ML-Fundamentos.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Aprendizado de Máquina - Preparação dos dados\n",
        "Caderno de Desenvolvimento <br>\n",
        "Curadoria de [Rafael Barbosa](https://www.linkedin.com/in/barbosa89/)\n",
        "\n",
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WCQi-s0Hpd5V"
      },
      "source": [
        "Preparar dataframe para aprendizado de máquina."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "lblH8kIXzPZZ"
      },
      "outputs": [],
      "source": [
        "# Livrarias utilizadas\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import seaborn as sns"
      ]
    },
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      "execution_count": 3,
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        "colab": {
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              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
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              "      <td>39.1</td>\n",
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              "      <td>3750.0</td>\n",
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            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "3  Adelie  Torgersen             NaN            NaN                NaN   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "\n",
              "   body_mass_g     sex  \n",
              "0       3750.0    Male  \n",
              "1       3800.0  Female  \n",
              "2       3250.0  Female  \n",
              "3          NaN     NaN  \n",
              "4       3450.0  Female  "
            ]
          },
          "execution_count": 3,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Carregando a base de dados\n",
        "df = sns.load_dataset('penguins')\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HrTLgE0tki6P"
      },
      "source": [
        "## **1. Valores nulos**"
      ]
    },
    {
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              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-3ca19eaf-b888-4bbb-8705-9e87691adeb9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3ca19eaf-b888-4bbb-8705-9e87691adeb9')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-3ca19eaf-b888-4bbb-8705-9e87691adeb9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
              "\n",
              "   body_mass_g     sex  \n",
              "0       3750.0    Male  \n",
              "1       3800.0  Female  \n",
              "2       3250.0  Female  \n",
              "4       3450.0  Female  \n",
              "5       3650.0    Male  "
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Tratando os valores faltantes\n",
        "# Para a variável resposta, vamos descartar as linhas com valores faltantes\n",
        "df = df.dropna(subset=['species'])\n",
        "\n",
        "# Para atributos categóricos, vamos descartar as linhas com valores faltantes\n",
        "df = df.dropna(subset=['sex', 'island'])\n",
        "\n",
        "# Para atributos numéricos, vamos preencher os valores faltantes com a média\n",
        "for col in ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']:\n",
        "    df[col] = df[col].fillna(df[col].mean())\n",
        "\n",
        "# Verificando e removendo dados redundantes\n",
        "df = df.drop_duplicates()\n",
        "\n",
        "# Tratando outliers\n",
        "# Aqui, vamos considerar como outliers valores que estão 3 desvios padrão distante da média\n",
        "for col in ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']:\n",
        "    df = df[np.abs(df[col]-df[col].mean()) <= (3*df[col].std())]\n",
        "\n",
        "df.head()\n",
        "# Para o desbalanceamento dos dados, você pode usar a técnica de pesos na hora de treinar o modelo. Isso vai depender do algoritmo que você vai utilizar.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9YtwYCuk8SPU"
      },
      "source": [
        "## **2. Variáveis numéricas**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7tIjNOs8q6aZ"
      },
      "source": [
        "Identifique as variáveis numéricas e crie uma nova coluna **padronizando** seus valores. A nova coluna deve ter o mesmo nome da coluna original acrescidade de \"*_std*\"."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QchO_rKR8tyx"
      },
      "source": [
        "> **Nota**: Você não deve tratar a variável resposta."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "IwTTh4VKkdKN",
        "outputId": "e9e979e2-4a94-4aa4-b061-d4e4044e5c50"
      },
      "outputs": [
        {
          "data": {
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              "      <th></th>\n",
              "      <th>species</th>\n",
              "      <th>island</th>\n",
              "      <th>bill_length_mm</th>\n",
              "      <th>bill_depth_mm</th>\n",
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              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.1</td>\n",
              "      <td>18.7</td>\n",
              "      <td>181.0</td>\n",
              "      <td>3750.0</td>\n",
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              "      <td>195.0</td>\n",
              "      <td>3250.0</td>\n",
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              "      <td>-0.425733</td>\n",
              "      <td>-1.188572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
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              "      <td>Torgersen</td>\n",
              "      <td>36.7</td>\n",
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              "      <td>-0.568429</td>\n",
              "      <td>-0.940192</td>\n",
              "    </tr>\n",
              "    <tr>\n",
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              "      <td>Adelie</td>\n",
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              "      <td>39.3</td>\n",
              "      <td>20.6</td>\n",
              "      <td>190.0</td>\n",
              "      <td>3650.0</td>\n",
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              "      <td>1.744400</td>\n",
              "      <td>-0.782474</td>\n",
              "      <td>-0.691811</td>\n",
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              "    }\n",
              "  }\n",
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              "\n",
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              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-db4798d5-9c97-4520-820b-df4642758e9a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
              "\n",
              "   body_mass_g     sex  bill_length_mm_std  bill_depth_mm_std  \\\n",
              "0       3750.0    Male           -0.894695           0.779559   \n",
              "1       3800.0  Female           -0.821552           0.119404   \n",
              "2       3250.0  Female           -0.675264           0.424091   \n",
              "4       3450.0  Female           -1.333559           1.084246   \n",
              "5       3650.0    Male           -0.858123           1.744400   \n",
              "\n",
              "   flipper_length_mm_std  body_mass_g_std  \n",
              "0              -1.424608        -0.567621  \n",
              "1              -1.067867        -0.505525  \n",
              "2              -0.425733        -1.188572  \n",
              "4              -0.568429        -0.940192  \n",
              "5              -0.782474        -0.691811  "
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# resposta da questão 1.2\n",
        "\n",
        "# Identificando as colunas numéricas\n",
        "num_cols = ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g']\n",
        "\n",
        "# Padronizando as colunas numéricas e criando novas colunas com os valores padronizados\n",
        "for col in num_cols:\n",
        "    media = df[col].mean()\n",
        "    desvio_padrao = df[col].std()\n",
        "    df[col + '_std'] = df[col].apply(lambda x: (x - media) / desvio_padrao)\n",
        "\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TTh7w8rgkznY"
      },
      "source": [
        "## **3. Variáveis categóricas**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "clBerimQs2PY"
      },
      "source": [
        "Identifique as variáveis categóricas nominais e ordinais, crie uma nova coluna aplicando a técnica correta de conversão a seus valores. A nova coluna deve ter o mesmo nome da coluna original acrescidade de \"*_nom*\" ou \"*_ord*\"."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BqpAVY109BWA"
      },
      "source": [
        "> **Nota**: Você não deve tratar a variável resposta."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "fohdVuLzkdKP",
        "outputId": "5e9b6290-86fe-4ea8-8f15-ba1703072b09"
      },
      "outputs": [
        {
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              "      <th></th>\n",
              "      <th>species</th>\n",
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              "      <th>sex_nom</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.1</td>\n",
              "      <td>18.7</td>\n",
              "      <td>181.0</td>\n",
              "      <td>3750.0</td>\n",
              "      <td>Male</td>\n",
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              "    </tr>\n",
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              "      <td>Adelie</td>\n",
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              "      <td>17.4</td>\n",
              "      <td>186.0</td>\n",
              "      <td>3800.0</td>\n",
              "      <td>Female</td>\n",
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              "      <td>-0.505525</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>40.3</td>\n",
              "      <td>18.0</td>\n",
              "      <td>195.0</td>\n",
              "      <td>3250.0</td>\n",
              "      <td>Female</td>\n",
              "      <td>-0.675264</td>\n",
              "      <td>0.424091</td>\n",
              "      <td>-0.425733</td>\n",
              "      <td>-1.188572</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>36.7</td>\n",
              "      <td>19.3</td>\n",
              "      <td>193.0</td>\n",
              "      <td>3450.0</td>\n",
              "      <td>Female</td>\n",
              "      <td>-1.333559</td>\n",
              "      <td>1.084246</td>\n",
              "      <td>-0.568429</td>\n",
              "      <td>-0.940192</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>Torgersen</td>\n",
              "      <td>39.3</td>\n",
              "      <td>20.6</td>\n",
              "      <td>190.0</td>\n",
              "      <td>3650.0</td>\n",
              "      <td>Male</td>\n",
              "      <td>-0.858123</td>\n",
              "      <td>1.744400</td>\n",
              "      <td>-0.782474</td>\n",
              "      <td>-0.691811</td>\n",
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              "    async function quickchart(key) {\n",
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              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "  species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
              "0  Adelie  Torgersen            39.1           18.7              181.0   \n",
              "1  Adelie  Torgersen            39.5           17.4              186.0   \n",
              "2  Adelie  Torgersen            40.3           18.0              195.0   \n",
              "4  Adelie  Torgersen            36.7           19.3              193.0   \n",
              "5  Adelie  Torgersen            39.3           20.6              190.0   \n",
              "\n",
              "   body_mass_g     sex  bill_length_mm_std  bill_depth_mm_std  \\\n",
              "0       3750.0    Male           -0.894695           0.779559   \n",
              "1       3800.0  Female           -0.821552           0.119404   \n",
              "2       3250.0  Female           -0.675264           0.424091   \n",
              "4       3450.0  Female           -1.333559           1.084246   \n",
              "5       3650.0    Male           -0.858123           1.744400   \n",
              "\n",
              "   flipper_length_mm_std  body_mass_g_std  island_nom  sex_nom  \n",
              "0              -1.424608        -0.567621           2        1  \n",
              "1              -1.067867        -0.505525           2        0  \n",
              "2              -0.425733        -1.188572           2        0  \n",
              "4              -0.568429        -0.940192           2        0  \n",
              "5              -0.782474        -0.691811           2        1  "
            ]
          },
          "execution_count": 7,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# resposta da questão 1.3\n",
        "\n",
        "# Identificando as colunas categóricas nominais\n",
        "nom_cols = ['island', 'sex']\n",
        "\n",
        "# Aplicando a técnica de conversão para as colunas nominais\n",
        "for col in nom_cols:\n",
        "    df[col + '_nom'] = df[col].astype('category').cat.codes\n",
        "\n",
        "# Identificando as colunas categóricas ordinais\n",
        "# Neste caso, vamos assumir que não temos nenhuma variável ordinal.\n",
        "# Mas se tivéssemos, poderíamos fazer algo assim:\n",
        "# ord_cols = ['ord_col_example']\n",
        "# for col in ord_cols:\n",
        "#     df[col + '_ord'] = df[col].map({'Low': 1, 'Medium': 2, 'High': 3})\n",
        "\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AvkcQD9E9DGE"
      },
      "source": [
        "## **4. Limpeza**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D03kCy8-9DGE"
      },
      "source": [
        "Descarte as colunas originais e mantenha apenas a variável resposta e as variáveis preditivas com o sufixo *_std*\", *_nom*\" e \"*_ord*\"."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
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          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "TuEOO6009DGE",
        "outputId": "a04692e1-89e9-42f6-fc5c-1af1f5cf396b"
      },
      "outputs": [
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              "      <th></th>\n",
              "      <th>species</th>\n",
              "      <th>bill_length_mm_std</th>\n",
              "      <th>bill_depth_mm_std</th>\n",
              "      <th>flipper_length_mm_std</th>\n",
              "      <th>body_mass_g_std</th>\n",
              "      <th>island_nom</th>\n",
              "      <th>sex_nom</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>-0.894695</td>\n",
              "      <td>0.779559</td>\n",
              "      <td>-1.424608</td>\n",
              "      <td>-0.567621</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>-0.821552</td>\n",
              "      <td>0.119404</td>\n",
              "      <td>-1.067867</td>\n",
              "      <td>-0.505525</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>-0.675264</td>\n",
              "      <td>0.424091</td>\n",
              "      <td>-0.425733</td>\n",
              "      <td>-1.188572</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>-1.333559</td>\n",
              "      <td>1.084246</td>\n",
              "      <td>-0.568429</td>\n",
              "      <td>-0.940192</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Adelie</td>\n",
              "      <td>-0.858123</td>\n",
              "      <td>1.744400</td>\n",
              "      <td>-0.782474</td>\n",
              "      <td>-0.691811</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  <style>\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "      background-color: #3B4455;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
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              "  </style>\n",
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              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-69307c25-3f6d-4aef-9c32-2ac021f2b96d button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-69307c25-3f6d-4aef-9c32-2ac021f2b96d');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "<div id=\"df-e2b199be-0744-4de4-9fae-51ab05dbd1d1\">\n",
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              "            title=\"Suggest charts.\"\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-e2b199be-0744-4de4-9fae-51ab05dbd1d1 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "  species  bill_length_mm_std  bill_depth_mm_std  flipper_length_mm_std  \\\n",
              "0  Adelie           -0.894695           0.779559              -1.424608   \n",
              "1  Adelie           -0.821552           0.119404              -1.067867   \n",
              "2  Adelie           -0.675264           0.424091              -0.425733   \n",
              "4  Adelie           -1.333559           1.084246              -0.568429   \n",
              "5  Adelie           -0.858123           1.744400              -0.782474   \n",
              "\n",
              "   body_mass_g_std  island_nom  sex_nom  \n",
              "0        -0.567621           2        1  \n",
              "1        -0.505525           2        0  \n",
              "2        -1.188572           2        0  \n",
              "4        -0.940192           2        0  \n",
              "5        -0.691811           2        1  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Criando uma lista com os nomes das colunas originais\n",
        "original_cols = ['bill_length_mm', 'bill_depth_mm', 'flipper_length_mm', 'body_mass_g', 'island', 'sex']\n",
        "\n",
        "# Descartando as colunas originais\n",
        "df = df.drop(columns=original_cols)\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "waxn4B2UDHyl"
      },
      "source": [
        "---"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}