Pokemanos.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rikcav/pokemanos/blob/henrique/Pokemanos.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3bb26880-0b40-4a7d-a848-d01f0c09e096"
      },
      "source": [
        "#### Importação dos dados"
      ],
      "id": "3bb26880-0b40-4a7d-a848-d01f0c09e096"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "59241f96-f83e-4771-bf47-7598022201f2"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "id": "59241f96-f83e-4771-bf47-7598022201f2"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4cd10100-6322-4b00-9503-2c31604d7d46"
      },
      "outputs": [],
      "source": [
        "pokemon = pd.read_csv('./data/pokemon.csv')\n",
        "colors = pd.read_csv('./data/colors.csv')[['name', 'hex1', 'hex2', 'hex3']]\n",
        "animal_types = pd.read_csv('./data/animal_types.csv')"
      ],
      "id": "4cd10100-6322-4b00-9503-2c31604d7d46"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3bc6833b-3261-4b9f-82d5-4781c0440d7a"
      },
      "source": [
        "#### Tratamento de nulos"
      ],
      "id": "3bc6833b-3261-4b9f-82d5-4781c0440d7a"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3687bbed-df35-4567-859b-9d56eb22e337"
      },
      "outputs": [],
      "source": [
        "pokemon['type2'].fillna(pokemon['type1'], inplace=True)\n",
        "pokemon['height_m'].fillna(pokemon['height_m'].median(), inplace=True)\n",
        "pokemon['percentage_male'].fillna(pokemon['percentage_male'].median(), inplace=True)\n",
        "pokemon['weight_kg'].fillna(pokemon['weight_kg'].median(), inplace=True)"
      ],
      "id": "3687bbed-df35-4567-859b-9d56eb22e337"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b6d0b574-5d38-4703-8f64-64df2d12b491"
      },
      "source": [
        "#### Mescla de tabelas"
      ],
      "id": "b6d0b574-5d38-4703-8f64-64df2d12b491"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "412a0d95-1350-42b9-b967-b1183b2e1e4f"
      },
      "outputs": [],
      "source": [
        "merged_df = pd.merge(pokemon, colors, left_on='name', right_on='name', how='left')\n",
        "merged_df = pd.merge(merged_df,animal_types, left_on='name', right_on='pokemon', how='left')\n",
        "pokemon = merged_df.copy()"
      ],
      "id": "412a0d95-1350-42b9-b967-b1183b2e1e4f"
    },
    {
      "cell_type": "code",
      "source": [
        "df = pokemon[['type1', 'is_legendary']]\n",
        "df[df['type1'] == 'psychic'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mmVIE-w-wP20",
        "outputId": "60435c61-cbbd-4698-fc9c-dfc6cf2f4b74"
      },
      "id": "mmVIE-w-wP20",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "type1    is_legendary\n",
              "psychic  0               36\n",
              "         1               17\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 499
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(pokemon.isna().sum().tolist())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "etp7wOuI2u53",
        "outputId": "c704d45c-82b6-48b8-e32e-0f14f57072a0"
      },
      "id": "etp7wOuI2u53",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 205, 205, 205]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pokemon = pokemon.dropna()"
      ],
      "metadata": {
        "id": "xh3d_0YRx3mS"
      },
      "id": "xh3d_0YRx3mS",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pokemon.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nu12lpIj221O",
        "outputId": "974a28c7-b3f6-4ba9-8afb-e713f47022f7"
      },
      "id": "nu12lpIj221O",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(596, 47)"
            ]
          },
          "metadata": {},
          "execution_count": 502
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "628217e7-9c3b-4bc1-993a-5b8dce809287"
      },
      "source": [
        "#### Tranformação dos hex codes em cores rgb"
      ],
      "id": "628217e7-9c3b-4bc1-993a-5b8dce809287"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0b705bc3-26af-4897-92a5-bd6129d5558a"
      },
      "outputs": [],
      "source": [
        "# Função que transforma HEX em RGB\n",
        "def hex_to_rgb(hex_code):\n",
        "    hex_code = hex_code.lstrip('#')\n",
        "    r = int(hex_code[0:2], 16)\n",
        "    g = int(hex_code[2:4], 16)\n",
        "    b = int(hex_code[4:6], 16)\n",
        "    return r, g, b"
      ],
      "id": "0b705bc3-26af-4897-92a5-bd6129d5558a"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "413f5b6c-8124-4daa-b6df-5c15c6f7ece3"
      },
      "outputs": [],
      "source": [
        "# Criação de novas colunas para as cores RGB\n",
        "pokemon['rgb1'] = pokemon['hex1'].apply(hex_to_rgb)\n",
        "pokemon['rgb2'] = pokemon['hex2'].apply(hex_to_rgb)\n",
        "pokemon['rgb3'] = pokemon['hex3'].apply(hex_to_rgb)"
      ],
      "id": "413f5b6c-8124-4daa-b6df-5c15c6f7ece3"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "02fbb817-4fc2-46fb-a256-9324d69b03a6"
      },
      "outputs": [],
      "source": [
        "# Drop das colunas de HEX\n",
        "pokemon = pokemon.drop(['hex1', 'hex2', 'hex3'], axis=1)"
      ],
      "id": "02fbb817-4fc2-46fb-a256-9324d69b03a6"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "223c8aee-e5c1-47fb-9a75-bf0387b41c0d"
      },
      "outputs": [],
      "source": [
        "# Criação de novas colunas(Red, Green, Blue) para cada cor\n",
        "pokemon['red1'] = pokemon['rgb1'].apply(lambda x: x[0])\n",
        "pokemon['green1'] = pokemon['rgb1'].apply(lambda x: x[1])\n",
        "pokemon['blue1'] = pokemon['rgb1'].apply(lambda x: x[2])\n",
        "\n",
        "pokemon['red2'] = pokemon['rgb2'].apply(lambda x: x[0])\n",
        "pokemon['green2'] = pokemon['rgb2'].apply(lambda x: x[1])\n",
        "pokemon['blue2'] = pokemon['rgb2'].apply(lambda x: x[2])\n",
        "\n",
        "pokemon['red3'] = pokemon['rgb3'].apply(lambda x: x[0])\n",
        "pokemon['green3'] = pokemon['rgb3'].apply(lambda x: x[1])\n",
        "pokemon['blue3'] = pokemon['rgb3'].apply(lambda x: x[2])"
      ],
      "id": "223c8aee-e5c1-47fb-9a75-bf0387b41c0d"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "c87bb69a-83b9-4a94-8d11-7425b03d88c9"
      },
      "outputs": [],
      "source": [
        "# Drop das colunas antigas de RGB\n",
        "pokemon = pokemon.drop(['rgb1','rgb2','rgb3'], axis=1)"
      ],
      "id": "c87bb69a-83b9-4a94-8d11-7425b03d88c9"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0f8cd6de-a44c-46ad-8c53-cddf3d28216d"
      },
      "outputs": [],
      "source": [
        "# Tratamento da coluna capture_rate\n",
        "pokemon['capture_rate'] = pd.to_numeric(pokemon['capture_rate'], errors='coerce')"
      ],
      "id": "0f8cd6de-a44c-46ad-8c53-cddf3d28216d"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1e321254-9baf-4028-9bf8-c4457133b1f2"
      },
      "source": [
        "#### Coisas úteis para visualização de dados"
      ],
      "id": "1e321254-9baf-4028-9bf8-c4457133b1f2"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "f00a20d5-80de-454e-a9a0-4f5f75be33ca"
      },
      "outputs": [],
      "source": [
        "# import matplotlib.pyplot as plt\n",
        "\n",
        "# # pokemon[(pokemon['generation'] == 6)]['type1'].value_counts().plot(kind='pie')\n",
        "# pokemon.groupby('type1')['sp_defense'].mean().plot(kind='bar')"
      ],
      "id": "f00a20d5-80de-454e-a9a0-4f5f75be33ca"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "e8fd150c-0199-444e-ba6f-ad048be72775"
      },
      "outputs": [],
      "source": [
        "# pokemon.groupby('type2')['sp_defense'].mean().plot(kind='bar')"
      ],
      "id": "e8fd150c-0199-444e-ba6f-ad048be72775"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6ff92aa6-4df3-40fd-9a61-5ab26cdecc62"
      },
      "source": [
        "#### Tratamento dos tipos de pokémon"
      ],
      "id": "6ff92aa6-4df3-40fd-9a61-5ab26cdecc62"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "366aa6b2-03ad-4106-839b-1738b88b6177"
      },
      "outputs": [],
      "source": [
        "types = ['water', 'grass', 'fire', 'electric', 'psychic', 'ground', 'poison', 'rock', 'dark', 'fairy', 'dragon', 'ice']\n",
        "pokemon['unique_type'] = pokemon['type1']\n",
        "pokemon = pokemon[pokemon['unique_type'].isin(types)]"
      ],
      "id": "366aa6b2-03ad-4106-839b-1738b88b6177"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "13255af0-eb26-45ff-983d-233120aecb8f"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import LabelEncoder"
      ],
      "id": "13255af0-eb26-45ff-983d-233120aecb8f"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4ed47039-d4af-4b37-8386-cbbafa62d897",
        "outputId": "71ea05e4-d1b6-42b2-a8b2-6508e61879e7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "water       109\n",
              "grass        77\n",
              "fire         45\n",
              "electric     31\n",
              "psychic      26\n",
              "ground       25\n",
              "poison       24\n",
              "rock         20\n",
              "dark         19\n",
              "fairy        13\n",
              "dragon       13\n",
              "ice          10\n",
              "Name: unique_type, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 513
        }
      ],
      "source": [
        "pokemon['unique_type'].value_counts()"
      ],
      "id": "4ed47039-d4af-4b37-8386-cbbafa62d897"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "b37695f6-9583-491a-80a3-5b66d68b08e5"
      },
      "outputs": [],
      "source": [
        "le = LabelEncoder().fit(pokemon['unique_type'])"
      ],
      "id": "b37695f6-9583-491a-80a3-5b66d68b08e5"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d1c905f2-b51d-418e-8915-219995db3e7c",
        "outputId": "2fa6848d-313f-45bf-dbed-61c4d88f4289"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['dark', 'dragon', 'electric', 'fairy', 'fire', 'grass', 'ground',\n",
              "       'ice', 'poison', 'psychic', 'rock', 'water'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 515
        }
      ],
      "source": [
        "le.classes_"
      ],
      "id": "d1c905f2-b51d-418e-8915-219995db3e7c"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "a71c4845-5341-4c4f-b0fd-067027fcbde9"
      },
      "outputs": [],
      "source": [
        "unique_type_tranformed = le.transform(pokemon['unique_type'])"
      ],
      "id": "a71c4845-5341-4c4f-b0fd-067027fcbde9"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eae99570-cc4b-48a3-98eb-571199253c42"
      },
      "outputs": [],
      "source": [
        "# Drop das antigas colunas de tipos 1 e 2\n",
        "pokemon.drop(['type1', 'type2'], axis=1, inplace=True)"
      ],
      "id": "eae99570-cc4b-48a3-98eb-571199253c42"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "996b9e87-6037-4ec7-99e3-c670b345afd0"
      },
      "outputs": [],
      "source": [
        "pokemon['unique_type'] = unique_type_tranformed"
      ],
      "id": "996b9e87-6037-4ec7-99e3-c670b345afd0"
    },
    {
      "cell_type": "code",
      "source": [
        "# pokemon.drop(['specific_type'], axis=1, inplace=True)"
      ],
      "metadata": {
        "id": "Wt_eEv3N5gav"
      },
      "id": "Wt_eEv3N5gav",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### One-hot encode"
      ],
      "metadata": {
        "id": "XN_oevLeyUCv"
      },
      "id": "XN_oevLeyUCv"
    },
    {
      "cell_type": "code",
      "source": [
        "columns_to_hot_encode = ['super_type', 'specific_type']\n",
        "for c in columns_to_hot_encode:\n",
        "  pokemon = pd.get_dummies(pokemon, columns=[c], prefix=c)"
      ],
      "metadata": {
        "id": "ugFQHYGWyaSU"
      },
      "id": "ugFQHYGWyaSU",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pokemon.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PZYoqNjM1Zap",
        "outputId": "42653224-b19c-47d8-aea7-ef01c59af8a9"
      },
      "id": "PZYoqNjM1Zap",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     abilities  against_bug  against_dark  against_dragon  \\\n",
              "0  ['Overgrow', 'Chlorophyll']          1.0           1.0             1.0   \n",
              "1  ['Overgrow', 'Chlorophyll']          1.0           1.0             1.0   \n",
              "2  ['Overgrow', 'Chlorophyll']          1.0           1.0             1.0   \n",
              "3     ['Blaze', 'Solar Power']          0.5           1.0             1.0   \n",
              "4     ['Blaze', 'Solar Power']          0.5           1.0             1.0   \n",
              "\n",
              "   against_electric  against_fairy  against_fight  against_fire  \\\n",
              "0               0.5            0.5            0.5           2.0   \n",
              "1               0.5            0.5            0.5           2.0   \n",
              "2               0.5            0.5            0.5           2.0   \n",
              "3               1.0            0.5            1.0           0.5   \n",
              "4               1.0            0.5            1.0           0.5   \n",
              "\n",
              "   against_flying  against_ghost  against_grass  against_ground  against_ice  \\\n",
              "0             2.0            1.0           0.25             1.0          2.0   \n",
              "1             2.0            1.0           0.25             1.0          2.0   \n",
              "2             2.0            1.0           0.25             1.0          2.0   \n",
              "3             1.0            1.0           0.50             2.0          0.5   \n",
              "4             1.0            1.0           0.50             2.0          0.5   \n",
              "\n",
              "   against_normal  against_poison  against_psychic  against_rock  \\\n",
              "0             1.0             1.0              2.0           1.0   \n",
              "1             1.0             1.0              2.0           1.0   \n",
              "2             1.0             1.0              2.0           1.0   \n",
              "3             1.0             1.0              1.0           2.0   \n",
              "4             1.0             1.0              1.0           2.0   \n",
              "\n",
              "   against_steel  against_water  attack  base_egg_steps  base_happiness  \\\n",
              "0            1.0            0.5      49            5120              70   \n",
              "1            1.0            0.5      62            5120              70   \n",
              "2            1.0            0.5     100            5120              70   \n",
              "3            0.5            2.0      52            5120              70   \n",
              "4            0.5            2.0      64            5120              70   \n",
              "\n",
              "   base_total  capture_rate   classfication  defense  experience_growth  \\\n",
              "0         318            45    Seed Pokémon       49            1059860   \n",
              "1         405            45    Seed Pokémon       63            1059860   \n",
              "2         625            45    Seed Pokémon      123            1059860   \n",
              "3         309            45  Lizard Pokémon       43            1059860   \n",
              "4         405            45   Flame Pokémon       58            1059860   \n",
              "\n",
              "   height_m  hp     japanese_name        name  percentage_male  \\\n",
              "0       0.7  45  Fushigidaneフシギダネ   Bulbasaur             88.1   \n",
              "1       1.0  60   Fushigisouフシギソウ     Ivysaur             88.1   \n",
              "2       2.0  80  Fushigibanaフシギバナ    Venusaur             88.1   \n",
              "3       0.6  39      Hitokageヒトカゲ  Charmander             88.1   \n",
              "4       1.1  58       Lizardoリザード  Charmeleon             88.1   \n",
              "\n",
              "   pokedex_number  sp_attack  sp_defense  speed  weight_kg  generation  \\\n",
              "0               1         65          65     45        6.9           1   \n",
              "1               2         80          80     60       13.0           1   \n",
              "2               3        122         120     80      100.0           1   \n",
              "3               4         60          50     65        8.5           1   \n",
              "4               5         80          65     80       19.0           1   \n",
              "\n",
              "   is_legendary     pokemon  red1  green1  blue1  red2  green2  blue2  red3  \\\n",
              "0             0   Bulbasaur    57     148    148    98     213    180   131   \n",
              "1             0     Ivysaur    90     205    189    32     148    131    49   \n",
              "2             0    Venusaur    32     180    156    90     213    197   255   \n",
              "3             0  Charmander   255     148     65   222      82     57   255   \n",
              "4             0  Charmeleon   205      57     57   255      82     74   255   \n",
              "\n",
              "   green3  blue3  unique_type  super_type_Amphibian Pokémon  \\\n",
              "0     238    197            5                             1   \n",
              "1     123     82            5                             1   \n",
              "2     123    115            5                             1   \n",
              "3     213    123            4                             1   \n",
              "4      65      0            4                             1   \n",
              "\n",
              "   super_type_Arthropod Pokémon  super_type_Avian Pokémon  \\\n",
              "0                             0                         0   \n",
              "1                             0                         0   \n",
              "2                             0                         0   \n",
              "3                             0                         0   \n",
              "4                             0                         0   \n",
              "\n",
              "   super_type_Clitellata Pokémon  super_type_Cnidaria Pokémon  \\\n",
              "0                              0                            0   \n",
              "1                              0                            0   \n",
              "2                              0                            0   \n",
              "3                              0                            0   \n",
              "4                              0                            0   \n",
              "\n",
              "   super_type_Echinoderm Pokémon  super_type_Fish Pokémon  \\\n",
              "0                              0                        0   \n",
              "1                              0                        0   \n",
              "2                              0                        0   \n",
              "3                              0                        0   \n",
              "4                              0                        0   \n",
              "\n",
              "   super_type_Mammalian Pokémon  super_type_Mollusc Pokémon  \\\n",
              "0                             0                           0   \n",
              "1                             0                           0   \n",
              "2                             0                           0   \n",
              "3                             0                           0   \n",
              "4                             0                           0   \n",
              "\n",
              "   super_type_Plant Pokémon  super_type_Reptilian Pokémon  \\\n",
              "0                         0                             0   \n",
              "1                         0                             0   \n",
              "2                         0                             0   \n",
              "3                         0                             0   \n",
              "4                         0                             0   \n",
              "\n",
              "   specific_type_Anglerfish-based  specific_type_Anteater-based  \\\n",
              "0                               0                             0   \n",
              "1                               0                             0   \n",
              "2                               0                             0   \n",
              "3                               0                             0   \n",
              "4                               0                             0   \n",
              "\n",
              "   specific_type_Antlion-based  specific_type_Banana tree-based  \\\n",
              "0                            0                                0   \n",
              "1                            0                                0   \n",
              "2                            0                                0   \n",
              "3                            0                                0   \n",
              "4                            0                                0   \n",
              "\n",
              "   specific_type_Bat-based  specific_type_Bear-based  \\\n",
              "0                        0                         0   \n",
              "1                        0                         0   \n",
              "2                        0                         0   \n",
              "3                        0                         0   \n",
              "4                        0                         0   \n",
              "\n",
              "   specific_type_Bird-based  specific_type_Bivalve-based  \\\n",
              "0                         0                            0   \n",
              "1                         0                            0   \n",
              "2                         0                            0   \n",
              "3                         0                            0   \n",
              "4                         0                            0   \n",
              "\n",
              "   specific_type_Bluebird-based  specific_type_Bovine-based  \\\n",
              "0                             0                           0   \n",
              "1                             0                           0   \n",
              "2                             0                           0   \n",
              "3                             0                           0   \n",
              "4                             0                           0   \n",
              "\n",
              "   specific_type_Bud-based  specific_type_Butterflyfish-based  \\\n",
              "0                        0                                  0   \n",
              "1                        0                                  0   \n",
              "2                        0                                  0   \n",
              "3                        0                                  0   \n",
              "4                        0                                  0   \n",
              "\n",
              "   specific_type_Cactus-based  specific_type_Camel-based  \\\n",
              "0                           0                          0   \n",
              "1                           0                          0   \n",
              "2                           0                          0   \n",
              "3                           0                          0   \n",
              "4                           0                          0   \n",
              "\n",
              "   specific_type_Canine-based  specific_type_Caprid-based  \\\n",
              "0                           0                           0   \n",
              "1                           0                           0   \n",
              "2                           0                           0   \n",
              "3                           0                           0   \n",
              "4                           0                           0   \n",
              "\n",
              "   specific_type_Carp-based  specific_type_Catfish-based  \\\n",
              "0                         0                            0   \n",
              "1                         0                            0   \n",
              "2                         0                            0   \n",
              "3                         0                            0   \n",
              "4                         0                            0   \n",
              "\n",
              "   specific_type_Cephalopod-based  specific_type_Cherry-based  \\\n",
              "0                               0                           0   \n",
              "1                               0                           0   \n",
              "2                               0                           0   \n",
              "3                               0                           0   \n",
              "4                               0                           0   \n",
              "\n",
              "   specific_type_Chestnut-based  specific_type_Cocoon-based  \\\n",
              "0                             0                           0   \n",
              "1                             0                           0   \n",
              "2                             0                           0   \n",
              "3                             0                           0   \n",
              "4                             0                           0   \n",
              "\n",
              "   specific_type_Coelacanth-based  specific_type_Coniferous tree-based  \\\n",
              "0                               0                                    0   \n",
              "1                               0                                    0   \n",
              "2                               0                                    0   \n",
              "3                               0                                    0   \n",
              "4                               0                                    0   \n",
              "\n",
              "   specific_type_Coral-based  specific_type_Cotton-based  \\\n",
              "0                          0                           0   \n",
              "1                          0                           0   \n",
              "2                          0                           0   \n",
              "3                          0                           0   \n",
              "4                          0                           0   \n",
              "\n",
              "   specific_type_Crinoid-based  specific_type_Crocodile-based  \\\n",
              "0                            0                              0   \n",
              "1                            0                              0   \n",
              "2                            0                              0   \n",
              "3                            0                              0   \n",
              "4                            0                              0   \n",
              "\n",
              "   specific_type_Crow-based  specific_type_Crustacean-based  \\\n",
              "0                         0                               0   \n",
              "1                         0                               0   \n",
              "2                         0                               0   \n",
              "3                         0                               0   \n",
              "4                         0                               0   \n",
              "\n",
              "   specific_type_Dandelion-based  specific_type_Deer-based  \\\n",
              "0                              0                         0   \n",
              "1                              0                         0   \n",
              "2                              0                         0   \n",
              "3                              0                         0   \n",
              "4                              0                         0   \n",
              "\n",
              "   specific_type_Dinocaridid-based  specific_type_Dinosaur-based  \\\n",
              "0                                0                             0   \n",
              "1                                0                             0   \n",
              "2                                0                             0   \n",
              "3                                0                             0   \n",
              "4                                0                             0   \n",
              "\n",
              "   specific_type_Discus-based  specific_type_Duck-based  \\\n",
              "0                           0                         0   \n",
              "1                           0                         0   \n",
              "2                           0                         0   \n",
              "3                           0                         0   \n",
              "4                           0                         0   \n",
              "\n",
              "   specific_type_Durian-based  specific_type_Earthworm-based  \\\n",
              "0                           0                              0   \n",
              "1                           0                              0   \n",
              "2                           0                              0   \n",
              "3                           0                              0   \n",
              "4                           0                              0   \n",
              "\n",
              "   specific_type_Eel-based  specific_type_Elephant-based  \\\n",
              "0                        0                             0   \n",
              "1                        0                             0   \n",
              "2                        0                             0   \n",
              "3                        0                             0   \n",
              "4                        0                             0   \n",
              "\n",
              "   specific_type_Equidae-based  specific_type_Falcon-based  \\\n",
              "0                            0                           0   \n",
              "1                            0                           0   \n",
              "2                            0                           0   \n",
              "3                            0                           0   \n",
              "4                            0                           0   \n",
              "\n",
              "   specific_type_Feline-based  specific_type_Flamingo-based  \\\n",
              "0                           0                             0   \n",
              "1                           0                             0   \n",
              "2                           0                             0   \n",
              "3                           0                             0   \n",
              "4                           0                             0   \n",
              "\n",
              "   specific_type_Flatfish-based  specific_type_Flower-based  \\\n",
              "0                             0                           0   \n",
              "1                             0                           0   \n",
              "2                             0                           0   \n",
              "3                             0                           0   \n",
              "4                             0                           0   \n",
              "\n",
              "   specific_type_Fly agaric-based  specific_type_Fox-based  \\\n",
              "0                               0                        0   \n",
              "1                               0                        0   \n",
              "2                               0                        0   \n",
              "3                               0                        0   \n",
              "4                               0                        0   \n",
              "\n",
              "   specific_type_Frog- and toad-based  specific_type_Fungus-based  \\\n",
              "0                                   1                           0   \n",
              "1                                   1                           0   \n",
              "2                                   1                           0   \n",
              "3                                   0                           0   \n",
              "4                                   0                           0   \n",
              "\n",
              "   specific_type_Galliform-based  specific_type_Gastropod-based  \\\n",
              "0                              0                              0   \n",
              "1                              0                              0   \n",
              "2                              0                              0   \n",
              "3                              0                              0   \n",
              "4                              0                              0   \n",
              "\n",
              "   specific_type_Geastrales-based  specific_type_Geranium-based  \\\n",
              "0                               0                             0   \n",
              "1                               0                             0   \n",
              "2                               0                             0   \n",
              "3                               0                             0   \n",
              "4                               0                             0   \n",
              "\n",
              "   specific_type_Glyptodont-based  specific_type_Hedgehog-based  \\\n",
              "0                               0                             0   \n",
              "1                               0                             0   \n",
              "2                               0                             0   \n",
              "3                               0                             0   \n",
              "4                               0                             0   \n",
              "\n",
              "   specific_type_Hippopotamus-based  specific_type_Honeycreeper-based  \\\n",
              "0                                 0                                 0   \n",
              "1                                 0                                 0   \n",
              "2                                 0                                 0   \n",
              "3                                 0                                 0   \n",
              "4                                 0                                 0   \n",
              "\n",
              "   specific_type_Horseshoe crab-based  specific_type_Hyena-based  \\\n",
              "0                                   0                          0   \n",
              "1                                   0                          0   \n",
              "2                                   0                          0   \n",
              "3                                   0                          0   \n",
              "4                                   0                          0   \n",
              "\n",
              "   specific_type_Jellyfish-based  specific_type_Kangaroo-based  \\\n",
              "0                              0                             0   \n",
              "1                              0                             0   \n",
              "2                              0                             0   \n",
              "3                              0                             0   \n",
              "4                              0                             0   \n",
              "\n",
              "   specific_type_Lamprey-based  specific_type_Leaf-based  \\\n",
              "0                            0                         0   \n",
              "1                            0                         0   \n",
              "2                            0                         0   \n",
              "3                            0                         0   \n",
              "4                            0                         0   \n",
              "\n",
              "   specific_type_Lepidopteran-based  specific_type_Lilium-based  \\\n",
              "0                                 0                           0   \n",
              "1                                 0                           0   \n",
              "2                                 0                           0   \n",
              "3                                 0                           0   \n",
              "4                                 0                           0   \n",
              "\n",
              "   specific_type_Lizard-based  specific_type_Loach-based  \\\n",
              "0                           0                          0   \n",
              "1                           0                          0   \n",
              "2                           0                          0   \n",
              "3                           0                          0   \n",
              "4                           0                          0   \n",
              "\n",
              "   specific_type_Mangosteen-based  specific_type_Manta ray-based  \\\n",
              "0                               0                              0   \n",
              "1                               0                              0   \n",
              "2                               0                              0   \n",
              "3                               0                              0   \n",
              "4                               0                              0   \n",
              "\n",
              "   specific_type_Mantis-based  specific_type_Marlin-based  \\\n",
              "0                           0                           0   \n",
              "1                           0                           0   \n",
              "2                           0                           0   \n",
              "3                           0                           0   \n",
              "4                           0                           0   \n",
              "\n",
              "   specific_type_Mole-based  specific_type_Oak tree-based  \\\n",
              "0                         0                             0   \n",
              "1                         0                             0   \n",
              "2                         0                             0   \n",
              "3                         0                             0   \n",
              "4                         0                             0   \n",
              "\n",
              "   specific_type_Orca-based  specific_type_Owl-based  \\\n",
              "0                         0                        0   \n",
              "1                         0                        0   \n",
              "2                         0                        0   \n",
              "3                         0                        0   \n",
              "4                         0                        0   \n",
              "\n",
              "   specific_type_Palm tree-based  specific_type_Pangolin-based  \\\n",
              "0                              0                             0   \n",
              "1                              0                             0   \n",
              "2                              0                             0   \n",
              "3                              0                             0   \n",
              "4                              0                             0   \n",
              "\n",
              "   specific_type_Pelican-based  specific_type_Penguin-based  \\\n",
              "0                            0                            0   \n",
              "1                            0                            0   \n",
              "2                            0                            0   \n",
              "3                            0                            0   \n",
              "4                            0                            0   \n",
              "\n",
              "   specific_type_Percoid-based  specific_type_Pig-based  \\\n",
              "0                            0                        0   \n",
              "1                            0                        0   \n",
              "2                            0                        0   \n",
              "3                            0                        0   \n",
              "4                            0                        0   \n",
              "\n",
              "   specific_type_Pinniped-based  specific_type_Piranha-based  \\\n",
              "0                             0                            0   \n",
              "1                             0                            0   \n",
              "2                             0                            0   \n",
              "3                             0                            0   \n",
              "4                             0                            0   \n",
              "\n",
              "   specific_type_Pitcher plant-based  specific_type_Plectognathi-based  \\\n",
              "0                                  0                                 0   \n",
              "1                                  0                                 0   \n",
              "2                                  0                                 0   \n",
              "3                                  0                                 0   \n",
              "4                                  0                                 0   \n",
              "\n",
              "   specific_type_Plesiosaur-based  specific_type_Primate-based  \\\n",
              "0                               0                            0   \n",
              "1                               0                            0   \n",
              "2                               0                            0   \n",
              "3                               0                            0   \n",
              "4                               0                            0   \n",
              "\n",
              "   specific_type_Pterosaur-based  specific_type_Quetzal-based  \\\n",
              "0                              0                            0   \n",
              "1                              0                            0   \n",
              "2                              0                            0   \n",
              "3                              0                            0   \n",
              "4                              0                            0   \n",
              "\n",
              "   specific_type_Rabbit-based  specific_type_Rafflesia-based  \\\n",
              "0                           0                              0   \n",
              "1                           0                              0   \n",
              "2                           0                              0   \n",
              "3                           0                              0   \n",
              "4                           0                              0   \n",
              "\n",
              "   specific_type_Rhinoceros-based  specific_type_Robin-based  \\\n",
              "0                               0                          0   \n",
              "1                               0                          0   \n",
              "2                               0                          0   \n",
              "3                               0                          0   \n",
              "4                               0                          0   \n",
              "\n",
              "   specific_type_Rodent-based  specific_type_Rose-based  \\\n",
              "0                           0                         0   \n",
              "1                           0                         0   \n",
              "2                           0                         0   \n",
              "3                           0                         0   \n",
              "4                           0                         0   \n",
              "\n",
              "   specific_type_Salamander-based  specific_type_Sardine-based  \\\n",
              "0                               0                            0   \n",
              "1                               0                            0   \n",
              "2                               0                            0   \n",
              "3                               1                            0   \n",
              "4                               1                            0   \n",
              "\n",
              "   specific_type_Scorpion-based  specific_type_Sea cucumber-based  \\\n",
              "0                             0                                 0   \n",
              "1                             0                                 0   \n",
              "2                             0                                 0   \n",
              "3                             0                                 0   \n",
              "4                             0                                 0   \n",
              "\n",
              "   specific_type_Seagull-based  specific_type_Shark-based  \\\n",
              "0                            0                          0   \n",
              "1                            0                          0   \n",
              "2                            0                          0   \n",
              "3                            0                          0   \n",
              "4                            0                          0   \n",
              "\n",
              "   specific_type_Skunk-based  specific_type_Snake-based  \\\n",
              "0                          0                          0   \n",
              "1                          0                          0   \n",
              "2                          0                          0   \n",
              "3                          0                          0   \n",
              "4                          0                          0   \n",
              "\n",
              "   specific_type_Spider-based  specific_type_Starfish-based  \\\n",
              "0                           0                             0   \n",
              "1                           0                             0   \n",
              "2                           0                             0   \n",
              "3                           0                             0   \n",
              "4                           0                             0   \n",
              "\n",
              "   specific_type_Sunflower-based  specific_type_Swan-based  \\\n",
              "0                              0                         0   \n",
              "1                              0                         0   \n",
              "2                              0                         0   \n",
              "3                              0                         0   \n",
              "4                              0                         0   \n",
              "\n",
              "   specific_type_Syngnathidae-based  specific_type_Tapir-based  \\\n",
              "0                                 0                          0   \n",
              "1                                 0                          0   \n",
              "2                                 0                          0   \n",
              "3                                 0                          0   \n",
              "4                                 0                          0   \n",
              "\n",
              "   specific_type_Tree-based  specific_type_Trilobite-based  \\\n",
              "0                         0                              0   \n",
              "1                         0                              0   \n",
              "2                         0                              0   \n",
              "3                         0                              0   \n",
              "4                         0                              0   \n",
              "\n",
              "   specific_type_Turtle-based  specific_type_Venus flytrap-based  \\\n",
              "0                           0                                  0   \n",
              "1                           0                                  0   \n",
              "2                           0                                  0   \n",
              "3                           0                                  0   \n",
              "4                           0                                  0   \n",
              "\n",
              "   specific_type_Vine-based  specific_type_Vulture-based  \\\n",
              "0                         0                            0   \n",
              "1                         0                            0   \n",
              "2                         0                            0   \n",
              "3                         0                            0   \n",
              "4                         0                            0   \n",
              "\n",
              "   specific_type_Water lily-based  specific_type_Weasel-based  \\\n",
              "0                               0                           0   \n",
              "1                               0                           0   \n",
              "2                               0                           0   \n",
              "3                               0                           0   \n",
              "4                               0                           0   \n",
              "\n",
              "   specific_type_Whale-based  specific_type_Wolf-based  \n",
              "0                          0                         0  \n",
              "1                          0                         0  \n",
              "2                          0                         0  \n",
              "3                          0                         0  \n",
              "4                          0                         0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f7d95821-198e-4dc6-ba4c-fc1a91a3ed10\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>abilities</th>\n",
              "      <th>against_bug</th>\n",
              "      <th>against_dark</th>\n",
              "      <th>against_dragon</th>\n",
              "      <th>against_electric</th>\n",
              "      <th>against_fairy</th>\n",
              "      <th>against_fight</th>\n",
              "      <th>against_fire</th>\n",
              "      <th>against_flying</th>\n",
              "      <th>against_ghost</th>\n",
              "      <th>against_grass</th>\n",
              "      <th>against_ground</th>\n",
              "      <th>against_ice</th>\n",
              "      <th>against_normal</th>\n",
              "      <th>against_poison</th>\n",
              "      <th>against_psychic</th>\n",
              "      <th>against_rock</th>\n",
              "      <th>against_steel</th>\n",
              "      <th>against_water</th>\n",
              "      <th>attack</th>\n",
              "      <th>base_egg_steps</th>\n",
              "      <th>base_happiness</th>\n",
              "      <th>base_total</th>\n",
              "      <th>capture_rate</th>\n",
              "      <th>classfication</th>\n",
              "      <th>defense</th>\n",
              "      <th>experience_growth</th>\n",
              "      <th>height_m</th>\n",
              "      <th>hp</th>\n",
              "      <th>japanese_name</th>\n",
              "      <th>name</th>\n",
              "      <th>percentage_male</th>\n",
              "      <th>pokedex_number</th>\n",
              "      <th>sp_attack</th>\n",
              "      <th>sp_defense</th>\n",
              "      <th>speed</th>\n",
              "      <th>weight_kg</th>\n",
              "      <th>generation</th>\n",
              "      <th>is_legendary</th>\n",
              "      <th>pokemon</th>\n",
              "      <th>red1</th>\n",
              "      <th>green1</th>\n",
              "      <th>blue1</th>\n",
              "      <th>red2</th>\n",
              "      <th>green2</th>\n",
              "      <th>blue2</th>\n",
              "      <th>red3</th>\n",
              "      <th>green3</th>\n",
              "      <th>blue3</th>\n",
              "      <th>unique_type</th>\n",
              "      <th>super_type_Amphibian Pokémon</th>\n",
              "      <th>super_type_Arthropod Pokémon</th>\n",
              "      <th>super_type_Avian Pokémon</th>\n",
              "      <th>super_type_Clitellata Pokémon</th>\n",
              "      <th>super_type_Cnidaria Pokémon</th>\n",
              "      <th>super_type_Echinoderm Pokémon</th>\n",
              "      <th>super_type_Fish Pokémon</th>\n",
              "      <th>super_type_Mammalian Pokémon</th>\n",
              "      <th>super_type_Mollusc Pokémon</th>\n",
              "      <th>super_type_Plant Pokémon</th>\n",
              "      <th>super_type_Reptilian Pokémon</th>\n",
              "      <th>specific_type_Anglerfish-based</th>\n",
              "      <th>specific_type_Anteater-based</th>\n",
              "      <th>specific_type_Antlion-based</th>\n",
              "      <th>specific_type_Banana tree-based</th>\n",
              "      <th>specific_type_Bat-based</th>\n",
              "      <th>specific_type_Bear-based</th>\n",
              "      <th>specific_type_Bird-based</th>\n",
              "      <th>specific_type_Bivalve-based</th>\n",
              "      <th>specific_type_Bluebird-based</th>\n",
              "      <th>specific_type_Bovine-based</th>\n",
              "      <th>specific_type_Bud-based</th>\n",
              "      <th>specific_type_Butterflyfish-based</th>\n",
              "      <th>specific_type_Cactus-based</th>\n",
              "      <th>specific_type_Camel-based</th>\n",
              "      <th>specific_type_Canine-based</th>\n",
              "      <th>specific_type_Caprid-based</th>\n",
              "      <th>specific_type_Carp-based</th>\n",
              "      <th>specific_type_Catfish-based</th>\n",
              "      <th>specific_type_Cephalopod-based</th>\n",
              "      <th>specific_type_Cherry-based</th>\n",
              "      <th>specific_type_Chestnut-based</th>\n",
              "      <th>specific_type_Cocoon-based</th>\n",
              "      <th>specific_type_Coelacanth-based</th>\n",
              "      <th>specific_type_Coniferous tree-based</th>\n",
              "      <th>specific_type_Coral-based</th>\n",
              "      <th>specific_type_Cotton-based</th>\n",
              "      <th>specific_type_Crinoid-based</th>\n",
              "      <th>specific_type_Crocodile-based</th>\n",
              "      <th>specific_type_Crow-based</th>\n",
              "      <th>specific_type_Crustacean-based</th>\n",
              "      <th>specific_type_Dandelion-based</th>\n",
              "      <th>specific_type_Deer-based</th>\n",
              "      <th>specific_type_Dinocaridid-based</th>\n",
              "      <th>specific_type_Dinosaur-based</th>\n",
              "      <th>specific_type_Discus-based</th>\n",
              "      <th>specific_type_Duck-based</th>\n",
              "      <th>specific_type_Durian-based</th>\n",
              "      <th>specific_type_Earthworm-based</th>\n",
              "      <th>specific_type_Eel-based</th>\n",
              "      <th>specific_type_Elephant-based</th>\n",
              "      <th>specific_type_Equidae-based</th>\n",
              "      <th>specific_type_Falcon-based</th>\n",
              "      <th>specific_type_Feline-based</th>\n",
              "      <th>specific_type_Flamingo-based</th>\n",
              "      <th>specific_type_Flatfish-based</th>\n",
              "      <th>specific_type_Flower-based</th>\n",
              "      <th>specific_type_Fly agaric-based</th>\n",
              "      <th>specific_type_Fox-based</th>\n",
              "      <th>specific_type_Frog- and toad-based</th>\n",
              "      <th>specific_type_Fungus-based</th>\n",
              "      <th>specific_type_Galliform-based</th>\n",
              "      <th>specific_type_Gastropod-based</th>\n",
              "      <th>specific_type_Geastrales-based</th>\n",
              "      <th>specific_type_Geranium-based</th>\n",
              "      <th>specific_type_Glyptodont-based</th>\n",
              "      <th>specific_type_Hedgehog-based</th>\n",
              "      <th>specific_type_Hippopotamus-based</th>\n",
              "      <th>specific_type_Honeycreeper-based</th>\n",
              "      <th>specific_type_Horseshoe crab-based</th>\n",
              "      <th>specific_type_Hyena-based</th>\n",
              "      <th>specific_type_Jellyfish-based</th>\n",
              "      <th>specific_type_Kangaroo-based</th>\n",
              "      <th>specific_type_Lamprey-based</th>\n",
              "      <th>specific_type_Leaf-based</th>\n",
              "      <th>specific_type_Lepidopteran-based</th>\n",
              "      <th>specific_type_Lilium-based</th>\n",
              "      <th>specific_type_Lizard-based</th>\n",
              "      <th>specific_type_Loach-based</th>\n",
              "      <th>specific_type_Mangosteen-based</th>\n",
              "      <th>specific_type_Manta ray-based</th>\n",
              "      <th>specific_type_Mantis-based</th>\n",
              "      <th>specific_type_Marlin-based</th>\n",
              "      <th>specific_type_Mole-based</th>\n",
              "      <th>specific_type_Oak tree-based</th>\n",
              "      <th>specific_type_Orca-based</th>\n",
              "      <th>specific_type_Owl-based</th>\n",
              "      <th>specific_type_Palm tree-based</th>\n",
              "      <th>specific_type_Pangolin-based</th>\n",
              "      <th>specific_type_Pelican-based</th>\n",
              "      <th>specific_type_Penguin-based</th>\n",
              "      <th>specific_type_Percoid-based</th>\n",
              "      <th>specific_type_Pig-based</th>\n",
              "      <th>specific_type_Pinniped-based</th>\n",
              "      <th>specific_type_Piranha-based</th>\n",
              "      <th>specific_type_Pitcher plant-based</th>\n",
              "      <th>specific_type_Plectognathi-based</th>\n",
              "      <th>specific_type_Plesiosaur-based</th>\n",
              "      <th>specific_type_Primate-based</th>\n",
              "      <th>specific_type_Pterosaur-based</th>\n",
              "      <th>specific_type_Quetzal-based</th>\n",
              "      <th>specific_type_Rabbit-based</th>\n",
              "      <th>specific_type_Rafflesia-based</th>\n",
              "      <th>specific_type_Rhinoceros-based</th>\n",
              "      <th>specific_type_Robin-based</th>\n",
              "      <th>specific_type_Rodent-based</th>\n",
              "      <th>specific_type_Rose-based</th>\n",
              "      <th>specific_type_Salamander-based</th>\n",
              "      <th>specific_type_Sardine-based</th>\n",
              "      <th>specific_type_Scorpion-based</th>\n",
              "      <th>specific_type_Sea cucumber-based</th>\n",
              "      <th>specific_type_Seagull-based</th>\n",
              "      <th>specific_type_Shark-based</th>\n",
              "      <th>specific_type_Skunk-based</th>\n",
              "      <th>specific_type_Snake-based</th>\n",
              "      <th>specific_type_Spider-based</th>\n",
              "      <th>specific_type_Starfish-based</th>\n",
              "      <th>specific_type_Sunflower-based</th>\n",
              "      <th>specific_type_Swan-based</th>\n",
              "      <th>specific_type_Syngnathidae-based</th>\n",
              "      <th>specific_type_Tapir-based</th>\n",
              "      <th>specific_type_Tree-based</th>\n",
              "      <th>specific_type_Trilobite-based</th>\n",
              "      <th>specific_type_Turtle-based</th>\n",
              "      <th>specific_type_Venus flytrap-based</th>\n",
              "      <th>specific_type_Vine-based</th>\n",
              "      <th>specific_type_Vulture-based</th>\n",
              "      <th>specific_type_Water lily-based</th>\n",
              "      <th>specific_type_Weasel-based</th>\n",
              "      <th>specific_type_Whale-based</th>\n",
              "      <th>specific_type_Wolf-based</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>['Overgrow', 'Chlorophyll']</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.25</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>49</td>\n",
              "      <td>5120</td>\n",
              "      <td>70</td>\n",
              "      <td>318</td>\n",
              "      <td>45</td>\n",
              "      <td>Seed Pokémon</td>\n",
              "      <td>49</td>\n",
              "      <td>1059860</td>\n",
              "      <td>0.7</td>\n",
              "      <td>45</td>\n",
              "      <td>Fushigidaneフシギダネ</td>\n",
              "      <td>Bulbasaur</td>\n",
              "      <td>88.1</td>\n",
              "      <td>1</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>45</td>\n",
              "      <td>6.9</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Bulbasaur</td>\n",
              "      <td>57</td>\n",
              "      <td>148</td>\n",
              "      <td>148</td>\n",
              "      <td>98</td>\n",
              "      <td>213</td>\n",
              "      <td>180</td>\n",
              "      <td>131</td>\n",
              "      <td>238</td>\n",
              "      <td>197</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>['Overgrow', 'Chlorophyll']</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.25</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>62</td>\n",
              "      <td>5120</td>\n",
              "      <td>70</td>\n",
              "      <td>405</td>\n",
              "      <td>45</td>\n",
              "      <td>Seed Pokémon</td>\n",
              "      <td>63</td>\n",
              "      <td>1059860</td>\n",
              "      <td>1.0</td>\n",
              "      <td>60</td>\n",
              "      <td>Fushigisouフシギソウ</td>\n",
              "      <td>Ivysaur</td>\n",
              "      <td>88.1</td>\n",
              "      <td>2</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>60</td>\n",
              "      <td>13.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Ivysaur</td>\n",
              "      <td>90</td>\n",
              "      <td>205</td>\n",
              "      <td>189</td>\n",
              "      <td>32</td>\n",
              "      <td>148</td>\n",
              "      <td>131</td>\n",
              "      <td>49</td>\n",
              "      <td>123</td>\n",
              "      <td>82</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>['Overgrow', 'Chlorophyll']</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.25</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>100</td>\n",
              "      <td>5120</td>\n",
              "      <td>70</td>\n",
              "      <td>625</td>\n",
              "      <td>45</td>\n",
              "      <td>Seed Pokémon</td>\n",
              "      <td>123</td>\n",
              "      <td>1059860</td>\n",
              "      <td>2.0</td>\n",
              "      <td>80</td>\n",
              "      <td>Fushigibanaフシギバナ</td>\n",
              "      <td>Venusaur</td>\n",
              "      <td>88.1</td>\n",
              "      <td>3</td>\n",
              "      <td>122</td>\n",
              "      <td>120</td>\n",
              "      <td>80</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Venusaur</td>\n",
              "      <td>32</td>\n",
              "      <td>180</td>\n",
              "      <td>156</td>\n",
              "      <td>90</td>\n",
              "      <td>213</td>\n",
              "      <td>197</td>\n",
              "      <td>255</td>\n",
              "      <td>123</td>\n",
              "      <td>115</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>['Blaze', 'Solar Power']</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>52</td>\n",
              "      <td>5120</td>\n",
              "      <td>70</td>\n",
              "      <td>309</td>\n",
              "      <td>45</td>\n",
              "      <td>Lizard Pokémon</td>\n",
              "      <td>43</td>\n",
              "      <td>1059860</td>\n",
              "      <td>0.6</td>\n",
              "      <td>39</td>\n",
              "      <td>Hitokageヒトカゲ</td>\n",
              "      <td>Charmander</td>\n",
              "      <td>88.1</td>\n",
              "      <td>4</td>\n",
              "      <td>60</td>\n",
              "      <td>50</td>\n",
              "      <td>65</td>\n",
              "      <td>8.5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Charmander</td>\n",
              "      <td>255</td>\n",
              "      <td>148</td>\n",
              "      <td>65</td>\n",
              "      <td>222</td>\n",
              "      <td>82</td>\n",
              "      <td>57</td>\n",
              "      <td>255</td>\n",
              "      <td>213</td>\n",
              "      <td>123</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>['Blaze', 'Solar Power']</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.50</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.5</td>\n",
              "      <td>2.0</td>\n",
              "      <td>64</td>\n",
              "      <td>5120</td>\n",
              "      <td>70</td>\n",
              "      <td>405</td>\n",
              "      <td>45</td>\n",
              "      <td>Flame Pokémon</td>\n",
              "      <td>58</td>\n",
              "      <td>1059860</td>\n",
              "      <td>1.1</td>\n",
              "      <td>58</td>\n",
              "      <td>Lizardoリザード</td>\n",
              "      <td>Charmeleon</td>\n",
              "      <td>88.1</td>\n",
              "      <td>5</td>\n",
              "      <td>80</td>\n",
              "      <td>65</td>\n",
              "      <td>80</td>\n",
              "      <td>19.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>Charmeleon</td>\n",
              "      <td>205</td>\n",
              "      <td>57</td>\n",
              "      <td>57</td>\n",
              "      <td>255</td>\n",
              "      <td>82</td>\n",
              "      <td>74</td>\n",
              "      <td>255</td>\n",
              "      <td>65</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f7d95821-198e-4dc6-ba4c-fc1a91a3ed10')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      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",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-f7d95821-198e-4dc6-ba4c-fc1a91a3ed10 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-f7d95821-198e-4dc6-ba4c-fc1a91a3ed10');\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-60d2a30f-b09f-4c19-8400-cc6bacfd0b35\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-60d2a30f-b09f-4c19-8400-cc6bacfd0b35')\"\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",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\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-60d2a30f-b09f-4c19-8400-cc6bacfd0b35 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "pokemon"
            }
          },
          "metadata": {},
          "execution_count": 521
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "843face8-aba1-4b32-8a9c-b9b9e1d1c0a1"
      },
      "source": [
        "#### Tratamento das colunas"
      ],
      "id": "843face8-aba1-4b32-8a9c-b9b9e1d1c0a1"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4ac03acf-f9b0-4831-88cc-341705b5515e"
      },
      "outputs": [],
      "source": [
        "pokemon.drop(['height_m', 'name', 'japanese_name', 'pokedex_number', 'percentage_male',\n",
        "              'classfication', 'base_egg_steps', 'base_happiness', 'abilities',\n",
        "              'experience_growth', 'defense', 'base_total', 'speed'], axis=1, inplace=True)"
      ],
      "id": "4ac03acf-f9b0-4831-88cc-341705b5515e"
    },
    {
      "cell_type": "code",
      "source": [
        "against_columns = pokemon.filter(regex='^against').columns"
      ],
      "metadata": {
        "id": "cC0oAL9I_cDE"
      },
      "id": "cC0oAL9I_cDE",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6c4a0681-cb54-491a-a143-198889f2fe6b"
      },
      "outputs": [],
      "source": [
        "pokemon = pokemon.drop(columns=against_columns)"
      ],
      "id": "6c4a0681-cb54-491a-a143-198889f2fe6b"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "7b71e58e-30af-45f5-9b2e-0250825a65fd"
      },
      "outputs": [],
      "source": [
        "for column in pokemon.columns:\n",
        "    pokemon[column] = pd.to_numeric(pokemon[column], errors='coerce')"
      ],
      "id": "7b71e58e-30af-45f5-9b2e-0250825a65fd"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "9594a335-708e-44c2-adcd-6d24770616b3"
      },
      "outputs": [],
      "source": [
        "pokemon['capture_rate'].fillna(pokemon['capture_rate'].median(), inplace=True)"
      ],
      "id": "9594a335-708e-44c2-adcd-6d24770616b3"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "945629ff-008f-4348-beab-3bb8b584bf2d",
        "outputId": "4fb1e5bf-6cad-4f4d-c8ea-45e78790eaa8"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "False"
            ]
          },
          "metadata": {},
          "execution_count": 527
        }
      ],
      "source": [
        "not 0 in pokemon.isna().sum().tolist()"
      ],
      "id": "945629ff-008f-4348-beab-3bb8b584bf2d"
    },
    {
      "cell_type": "code",
      "source": [
        "pokemon.columns[pokemon.isna().any()]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EfwnP-Pu-R3q",
        "outputId": "0f57abae-3e2c-437d-94df-eed572cc4f99"
      },
      "id": "EfwnP-Pu-R3q",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['pokemon'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 528
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pokemon.drop(columns='pokemon', inplace=True)"
      ],
      "metadata": {
        "id": "x2Dw5F4w-0xC"
      },
      "id": "x2Dw5F4w-0xC",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Tentativa de clusterização por cores"
      ],
      "metadata": {
        "id": "tQ2fGWDBA2-z"
      },
      "id": "tQ2fGWDBA2-z"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "39zjh1W5H0ei"
      },
      "outputs": [],
      "source": [
        "# colors = {\n",
        "#     \"black\": [0, 0, 0],\n",
        "#     \"white\": [255, 255, 255],\n",
        "#     \"grey\": [184, 184, 208],\n",
        "#     \"red\": [255, 0, 0],\n",
        "#     \"blue\": [104, 144, 240],\n",
        "#     \"green\": [94, 200, 80],\n",
        "#     \"yellow\": [255, 255, 0],\n",
        "#     \"orange\": [255, 125, 0],\n",
        "#     \"pink\": [238, 153, 172],\n",
        "#     \"purple\": [187, 151, 252]\n",
        "# }\n",
        "# lista_cores = []\n",
        "# lista_cores2 = []\n",
        "# lista_cores3 = []\n",
        "\n",
        "# red = pokemon['red1'].to_list()\n",
        "# green = pokemon['green1'].to_list()\n",
        "# blue = pokemon['blue1'].to_list()\n",
        "\n",
        "# red2 = pokemon['red2'].to_list()\n",
        "# green2 = pokemon['green2'].to_list()\n",
        "# blue2 = pokemon['blue2'].to_list()\n",
        "\n",
        "# red3 = pokemon['red3'].to_list()\n",
        "# green3 = pokemon['green3'].to_list()\n",
        "# blue3 = pokemon['blue3'].to_list()\n",
        "\n",
        "\n",
        "# for c in range(0, len(red)):\n",
        "#   lista_temp = []\n",
        "#   lista_temp.append(red[c])\n",
        "#   lista_temp.append(green[c])\n",
        "#   lista_temp.append(blue[c])\n",
        "#   lista_cores.append(lista_temp)\n",
        "\n",
        "#   lista_temp2 = []\n",
        "\n",
        "#   lista_temp2.append(red2[c])\n",
        "#   lista_temp2.append(green2[c])\n",
        "#   lista_temp2.append(blue2[c])\n",
        "#   lista_cores2.append(lista_temp2)\n",
        "\n",
        "#   lista_temp3 = []\n",
        "\n",
        "#   lista_temp3.append(red3[c])\n",
        "#   lista_temp3.append(green3[c])\n",
        "#   lista_temp3.append(blue3[c])\n",
        "#   lista_cores3.append(lista_temp3)\n",
        "\n",
        "\n",
        "# closest_colors = []\n",
        "# closest_colors2 = []\n",
        "# closest_colors3 = []\n",
        "# def euclidean_distance(color1, color2):\n",
        "#     return np.linalg.norm(np.array(color1) - np.array(color2))\n",
        "\n",
        "\n",
        "# for x in lista_cores:\n",
        "#     min_distance = float('inf')\n",
        "#     closest_color = None\n",
        "#     for color_name, color_values in colors.items():\n",
        "#         distance = euclidean_distance(x, color_values)\n",
        "#         if distance < min_distance:\n",
        "#             min_distance = distance\n",
        "#             closest_color = color_name\n",
        "#     closest_colors.append(closest_color)\n",
        "\n",
        "\n",
        "# for x in lista_cores2:\n",
        "#     min_distance = float('inf')\n",
        "#     closest_color2 = None\n",
        "#     for color_name, color_values in colors.items():\n",
        "#         distance = euclidean_distance(x, color_values)\n",
        "#         if distance < min_distance:\n",
        "#             min_distance = distance\n",
        "#             closest_color2 = color_name\n",
        "#     closest_colors2.append(closest_color2)\n",
        "\n",
        "\n",
        "# for x in lista_cores2:\n",
        "#     min_distance = float('inf')\n",
        "#     closest_color3 = None\n",
        "#     for color_name, color_values in colors.items():\n",
        "#         distance = euclidean_distance(x, color_values)\n",
        "#         if distance < min_distance:\n",
        "#             min_distance = distance\n",
        "#             closest_color3 = color_name\n",
        "#     closest_colors3.append(closest_color3)\n",
        "\n",
        "# pokemon[\"primary_color\"] = closest_colors\n",
        "# pokemon[\"secondary_color\"] = closest_colors2\n",
        "# pokemon[\"tertiary_color\"] = closest_colors3"
      ],
      "id": "39zjh1W5H0ei"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "yhX7oRMwP0yr"
      },
      "outputs": [],
      "source": [
        "# import sklearn.cluster as cluster"
      ],
      "id": "yhX7oRMwP0yr"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "0GorFmcuh-NI"
      },
      "outputs": [],
      "source": [
        "# kmeans = cluster.KMeans(n_clusters = 10, init=\"k-means++\")\n",
        "# kmeans = kmeans.fit(pokemon[['red1', 'green1', 'blue1']])\n",
        "# kmeans.cluster_centers_\n",
        "# pokemon['primary_color'] = kmeans.labels_\n",
        "# pokemon"
      ],
      "id": "0GorFmcuh-NI"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eSs3BVCVfaHK"
      },
      "outputs": [],
      "source": [
        "# from sklearn.preprocessing import LabelEncoder\n",
        "\n",
        "# pokemon['primary_color']\n",
        "\n",
        "# le = LabelEncoder().fit(pokemon['primary_color'])\n",
        "\n",
        "# le.classes_\n",
        "\n",
        "# unique_type_tranformed = le.transform(pokemon['primary_color'])\n",
        "# pokemon['primary_color'] = unique_type_tranformed\n",
        "\n",
        "\n",
        "# pokemon['secondary_color']\n",
        "\n",
        "# le = LabelEncoder().fit(pokemon['secondary_color'])\n",
        "\n",
        "# le.classes_\n",
        "\n",
        "# unique_type_tranformed = le.transform(pokemon['secondary_color'])\n",
        "# pokemon['secondary_color'] = unique_type_tranformed\n",
        "\n",
        "\n",
        "# pokemon['tertiary_color']\n",
        "\n",
        "# le = LabelEncoder().fit(pokemon['tertiary_color'])\n",
        "\n",
        "# le.classes_\n",
        "\n",
        "# unique_type_tranformed = le.transform(pokemon['tertiary_color'])\n",
        "# pokemon['tertiary_color'] = unique_type_tranformed"
      ],
      "id": "eSs3BVCVfaHK"
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Divisão de colunas de características e alvo"
      ],
      "metadata": {
        "id": "QT6bcvgZBBWg"
      },
      "id": "QT6bcvgZBBWg"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "818141d2-929e-4788-ba48-65a1fdf79c64"
      },
      "outputs": [],
      "source": [
        "X = pokemon.drop(['unique_type'], axis=1)"
      ],
      "id": "818141d2-929e-4788-ba48-65a1fdf79c64"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "b58c2380-3e03-4ade-a045-8efb3bf0b934"
      },
      "outputs": [],
      "source": [
        "y = pokemon['unique_type']"
      ],
      "id": "b58c2380-3e03-4ade-a045-8efb3bf0b934"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4c156791-7bc6-4169-951b-5f41859ab743",
        "outputId": "cae4fa4d-bd35-463d-d809-b1c648862129"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   attack  capture_rate  hp  sp_attack  sp_defense  weight_kg  generation  \\\n",
              "0      49            45  45         65          65        6.9           1   \n",
              "1      62            45  60         80          80       13.0           1   \n",
              "2     100            45  80        122         120      100.0           1   \n",
              "3      52            45  39         60          50        8.5           1   \n",
              "4      64            45  58         80          65       19.0           1   \n",
              "\n",
              "   is_legendary  red1  green1  blue1  red2  green2  blue2  red3  green3  \\\n",
              "0             0    57     148    148    98     213    180   131     238   \n",
              "1             0    90     205    189    32     148    131    49     123   \n",
              "2             0    32     180    156    90     213    197   255     123   \n",
              "3             0   255     148     65   222      82     57   255     213   \n",
              "4             0   205      57     57   255      82     74   255      65   \n",
              "\n",
              "   blue3  super_type_Amphibian Pokémon  super_type_Arthropod Pokémon  \\\n",
              "0    197                             1                             0   \n",
              "1     82                             1                             0   \n",
              "2    115                             1                             0   \n",
              "3    123                             1                             0   \n",
              "4      0                             1                             0   \n",
              "\n",
              "   super_type_Avian Pokémon  super_type_Clitellata Pokémon  \\\n",
              "0                         0                              0   \n",
              "1                         0                              0   \n",
              "2                         0                              0   \n",
              "3                         0                              0   \n",
              "4                         0                              0   \n",
              "\n",
              "   super_type_Cnidaria Pokémon  super_type_Echinoderm Pokémon  \\\n",
              "0                            0                              0   \n",
              "1                            0                              0   \n",
              "2                            0                              0   \n",
              "3                            0                              0   \n",
              "4                            0                              0   \n",
              "\n",
              "   super_type_Fish Pokémon  super_type_Mammalian Pokémon  \\\n",
              "0                        0                             0   \n",
              "1                        0                             0   \n",
              "2                        0                             0   \n",
              "3                        0                             0   \n",
              "4                        0                             0   \n",
              "\n",
              "   super_type_Mollusc Pokémon  super_type_Plant Pokémon  \\\n",
              "0                           0                         0   \n",
              "1                           0                         0   \n",
              "2                           0                         0   \n",
              "3                           0                         0   \n",
              "4                           0                         0   \n",
              "\n",
              "   super_type_Reptilian Pokémon  specific_type_Anglerfish-based  \\\n",
              "0                             0                               0   \n",
              "1                             0                               0   \n",
              "2                             0                               0   \n",
              "3                             0                               0   \n",
              "4                             0                               0   \n",
              "\n",
              "   specific_type_Anteater-based  specific_type_Antlion-based  \\\n",
              "0                             0                            0   \n",
              "1                             0                            0   \n",
              "2                             0                            0   \n",
              "3                             0                            0   \n",
              "4                             0                            0   \n",
              "\n",
              "   specific_type_Banana tree-based  specific_type_Bat-based  \\\n",
              "0                                0                        0   \n",
              "1                                0                        0   \n",
              "2                                0                        0   \n",
              "3                                0                        0   \n",
              "4                                0                        0   \n",
              "\n",
              "   specific_type_Bear-based  specific_type_Bird-based  \\\n",
              "0                         0                         0   \n",
              "1                         0                         0   \n",
              "2                         0                         0   \n",
              "3                         0                         0   \n",
              "4                         0                         0   \n",
              "\n",
              "   specific_type_Bivalve-based  specific_type_Bluebird-based  \\\n",
              "0                            0                             0   \n",
              "1                            0                             0   \n",
              "2                            0                             0   \n",
              "3                            0                             0   \n",
              "4                            0                             0   \n",
              "\n",
              "   specific_type_Bovine-based  specific_type_Bud-based  \\\n",
              "0                           0                        0   \n",
              "1                           0                        0   \n",
              "2                           0                        0   \n",
              "3                           0                        0   \n",
              "4                           0                        0   \n",
              "\n",
              "   specific_type_Butterflyfish-based  specific_type_Cactus-based  \\\n",
              "0                                  0                           0   \n",
              "1                                  0                           0   \n",
              "2                                  0                           0   \n",
              "3                                  0                           0   \n",
              "4                                  0                           0   \n",
              "\n",
              "   specific_type_Camel-based  specific_type_Canine-based  \\\n",
              "0                          0                           0   \n",
              "1                          0                           0   \n",
              "2                          0                           0   \n",
              "3                          0                           0   \n",
              "4                          0                           0   \n",
              "\n",
              "   specific_type_Caprid-based  specific_type_Carp-based  \\\n",
              "0                           0                         0   \n",
              "1                           0                         0   \n",
              "2                           0                         0   \n",
              "3                           0                         0   \n",
              "4                           0                         0   \n",
              "\n",
              "   specific_type_Catfish-based  specific_type_Cephalopod-based  \\\n",
              "0                            0                               0   \n",
              "1                            0                               0   \n",
              "2                            0                               0   \n",
              "3                            0                               0   \n",
              "4                            0                               0   \n",
              "\n",
              "   specific_type_Cherry-based  specific_type_Chestnut-based  \\\n",
              "0                           0                             0   \n",
              "1                           0                             0   \n",
              "2                           0                             0   \n",
              "3                           0                             0   \n",
              "4                           0                             0   \n",
              "\n",
              "   specific_type_Cocoon-based  specific_type_Coelacanth-based  \\\n",
              "0                           0                               0   \n",
              "1                           0                               0   \n",
              "2                           0                               0   \n",
              "3                           0                               0   \n",
              "4                           0                               0   \n",
              "\n",
              "   specific_type_Coniferous tree-based  specific_type_Coral-based  \\\n",
              "0                                    0                          0   \n",
              "1                                    0                          0   \n",
              "2                                    0                          0   \n",
              "3                                    0                          0   \n",
              "4                                    0                          0   \n",
              "\n",
              "   specific_type_Cotton-based  specific_type_Crinoid-based  \\\n",
              "0                           0                            0   \n",
              "1                           0                            0   \n",
              "2                           0                            0   \n",
              "3                           0                            0   \n",
              "4                           0                            0   \n",
              "\n",
              "   specific_type_Crocodile-based  specific_type_Crow-based  \\\n",
              "0                              0                         0   \n",
              "1                              0                         0   \n",
              "2                              0                         0   \n",
              "3                              0                         0   \n",
              "4                              0                         0   \n",
              "\n",
              "   specific_type_Crustacean-based  specific_type_Dandelion-based  \\\n",
              "0                               0                              0   \n",
              "1                               0                              0   \n",
              "2                               0                              0   \n",
              "3                               0                              0   \n",
              "4                               0                              0   \n",
              "\n",
              "   specific_type_Deer-based  specific_type_Dinocaridid-based  \\\n",
              "0                         0                                0   \n",
              "1                         0                                0   \n",
              "2                         0                                0   \n",
              "3                         0                                0   \n",
              "4                         0                                0   \n",
              "\n",
              "   specific_type_Dinosaur-based  specific_type_Discus-based  \\\n",
              "0                             0                           0   \n",
              "1                             0                           0   \n",
              "2                             0                           0   \n",
              "3                             0                           0   \n",
              "4                             0                           0   \n",
              "\n",
              "   specific_type_Duck-based  specific_type_Durian-based  \\\n",
              "0                         0                           0   \n",
              "1                         0                           0   \n",
              "2                         0                           0   \n",
              "3                         0                           0   \n",
              "4                         0                           0   \n",
              "\n",
              "   specific_type_Earthworm-based  specific_type_Eel-based  \\\n",
              "0                              0                        0   \n",
              "1                              0                        0   \n",
              "2                              0                        0   \n",
              "3                              0                        0   \n",
              "4                              0                        0   \n",
              "\n",
              "   specific_type_Elephant-based  specific_type_Equidae-based  \\\n",
              "0                             0                            0   \n",
              "1                             0                            0   \n",
              "2                             0                            0   \n",
              "3                             0                            0   \n",
              "4                             0                            0   \n",
              "\n",
              "   specific_type_Falcon-based  specific_type_Feline-based  \\\n",
              "0                           0                           0   \n",
              "1                           0                           0   \n",
              "2                           0                           0   \n",
              "3                           0                           0   \n",
              "4                           0                           0   \n",
              "\n",
              "   specific_type_Flamingo-based  specific_type_Flatfish-based  \\\n",
              "0                             0                             0   \n",
              "1                             0                             0   \n",
              "2                             0                             0   \n",
              "3                             0                             0   \n",
              "4                             0                             0   \n",
              "\n",
              "   specific_type_Flower-based  specific_type_Fly agaric-based  \\\n",
              "0                           0                               0   \n",
              "1                           0                               0   \n",
              "2                           0                               0   \n",
              "3                           0                               0   \n",
              "4                           0                               0   \n",
              "\n",
              "   specific_type_Fox-based  specific_type_Frog- and toad-based  \\\n",
              "0                        0                                   1   \n",
              "1                        0                                   1   \n",
              "2                        0                                   1   \n",
              "3                        0                                   0   \n",
              "4                        0                                   0   \n",
              "\n",
              "   specific_type_Fungus-based  specific_type_Galliform-based  \\\n",
              "0                           0                              0   \n",
              "1                           0                              0   \n",
              "2                           0                              0   \n",
              "3                           0                              0   \n",
              "4                           0                              0   \n",
              "\n",
              "   specific_type_Gastropod-based  specific_type_Geastrales-based  \\\n",
              "0                              0                               0   \n",
              "1                              0                               0   \n",
              "2                              0                               0   \n",
              "3                              0                               0   \n",
              "4                              0                               0   \n",
              "\n",
              "   specific_type_Geranium-based  specific_type_Glyptodont-based  \\\n",
              "0                             0                               0   \n",
              "1                             0                               0   \n",
              "2                             0                               0   \n",
              "3                             0                               0   \n",
              "4                             0                               0   \n",
              "\n",
              "   specific_type_Hedgehog-based  specific_type_Hippopotamus-based  \\\n",
              "0                             0                                 0   \n",
              "1                             0                                 0   \n",
              "2                             0                                 0   \n",
              "3                             0                                 0   \n",
              "4                             0                                 0   \n",
              "\n",
              "   specific_type_Honeycreeper-based  specific_type_Horseshoe crab-based  \\\n",
              "0                                 0                                   0   \n",
              "1                                 0                                   0   \n",
              "2                                 0                                   0   \n",
              "3                                 0                                   0   \n",
              "4                                 0                                   0   \n",
              "\n",
              "   specific_type_Hyena-based  specific_type_Jellyfish-based  \\\n",
              "0                          0                              0   \n",
              "1                          0                              0   \n",
              "2                          0                              0   \n",
              "3                          0                              0   \n",
              "4                          0                              0   \n",
              "\n",
              "   specific_type_Kangaroo-based  specific_type_Lamprey-based  \\\n",
              "0                             0                            0   \n",
              "1                             0                            0   \n",
              "2                             0                            0   \n",
              "3                             0                            0   \n",
              "4                             0                            0   \n",
              "\n",
              "   specific_type_Leaf-based  specific_type_Lepidopteran-based  \\\n",
              "0                         0                                 0   \n",
              "1                         0                                 0   \n",
              "2                         0                                 0   \n",
              "3                         0                                 0   \n",
              "4                         0                                 0   \n",
              "\n",
              "   specific_type_Lilium-based  specific_type_Lizard-based  \\\n",
              "0                           0                           0   \n",
              "1                           0                           0   \n",
              "2                           0                           0   \n",
              "3                           0                           0   \n",
              "4                           0                           0   \n",
              "\n",
              "   specific_type_Loach-based  specific_type_Mangosteen-based  \\\n",
              "0                          0                               0   \n",
              "1                          0                               0   \n",
              "2                          0                               0   \n",
              "3                          0                               0   \n",
              "4                          0                               0   \n",
              "\n",
              "   specific_type_Manta ray-based  specific_type_Mantis-based  \\\n",
              "0                              0                           0   \n",
              "1                              0                           0   \n",
              "2                              0                           0   \n",
              "3                              0                           0   \n",
              "4                              0                           0   \n",
              "\n",
              "   specific_type_Marlin-based  specific_type_Mole-based  \\\n",
              "0                           0                         0   \n",
              "1                           0                         0   \n",
              "2                           0                         0   \n",
              "3                           0                         0   \n",
              "4                           0                         0   \n",
              "\n",
              "   specific_type_Oak tree-based  specific_type_Orca-based  \\\n",
              "0                             0                         0   \n",
              "1                             0                         0   \n",
              "2                             0                         0   \n",
              "3                             0                         0   \n",
              "4                             0                         0   \n",
              "\n",
              "   specific_type_Owl-based  specific_type_Palm tree-based  \\\n",
              "0                        0                              0   \n",
              "1                        0                              0   \n",
              "2                        0                              0   \n",
              "3                        0                              0   \n",
              "4                        0                              0   \n",
              "\n",
              "   specific_type_Pangolin-based  specific_type_Pelican-based  \\\n",
              "0                             0                            0   \n",
              "1                             0                            0   \n",
              "2                             0                            0   \n",
              "3                             0                            0   \n",
              "4                             0                            0   \n",
              "\n",
              "   specific_type_Penguin-based  specific_type_Percoid-based  \\\n",
              "0                            0                            0   \n",
              "1                            0                            0   \n",
              "2                            0                            0   \n",
              "3                            0                            0   \n",
              "4                            0                            0   \n",
              "\n",
              "   specific_type_Pig-based  specific_type_Pinniped-based  \\\n",
              "0                        0                             0   \n",
              "1                        0                             0   \n",
              "2                        0                             0   \n",
              "3                        0                             0   \n",
              "4                        0                             0   \n",
              "\n",
              "   specific_type_Piranha-based  specific_type_Pitcher plant-based  \\\n",
              "0                            0                                  0   \n",
              "1                            0                                  0   \n",
              "2                            0                                  0   \n",
              "3                            0                                  0   \n",
              "4                            0                                  0   \n",
              "\n",
              "   specific_type_Plectognathi-based  specific_type_Plesiosaur-based  \\\n",
              "0                                 0                               0   \n",
              "1                                 0                               0   \n",
              "2                                 0                               0   \n",
              "3                                 0                               0   \n",
              "4                                 0                               0   \n",
              "\n",
              "   specific_type_Primate-based  specific_type_Pterosaur-based  \\\n",
              "0                            0                              0   \n",
              "1                            0                              0   \n",
              "2                            0                              0   \n",
              "3                            0                              0   \n",
              "4                            0                              0   \n",
              "\n",
              "   specific_type_Quetzal-based  specific_type_Rabbit-based  \\\n",
              "0                            0                           0   \n",
              "1                            0                           0   \n",
              "2                            0                           0   \n",
              "3                            0                           0   \n",
              "4                            0                           0   \n",
              "\n",
              "   specific_type_Rafflesia-based  specific_type_Rhinoceros-based  \\\n",
              "0                              0                               0   \n",
              "1                              0                               0   \n",
              "2                              0                               0   \n",
              "3                              0                               0   \n",
              "4                              0                               0   \n",
              "\n",
              "   specific_type_Robin-based  specific_type_Rodent-based  \\\n",
              "0                          0                           0   \n",
              "1                          0                           0   \n",
              "2                          0                           0   \n",
              "3                          0                           0   \n",
              "4                          0                           0   \n",
              "\n",
              "   specific_type_Rose-based  specific_type_Salamander-based  \\\n",
              "0                         0                               0   \n",
              "1                         0                               0   \n",
              "2                         0                               0   \n",
              "3                         0                               1   \n",
              "4                         0                               1   \n",
              "\n",
              "   specific_type_Sardine-based  specific_type_Scorpion-based  \\\n",
              "0                            0                             0   \n",
              "1                            0                             0   \n",
              "2                            0                             0   \n",
              "3                            0                             0   \n",
              "4                            0                             0   \n",
              "\n",
              "   specific_type_Sea cucumber-based  specific_type_Seagull-based  \\\n",
              "0                                 0                            0   \n",
              "1                                 0                            0   \n",
              "2                                 0                            0   \n",
              "3                                 0                            0   \n",
              "4                                 0                            0   \n",
              "\n",
              "   specific_type_Shark-based  specific_type_Skunk-based  \\\n",
              "0                          0                          0   \n",
              "1                          0                          0   \n",
              "2                          0                          0   \n",
              "3                          0                          0   \n",
              "4                          0                          0   \n",
              "\n",
              "   specific_type_Snake-based  specific_type_Spider-based  \\\n",
              "0                          0                           0   \n",
              "1                          0                           0   \n",
              "2                          0                           0   \n",
              "3                          0                           0   \n",
              "4                          0                           0   \n",
              "\n",
              "   specific_type_Starfish-based  specific_type_Sunflower-based  \\\n",
              "0                             0                              0   \n",
              "1                             0                              0   \n",
              "2                             0                              0   \n",
              "3                             0                              0   \n",
              "4                             0                              0   \n",
              "\n",
              "   specific_type_Swan-based  specific_type_Syngnathidae-based  \\\n",
              "0                         0                                 0   \n",
              "1                         0                                 0   \n",
              "2                         0                                 0   \n",
              "3                         0                                 0   \n",
              "4                         0                                 0   \n",
              "\n",
              "   specific_type_Tapir-based  specific_type_Tree-based  \\\n",
              "0                          0                         0   \n",
              "1                          0                         0   \n",
              "2                          0                         0   \n",
              "3                          0                         0   \n",
              "4                          0                         0   \n",
              "\n",
              "   specific_type_Trilobite-based  specific_type_Turtle-based  \\\n",
              "0                              0                           0   \n",
              "1                              0                           0   \n",
              "2                              0                           0   \n",
              "3                              0                           0   \n",
              "4                              0                           0   \n",
              "\n",
              "   specific_type_Venus flytrap-based  specific_type_Vine-based  \\\n",
              "0                                  0                         0   \n",
              "1                                  0                         0   \n",
              "2                                  0                         0   \n",
              "3                                  0                         0   \n",
              "4                                  0                         0   \n",
              "\n",
              "   specific_type_Vulture-based  specific_type_Water lily-based  \\\n",
              "0                            0                               0   \n",
              "1                            0                               0   \n",
              "2                            0                               0   \n",
              "3                            0                               0   \n",
              "4                            0                               0   \n",
              "\n",
              "   specific_type_Weasel-based  specific_type_Whale-based  \\\n",
              "0                           0                          0   \n",
              "1                           0                          0   \n",
              "2                           0                          0   \n",
              "3                           0                          0   \n",
              "4                           0                          0   \n",
              "\n",
              "   specific_type_Wolf-based  \n",
              "0                         0  \n",
              "1                         0  \n",
              "2                         0  \n",
              "3                         0  \n",
              "4                         0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-16ebd72f-44dd-4ad8-906f-4386fb672478\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>attack</th>\n",
              "      <th>capture_rate</th>\n",
              "      <th>hp</th>\n",
              "      <th>sp_attack</th>\n",
              "      <th>sp_defense</th>\n",
              "      <th>weight_kg</th>\n",
              "      <th>generation</th>\n",
              "      <th>is_legendary</th>\n",
              "      <th>red1</th>\n",
              "      <th>green1</th>\n",
              "      <th>blue1</th>\n",
              "      <th>red2</th>\n",
              "      <th>green2</th>\n",
              "      <th>blue2</th>\n",
              "      <th>red3</th>\n",
              "      <th>green3</th>\n",
              "      <th>blue3</th>\n",
              "      <th>super_type_Amphibian Pokémon</th>\n",
              "      <th>super_type_Arthropod Pokémon</th>\n",
              "      <th>super_type_Avian Pokémon</th>\n",
              "      <th>super_type_Clitellata Pokémon</th>\n",
              "      <th>super_type_Cnidaria Pokémon</th>\n",
              "      <th>super_type_Echinoderm Pokémon</th>\n",
              "      <th>super_type_Fish Pokémon</th>\n",
              "      <th>super_type_Mammalian Pokémon</th>\n",
              "      <th>super_type_Mollusc Pokémon</th>\n",
              "      <th>super_type_Plant Pokémon</th>\n",
              "      <th>super_type_Reptilian Pokémon</th>\n",
              "      <th>specific_type_Anglerfish-based</th>\n",
              "      <th>specific_type_Anteater-based</th>\n",
              "      <th>specific_type_Antlion-based</th>\n",
              "      <th>specific_type_Banana tree-based</th>\n",
              "      <th>specific_type_Bat-based</th>\n",
              "      <th>specific_type_Bear-based</th>\n",
              "      <th>specific_type_Bird-based</th>\n",
              "      <th>specific_type_Bivalve-based</th>\n",
              "      <th>specific_type_Bluebird-based</th>\n",
              "      <th>specific_type_Bovine-based</th>\n",
              "      <th>specific_type_Bud-based</th>\n",
              "      <th>specific_type_Butterflyfish-based</th>\n",
              "      <th>specific_type_Cactus-based</th>\n",
              "      <th>specific_type_Camel-based</th>\n",
              "      <th>specific_type_Canine-based</th>\n",
              "      <th>specific_type_Caprid-based</th>\n",
              "      <th>specific_type_Carp-based</th>\n",
              "      <th>specific_type_Catfish-based</th>\n",
              "      <th>specific_type_Cephalopod-based</th>\n",
              "      <th>specific_type_Cherry-based</th>\n",
              "      <th>specific_type_Chestnut-based</th>\n",
              "      <th>specific_type_Cocoon-based</th>\n",
              "      <th>specific_type_Coelacanth-based</th>\n",
              "      <th>specific_type_Coniferous tree-based</th>\n",
              "      <th>specific_type_Coral-based</th>\n",
              "      <th>specific_type_Cotton-based</th>\n",
              "      <th>specific_type_Crinoid-based</th>\n",
              "      <th>specific_type_Crocodile-based</th>\n",
              "      <th>specific_type_Crow-based</th>\n",
              "      <th>specific_type_Crustacean-based</th>\n",
              "      <th>specific_type_Dandelion-based</th>\n",
              "      <th>specific_type_Deer-based</th>\n",
              "      <th>specific_type_Dinocaridid-based</th>\n",
              "      <th>specific_type_Dinosaur-based</th>\n",
              "      <th>specific_type_Discus-based</th>\n",
              "      <th>specific_type_Duck-based</th>\n",
              "      <th>specific_type_Durian-based</th>\n",
              "      <th>specific_type_Earthworm-based</th>\n",
              "      <th>specific_type_Eel-based</th>\n",
              "      <th>specific_type_Elephant-based</th>\n",
              "      <th>specific_type_Equidae-based</th>\n",
              "      <th>specific_type_Falcon-based</th>\n",
              "      <th>specific_type_Feline-based</th>\n",
              "      <th>specific_type_Flamingo-based</th>\n",
              "      <th>specific_type_Flatfish-based</th>\n",
              "      <th>specific_type_Flower-based</th>\n",
              "      <th>specific_type_Fly agaric-based</th>\n",
              "      <th>specific_type_Fox-based</th>\n",
              "      <th>specific_type_Frog- and toad-based</th>\n",
              "      <th>specific_type_Fungus-based</th>\n",
              "      <th>specific_type_Galliform-based</th>\n",
              "      <th>specific_type_Gastropod-based</th>\n",
              "      <th>specific_type_Geastrales-based</th>\n",
              "      <th>specific_type_Geranium-based</th>\n",
              "      <th>specific_type_Glyptodont-based</th>\n",
              "      <th>specific_type_Hedgehog-based</th>\n",
              "      <th>specific_type_Hippopotamus-based</th>\n",
              "      <th>specific_type_Honeycreeper-based</th>\n",
              "      <th>specific_type_Horseshoe crab-based</th>\n",
              "      <th>specific_type_Hyena-based</th>\n",
              "      <th>specific_type_Jellyfish-based</th>\n",
              "      <th>specific_type_Kangaroo-based</th>\n",
              "      <th>specific_type_Lamprey-based</th>\n",
              "      <th>specific_type_Leaf-based</th>\n",
              "      <th>specific_type_Lepidopteran-based</th>\n",
              "      <th>specific_type_Lilium-based</th>\n",
              "      <th>specific_type_Lizard-based</th>\n",
              "      <th>specific_type_Loach-based</th>\n",
              "      <th>specific_type_Mangosteen-based</th>\n",
              "      <th>specific_type_Manta ray-based</th>\n",
              "      <th>specific_type_Mantis-based</th>\n",
              "      <th>specific_type_Marlin-based</th>\n",
              "      <th>specific_type_Mole-based</th>\n",
              "      <th>specific_type_Oak tree-based</th>\n",
              "      <th>specific_type_Orca-based</th>\n",
              "      <th>specific_type_Owl-based</th>\n",
              "      <th>specific_type_Palm tree-based</th>\n",
              "      <th>specific_type_Pangolin-based</th>\n",
              "      <th>specific_type_Pelican-based</th>\n",
              "      <th>specific_type_Penguin-based</th>\n",
              "      <th>specific_type_Percoid-based</th>\n",
              "      <th>specific_type_Pig-based</th>\n",
              "      <th>specific_type_Pinniped-based</th>\n",
              "      <th>specific_type_Piranha-based</th>\n",
              "      <th>specific_type_Pitcher plant-based</th>\n",
              "      <th>specific_type_Plectognathi-based</th>\n",
              "      <th>specific_type_Plesiosaur-based</th>\n",
              "      <th>specific_type_Primate-based</th>\n",
              "      <th>specific_type_Pterosaur-based</th>\n",
              "      <th>specific_type_Quetzal-based</th>\n",
              "      <th>specific_type_Rabbit-based</th>\n",
              "      <th>specific_type_Rafflesia-based</th>\n",
              "      <th>specific_type_Rhinoceros-based</th>\n",
              "      <th>specific_type_Robin-based</th>\n",
              "      <th>specific_type_Rodent-based</th>\n",
              "      <th>specific_type_Rose-based</th>\n",
              "      <th>specific_type_Salamander-based</th>\n",
              "      <th>specific_type_Sardine-based</th>\n",
              "      <th>specific_type_Scorpion-based</th>\n",
              "      <th>specific_type_Sea cucumber-based</th>\n",
              "      <th>specific_type_Seagull-based</th>\n",
              "      <th>specific_type_Shark-based</th>\n",
              "      <th>specific_type_Skunk-based</th>\n",
              "      <th>specific_type_Snake-based</th>\n",
              "      <th>specific_type_Spider-based</th>\n",
              "      <th>specific_type_Starfish-based</th>\n",
              "      <th>specific_type_Sunflower-based</th>\n",
              "      <th>specific_type_Swan-based</th>\n",
              "      <th>specific_type_Syngnathidae-based</th>\n",
              "      <th>specific_type_Tapir-based</th>\n",
              "      <th>specific_type_Tree-based</th>\n",
              "      <th>specific_type_Trilobite-based</th>\n",
              "      <th>specific_type_Turtle-based</th>\n",
              "      <th>specific_type_Venus flytrap-based</th>\n",
              "      <th>specific_type_Vine-based</th>\n",
              "      <th>specific_type_Vulture-based</th>\n",
              "      <th>specific_type_Water lily-based</th>\n",
              "      <th>specific_type_Weasel-based</th>\n",
              "      <th>specific_type_Whale-based</th>\n",
              "      <th>specific_type_Wolf-based</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>49</td>\n",
              "      <td>45</td>\n",
              "      <td>45</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>6.9</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>57</td>\n",
              "      <td>148</td>\n",
              "      <td>148</td>\n",
              "      <td>98</td>\n",
              "      <td>213</td>\n",
              "      <td>180</td>\n",
              "      <td>131</td>\n",
              "      <td>238</td>\n",
              "      <td>197</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>62</td>\n",
              "      <td>45</td>\n",
              "      <td>60</td>\n",
              "      <td>80</td>\n",
              "      <td>80</td>\n",
              "      <td>13.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>90</td>\n",
              "      <td>205</td>\n",
              "      <td>189</td>\n",
              "      <td>32</td>\n",
              "      <td>148</td>\n",
              "      <td>131</td>\n",
              "      <td>49</td>\n",
              "      <td>123</td>\n",
              "      <td>82</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100</td>\n",
              "      <td>45</td>\n",
              "      <td>80</td>\n",
              "      <td>122</td>\n",
              "      <td>120</td>\n",
              "      <td>100.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>32</td>\n",
              "      <td>180</td>\n",
              "      <td>156</td>\n",
              "      <td>90</td>\n",
              "      <td>213</td>\n",
              "      <td>197</td>\n",
              "      <td>255</td>\n",
              "      <td>123</td>\n",
              "      <td>115</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>52</td>\n",
              "      <td>45</td>\n",
              "      <td>39</td>\n",
              "      <td>60</td>\n",
              "      <td>50</td>\n",
              "      <td>8.5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>255</td>\n",
              "      <td>148</td>\n",
              "      <td>65</td>\n",
              "      <td>222</td>\n",
              "      <td>82</td>\n",
              "      <td>57</td>\n",
              "      <td>255</td>\n",
              "      <td>213</td>\n",
              "      <td>123</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>64</td>\n",
              "      <td>45</td>\n",
              "      <td>58</td>\n",
              "      <td>80</td>\n",
              "      <td>65</td>\n",
              "      <td>19.0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>205</td>\n",
              "      <td>57</td>\n",
              "      <td>57</td>\n",
              "      <td>255</td>\n",
              "      <td>82</td>\n",
              "      <td>74</td>\n",
              "      <td>255</td>\n",
              "      <td>65</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-16ebd72f-44dd-4ad8-906f-4386fb672478')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      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",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-16ebd72f-44dd-4ad8-906f-4386fb672478 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-16ebd72f-44dd-4ad8-906f-4386fb672478');\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-f3cea3d8-3551-437f-ad7b-b9430a9c9abd\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f3cea3d8-3551-437f-ad7b-b9430a9c9abd')\"\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",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\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-f3cea3d8-3551-437f-ad7b-b9430a9c9abd button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "X"
            }
          },
          "metadata": {},
          "execution_count": 536
        }
      ],
      "source": [
        "X.head()"
      ],
      "id": "4c156791-7bc6-4169-951b-5f41859ab743"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ca55d3c3-eefd-4c2c-acd9-6c32789ec146",
        "outputId": "921ca690-048f-4c71-c7d1-c6c26c08cae8"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 412 entries, 0 to 799\n",
            "Columns: 148 entries, attack to specific_type_Wolf-based\n",
            "dtypes: float64(1), int64(16), uint8(131)\n",
            "memory usage: 110.6 KB\n"
          ]
        }
      ],
      "source": [
        "X.info()"
      ],
      "id": "ca55d3c3-eefd-4c2c-acd9-6c32789ec146"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "27549671-608e-4181-89df-8deae9161974"
      },
      "outputs": [],
      "source": [
        "pd.set_option('display.max_columns', None)"
      ],
      "id": "27549671-608e-4181-89df-8deae9161974"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "c9622803-b97f-4647-8d6c-fee2924475a6"
      },
      "source": [
        "#### Normalização"
      ],
      "id": "c9622803-b97f-4647-8d6c-fee2924475a6"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ffd04013-8b99-482f-afd3-35a70d0b90b6"
      },
      "outputs": [],
      "source": [
        "from sklearn.preprocessing import Normalizer\n",
        "\n",
        "norm_X = Normalizer().fit_transform(X)"
      ],
      "id": "ffd04013-8b99-482f-afd3-35a70d0b90b6"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "710a770b-02fa-4be5-83b9-7cd205fc8d0b"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split"
      ],
      "id": "710a770b-02fa-4be5-83b9-7cd205fc8d0b"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "21b8eca4-6f7b-47b3-b89b-e8179d2ff6ee"
      },
      "outputs": [],
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(norm_X, y, test_size=0.20, random_state=42)"
      ],
      "id": "21b8eca4-6f7b-47b3-b89b-e8179d2ff6ee"
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### KNN"
      ],
      "metadata": {
        "id": "DrVRTT8_-o-o"
      },
      "id": "DrVRTT8_-o-o"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "f30a1fa4-5c83-4078-8169-a2de89b2063e"
      },
      "outputs": [],
      "source": [
        "from sklearn.neighbors import KNeighborsClassifier\n",
        "from sklearn.metrics import confusion_matrix, accuracy_score, ConfusionMatrixDisplay"
      ],
      "id": "f30a1fa4-5c83-4078-8169-a2de89b2063e"
    },
    {
      "cell_type": "code",
      "source": [
        "neighbours = [5, 10, 15, 20, 25, 30, 35, 40]\n",
        "weights = ['uniform', 'distance']\n",
        "algorithm = ['ball_tree', 'kd_tree', 'brute']\n",
        "leaf_size = [25, 30, 35, 40, 45]\n",
        "best_params = {\"neighbours\": 0, \"weights\": \"uniform\", \"algorithm\": \"ball_tree\", \"leaf_size\": 30}\n",
        "best_acc = 0\n",
        "\n",
        "\n",
        "for n in neighbours:\n",
        "  for w in weights:\n",
        "    for a in algorithm:\n",
        "      for l in leaf_size:\n",
        "        model = KNeighborsClassifier(n_neighbors=n, weights=w, algorithm=a, leaf_size=l)\n",
        "        model.fit(X_train, y_train)\n",
        "        prev = model.predict(X_test)\n",
        "        acc = accuracy_score(y_test, prev) * 100\n",
        "        if acc > best_acc:\n",
        "          best_acc = acc\n",
        "          best_params['neighbours'] = n\n",
        "          best_params['weights'] = w\n",
        "          best_params['algorithm'] = a\n",
        "          best_params['leaf_size'] = l"
      ],
      "metadata": {
        "id": "fwWzjJRHYlak"
      },
      "id": "fwWzjJRHYlak",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "best_params"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "veLPcd8TYqEG",
        "outputId": "eb31deb7-fecd-40b0-a8e4-bde86abd50c9"
      },
      "id": "veLPcd8TYqEG",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'neighbours': 15,\n",
              " 'weights': 'uniform',\n",
              " 'algorithm': 'ball_tree',\n",
              " 'leaf_size': 25}"
            ]
          },
          "metadata": {},
          "execution_count": 544
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "16f78ac4-bca9-4833-95d3-ef240038f071"
      },
      "outputs": [],
      "source": [
        "neigh = KNeighborsClassifier(algorithm='ball_tree', n_neighbors=15, weights='uniform', leaf_size=25).fit(X_train, y_train)"
      ],
      "id": "16f78ac4-bca9-4833-95d3-ef240038f071"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "2a1a726d-0c6b-406b-8ada-1e776e6abaee"
      },
      "outputs": [],
      "source": [
        "y_pred = neigh.predict(X_test)"
      ],
      "id": "2a1a726d-0c6b-406b-8ada-1e776e6abaee"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "c1c00693-d2cb-4c64-ac5f-f6a19027579f"
      },
      "outputs": [],
      "source": [
        "from sklearn.metrics import confusion_matrix, accuracy_score, ConfusionMatrixDisplay\n",
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt"
      ],
      "id": "c1c00693-d2cb-4c64-ac5f-f6a19027579f"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "917c42a6-db33-43be-9aa7-dae459e3179c",
        "outputId": "db1679ba-5273-478e-b3ca-86eefca4817a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "cm = confusion_matrix(y_test, y_pred)\n",
        "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=le.classes_.tolist())\n",
        "disp.plot(xticks_rotation='vertical');"
      ],
      "id": "917c42a6-db33-43be-9aa7-dae459e3179c"
    },
    {
      "cell_type": "code",
      "source": [
        "X_train_pred = neigh.predict(X_train)"
      ],
      "metadata": {
        "id": "zWtq9TwJ_6Le"
      },
      "id": "zWtq9TwJ_6Le",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "round(accuracy_score(y_train, X_train_pred) * 100, 2) # Porcentagem treino"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yjBOxYmrAD-D",
        "outputId": "27b50e87-031d-4979-ec3f-e2c34ccef1e8"
      },
      "id": "yjBOxYmrAD-D",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "42.55"
            ]
          },
          "metadata": {},
          "execution_count": 550
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2395feb0-6be1-49a9-971d-51d54367f45f",
        "outputId": "066e70ef-1cf4-4ef3-aea5-8b3e80c901d9"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "53.01"
            ]
          },
          "metadata": {},
          "execution_count": 551
        }
      ],
      "source": [
        "round(accuracy_score(y_test, y_pred) * 100, 2) # Porcentagem teste"
      ],
      "id": "2395feb0-6be1-49a9-971d-51d54367f45f"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "c2c1e95f-44ac-4266-b9d8-678b58b24227",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "outputId": "13096f3c-bf55-4f57-ac80-981cdb6bf248"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "cm = confusion_matrix(X_train_pred, y_train)\n",
        "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=le.classes_.tolist())\n",
        "disp.plot(xticks_rotation='vertical');"
      ],
      "id": "c2c1e95f-44ac-4266-b9d8-678b58b24227"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "41f64b4f-4b33-4cbc-8cdf-43ebb6c40ec1",
        "outputId": "c5d00635-b114-4af2-a39e-13e52eb4184d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(12,)"
            ]
          },
          "metadata": {},
          "execution_count": 553
        }
      ],
      "source": [
        "np.unique(y_test).shape"
      ],
      "id": "41f64b4f-4b33-4cbc-8cdf-43ebb6c40ec1"
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### MLP"
      ],
      "metadata": {
        "id": "xgW-IwUt8Uxm"
      },
      "id": "xgW-IwUt8Uxm"
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ElgqURJgPrJO"
      },
      "outputs": [],
      "source": [
        "from sklearn.neural_network import MLPClassifier\n",
        "import warnings\n",
        "warnings.filterwarnings('ignore')\n",
        "scale = Normalizer()"
      ],
      "id": "ElgqURJgPrJO"
    },
    {
      "cell_type": "code",
      "source": [
        "# X_train, X_val, y_train, y_val = train_test_split(X_train, y_train, test_size=0.2, random_state=42)\n",
        "# x_train_norm = scale.fit_transform(X_train)\n",
        "# x_val_norm = scale.fit_transform(X_val)"
      ],
      "metadata": {
        "id": "HeY1kHzF8bns"
      },
      "id": "HeY1kHzF8bns",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.15, random_state=42)"
      ],
      "metadata": {
        "id": "nZQKpqoq8rOd"
      },
      "id": "nZQKpqoq8rOd",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "scale = Normalizer()\n",
        "X_train_norm = scale.fit_transform(X_train)\n",
        "X_test_norm = scale.fit_transform(X_test)"
      ],
      "metadata": {
        "id": "zDF0Ho9p4696"
      },
      "id": "zDF0Ho9p4696",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "modelo = MLPClassifier(\n",
        "            hidden_layer_sizes = (50,), activation = 'logistic',\n",
        "            learning_rate_init = 0.001, max_iter = 1000)\n",
        "modelo.fit(X_train_norm, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "oUCODpgz3adX",
        "outputId": "90edd764-9628-476f-ed15-fdf3b2d9b250"
      },
      "id": "oUCODpgz3adX",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "MLPClassifier(activation='logistic', hidden_layer_sizes=(50,), max_iter=1000)"
            ],
            "text/html": [
              "<style>#sk-container-id-14 {color: black;background-color: white;}#sk-container-id-14 pre{padding: 0;}#sk-container-id-14 div.sk-toggleable {background-color: white;}#sk-container-id-14 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-14 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-14 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-14 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-14 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-14 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-14 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-14 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-14 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-14 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-14 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-14 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-14 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-14 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-14 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-14 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-14 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-14 div.sk-item {position: relative;z-index: 1;}#sk-container-id-14 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-14 div.sk-item::before, #sk-container-id-14 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-14 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-14 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-14 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-14 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-14 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-14 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-14 div.sk-label-container {text-align: center;}#sk-container-id-14 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-14 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-14\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>MLPClassifier(activation=&#x27;logistic&#x27;, hidden_layer_sizes=(50,), max_iter=1000)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-14\" type=\"checkbox\" checked><label for=\"sk-estimator-id-14\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">MLPClassifier</label><div class=\"sk-toggleable__content\"><pre>MLPClassifier(activation=&#x27;logistic&#x27;, hidden_layer_sizes=(50,), max_iter=1000)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 577
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Melhores parâmetros"
      ],
      "metadata": {
        "id": "6Sgdguf-9kaO"
      },
      "id": "6Sgdguf-9kaO"
    },
    {
      "cell_type": "code",
      "source": [
        "# h_neuronios = [10, 50, 100]\n",
        "# f_activations = ['relu', 'logistic']\n",
        "# learning_rate_init_values = [0.1, 0.001, 0.0001]\n",
        "# qtd_epochs = [10, 100, 1000]\n",
        "\n",
        "\n",
        "# melhor_parametros = \"\"\n",
        "# best_model = None\n",
        "# best_mean_acc = 0\n",
        "\n",
        "# for h in h_neuronios:\n",
        "#   for f in f_activations:\n",
        "#     for r in learning_rate_init_values:\n",
        "#       for e in qtd_epochs:\n",
        "\n",
        "#         modelo = MLPClassifier(\n",
        "#             hidden_layer_sizes = (h,), activation = f,\n",
        "#             learning_rate_init = r, max_iter = e )\n",
        "\n",
        "#         sum_acc = 0\n",
        "#         for i in range(5):\n",
        "\n",
        "#           modelo.fit(x_train_norm, y_train)\n",
        "#           prev = modelo.predict(x_val_norm)\n",
        "#           acc = accuracy_score(y_val, prev) * 100\n",
        "\n",
        "#           sum_acc += acc\n",
        "\n",
        "#         mean_acc = sum_acc/5\n",
        "#         if mean_acc > best_mean_acc:\n",
        "#           best_mean_acc = mean_acc\n",
        "#           best_model = modelo\n",
        "#           melhor_parametros = f\"h:{h}-f:{f}-r:{r}-e:{e} --- ACC: {acc}\""
      ],
      "metadata": {
        "id": "QjS7dTd78dQd"
      },
      "id": "QjS7dTd78dQd",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# melhor_parametros"
      ],
      "metadata": {
        "id": "5N9duPAr8ndo"
      },
      "id": "5N9duPAr8ndo",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Previsão e métrica"
      ],
      "metadata": {
        "id": "AYX7Gom4GUUy"
      },
      "id": "AYX7Gom4GUUy"
    },
    {
      "cell_type": "code",
      "source": [
        "X_train_prev = modelo.predict(X_train)"
      ],
      "metadata": {
        "id": "r93jsEp_B9MS"
      },
      "id": "r93jsEp_B9MS",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "round(accuracy_score(y_train, X_train_prev) * 100, 2) # Porcentagem do treino"
      ],
      "metadata": {
        "id": "RwIZ-qG1B01m",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f196d5ae-22f9-4221-8166-47547a0d4b45"
      },
      "id": "RwIZ-qG1B01m",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "41.14"
            ]
          },
          "metadata": {},
          "execution_count": 581
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "prev = modelo.predict(X_test)"
      ],
      "metadata": {
        "id": "-WdABAoL8tju"
      },
      "id": "-WdABAoL8tju",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "round(accuracy_score(y_test, prev) * 100, 2) # Porcentagem do teste"
      ],
      "metadata": {
        "id": "H6KxBJy88vCE",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c6c97076-a45c-45e1-c172-c5b991790c4f"
      },
      "id": "H6KxBJy88vCE",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "41.94"
            ]
          },
          "metadata": {},
          "execution_count": 583
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cm = confusion_matrix(y_test, prev)\n",
        "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=le.classes_.tolist())\n",
        "disp.plot(xticks_rotation='vertical');"
      ],
      "metadata": {
        "id": "rWzj47OC-W4n",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 493
        },
        "outputId": "88082eb3-2f89-4d63-d5ed-b97586282154"
      },
      "id": "rWzj47OC-W4n",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Decision Tree"
      ],
      "metadata": {
        "id": "F8JVjGLt_9b9"
      },
      "id": "F8JVjGLt_9b9"
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.tree import DecisionTreeClassifier"
      ],
      "metadata": {
        "id": "8us1awHsFwXh"
      },
      "id": "8us1awHsFwXh",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Melhores parâmetros"
      ],
      "metadata": {
        "id": "IRGYENoEGBO5"
      },
      "id": "IRGYENoEGBO5"
    },
    {
      "cell_type": "code",
      "source": [
        "# from sklearn.tree import DecisionTreeClassifier\n",
        "# criterios = [\"gini\", \"entropy\", \"log_loss\"]\n",
        "# max_depth = [2, 4, 8, 10]\n",
        "# best_params = {\"criterio\" : \"entropy\", \"max_depth\": 0}\n",
        "# best_acc = 0\n",
        "\n",
        "\n",
        "# for c in criterios:\n",
        "#   for m in max_depth:\n",
        "\n",
        "#     modelo = DecisionTreeClassifier(\n",
        "#         criterion=c,\n",
        "#         max_depth=m,\n",
        "#         random_state = 42\n",
        "#         )\n",
        "\n",
        "#     modelo.fit(X_train, y_train)\n",
        "#     prev = modelo.predict(X_val)\n",
        "#     acc = accuracy_score(y_val, prev) * 100\n",
        "#     if acc > best_acc:\n",
        "#       print(best_acc)\n",
        "#       best_acc = acc\n",
        "#       best_params['criterio'] = c\n",
        "#       best_params['max_depth'] = m"
      ],
      "metadata": {
        "id": "W8Iw0EuBApJa"
      },
      "id": "W8Iw0EuBApJa",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# best_params"
      ],
      "metadata": {
        "id": "XCkAYy87A5AL"
      },
      "id": "XCkAYy87A5AL",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Treino"
      ],
      "metadata": {
        "id": "Bc9124InGFkB"
      },
      "id": "Bc9124InGFkB"
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
      ],
      "metadata": {
        "id": "DLiv67y7A7VJ"
      },
      "id": "DLiv67y7A7VJ",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "modelo = DecisionTreeClassifier(\n",
        "        criterion='entropy',\n",
        "        max_depth=10,\n",
        "        random_state = 42\n",
        "        )"
      ],
      "metadata": {
        "id": "MPQJnCI_A-4a"
      },
      "id": "MPQJnCI_A-4a",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "modelo.fit(X_train, y_train)"
      ],
      "metadata": {
        "id": "Qq-YMXUvBCkM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c6c7bf1f-0887-4d78-906a-5521467582d8"
      },
      "id": "Qq-YMXUvBCkM",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DecisionTreeClassifier(criterion='entropy', max_depth=10, random_state=42)"
            ],
            "text/html": [
              "<style>#sk-container-id-17 {color: black;background-color: white;}#sk-container-id-17 pre{padding: 0;}#sk-container-id-17 div.sk-toggleable {background-color: white;}#sk-container-id-17 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-17 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-17 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-17 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-17 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-17 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-17 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-17 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-17 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-17 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-17 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-17 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-17 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-17 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-17 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-17 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-17 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-17 div.sk-item {position: relative;z-index: 1;}#sk-container-id-17 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-17 div.sk-item::before, #sk-container-id-17 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-17 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-17 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-17 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-17 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-17 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-17 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-17 div.sk-label-container {text-align: center;}#sk-container-id-17 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-17 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-17\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=10, random_state=42)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-17\" type=\"checkbox\" checked><label for=\"sk-estimator-id-17\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">DecisionTreeClassifier</label><div class=\"sk-toggleable__content\"><pre>DecisionTreeClassifier(criterion=&#x27;entropy&#x27;, max_depth=10, random_state=42)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 617
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##### Previsão e métrica"
      ],
      "metadata": {
        "id": "K79oQ71PGJOI"
      },
      "id": "K79oQ71PGJOI"
    },
    {
      "cell_type": "code",
      "source": [
        "X_train_prev2 = modelo.predict(X_train)"
      ],
      "metadata": {
        "id": "nJrmp8AhCVlZ"
      },
      "id": "nJrmp8AhCVlZ",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "round(accuracy_score(y_train, X_train_prev2) * 100, 2) # Porcentagem do treino"
      ],
      "metadata": {
        "id": "oEblaJbCCVYD",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "fc255bfb-a015-498b-f587-a96d32bb1ddb"
      },
      "id": "oEblaJbCCVYD",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "99.7"
            ]
          },
          "metadata": {},
          "execution_count": 619
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "prev = modelo.predict(X_test)"
      ],
      "metadata": {
        "id": "59xCIWPMBEYv"
      },
      "id": "59xCIWPMBEYv",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "round(accuracy_score(y_test, prev) * 100, 2) # Porcentagem do teste"
      ],
      "metadata": {
        "id": "dCnTnMRKBEnt",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8d785434-e823-4517-8f6b-1471645644fb"
      },
      "id": "dCnTnMRKBEnt",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "44.58"
            ]
          },
          "metadata": {},
          "execution_count": 621
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# import graphviz\n",
        "# from sklearn.tree import plot_tree\n",
        "# from sklearn import tree\n",
        "# dot_data = tree.export_graphviz(modelo, out_file=None)\n",
        "# graph = graphviz.Source(dot_data)\n",
        "# graph.render(\"Pokemon\")"
      ],
      "metadata": {
        "id": "zXV531DcBNvn"
      },
      "id": "zXV531DcBNvn",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cm = confusion_matrix(y_test, prev)\n",
        "disp = ConfusionMatrixDisplay(confusion_matrix=cm, display_labels=le.classes_.tolist())\n",
        "disp.plot(xticks_rotation='vertical');"
      ],
      "metadata": {
        "id": "TiTDZ244CCCy",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "cb1b81c0-c7f0-46b4-ba1d-5d27d992aaf2"
      },
      "id": "TiTDZ244CCCy",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": [],
      "collapsed_sections": [
        "3bb26880-0b40-4a7d-a848-d01f0c09e096",
        "3bc6833b-3261-4b9f-82d5-4781c0440d7a",
        "b6d0b574-5d38-4703-8f64-64df2d12b491",
        "628217e7-9c3b-4bc1-993a-5b8dce809287",
        "1e321254-9baf-4028-9bf8-c4457133b1f2",
        "6ff92aa6-4df3-40fd-9a61-5ab26cdecc62",
        "XN_oevLeyUCv",
        "843face8-aba1-4b32-8a9c-b9b9e1d1c0a1",
        "tQ2fGWDBA2-z",
        "QT6bcvgZBBWg",
        "c9622803-b97f-4647-8d6c-fee2924475a6",
        "xgW-IwUt8Uxm",
        "6Sgdguf-9kaO",
        "AYX7Gom4GUUy",
        "F8JVjGLt_9b9",
        "IRGYENoEGBO5",
        "Bc9124InGFkB",
        "K79oQ71PGJOI"
      ],
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3 (ipykernel)",
      "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": "3.11.7"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}