projeto_album_one_piece.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "projeto-album-one-piece.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "HxKBrGOtZr61",
        "PgVk9DWvmjsj",
        "e7QRuWoXKhdU"
      ],
      "authorship_tag": "ABX9TyNRk9mLmbscM3egP26PwvGi",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/massilva/dominando-data-science/blob/main/projeto_album_one_piece.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e_5dr4PlOXfU"
      },
      "source": [
        "## PROJETO: Álbum One Piece 2021\n",
        "\n",
        "Total de cromos: **212**.<br/>\n",
        "Preço do livro ilustrado capa brochura: **R\\$ 10,00**.<br/>\n",
        "Envelope com 4 cromos: **R$ 4,00**.  \n",
        "\n",
        "### SUPOSIÇÕES\n",
        "\n",
        "Todas as figurinhas tem igual probabilidade de serem sorteradas.\n",
        "Um pacotinho é comprado por vez até que se complete o álbum.\n",
        "\n",
        "### ALGORITMO\n",
        "\n",
        "Comprar um pacotinho de figurinhas (4 figurinhas cada, que podem ser repetidas);\n",
        "\n",
        "Colar no álbum e verificar se o álbum está completo;\n",
        "\n",
        "Caso esteja incompleto, comprar mais um pacotinho, caso contrário, terminar.\n",
        "\n",
        "### PERGUNTAS\n",
        "\n",
        "1. Qual o valor médio investido para completar o álbum nessas condições?\n",
        "2. Quantos pacotes são necessários comprar, em média, para completar o álbum?\n",
        "3. Qual é a distribuição empírica do valor investido para completar o álbum?\n",
        "4. Qual a probabilidade de se gastar menos que R$1500,00 para completar o álbum?\n",
        "5. Qual a probabilidade de se gastar mais do que a média para completar o álbum?\n",
        "6. Qual é um intervalo de confiança de 95% para o gasto ao se completar o álbum?\n",
        "7. Qual o valor médio gasto caso se esteja completando o álbum com mais um amigo?\n",
        "8. Qual o valor médio gasto caso se esteja completando o álbum com mais dois amigos?\n",
        "9. Quantas vezes saiu a figurinha mais repetida, em média ?\n",
        "10. Em média, quantas figurinhas não se repetem ao completar o album ?\n",
        "11. Faça um gráfico de porcentagem completa esperada em função do número de pacotes comprados.\n",
        "\n",
        "### Exercícios\n",
        "\n",
        "**Exercício 1**\n",
        "\n",
        "Considere um balde cuja base possui raio $r_1$ e altura igual ao diâmetro da base. Considere também uma esfera de raio $r_2$ cheia de água. Faça um programa que verifique se o volume da esfera cabe no balde, dados os valores de $r_1$ e $r_2$.\n",
        "\n",
        "**Exercício 2**\n",
        "\n",
        "Crie uma função que simule o jogo do jokempô, isto é, dada a entrada de dois jogadores, retorne a indicação de qual deles venceu.\n",
        "\n",
        "**Exercício 3**\n",
        "\n",
        "Faça um programa que simule uma slot machine. Uma slot machine é uma máquina muito comum em cassinos. A pessoa puxa uma alavanca e aparecem na tela 3 símbolos aleatoriamente, de uma lista com diversos deles. Se os símbolos forem iguais, então a pessoa ganha. A pessoa entrar com um tanto escolhido de fichas, e joga até que acabe. Quando o programa terminar, uma mensagem resumindo os totais que ela ganhou deve ser exibida\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HxKBrGOtZr61"
      },
      "source": [
        "### Algoritmo"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bb7EcAPuZwi8"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "total_figurinhas = 7#212\n",
        "preco_album = 10.0\n",
        "preco_envelope = 4.0\n",
        "fig_no_envelope = 4\n",
        "\n",
        "def simula_album():\n",
        "  album = np.zeros(total_figurinhas)\n",
        "  album_incompleto = True\n",
        "  faixa = np.arange(0, total_figurinhas)\n",
        "  qtd_pacotes = 0\n",
        "\n",
        "  while album_incompleto:\n",
        "    pacote = np.random.choice(faixa, size = fig_no_envelope)\n",
        "    qtd_pacotes += 1\n",
        "\n",
        "    for figurinha in pacote:\n",
        "      album[figurinha] += 1\n",
        "\n",
        "    album_incompleto = not np.all(album)\n",
        "\n",
        "  return qtd_pacotes * preco_envelope + preco_album, qtd_pacotes"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PgVk9DWvmjsj"
      },
      "source": [
        "### Perguntas"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0RfHI0PGmrK7",
        "outputId": "40e1ad41-dcd7-4c37-cfaa-21c7bab3923f"
      },
      "source": [
        "simulacoes, resultados, pacotes = 100, [], 0\n",
        "\n",
        "for _ in range(simulacoes):\n",
        "  custo, qtd_pacotes = simula_album()\n",
        "  resultados.append(custo);\n",
        "  pacotes += qtd_pacotes\n",
        "\n",
        "resultados = np.array(resultados)\n",
        "media = resultados.mean()\n",
        "print(f'01. Valor médio investido: {media}')\n",
        "print(f'02. Qtds. de pacotes: {pacotes / simulacoes}')\n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1. Valor médio investido: 29.32\n",
            "2. Qtds. de pacotes: 4.83\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "tqISgeRXyttb",
        "outputId": "b88f62d7-7081-4de8-ab48-17a362b8374a"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "plt.hist(resultados, bins = 20, density = True, color = 'royalblue', edgecolor = 'black')\n",
        "plt.title('03. Distribuição Empírica do Valor Gasto para Completar o Álbum')\n",
        "plt.show()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8PPAY5NfCRZN",
        "outputId": "cc8f5caa-1bf1-472b-cfe3-7f7d8f8dd59b"
      },
      "source": [
        "prob1 = sum(resultados < 1500) / simulacoes\n",
        "prob2 = sum(resultados > media) / simulacoes\n",
        "\n",
        "print(f'04. A probabilidade de se gastar menos de 1500 é: {prob1 * 100:.2f}%')\n",
        "print(f'05. A probabilidade de se gastar mais do que a média é: {prob2 * 100:.2f}%')"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4. A probabilidade de se gastar menos de 1500 é: 100.00%\n",
            "5. A probabilidade de se gastar mais do que a média é: 48.00%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Vg4h_jljDgDb",
        "outputId": "3ed1bf09-d5e4-4c80-ad3b-6e92c4e27090"
      },
      "source": [
        "qts = np.quantile(resultados, [0.025, 0.975])\n",
        "print(f'06. O intervalo de confiança de 95% para o gasto total é ({qts[0]:.2f}, {qts[1]:.2f})')"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "6. O intervalo de confiança de 95% para o gasto total é (22.00, 42.00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OkOuycLuI1h4",
        "outputId": "bb3edbf9-2ca7-4c69-87ca-dec13434b91c"
      },
      "source": [
        "def simula_album_2(qtd_albuns=1):\n",
        "  album = np.zeros(total_figurinhas).astype(int)\n",
        "  album_incompleto = True\n",
        "  faixa = np.arange(0, total_figurinhas)\n",
        "  qtd_pacotes = 0\n",
        "\n",
        "  while album_incompleto:\n",
        "    pacote = np.random.choice(faixa, size = fig_no_envelope)\n",
        "    qtd_pacotes += 1\n",
        "\n",
        "    for figurinha in pacote:\n",
        "      album[figurinha] += 1\n",
        "\n",
        "    album_incompleto = not np.all(album)\n",
        "\n",
        "  gasto = qtd_pacotes * preco_envelope + preco_album * qtd_albuns\n",
        "\n",
        "  # gasto por album\n",
        "  return gasto / qtd_albuns, album\n",
        "\n",
        "\n",
        "def simulacao_albuns(qtd, simulacoes = 1000):\n",
        "    return [simula_album_2(qtd) for _ in range(simulacoes)]\n",
        "\n",
        "total_album = np.array([])\n",
        "\n",
        "for qtd in range(2, 4):\n",
        "  simulacao = simulacao_albuns(qtd = qtd, simulacoes = 2)\n",
        "  medias, albuns = zip(*simulacao)\n",
        "  media = np.array(medias).mean()\n",
        "  print(f'0{5 + qtd}. Custo médio entre {qtd} amigos: {round(media, 2)}')\n",
        "\n",
        "  album_somado = np.array(sum(albuns))\n",
        "  total_album = total_album + album_somado if total_album.size else album_somado\n",
        "\n",
        "mais = total_album.max()\n",
        "mais_repete = np.where(total_album == mais)[0]\n",
        "print(f'09. A(s) figurinha(s) que mais se repete é {mais_repete} #{mais}')\n",
        "\n",
        "menos = total_album.min()\n",
        "menos_repete = np.where(total_album == menos)[0]\n",
        "print(f'10. A(s) figurinha(s) que menos se repete é {menos_repete} #{menos}')\n"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "07. Custo médio entre 2 amigos: 19.0\n",
            "08. Custo médio entre 3 amigos: 19.33\n",
            "09. A(s) figurinha(s) que mais se repete é [4] #20\n",
            "10. A(s) figurinha(s) que menos se repete é [3] #8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e7QRuWoXKhdU"
      },
      "source": [
        "### Exercícios"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nVG26ZbdKpt5",
        "outputId": "6cfccf5f-7fcc-48d4-d32f-95fae45581f7"
      },
      "source": [
        "import math\n",
        "\n",
        "def esfera_cabe_no_balde(r1, r2, verboso=False):\n",
        "  altura = 2 * r1\n",
        "  volume_balde = math.pi * r1 ** 2 * altura\n",
        "  volume_esfera =  math.pi * r2 ** 3 * 4 / 3\n",
        "\n",
        "  if verboso:\n",
        "    print(f'vol. balde: {volume_balde}, vol. esfera: {volume_esfera}, razão: {volume_balde / volume_esfera}')\n",
        "\n",
        "  return volume_balde / volume_esfera >= 1\n",
        "\n",
        "print('EX01')\n",
        "'''\n",
        "Exercício 1\n",
        "Considere um balde cuja base possui raio $r_1$ e altura igual ao diâmetro da base. Considere também uma esfera de raio $r_2$ cheia de água. Faça um programa que verifique se o volume da esfera cabe no balde, dados os valores de $r_1$ e $r_2$.\n",
        "'''\n",
        "\n",
        "r1, r2 = 1, 1\n",
        "print(f'R1: {r1}, R2: {r2}: {esfera_cabe_no_balde(r1, r2)}')\n",
        "\n",
        "def valida(jogador1, jogada1, jogador2, jogada2):\n",
        "  if jogador1.lower() == jogada1 and jogador2.lower() == jogada2:\n",
        "    return jogador1\n",
        "\n",
        "  if jogador1.lower() == jogada2 and jogador2.lower() == jogada1:\n",
        "    return jogador2\n",
        "\n",
        "  return None\n",
        "\n",
        "print()\n",
        "print('EX02')\n",
        "'''\n",
        "Exercício 2\n",
        "Crie uma função que simule o jogo do jokempô, isto é, dada a entrada de dois jogadores, retorne a indicação de qual deles venceu.\n",
        "'''\n",
        "\n",
        "jogadas = ['pedra', 'tesoura', 'papel']\n",
        "ganha_de = {'pedra': 'tesoura', 'tesoura': 'papel', 'papel': 'pedra'}\n",
        "mensagens = {\n",
        "  'pedra': 'A pedra amassou a tesoura !',\n",
        "  'tesoura': 'A tesoura cortou o papel !',\n",
        "  'papel': 'O papel embrulhou a pedra !',\n",
        "}\n",
        "\n",
        "def jokempo(jogador1, jogador2):\n",
        "  jogadores = [jogador1.lower(), jogador2.lower()]\n",
        "  jogada1, jogada2 = jogadores\n",
        "\n",
        "  for jogada in jogadas:\n",
        "    vencedor = valida(jogador1, jogada, jogador2, ganha_de[jogada]) \n",
        "    if vencedor:\n",
        "      return vencedor == jogador1 and 'Jogador 1' or 'Jogador 2', mensagens[jogada]\n",
        "\n",
        "  return None, None\n",
        "\n",
        "for jogada1 in jogadas:\n",
        "  for jogada2 in jogadas:\n",
        "    jogador, mensagem = jokempo(jogada1, jogada2)\n",
        "    mensagem_jogada = f'`{jogada1}` VS `{jogada2}`'\n",
        "    if jogador:\n",
        "      print(f'{mensagem_jogada}: O {jogador} venceu, {mensagem}')\n",
        "    else:\n",
        "      print(f'{mensagem_jogada}: Houve empate')\n",
        "\n",
        "print()\n",
        "print('EX03')\n",
        "'''\n",
        "Exercício 3\n",
        "Faça um programa que simule uma slot machine. Uma slot machine é uma máquina muito comum em cassinos. \n",
        "A pessoa puxa uma alavanca e aparecem na tela 3 símbolos aleatoriamente, de uma lista com diversos deles. \n",
        "Se os símbolos forem iguais, então a pessoa ganha. A pessoa entrar com um tanto escolhido de fichas, e \n",
        "joga até que acabe. Quando o programa terminar, uma mensagem resumindo os totais que ela ganhou deve ser exibida\n",
        "'''\n",
        "import random, string\n",
        "\n",
        "simbolos = list(string.ascii_lowercase)\n",
        "\n",
        "def puxa_alavanca():\n",
        "  rodada = random.choices(simbolos, k=3)\n",
        "  return [1 for item in rodada if rodada[0] == item]\n",
        "\n",
        "fichas = 100\n",
        "ganhos = 0\n",
        "\n",
        "for _ in range(fichas):\n",
        "  resultado = puxa_alavanca()\n",
        "  ganhos += len(resultado) == 3 and 1 or 0\n",
        "\n",
        "print(f'De {fichas} ganhou {ganhos} vezes ({ganhos / fichas * 100}%)')\n"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "EX01\n",
            "R1: 1, R2: 1: True\n",
            "\n",
            "EX02\n",
            "`pedra` VS `pedra`: Houve empate\n",
            "`pedra` VS `tesoura`: O Jogador 1 venceu, A pedra amassou a tesoura !\n",
            "`pedra` VS `papel`: O Jogador 2 venceu, O papel embrulhou a pedra !\n",
            "`tesoura` VS `pedra`: O Jogador 2 venceu, A pedra amassou a tesoura !\n",
            "`tesoura` VS `tesoura`: Houve empate\n",
            "`tesoura` VS `papel`: O Jogador 1 venceu, A tesoura cortou o papel !\n",
            "`papel` VS `pedra`: O Jogador 1 venceu, O papel embrulhou a pedra !\n",
            "`papel` VS `tesoura`: O Jogador 2 venceu, A tesoura cortou o papel !\n",
            "`papel` VS `papel`: Houve empate\n",
            "\n",
            "EX03\n",
            "De 100 ganhou 1 vezes (1.0%)\n"
          ]
        }
      ]
    }
  ]
}