS"
      },
      "source": [
        "# 3.1 Criando listas\n",
        "\n",
        "Listas são sequências **mutáveis** que são utilizadas para armazenar coleções de itens, geralmente homogêneos. Podem ser construídas de várias formas:\n",
        "```\n",
        "- Utilizando um par de colchetes: [ ], [ 1 ]\n",
        "- Utilizando um par de colchetes com itens separados por vírgulas: [ 1, 2, 3 ]\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 82,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "aE4UWF10ltnS",
        "outputId": "1c27be59-52b0-4016-c38b-c773e44c1b8d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 82,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios = ['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva']\n",
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 83,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "pP7P-9Nfq-Pp",
        "outputId": "de4eac13-491f-4b90-c335-74a5fd80dd00"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "execution_count": 83,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(Acessorios)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Mmlkh5TVltnT"
      },
      "source": [
        "### Lista com tipos de dados variados"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "Mfpu7NoJltnT"
      },
      "outputs": [],
      "source": [
        "Carro_1 = ['Jetta Variant', 'Motor 4.0 Turbo', 2003, 44410.0, False, ['Rodas de liga', 'Travas elétricas', 'Piloto automático'], 88078.64]\n",
        "Carro_2 = ['Passat', 'Motor Diesel', 1991, 5712.0, False, ['Central multimídia', 'Teto panorâmico', 'Freios ABS'], 106161.94]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 85,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "EJSJFJjKltnV",
        "outputId": "5a7be390-e75c-4c36-934a-ce3b8d28a837"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Jetta Variant',\n",
              " 'Motor 4.0 Turbo',\n",
              " 2003,\n",
              " 44410.0,\n",
              " False,\n",
              " ['Rodas de liga', 'Travas elétricas', 'Piloto automático'],\n",
              " 88078.64]"
            ]
          },
          "execution_count": 85,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carro_1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 86,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "7MMG7L8VltnX",
        "outputId": "b2d5304a-6542-4fb5-f9d5-f2abbf29340f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Passat',\n",
              " 'Motor Diesel',\n",
              " 1991,\n",
              " 5712.0,\n",
              " False,\n",
              " ['Central multimídia', 'Teto panorâmico', 'Freios ABS'],\n",
              " 106161.94]"
            ]
          },
          "execution_count": 86,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carro_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 87,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "colab_type": "code",
        "id": "7E8erLgZltnZ",
        "outputId": "02cbc474-fce5-4cd9-cdfe-b2de135d0d6d"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant',\n",
              "  'Motor 4.0 Turbo',\n",
              "  2003,\n",
              "  44410.0,\n",
              "  False,\n",
              "  ['Rodas de liga', 'Travas elétricas', 'Piloto automático'],\n",
              "  88078.64],\n",
              " ['Passat',\n",
              "  'Motor Diesel',\n",
              "  1991,\n",
              "  5712.0,\n",
              "  False,\n",
              "  ['Central multimídia', 'Teto panorâmico', 'Freios ABS'],\n",
              "  106161.94]]"
            ]
          },
          "execution_count": 87,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carros = [Carro_1, Carro_2]\n",
        "Carros"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "5yMXJ0xdltna"
      },
      "source": [
        "# 3.2 Operações com listas\n",
        "\n",
        "https://docs.python.org/3.6/library/stdtypes.html#common-sequence-operations"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "YSorJOGlltna"
      },
      "source": [
        "## *x in A*\n",
        "\n",
        "Retorna **True** se um elemento da lista *A* for igual a *x*."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 88,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "GgSP_nlHltnb",
        "outputId": "21ad051b-0256-4cde-b3f0-8d18da4128c1"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 88,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 89,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "_JyyHPmWltnd",
        "outputId": "5b4d5691-db4c-45a4-b77e-208cdb0c92e7"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 89,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "'Rodas de liga' in Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 90,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "tebg9gAyltne",
        "outputId": "74a70937-2fa0-4360-fef8-68aa41df4b99"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "execution_count": 90,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "'4 X 4' in Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 91,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "W_1PKJYsltnf",
        "outputId": "a073b8b0-80a4-4061-cf91-6d4e6bedf30f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "execution_count": 91,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "'Rodas de liga' not in Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 92,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "1WNsBXFyltng",
        "outputId": "33f0ee4b-b205-49f8-97ea-e8d158790394"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "True"
            ]
          },
          "execution_count": 92,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "'4 X 4' not in Acessorios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RF6_rf90ltnh"
      },
      "source": [
        "## *A + B*\n",
        "\n",
        "Concatena as listas *A* e *B*."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "8lnzbYnRltnh"
      },
      "outputs": [],
      "source": [
        "A = ['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro']\n",
        "B = ['Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 94,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "SzbiHHF4ltni",
        "outputId": "162c076d-a363-4824-9373-8e3cc8b87fc4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro']"
            ]
          },
          "execution_count": 94,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "A"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 95,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 85
        },
        "colab_type": "code",
        "id": "It5Cn5aXltni",
        "outputId": "8bb676f0-e220-44ec-f1a9-9bb6459fc119"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 95,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "B"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 96,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "l7gF4Ph5ltnj",
        "outputId": "ccef553c-14ea-44eb-a918-1cda3871bd9f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 96,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "A + B"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "iTv5t7zAltnk"
      },
      "source": [
        "## *len(A)*\n",
        "\n",
        "Tamanho da lista A."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 97,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "dtbuCDSOltnk",
        "outputId": "a7ec9c6e-ff92-47c5-92ba-339443af6695"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "8"
            ]
          },
          "execution_count": 97,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(Acessorios)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "k7wWCbAmltnl"
      },
      "source": [
        "# 3.3 Seleções em listas"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "uF3NmgUaltnl"
      },
      "source": [
        "## *A[ i ]*\n",
        "\n",
        "Retorna o i-ésimo item da lista *A*.\n",
        "\n",
        "<font color=red>**Observação:**</font> Listas têm indexação com origem no zero."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 98,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "f5ct7w1Wltnm",
        "outputId": "8864edf0-b235-4edc-e484-41cbe786e376"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 98,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 99,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "-BLG7yifltnn",
        "outputId": "64bb04b6-6e31-4bfc-e25a-1c6230df80b1"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Rodas de liga'"
            ]
          },
          "execution_count": 99,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 100,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "SoL6PIjJltno",
        "outputId": "93a81938-d5d2-4c7b-d824-4a17f902a5af"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Travas elétricas'"
            ]
          },
          "execution_count": 100,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios[1]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 101,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "pGMDc5FLltnq",
        "outputId": "82b87444-5aba-4e5a-90c7-7b92f2ba8da6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Sensor de chuva'"
            ]
          },
          "execution_count": 101,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios[-1]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 102,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        },
        "colab_type": "code",
        "id": "m3AaFe73ltnr",
        "outputId": "f9ba9cc5-d61b-42f3-9cf6-1ac312d4e289"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant',\n",
              "  'Motor 4.0 Turbo',\n",
              "  2003,\n",
              "  44410.0,\n",
              "  False,\n",
              "  ['Rodas de liga', 'Travas elétricas', 'Piloto automático'],\n",
              "  88078.64],\n",
              " ['Passat',\n",
              "  'Motor Diesel',\n",
              "  1991,\n",
              "  5712.0,\n",
              "  False,\n",
              "  ['Central multimídia', 'Teto panorâmico', 'Freios ABS'],\n",
              "  106161.94]]"
            ]
          },
          "execution_count": 102,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carros"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 103,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "AeDJviqoltns",
        "outputId": "790ec9f0-163c-4a9c-c513-2528f13ba7fa"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Jetta Variant',\n",
              " 'Motor 4.0 Turbo',\n",
              " 2003,\n",
              " 44410.0,\n",
              " False,\n",
              " ['Rodas de liga', 'Travas elétricas', 'Piloto automático'],\n",
              " 88078.64]"
            ]
          },
          "execution_count": 103,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carros[0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 104,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "KdenG1BZltnt",
        "outputId": "4dbc4088-d019-435a-9535-f4e75ebf70ff"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Jetta Variant'"
            ]
          },
          "execution_count": 104,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carros[0][0]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 105,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "iOjsfrlFltnu",
        "outputId": "767453aa-804f-46a0-b79f-758c68793f4c"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga', 'Travas elétricas', 'Piloto automático']"
            ]
          },
          "execution_count": 105,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carros[0][-2]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 106,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "6BrON70Zltnu",
        "outputId": "0a0bd591-f421-4ee7-8312-86ae4991622e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Travas elétricas'"
            ]
          },
          "execution_count": 106,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Carros[0][-2][1]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "9WgwxPIMltnv"
      },
      "source": [
        "## *A[ i : j ]*\n",
        "\n",
        "Recorta a lista *A* do índice i até o j. Neste fatiamento o elemento com índice i é **incluído** e o elemento com índice j **não é incluído** no resultado."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 107,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "bJzL2PMiltnv",
        "outputId": "de15a5a4-7c50-4916-c8ec-3754a639c125"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 107,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 108,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "sFAlJ4u_ltnw",
        "outputId": "96a8da29-e9f1-4f96-f00b-6c2556ff6026"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Piloto automático', 'Bancos de couro', 'Ar condicionado']"
            ]
          },
          "execution_count": 108,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios[2:5]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 109,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        },
        "colab_type": "code",
        "id": "dFdTBWa9ltnz",
        "outputId": "efcd12b4-1261-45e6-ffbe-142117008855"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 109,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios[2:]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 110,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "colab_type": "code",
        "id": "yxxB2-_Dltn0",
        "outputId": "c85fde97-c2f0-4a4c-d525-768dd783d82b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado']"
            ]
          },
          "execution_count": 110,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios[:5]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "R-S-LCPGltn0"
      },
      "source": [
        "# 3.4 Métodos de listas\n",
        "\n",
        "https://docs.python.org/3.6/library/stdtypes.html#mutable-sequence-types"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "2siXqYSlAjHR"
      },
      "outputs": [],
      "source": [
        "Acessorios = ['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva']"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "j9s2OyyPltn1"
      },
      "source": [
        "## *A.sort()*\n",
        "\n",
        "Ordena a lista *A*."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 112,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "A2dJGhFsltn1",
        "outputId": "9fb74514-57f7-4b03-cbcd-5d533d29cc9e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 112,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 113,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "VDWCHlTcltn2",
        "outputId": "143eb792-177f-4acc-af75-130c2eb16426"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Rodas de liga',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 113,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios.sort()\n",
        "Acessorios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "N9Spp7-xltn3"
      },
      "source": [
        "## *A.append(x)*\n",
        "\n",
        "Adiciona o elemento *x* no final da lista *A*."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 114,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        },
        "colab_type": "code",
        "id": "l7I_U-sRltn4",
        "outputId": "1a78841b-2724-47d2-8f25-509d51507cfe"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Rodas de liga',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas',\n",
              " '4 X 4']"
            ]
          },
          "execution_count": 114,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios.append('4 X 4')\n",
        "Acessorios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "eiP3oACPltn6"
      },
      "source": [
        "## *A.pop(i)*\n",
        "\n",
        "Remove e retorna o elemento de índice i da lista *A*.\n",
        "\n",
        "<font color=red>**Observação:**</font> Por *default* o método *pop()* remove e retorna o último elemento de uma lista."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 115,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "BoCKa5Hqltn6",
        "outputId": "96215373-89e4-4eeb-f556-7da3428b3a35"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'4 X 4'"
            ]
          },
          "execution_count": 115,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios.pop()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 116,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "GfGX1jw-ltn9",
        "outputId": "ee1ff47f-5e2d-4eba-f098-91d5302702c3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Rodas de liga',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 116,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 117,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "tppe9tqbltn-",
        "outputId": "e22fbedc-c4dc-48a0-97a9-2aa91bc73489"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "'Rodas de liga'"
            ]
          },
          "execution_count": 117,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios.pop(3)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 118,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "Ku6ZHTdJltn_",
        "outputId": "ee042ee6-f301-4dc7-845e-2f69ce869202"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 118,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "NySIp62hltoC"
      },
      "source": [
        "## *A.copy()*\n",
        "\n",
        "Cria uma cópia da lista *A*.\n",
        "\n",
        "<font color=red>**Observação:**</font> O mesmo resultado pode ser obtido com o seguinte código: \n",
        "```\n",
        "A[:]\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 119,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "yP9ODygcltoC",
        "outputId": "54d584d6-42c1-410f-f477-93d470ab12d9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 119,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios_2 = Acessorios\n",
        "Acessorios_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 120,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "W3eQdVWkltoF",
        "outputId": "fa3c1319-370c-4352-84c9-ab90b52194f6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas',\n",
              " '4 X 4']"
            ]
          },
          "execution_count": 120,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios_2.append('4 X 4')\n",
        "Acessorios_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 121,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "OVbvjjmdltoG",
        "outputId": "02aa1d88-56f8-41db-f19b-cce4437cc553"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas',\n",
              " '4 X 4']"
            ]
          },
          "execution_count": 121,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 122,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "P-MN1JfAltoH",
        "outputId": "4c32f833-c810-4521-a527-87b135bc037e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 122,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios.pop()\n",
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 123,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "ZVQ38eqVltoJ",
        "outputId": "ed28e52e-28c6-4898-c6d1-92094016d94a"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 123,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 124,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "bqPiw5wSltoM",
        "outputId": "62eb941d-e444-4fe8-8374-b3b6ed9866df"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 124,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios_2 = Acessorios.copy()\n",
        "Acessorios_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 125,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "Lo9WgzF6ltoP",
        "outputId": "4b20eda4-d273-4c16-9205-2ef1b803e376"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas',\n",
              " '4 X 4']"
            ]
          },
          "execution_count": 125,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios_2.append('4 X 4')\n",
        "Acessorios_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 126,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "r2LPHB34ltoQ",
        "outputId": "213b9621-cd22-4af6-b85b-b1f5630228b2"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 126,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 127,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "colab_type": "code",
        "id": "UQqUkO8YltoR",
        "outputId": "4736846d-298e-4572-c574-e22f2f27d579"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Ar condicionado',\n",
              " 'Bancos de couro',\n",
              " 'Piloto automático',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Sensor de estacionamento',\n",
              " 'Travas elétricas']"
            ]
          },
          "execution_count": 127,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios_2 = Acessorios[:]\n",
        "Acessorios_2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "8zMZNsg2ltoU"
      },
      "source": [
        "# <font color=green> 4. ESTRUTURAS DE REPETIÇÃO E CONDICIONAIS\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "gxUmCLyJltoU"
      },
      "source": [
        "# 4.1 Instrução *for*\n",
        "\n",
        "#### Formato padrão\n",
        "\n",
        "```\n",
        "for <variável> in <coleção>:\n",
        "    <instruções>\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Irl5oa0altoU"
      },
      "source": [
        "### Loops com listas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 128,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "BaXtCB-IJDf5",
        "outputId": "40a08937-3ef8-40bd-fc9b-4566aa975272"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva']"
            ]
          },
          "execution_count": 128,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios = ['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva']\n",
        "Acessorios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 129,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "Z459QqsFltoY",
        "outputId": "e9738899-0ed8-49f7-8f6d-78ac71bde218"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Rodas de liga\n",
            "Travas elétricas\n",
            "Piloto automático\n",
            "Bancos de couro\n",
            "Ar condicionado\n",
            "Sensor de estacionamento\n",
            "Sensor crepuscular\n",
            "Sensor de chuva\n"
          ]
        }
      ],
      "source": [
        "for item in Acessorios:\n",
        "  print(item)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Gbztj9T4ltoZ"
      },
      "source": [
        "###  List comprehensions\n",
        "\n",
        "https://docs.python.org/3.6/tutorial/datastructures.html#list-comprehensions"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "4Y8g0cSHjbof"
      },
      "source": [
        "*range()* -> https://docs.python.org/3.6/library/functions.html#func-range"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 130,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "xDo9TLdYltoZ",
        "outputId": "ba818a70-81bd-4f53-8e20-d6f22d4a4523"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "range(0, 10)"
            ]
          },
          "execution_count": 130,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "range(10)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 131,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "V12p_CQBltoc",
        "outputId": "05e3e80a-3303-414a-bd9a-f8034a1d7722"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]"
            ]
          },
          "execution_count": 131,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "list(range(10))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 132,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "colab_type": "code",
        "id": "OOzHHRWHltof",
        "outputId": "4175aee1-1a4e-49ea-9380-4c4334ad6536"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "0\n",
            "1\n",
            "4\n",
            "9\n",
            "16\n",
            "25\n",
            "36\n",
            "49\n",
            "64\n",
            "81\n"
          ]
        }
      ],
      "source": [
        "for i in range(10):\n",
        "  print(i ** 2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 133,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "TKynwnxgltog",
        "outputId": "c2e757a9-de60-4fc6-a7f7-9524cb8f9fdb"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
            ]
          },
          "execution_count": 133,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "quadrado = []\n",
        "for i in range(10):\n",
        "  quadrado.append(i ** 2)\n",
        "  \n",
        "quadrado"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 134,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "d77YH_dVltoh",
        "outputId": "e55b7f43-a2cc-4c99-f0e2-65c237e42387"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]"
            ]
          },
          "execution_count": 134,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "[i ** 2 for i in range(10)]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "AcAcaKFXltom"
      },
      "source": [
        "# 4.2 Loops aninhados"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 135,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "colab_type": "code",
        "id": "mjgJCo3dlton",
        "outputId": "c0f29b76-ec59-4ba0-cd56-45a0da8c9428"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Rodas de liga',\n",
              "  'Travas elétricas',\n",
              "  'Piloto automático',\n",
              "  'Bancos de couro',\n",
              "  'Ar condicionado',\n",
              "  'Sensor de estacionamento',\n",
              "  'Sensor crepuscular',\n",
              "  'Sensor de chuva'],\n",
              " ['Central multimídia',\n",
              "  'Teto panorâmico',\n",
              "  'Freios ABS',\n",
              "  '4 X 4',\n",
              "  'Painel digital',\n",
              "  'Piloto automático',\n",
              "  'Bancos de couro',\n",
              "  'Câmera de estacionamento'],\n",
              " ['Piloto automático',\n",
              "  'Controle de estabilidade',\n",
              "  'Sensor crepuscular',\n",
              "  'Freios ABS',\n",
              "  'Câmbio automático',\n",
              "  'Bancos de couro',\n",
              "  'Central multimídia',\n",
              "  'Vidros elétricos']]"
            ]
          },
          "execution_count": 135,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dados = [ \n",
        "    ['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva'],\n",
        "    ['Central multimídia', 'Teto panorâmico', 'Freios ABS', '4 X 4', 'Painel digital', 'Piloto automático', 'Bancos de couro', 'Câmera de estacionamento'],\n",
        "    ['Piloto automático', 'Controle de estabilidade', 'Sensor crepuscular', 'Freios ABS', 'Câmbio automático', 'Bancos de couro', 'Central multimídia', 'Vidros elétricos']\n",
        "]\n",
        "dados"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 136,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "colab_type": "code",
        "id": "pLgxwApVltop",
        "outputId": "58b13774-b1b7-45d9-df2f-05b8cf6ff8eb"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva']\n",
            "['Central multimídia', 'Teto panorâmico', 'Freios ABS', '4 X 4', 'Painel digital', 'Piloto automático', 'Bancos de couro', 'Câmera de estacionamento']\n",
            "['Piloto automático', 'Controle de estabilidade', 'Sensor crepuscular', 'Freios ABS', 'Câmbio automático', 'Bancos de couro', 'Central multimídia', 'Vidros elétricos']\n"
          ]
        }
      ],
      "source": [
        "for lista in dados:\n",
        "  print(lista)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 137,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "colab_type": "code",
        "id": "OYnDRvcYltor",
        "outputId": "b5b17d0a-0421-4cae-b8b9-6cbb5813ba85"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Rodas de liga\n",
            "Travas elétricas\n",
            "Piloto automático\n",
            "Bancos de couro\n",
            "Ar condicionado\n",
            "Sensor de estacionamento\n",
            "Sensor crepuscular\n",
            "Sensor de chuva\n",
            "Central multimídia\n",
            "Teto panorâmico\n",
            "Freios ABS\n",
            "4 X 4\n",
            "Painel digital\n",
            "Piloto automático\n",
            "Bancos de couro\n",
            "Câmera de estacionamento\n",
            "Piloto automático\n",
            "Controle de estabilidade\n",
            "Sensor crepuscular\n",
            "Freios ABS\n",
            "Câmbio automático\n",
            "Bancos de couro\n",
            "Central multimídia\n",
            "Vidros elétricos\n"
          ]
        }
      ],
      "source": [
        "for lista in dados:\n",
        "  for item in lista:\n",
        "    print(item)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 138,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "colab_type": "code",
        "id": "DbJa5_cJltos",
        "outputId": "4c9636c4-26b6-4ee4-dfe0-e45467129616"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Central multimídia',\n",
              " 'Teto panorâmico',\n",
              " 'Freios ABS',\n",
              " '4 X 4',\n",
              " 'Painel digital',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Câmera de estacionamento',\n",
              " 'Piloto automático',\n",
              " 'Controle de estabilidade',\n",
              " 'Sensor crepuscular',\n",
              " 'Freios ABS',\n",
              " 'Câmbio automático',\n",
              " 'Bancos de couro',\n",
              " 'Central multimídia',\n",
              " 'Vidros elétricos']"
            ]
          },
          "execution_count": 138,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessorios = []\n",
        "\n",
        "for lista in dados:\n",
        "  for item in lista:\n",
        "    Acessorios.append(item)\n",
        "    \n",
        "Acessorios"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RrGAOy1rn1Dj"
      },
      "source": [
        "## *set()*\n",
        "\n",
        "https://docs.python.org/3.6/library/stdtypes.html#types-set\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 139,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "colab_type": "code",
        "id": "CuB-9ClSltos",
        "outputId": "3d1af15e-63eb-4bd3-c948-949b264e7ef4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['4 X 4',\n",
              " 'Sensor de chuva',\n",
              " 'Ar condicionado',\n",
              " 'Central multimídia',\n",
              " 'Bancos de couro',\n",
              " 'Painel digital',\n",
              " 'Rodas de liga',\n",
              " 'Câmera de estacionamento',\n",
              " 'Freios ABS',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Controle de estabilidade',\n",
              " 'Teto panorâmico',\n",
              " 'Câmbio automático',\n",
              " 'Vidros elétricos',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de estacionamento']"
            ]
          },
          "execution_count": 139,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "list(set(Acessorios))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "9hHKKABhltot"
      },
      "source": [
        "### List comprehensions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 140,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "colab_type": "code",
        "id": "T6t79LTlltot",
        "outputId": "83e1cad0-d46a-4f53-8a4b-2fb58840f15f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['Rodas de liga',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Ar condicionado',\n",
              " 'Sensor de estacionamento',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de chuva',\n",
              " 'Central multimídia',\n",
              " 'Teto panorâmico',\n",
              " 'Freios ABS',\n",
              " '4 X 4',\n",
              " 'Painel digital',\n",
              " 'Piloto automático',\n",
              " 'Bancos de couro',\n",
              " 'Câmera de estacionamento',\n",
              " 'Piloto automático',\n",
              " 'Controle de estabilidade',\n",
              " 'Sensor crepuscular',\n",
              " 'Freios ABS',\n",
              " 'Câmbio automático',\n",
              " 'Bancos de couro',\n",
              " 'Central multimídia',\n",
              " 'Vidros elétricos']"
            ]
          },
          "execution_count": 140,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "[item for lista in dados for item in lista]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 141,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 306
        },
        "colab_type": "code",
        "id": "Vhvuh3l8bvHZ",
        "outputId": "4d141bf6-783f-47f8-95fc-d23a718925b4"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['4 X 4',\n",
              " 'Sensor de chuva',\n",
              " 'Ar condicionado',\n",
              " 'Central multimídia',\n",
              " 'Bancos de couro',\n",
              " 'Painel digital',\n",
              " 'Rodas de liga',\n",
              " 'Câmera de estacionamento',\n",
              " 'Freios ABS',\n",
              " 'Travas elétricas',\n",
              " 'Piloto automático',\n",
              " 'Controle de estabilidade',\n",
              " 'Teto panorâmico',\n",
              " 'Câmbio automático',\n",
              " 'Vidros elétricos',\n",
              " 'Sensor crepuscular',\n",
              " 'Sensor de estacionamento']"
            ]
          },
          "execution_count": 141,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "list(set([item for lista in dados for item in lista]))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "cJ4fPdj5ltou"
      },
      "source": [
        "# 4.3 Instrução *if*\n",
        "\n",
        "#### Formato padrão\n",
        "\n",
        "```\n",
        "if <condição>:\n",
        "     <instruções caso a condição seja verdadeira>\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "bqOYDJiWltou"
      },
      "source": [
        "### Operadores de comparação: $==$, $!=$, $>$, $<$, $>=$, $<=$\n",
        "### e\n",
        "### Operadores lógicos: $and$, $or$, $not$"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 157,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "colab_type": "code",
        "id": "5eY_XPmrltov",
        "outputId": "dfa39914-bff9-4ed6-b4d9-0386ea0f6c2b"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant', 2003, False],\n",
              " ['Passat', 1991, False],\n",
              " ['Crossfox', 1990, False],\n",
              " ['DS5', 2019, True],\n",
              " ['Aston Martin DB4', 2006, False],\n",
              " ['Palio Weekend', 2012, False],\n",
              " ['A5', 2019, True],\n",
              " ['Série 3 Cabrio', 2009, False],\n",
              " ['Dodge Jorney', 2019, False],\n",
              " ['Carens', 2011, False]]"
            ]
          },
          "execution_count": 157,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# 1º item da lista - Nome do veículo\n",
        "# 2º item da lista - Ano de fabricação\n",
        "# 3º item da lista - Veículo é zero km?\n",
        "\n",
        "dados = [\n",
        "    ['Jetta Variant', 2003, False],\n",
        "    ['Passat', 1991, False],\n",
        "    ['Crossfox', 1990, False],\n",
        "    ['DS5', 2019, True],\n",
        "    ['Aston Martin DB4', 2006, False],\n",
        "    ['Palio Weekend', 2012, False],\n",
        "    ['A5', 2019, True],\n",
        "    ['Série 3 Cabrio', 2009, False],\n",
        "    ['Dodge Jorney', 2019, False],\n",
        "    ['Carens', 2011, False]\n",
        "]\n",
        "dados"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 154,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "nyb0iDH1ltoy",
        "outputId": "e5541ea2-6c8d-40a3-a7b5-8667e20567f6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['DS5', 2019, True], ['A5', 2019, True]]"
            ]
          },
          "execution_count": 154,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "zero_km_Y = []\n",
        "\n",
        "for lista in dados:\n",
        "  if(lista[2] == True):\n",
        "    zero_km_Y.append(lista)\n",
        "    \n",
        "zero_km_Y"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 155,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "5MlITJppltoy",
        "outputId": "a47edb79-e00e-460f-c381-bb4af70cb09e"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant', 2003, False],\n",
              " ['Passat', 1991, False],\n",
              " ['Crossfox', 1990, False],\n",
              " ['Aston Martin DB4', 2006, False],\n",
              " ['Palio Weekend', 2012, False],\n",
              " ['Série 3 Cabrio', 2009, False],\n",
              " ['Dodge Jorney', 2019, False],\n",
              " ['Carens', 2011, False]]"
            ]
          },
          "execution_count": 155,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "zero_km_N = []\n",
        "\n",
        "for lista in dados:\n",
        "  if(lista[2] == False):\n",
        "    zero_km_N.append(lista)\n",
        "    \n",
        "zero_km_N"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "51Js0kXD0aRH"
      },
      "source": [
        "### List comprehensions"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 156,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "Ly4QUX5J0aRI",
        "outputId": "dd66e50c-ca18-4041-c62f-080fa8782d9f"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['DS5', 2019, True], ['A5', 2019, True]]"
            ]
          },
          "execution_count": 156,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "[lista for lista in dados if lista[2] == True]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "CKjrvO5Tltoz"
      },
      "source": [
        "# 4.4 Instruções *if-else* e *if-elif-else*\n",
        "\n",
        "#### Formato padrão\n",
        "\n",
        "```\n",
        "if <condição>:\n",
        "    <instruções caso a condição seja verdadeira>\n",
        "else:\n",
        "    <instruções caso a condição não seja verdadeira>\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "K_VORb47ltoz"
      },
      "outputs": [],
      "source": [
        "zero_km_Y, zero_km_N = [], []\n",
        "\n",
        "for lista in dados:\n",
        "  if(lista[2] == True):\n",
        "    zero_km_Y.append(lista)\n",
        "  else:\n",
        "    zero_km_N.append(lista)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 159,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "vhz5T7jDlto1",
        "outputId": "8c0db05e-ab1b-43a9-e506-acbd951309dd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['DS5', 2019, True], ['A5', 2019, True]]"
            ]
          },
          "execution_count": 159,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "zero_km_Y"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 160,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 153
        },
        "colab_type": "code",
        "id": "XlvlpPjhlto1",
        "outputId": "4aead204-889c-4636-9259-c2f8e2b954f5"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant', 2003, False],\n",
              " ['Passat', 1991, False],\n",
              " ['Crossfox', 1990, False],\n",
              " ['Aston Martin DB4', 2006, False],\n",
              " ['Palio Weekend', 2012, False],\n",
              " ['Série 3 Cabrio', 2009, False],\n",
              " ['Dodge Jorney', 2019, False],\n",
              " ['Carens', 2011, False]]"
            ]
          },
          "execution_count": 160,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "zero_km_N"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Z2-8WeN1lto2"
      },
      "source": [
        "#### Formato padrão\n",
        "\n",
        "```\n",
        "if <condição 1>:\n",
        "    <instruções caso a condição 1 seja verdadeira>\n",
        "elif <condição 2>:\n",
        "    <instruções caso a condição 2 seja verdadeira>\n",
        "elif <condição 3>:\n",
        "    <instruções caso a condição 3 seja verdadeira>\n",
        "                        .\n",
        "                        .\n",
        "                        .\n",
        "else:\n",
        "    <instruções caso as condições anteriores não sejam verdadeiras>\n",
        "```"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 161,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 187
        },
        "colab_type": "code",
        "id": "ggrbaB4Tlto2",
        "outputId": "51b9ddf0-a96f-46a7-a281-2f8c9c6e2171"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant', 2003, False],\n",
              " ['Passat', 1991, False],\n",
              " ['Crossfox', 1990, False],\n",
              " ['DS5', 2019, True],\n",
              " ['Aston Martin DB4', 2006, False],\n",
              " ['Palio Weekend', 2012, False],\n",
              " ['A5', 2019, True],\n",
              " ['Série 3 Cabrio', 2009, False],\n",
              " ['Dodge Jorney', 2019, False],\n",
              " ['Carens', 2011, False]]"
            ]
          },
          "execution_count": 161,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dados"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 143,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "colab_type": "code",
        "id": "KJgRc1F9lto3",
        "outputId": "4ae7bd3c-1397-45c7-b773-ac968ea37f59"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "AND\n",
            "(True and True) o resultado é: True\n",
            "(True and False) o resultado é: False\n",
            "(False and True) o resultado é: False\n",
            "(False and False) o resultado é: False\n"
          ]
        }
      ],
      "source": [
        "print('AND')\n",
        "print(f'(True and True) o resultado é: {True and True}')\n",
        "print(f'(True and False) o resultado é: {True and False}')\n",
        "print(f'(False and True) o resultado é: {False and True}')\n",
        "print(f'(False and False) o resultado é: {False and False}')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 144,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "colab_type": "code",
        "id": "sb0mSh-o0aRM",
        "outputId": "9a94b896-d4af-4e99-a4a2-cc65da7b088c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "OR\n",
            "(True or True) o resultado é: True\n",
            "(True or False) o resultado é: True\n",
            "(False or True) o resultado é: True\n",
            "(False or False) o resultado é: False\n"
          ]
        }
      ],
      "source": [
        "                            print('OR')\n",
        "print(f'(True or True) o resultado é: {True or True}')\n",
        "print(f'(True or False) o resultado é: {True or False}')\n",
        "print(f'(False or True) o resultado é: {False or True}')\n",
        "print(f'(False or False) o resultado é: {False or False}')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "AfNdTPzElto3"
      },
      "outputs": [],
      "source": [
        "A, B, C = [], [], []\n",
        "\n",
        "for lista in dados:\n",
        "  if(lista[1] <=2000):\n",
        "    A.append(lista)\n",
        "  elif(lista[1] > 2000 and lista[1] <= 2010):\n",
        "    B.append(lista)\n",
        "  else:\n",
        "    C.append(lista)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 167,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "colab_type": "code",
        "id": "5bN7SuvTlto4",
        "outputId": "f028696d-0ab9-4f96-c004-b471aa19eedf"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Passat', 1991, False], ['Crossfox', 1990, False]]"
            ]
          },
          "execution_count": 167,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "A"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 168,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        },
        "colab_type": "code",
        "id": "dDEl3Vfglto4",
        "outputId": "4a27e533-c13f-44db-dfeb-671daf0771b9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Jetta Variant', 2003, False],\n",
              " ['Aston Martin DB4', 2006, False],\n",
              " ['Série 3 Cabrio', 2009, False]]"
            ]
          },
          "execution_count": 168,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "B"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 169,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        },
        "colab_type": "code",
        "id": "Ot4HLQlelto5",
        "outputId": "af8473c0-ba79-4cad-aab4-832561d98264"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['DS5', 2019, True],\n",
              " ['Palio Weekend', 2012, False],\n",
              " ['A5', 2019, True],\n",
              " ['Dodge Jorney', 2019, False],\n",
              " ['Carens', 2011, False]]"
            ]
          },
          "execution_count": 169,
          "metadata": {
            "tags": []
          },
          "output_type": "execute_result"
        }
      ],
      "source": [
        "C"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "FN26ZBKJlto5"
      },
      "outputs": [],
      "source": [
        "A, B, C = [], [], []\n",
        "\n",
        "for lista in dados:\n",
        "  if(lista[1] <=2000):\n",
        "    A.append(lista)\n",
        "  elif(2000 < lista[1] <= 2010):\n",
        "    B.append(lista)\n",
        "  else:\n",
        "    C.append(lista)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "aRfQfubxlto6"
      },
      "source": [
        "# <font color=green> 5. NUMPY BÁSICO\n",
        "---\n",
        "\n",
        "Numpy é a abreviação de Numerical Python e é um dos pacotes mais importantes para processamento numérico em Python. Numpy oferece a base para a maioria dos pacotes de aplicações científicas que utilizem dados numéricos em Python (estruturas de dados e algoritmos). Pode-se destacar os seguintes recursos que o pacote Numpy contém:\n",
        "\n",
        "- Um poderoso objeto array multidimensional;\n",
        "- Funções matemáticas sofisticadas para operações com arrays sem a necessidade de utilização de laços *for*;\n",
        "- Recursos de algebra linear e geração de números aleatórios\n",
        "\n",
        "Além de seus óbvios usos científicos, o pacote NumPy também é muito utilizado em análise de dados como um eficiente contêiner multidimensional de dados genéricos para transporte entre diversos algoritmos e bibliotecas em Python.\n",
        "\n",
        "**Versão:** 1.16.5\n",
        "\n",
        "**Instalação:** https://scipy.org/install.html\n",
        "\n",
        "**Documentação:** https://numpy.org/doc/1.16/"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RtG2-g1ultme"
      },
      "source": [
        "### Pacotes\n",
        "\n",
        "Existem diversos pacotes Python disponíveis para download na internet. Cada pacote tem como objetivo a solução de determinado tipo de problema e para isso são desenvolvidos novos tipos, funções e métodos.\n",
        "\n",
        "Alguns pacotes são bastante utilizados em um contexto de ciência de dados como por exemplo:\n",
        "\n",
        "- Numpy\n",
        "- Pandas\n",
        "- Scikit-learn\n",
        "- Matplotlib\n",
        "\n",
        "Alguns pacotes não são distribuídos com a instalação default do Python. Neste caso devemos instalar os pacotes que necessitamos em nosso sistema para podermos utilizar suas funcionalidades."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "b8prsQjmltme"
      },
      "source": [
        "### Importando todo o pacote"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "lP0tqXHLltmf"
      },
      "outputs": [],
      "source": [
        "import numpy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "ESliJKAaQMRY"
      },
      "source": [
        "https://numpy.org/doc/1.16/reference/generated/numpy.arange.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "Y40UP3K7ltmg"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "numpy.arange(10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "84-53f4Lltmh"
      },
      "source": [
        "### Importando todo o pacote e atribuindo um novo nome "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "CzESWck7ltmi"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "import numpy as np\n",
        "\n",
        "np.arange(10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "WWawttSpltml"
      },
      "source": [
        "### Importando parte do pacote"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "8kTeo3Ltltmo"
      },
      "outputs": [],
      "source": [
        "from numpy import arange"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "4LPnpiEwltmt"
      },
      "outputs": [],
      "source": [
        "arange(10)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "VSmffnCklto6"
      },
      "source": [
        "# 5.1 Criando arrays Numpy"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "Wqpin_-Plto8"
      },
      "outputs": [],
      "source": [
        "import numpy as np"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "ock4Ku-Ulto8"
      },
      "source": [
        "### A partir de listas\n",
        "\n",
        "https://numpy.org/doc/1.16/user/basics.creation.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "82H-09CQlto9"
      },
      "outputs": [],
      "source": [
        "km = np.array([1000, 2300, 4987, 1500])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "8VYE3JSYlto9"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([1000, 2300, 4987, 1500])"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "OBsa5Cfplto-"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "numpy.ndarray"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "type(km)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RfQ3jJSAlto-"
      },
      "source": [
        "https://numpy.org/doc/1.16/user/basics.types.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "6yLpkJcAlto-"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "dtype('int64')"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km.dtype"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "1pFx86QPlto_"
      },
      "source": [
        "### A partir de dados externos\n",
        "\n",
        "https://numpy.org/doc/1.16/reference/generated/numpy.loadtxt.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "26pQLNgrlto_"
      },
      "outputs": [],
      "source": [
        "km = np.loadtxt(fname = './data/carros-km.txt', dtype = int)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "FoP42bdpltpA",
        "scrolled": true
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([ 44410,   5712,  37123,      0,  25757,  10728,      0,  77599,\n",
              "        99197,  37978,  12859,   8052,  89773,      0,  41457, 115607,\n",
              "        46449,      0,  37086,  15173, 101193,      0,  98079, 102959,\n",
              "            0,      0,   5795,      0,  58848,  94381,  30163,  53332,\n",
              "        17720,  33808,  90684,  43975,      0,      0,   5526,      0,\n",
              "        93415,  40762,      0,  86302,      0,   9755,  69945,   2395,\n",
              "            0,  80349,  85554,  50496,  67716,  93947,  35345,  81007,\n",
              "       119513,      0,      0,      0,      0,      0, 118895,  48509,\n",
              "       100912,  95649,      0,  90495,      0,  29132,  23802,  84992,\n",
              "        54395,  26731,  44329, 118236, 113808,    610,      0,      0,\n",
              "        12887,  79607,  90924,  42733,      0,      0, 117714, 113885,\n",
              "            0,  30511,  74867, 119760,   8356,  64247,  88661,   4539,\n",
              "       110116,  33215,  92001,      0,  81708,  70641,      0,  91277,\n",
              "        26544,  52596,  47503,  89056,  28834, 110564,  56638,  17357,\n",
              "        74015,  15196,      0,  10821,      0,      0,   9595,  99052,\n",
              "        52389, 119945,  96005,  31639,      0,  80187,      0,  58212,\n",
              "        61672,  32017,      0,  56944,      0,  86519,   4821, 101025,\n",
              "        30705,      0,  32555, 103389,      0,  55289,      0,      0,\n",
              "       115930,  66437,  96800,  14237,  19896, 113045, 114942,   3173,\n",
              "        83611,  25356,  88634,   2314,   2627,  52034,      0,      0,\n",
              "        79577, 108201,  76453,  57683,  96610, 109001,  26212,  45971,\n",
              "        49182,  49907,  38620,  60996,  73914, 107392,   9146,      0,\n",
              "        17924,      0, 116949,  20476,  52804,   8849,  91724,  32056,\n",
              "        74886,      0,      0,  52189,  83559,      0,  20328,      0,\n",
              "        75577,  33659, 104341,  25510,  18965,  87161,   6652,  55738,\n",
              "            0,      0,      0,  64320,      0,  68678,  71697,      0,\n",
              "        34783,  33772,  85127,  13606,  35647,  95128,  14046,  41194,\n",
              "            0,  96100, 103900,  43814,  24638,      0, 110966,  15987,\n",
              "        53369,  10077,  71544,    107,   8394,  41498, 116002, 100858,\n",
              "        67475,   8497,   4420,      0,  58537,      0,      0, 112016,\n",
              "        91840, 112787,      0,      0,   9293,      0,  55083,  48796,\n",
              "            0,  89685,  85384,  98108,  71280,  27505,  29981,  52637,\n",
              "         7685,  50188])"
            ]
          },
          "execution_count": 15,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "MNPjZJbYltpA"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "dtype('int64')"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km.dtype"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "_wnTg0wJltpB"
      },
      "source": [
        "### Arrays com duas dimensões"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 425
        },
        "colab_type": "code",
        "id": "Gt1dL27GltpB",
        "outputId": "6cf89502-f71a-426e-bbe8-06ec0226c9fe",
        "scrolled": true
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "[['Rodas de liga',\n",
              "  'Travas elétricas',\n",
              "  'Piloto automático',\n",
              "  'Bancos de couro',\n",
              "  'Ar condicionado',\n",
              "  'Sensor de estacionamento',\n",
              "  'Sensor crepuscular',\n",
              "  'Sensor de chuva'],\n",
              " ['Central multimídia',\n",
              "  'Teto panorâmico',\n",
              "  'Freios ABS',\n",
              "  '4 X 4',\n",
              "  'Painel digital',\n",
              "  'Piloto automático',\n",
              "  'Bancos de couro',\n",
              "  'Câmera de estacionamento'],\n",
              " ['Piloto automático',\n",
              "  'Controle de estabilidade',\n",
              "  'Sensor crepuscular',\n",
              "  'Freios ABS',\n",
              "  'Câmbio automático',\n",
              "  'Bancos de couro',\n",
              "  'Central multimídia',\n",
              "  'Vidros elétricos']]"
            ]
          },
          "execution_count": 17,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dados = [ \n",
        "    ['Rodas de liga', 'Travas elétricas', 'Piloto automático', 'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento', 'Sensor crepuscular', 'Sensor de chuva'],\n",
        "    ['Central multimídia', 'Teto panorâmico', 'Freios ABS', '4 X 4', 'Painel digital', 'Piloto automático', 'Bancos de couro', 'Câmera de estacionamento'],\n",
        "    ['Piloto automático', 'Controle de estabilidade', 'Sensor crepuscular', 'Freios ABS', 'Câmbio automático', 'Bancos de couro', 'Central multimídia', 'Vidros elétricos']\n",
        "]\n",
        "dados"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "IlbYeZPkltpC"
      },
      "outputs": [],
      "source": [
        "Acessórios = np.array(dados)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "FgjmWozgltpD",
        "scrolled": true
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "array([['Rodas de liga', 'Travas elétricas', 'Piloto automático',\n",
              "        'Bancos de couro', 'Ar condicionado', 'Sensor de estacionamento',\n",
              "        'Sensor crepuscular', 'Sensor de chuva'],\n",
              "       ['Central multimídia', 'Teto panorâmico', 'Freios ABS', '4 X 4',\n",
              "        'Painel digital', 'Piloto automático', 'Bancos de couro',\n",
              "        'Câmera de estacionamento'],\n",
              "       ['Piloto automático', 'Controle de estabilidade',\n",
              "        'Sensor crepuscular', 'Freios ABS', 'Câmbio automático',\n",
              "        'Bancos de couro', 'Central multimídia', 'Vidros elétricos']],\n",
              "      dtype='<U24')"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessórios"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "TDM9HskUltpD"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(258,)"
            ]
          },
          "execution_count": 20,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "km.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "bBmnzpF5ltpE"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(3, 8)"
            ]
          },
          "execution_count": 21,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "Acessórios.shape"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "cPbkST9pltpE"
      },
      "source": [
        "### Comparando desempenho com listas"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "tTPC-G4vltpE"
      },
      "outputs": [],
      "source": [
        "np_array = np.arange(1000000)\n",
        "\n",
        "py_list = list(range(1000000))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "PIC-ndg9ltpF"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 323 ms, sys: 0 ns, total: 323 ms\n",
            "Wall time: 347 ms\n"
          ]
        }
      ],
      "source": [
        "%time for _ in range(100): np_array *= 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "vXy57nk2ltpF"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "CPU times: user 8.4 s, sys: 969 ms, total: 9.37 s\n",
            "Wall time: 9.38 s\n"
          ]
        }
      ],
      "source": [
        "%time for _ in range(100): py_list = [x * 2 for x in py_list]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "ul4MuKyTltpG"
      },
      "source": [
        "# 5.2 Operações aritméticas com arrays Numpy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "QwnxO_rYltpH"
      },
      "source": [
        "### Operações entre arrays e constantes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "63KVHPK0ltpH"
      },
      "outputs": [],
      "source": [
        "km = [44410., 5712., 37123., 0., 25757.]\n",
        "anos = [2003, 1991, 1990, 2019, 2006]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "AryIZaBIltpH"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "s8GvEk4HltpI"
      },
      "outputs": [],
      "source": [
        "km = np.array([44410., 5712., 37123., 0., 25757.])\n",
        "anos = np.array([2003, 1991, 1990, 2019, 2006])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "aUnYV7OultpI"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "vg5yZ9IpltpJ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "qn1PUsM9ltpJ"
      },
      "source": [
        "### Operações entre arrays"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "gU_d5aZkltpJ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "U9DXntUEltpK"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "n0rPxgY1ltpL"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "o4-gsGICltpN"
      },
      "source": [
        "### Operações com arrays de duas dimensões"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "VT71Pbb3ltpN"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "bgDe00q8ltpO"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "jIQU2ugKltpP"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "dsgz-E5ZltpP"
      },
      "source": [
        "![1410-img01.png](https://caelum-online-public.s3.amazonaws.com/1410-pythondatascience/01/1410-img01.png)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "imANn6HultpQ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "Nkp9ljkvltpQ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "njJ2z3HJltpR"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "4CAwtS0-ltpR"
      },
      "source": [
        "# 5.3 Seleções com arrays Numpy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "QDAT1vODltpS"
      },
      "source": [
        "![1410-img01.png](https://caelum-online-public.s3.amazonaws.com/1410-pythondatascience/01/1410-img01.png)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "nZpPGS2TltpS"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "b--BIPcOltpT"
      },
      "source": [
        "![1410-img02.png](https://caelum-online-public.s3.amazonaws.com/1410-pythondatascience/01/1410-img02.png)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "86-hOHa7ltpT"
      },
      "source": [
        "### Indexação \n",
        "\n",
        "<font color=red>**Observação:**</font> A indexação tem origem no zero."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "mr0Q_X0JltpT"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "VxiR_IgdltpU"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "xGDomIyAltpU"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "QEO5Za5PltpV"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "rvkeMK8KltpV"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "X8c-lJRJltpW"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "fCWUSI1zltpZ"
      },
      "source": [
        "## <font color=green>**Dica:**</font>\n",
        "### *ndarray[ linha ][ coluna ]* ou *ndarray[ linha, coluna ]*"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "Nxc3uY-ZltpZ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "xp8ByjualtpZ"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "7osmTUC4ltpa"
      },
      "source": [
        " ### Fatiamentos\n",
        " \n",
        "A sintaxe para realizar fatiamento em um array Numpy é $i : j : k$ onde $i$ é o índice inicial, $j$ é o índice de parada, e $k$ é o indicador de passo ($k\\neq0$)\n",
        " \n",
        "<font color=red>**Observação:**</font> Nos fatiamentos (*slices*) o item com índice i é **incluído** e o item com índice j **não é incluído** no resultado."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "HEx4TbNlltpa"
      },
      "source": [
        "![1410-img01.png](https://caelum-online-public.s3.amazonaws.com/1410-pythondatascience/01/1410-img01.png)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "tlaD1SENltpb"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "vXLIO1cVltpc"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "kYLgsQcHltpc"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "H2MJpIasltpd"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "YVzf4fNCltpe"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "bPyQsUFPltpf"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "IRxfixG-ltpg"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "wfoJ84haltph"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "UeejSXUAltph"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "-fW4EXIqltpi"
      },
      "source": [
        "### Indexação com array booleano\n",
        "\n",
        "<font color=red>**Observação:**</font> Seleciona um grupo de linhas e colunas segundo os rótulos ou um array booleano."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "MgmH-rCSltpi"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "HN1i-BlLltpj"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "iXJa9tL4ltpj"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "54gH6X5eltpk"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "F3z6zMELltpk"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "pk8A68z1ltpl"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "WUVMN29_ltpm"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Acw1DffHltpn"
      },
      "source": [
        "# 5.4 Atributos e métodos de arrays Numpy"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RBnSne6Eltpo"
      },
      "source": [
        "### Atributos\n",
        "\n",
        "https://numpy.org/doc/1.16/reference/arrays.ndarray.html#array-attributes"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "stjvD6m8ltpo"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "uKqPxg2Zltpo"
      },
      "source": [
        "## *ndarray.shape*\n",
        "\n",
        "Retorna uma tupla com as dimensões do array."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "gmaZhF04ltpp"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "XaY6oXkmltpp"
      },
      "source": [
        "## *ndarray.ndim*\n",
        "\n",
        "Retorna o número de dimensões do array."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "inJ4HDjaltpq"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "ESgVt5xOltpq"
      },
      "source": [
        "## *ndarray.size*\n",
        "\n",
        "Retorna o número de elementos do array."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "BWr4efoiltpq"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Ox8JlBM3ltpr"
      },
      "source": [
        "## *ndarray.dtype*\n",
        "\n",
        "Retorna o tipo de dados dos elementos do array."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "npiL84Vfltpu"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "j7uPN16oltpv"
      },
      "source": [
        "## *ndarray.T*\n",
        "\n",
        "Retorna o array transposto, isto é, converte linhas em colunas e vice versa."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "bLjrrx56ltpv"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "5A9SlJQvltpw"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "e9r6ryTrltpw"
      },
      "source": [
        "### Métodos\n",
        "\n",
        "https://numpy.org/doc/1.16/reference/arrays.ndarray.html#array-methods"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "SR9KYy-0ltpw"
      },
      "source": [
        "## *ndarray.tolist()*\n",
        "\n",
        "Retorna o array como uma lista Python."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "C2aTAwOXltpw"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "bHxcxugPltpx"
      },
      "source": [
        "## *ndarray.reshape(shape[, order])*\n",
        "\n",
        "Retorna um array que contém os mesmos dados com uma nova forma."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "lwESxO71ltpx"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "sh9poyfzltpy"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "5332Xu8-ltpy"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "2RoZvbgHltpz"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "6q0dJZ-dltp0"
      },
      "outputs": [],
      "source": [
        "km = [44410, 5712, 37123, 0, 25757]\n",
        "anos = [2003, 1991, 1990, 2019, 2006]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "bs56aGrkltp0"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "s_GkTk2fltp1"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "xodm8DVZltp1"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Tdj5iArbltp2"
      },
      "source": [
        "## *ndarray.resize(new_shape[, refcheck])*\n",
        "\n",
        "Altera a forma e o tamanho do array."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "vB2zxCDtltp2"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "IMv0m4Multp2"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "wpAi9928ltp3"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "CJyuKqaFltp3"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "bj_iPZAultp4"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "GPSk7Q_Dltp4"
      },
      "source": [
        "# 5.5 Estatísticas com arrays Numpy\n",
        "\n",
        "https://numpy.org/doc/1.16/reference/arrays.ndarray.html#calculation\n",
        "\n",
        "e\n",
        "\n",
        "https://numpy.org/doc/1.16/reference/routines.statistics.html\n",
        "\n",
        "e\n",
        "\n",
        "https://numpy.org/doc/1.16/reference/routines.math.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "RH2u1orXltp5"
      },
      "outputs": [],
      "source": [
        "anos = np.loadtxt(fname = \"carros-anos.txt\", dtype = int)\n",
        "km = np.loadtxt(fname = \"carros-km.txt\")\n",
        "valor = np.loadtxt(fname = \"carros-valor.txt\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "wbITF7r6ltp5"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "U_x3SOVDltp7"
      },
      "source": [
        "https://numpy.org/doc/1.16/reference/generated/numpy.column_stack.html"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "wefxl-XBltp8"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "OzDTTmj8ltp_",
        "scrolled": true
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Me6yUU_RltqA"
      },
      "source": [
        "## *np.mean()*\n",
        "\n",
        "Retorna a média dos elementos do array ao longo do eixo especificado."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "MNEKcP38ltqA"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "sekHQ84zltqB"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "RpyETIVSltqC"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "_-kpcTI8ltqD",
        "scrolled": true
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "71jViVBUltqE"
      },
      "source": [
        "## *np.std()*\n",
        "\n",
        "Retorna o desvio padrão dos elementos do array ao longo do eixo especificado."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "lEwUbPx2ltqE",
        "scrolled": true
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "JTUH-vAeltqG"
      },
      "source": [
        "## *ndarray.sum()*\n",
        "\n",
        "Retorna a soma dos elementos do array ao longo do eixo especificado."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "jIi3yoaWltqG"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "X3QYbdYLltqH"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "WbBD5ixaltqH"
      },
      "source": [
        "## *np.sum()*\n",
        "\n",
        "Retorna a soma dos elementos do array ao longo do eixo especificado."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "omB6kgWgltqH"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "LiD4G3kQltqI"
      },
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {},
        "colab_type": "code",
        "id": "kpakpnntltqJ"
      },
      "outputs": [],
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "name": "Python_Data_Science_Numpy.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.10.4 64-bit",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.10.4"
    },
    "vscode": {
      "interpreter": {
        "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
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  },
  "nbformat": 4,
  "nbformat_minor": 0
}