Tech_Challenge_5_Previsão_de_ponto_de_virada_dos_alunos.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Notebook: Criação de modelo - Previsão do ponto de virada dos alunos\n",
        "Este notebook tem como objetivo criar um modelo XGBoost para prever o ponto de virada dos alunos, utilizando algumas características específicas. Uma parte dessas características envolve a análise de sentimentos via NLP para processar os comentários feitos pelos professores. Esses comentários ajudam o modelo a identificar o ponto de virada dos alunos, fornecendo uma visão mais clara sobre o progresso e as mudanças importantes em seu desempenho."
      ],
      "metadata": {
        "id": "ohWxBquUtbeq"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 1) Instalações e Imports"
      ],
      "metadata": {
        "id": "-Oa4QdkttYuR"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip show scikit-learn"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9Kxm1BInGTMY",
        "outputId": "3a97f366-84be-4c4e-dfab-1e7aa452d3dd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Name: scikit-learn\n",
            "Version: 1.3.2\n",
            "Summary: A set of python modules for machine learning and data mining\n",
            "Home-page: http://scikit-learn.org\n",
            "Author: \n",
            "Author-email: \n",
            "License: new BSD\n",
            "Location: /usr/local/lib/python3.10/dist-packages\n",
            "Requires: joblib, numpy, scipy, threadpoolctl\n",
            "Required-by: albumentations, bigframes, fastai, imbalanced-learn, librosa, mlxtend, sklearn-pandas, yellowbrick\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# para tratar datasets desbalanceados\n",
        "!pip install imbalanced-learn"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qU1cN-qFj198",
        "outputId": "f65b6452-964f-4294-bd1c-6c2f02bf61b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: imbalanced-learn in /usr/local/lib/python3.10/dist-packages (0.12.3)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.25.2)\n",
            "Requirement already satisfied: scipy>=1.5.0 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.13.1)\n",
            "Requirement already satisfied: scikit-learn>=1.0.2 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.3.2)\n",
            "Requirement already satisfied: joblib>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (1.4.2)\n",
            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from imbalanced-learn) (3.5.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# para utilizar no lemmatizer com um dicionário em pt-BR\n",
        "!python -m spacy download pt_core_news_sm"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wNJGF9LucMTG",
        "outputId": "84a78ff0-3411-4ed1-8107-ab09c9055e69"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pt-core-news-sm==3.7.0\n",
            "  Downloading https://github.com/explosion/spacy-models/releases/download/pt_core_news_sm-3.7.0/pt_core_news_sm-3.7.0-py3-none-any.whl (13.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.0/13.0 MB\u001b[0m \u001b[31m49.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: spacy<3.8.0,>=3.7.0 in /usr/local/lib/python3.10/dist-packages (from pt-core-news-sm==3.7.0) (3.7.5)\n",
            "Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.11 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.0.12)\n",
            "Requirement already satisfied: spacy-loggers<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.0.5)\n",
            "Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.0.10)\n",
            "Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.0.8)\n",
            "Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.0.9)\n",
            "Requirement already satisfied: thinc<8.3.0,>=8.2.2 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (8.2.5)\n",
            "Requirement already satisfied: wasabi<1.2.0,>=0.9.1 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.1.3)\n",
            "Requirement already satisfied: srsly<3.0.0,>=2.4.3 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.4.8)\n",
            "Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.0.10)\n",
            "Requirement already satisfied: weasel<0.5.0,>=0.1.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.4.1)\n",
            "Requirement already satisfied: typer<1.0.0,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.12.3)\n",
            "Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (4.66.4)\n",
            "Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.31.0)\n",
            "Requirement already satisfied: pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.8.2)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.1.4)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (71.0.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (24.1)\n",
            "Requirement already satisfied: langcodes<4.0.0,>=3.2.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.4.0)\n",
            "Requirement already satisfied: numpy>=1.19.0 in /usr/local/lib/python3.10/dist-packages (from spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.25.2)\n",
            "Requirement already satisfied: language-data>=1.2 in /usr/local/lib/python3.10/dist-packages (from langcodes<4.0.0,>=3.2.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.2.0)\n",
            "Requirement already satisfied: annotated-types>=0.4.0 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.7.0)\n",
            "Requirement already satisfied: pydantic-core==2.20.1 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.20.1)\n",
            "Requirement already satisfied: typing-extensions>=4.6.1 in /usr/local/lib/python3.10/dist-packages (from pydantic!=1.8,!=1.8.1,<3.0.0,>=1.7.4->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (4.12.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0.0,>=2.13.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2024.7.4)\n",
            "Requirement already satisfied: blis<0.8.0,>=0.7.8 in /usr/local/lib/python3.10/dist-packages (from thinc<8.3.0,>=8.2.2->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.7.11)\n",
            "Requirement already satisfied: confection<1.0.0,>=0.0.1 in /usr/local/lib/python3.10/dist-packages (from thinc<8.3.0,>=8.2.2->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.1.5)\n",
            "Requirement already satisfied: click>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0.0,>=0.3.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (8.1.7)\n",
            "Requirement already satisfied: shellingham>=1.3.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0.0,>=0.3.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.5.4)\n",
            "Requirement already satisfied: rich>=10.11.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0.0,>=0.3.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (13.7.1)\n",
            "Requirement already satisfied: cloudpathlib<1.0.0,>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from weasel<0.5.0,>=0.1.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.18.1)\n",
            "Requirement already satisfied: smart-open<8.0.0,>=5.2.1 in /usr/local/lib/python3.10/dist-packages (from weasel<0.5.0,>=0.1.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (7.0.4)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.1.5)\n",
            "Requirement already satisfied: marisa-trie>=0.7.7 in /usr/local/lib/python3.10/dist-packages (from language-data>=1.2->langcodes<4.0.0,>=3.2.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.2.0)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer<1.0.0,>=0.3.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer<1.0.0,>=0.3.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (2.16.1)\n",
            "Requirement already satisfied: wrapt in /usr/local/lib/python3.10/dist-packages (from smart-open<8.0.0,>=5.2.1->weasel<0.5.0,>=0.1.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (1.14.1)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0.0,>=0.3.0->spacy<3.8.0,>=3.7.0->pt-core-news-sm==3.7.0) (0.1.2)\n",
            "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
            "You can now load the package via spacy.load('pt_core_news_sm')\n",
            "\u001b[38;5;3m⚠ Restart to reload dependencies\u001b[0m\n",
            "If you are in a Jupyter or Colab notebook, you may need to restart Python in\n",
            "order to load all the package's dependencies. You can do this by selecting the\n",
            "'Restart kernel' or 'Restart runtime' option.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import joblib\n",
        "import nltk\n",
        "import re\n",
        "import string\n",
        "import unicodedata\n",
        "import spacy\n",
        "import joblib\n",
        "from nltk.tokenize import word_tokenize\n",
        "from nltk.corpus import stopwords\n",
        "from sklearn.ensemble import GradientBoostingClassifier\n",
        "from sklearn.preprocessing import StandardScaler, LabelEncoder, OneHotEncoder\n",
        "from sklearn.model_selection import train_test_split, cross_val_score, KFold, GridSearchCV, StratifiedKFold\n",
        "from sklearn.metrics import accuracy_score, classification_report\n",
        "from imblearn.over_sampling import SMOTE\n",
        "import warnings"
      ],
      "metadata": {
        "id": "WT3k_7QtZsEg"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pd.set_option('display.max_columns', None)\n",
        "warnings.filterwarnings('ignore')"
      ],
      "metadata": {
        "id": "8MnxeZ9SZ3nW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2) Baixando pacotes extras do NLTK e Spacy"
      ],
      "metadata": {
        "id": "ZqUDiw3tuDcn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# NTLK\n",
        "nltk.download('stopwords')\n",
        "nltk.download('punkt')\n",
        "\n",
        "# Spacy\n",
        "nlp_spacy_ptbr = spacy.load(\"pt_core_news_sm\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ND_ucx_CcXFm",
        "outputId": "290dba43-7818-4181-9e21-e13f68e6615c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 3) Carregamento da base de dados"
      ],
      "metadata": {
        "id": "v26OoHnWuJlp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.read_csv('/content/processado_base_full.csv', sep=';')\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "id": "2DJf7t9bZtA4",
        "outputId": "e383ebbc-583b-4644-95ae-b15c3e01a9b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  INSTITUICAO_ENSINO_ALUNO     NOME  IDADE_ALUNO  ANOS_PM FASE_TURMA  \\\n",
              "0           Escola Pública  ALUNO-1         11.0      2.0         2H   \n",
              "1           Escola Pública  ALUNO-3         12.0      2.0         3H   \n",
              "2           Escola Pública  ALUNO-4         10.0      2.0         1D   \n",
              "3           Escola Pública  ALUNO-5         10.0      1.0         2M   \n",
              "4       Rede Decisão/União  ALUNO-8         14.0      3.0         4L   \n",
              "\n",
              "  PONTO_VIRADA      INDE INDE_CONCEITO     PEDRA  \\\n",
              "0          Não  7.883752             B  Ametista   \n",
              "1          Não  7.856390             B  Ametista   \n",
              "2          Não  5.076252             D   Quartzo   \n",
              "3          Não  8.077085             B  Ametista   \n",
              "4          Sim  8.381391             B  Ametista   \n",
              "\n",
              "                                        DESTAQUE_IEG  \\\n",
              "0  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "1  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "2  Ponto a melhorar em 2021: Melhorar a sua entre...   \n",
              "3  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "4  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "\n",
              "                                        DESTAQUE_IDA  \\\n",
              "0  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "1  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "2  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "3  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "4  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "\n",
              "                                        DESTAQUE_IPV      IAA  IEG    IPS  \\\n",
              "0  Seu destaque em 2020: A sua boa integração aos...  8.50002  8.7  7.500   \n",
              "1  Seu destaque em 2020: A sua boa integração aos...  7.91667  8.9  7.500   \n",
              "2  Ponto a melhorar em 2021: Integrar-se mais aos...  8.00002  4.1  6.875   \n",
              "3  Seu destaque em 2020: A sua boa integração aos...  7.50002  8.0  7.500   \n",
              "4  Seu destaque em 2020: A sua boa integração aos...  8.33334  9.9  4.375   \n",
              "\n",
              "        IDA     IPP       IPV   IAN   ANO  FASE TURMA SINALIZADOR_INGRESSANTE  \\\n",
              "0  7.000000  5.9375  7.750000  10.0  2020   NaN   NaN                     NaN   \n",
              "1  5.500000  8.1250  8.111113  10.0  2020   NaN   NaN                     NaN   \n",
              "2  0.000000  7.1875  7.750000   5.0  2020   NaN   NaN                     NaN   \n",
              "3  7.500000  8.4375  8.166665  10.0  2020   NaN   NaN                     NaN   \n",
              "4  7.333333  8.7500  8.944450  10.0  2020   NaN   NaN                     NaN   \n",
              "\n",
              "  REC_EQUIPE_1 REC_EQUIPE_2 REC_EQUIPE_3 REC_EQUIPE_4 NIVEL_IDEAL  DEFASAGEM  \\\n",
              "0          NaN          NaN          NaN          NaN         NaN        NaN   \n",
              "1          NaN          NaN          NaN          NaN         NaN        NaN   \n",
              "2          NaN          NaN          NaN          NaN         NaN        NaN   \n",
              "3          NaN          NaN          NaN          NaN         NaN        NaN   \n",
              "4          NaN          NaN          NaN          NaN         NaN        NaN   \n",
              "\n",
              "   ANO_INGRESSO BOLSISTA  CG  CF  CT  NOTA_PORT  NOTA_MAT  NOTA_ING  QTD_AVAL  \\\n",
              "0           NaN      NaN NaN NaN NaN        NaN       NaN       NaN       NaN   \n",
              "1           NaN      NaN NaN NaN NaN        NaN       NaN       NaN       NaN   \n",
              "2           NaN      NaN NaN NaN NaN        NaN       NaN       NaN       NaN   \n",
              "3           NaN      NaN NaN NaN NaN        NaN       NaN       NaN       NaN   \n",
              "4           NaN      NaN NaN NaN NaN        NaN       NaN       NaN       NaN   \n",
              "\n",
              "  REC_AVA_1 REC_AVA_2 REC_AVA_3 REC_AVA_4 INDICADO_BOLSA  \n",
              "0       NaN       NaN       NaN       NaN            NaN  \n",
              "1       NaN       NaN       NaN       NaN            NaN  \n",
              "2       NaN       NaN       NaN       NaN            NaN  \n",
              "3       NaN       NaN       NaN       NaN            NaN  \n",
              "4       NaN       NaN       NaN       NaN            NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-34b9445a-b02a-42ab-b126-14306e7ebc74\" 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>INSTITUICAO_ENSINO_ALUNO</th>\n",
              "      <th>NOME</th>\n",
              "      <th>IDADE_ALUNO</th>\n",
              "      <th>ANOS_PM</th>\n",
              "      <th>FASE_TURMA</th>\n",
              "      <th>PONTO_VIRADA</th>\n",
              "      <th>INDE</th>\n",
              "      <th>INDE_CONCEITO</th>\n",
              "      <th>PEDRA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "      <th>ANO</th>\n",
              "      <th>FASE</th>\n",
              "      <th>TURMA</th>\n",
              "      <th>SINALIZADOR_INGRESSANTE</th>\n",
              "      <th>REC_EQUIPE_1</th>\n",
              "      <th>REC_EQUIPE_2</th>\n",
              "      <th>REC_EQUIPE_3</th>\n",
              "      <th>REC_EQUIPE_4</th>\n",
              "      <th>NIVEL_IDEAL</th>\n",
              "      <th>DEFASAGEM</th>\n",
              "      <th>ANO_INGRESSO</th>\n",
              "      <th>BOLSISTA</th>\n",
              "      <th>CG</th>\n",
              "      <th>CF</th>\n",
              "      <th>CT</th>\n",
              "      <th>NOTA_PORT</th>\n",
              "      <th>NOTA_MAT</th>\n",
              "      <th>NOTA_ING</th>\n",
              "      <th>QTD_AVAL</th>\n",
              "      <th>REC_AVA_1</th>\n",
              "      <th>REC_AVA_2</th>\n",
              "      <th>REC_AVA_3</th>\n",
              "      <th>REC_AVA_4</th>\n",
              "      <th>INDICADO_BOLSA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-1</td>\n",
              "      <td>11.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2H</td>\n",
              "      <td>Não</td>\n",
              "      <td>7.883752</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.50002</td>\n",
              "      <td>8.7</td>\n",
              "      <td>7.500</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>5.9375</td>\n",
              "      <td>7.750000</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-3</td>\n",
              "      <td>12.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3H</td>\n",
              "      <td>Não</td>\n",
              "      <td>7.856390</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>7.91667</td>\n",
              "      <td>8.9</td>\n",
              "      <td>7.500</td>\n",
              "      <td>5.500000</td>\n",
              "      <td>8.1250</td>\n",
              "      <td>8.111113</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-4</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1D</td>\n",
              "      <td>Não</td>\n",
              "      <td>5.076252</td>\n",
              "      <td>D</td>\n",
              "      <td>Quartzo</td>\n",
              "      <td>Ponto a melhorar em 2021: Melhorar a sua entre...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>8.00002</td>\n",
              "      <td>4.1</td>\n",
              "      <td>6.875</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>7.1875</td>\n",
              "      <td>7.750000</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-5</td>\n",
              "      <td>10.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2M</td>\n",
              "      <td>Não</td>\n",
              "      <td>8.077085</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>7.50002</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.500</td>\n",
              "      <td>7.500000</td>\n",
              "      <td>8.4375</td>\n",
              "      <td>8.166665</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-8</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4L</td>\n",
              "      <td>Sim</td>\n",
              "      <td>8.381391</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>9.9</td>\n",
              "      <td>4.375</td>\n",
              "      <td>7.333333</td>\n",
              "      <td>8.7500</td>\n",
              "      <td>8.944450</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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-34b9445a-b02a-42ab-b126-14306e7ebc74')\"\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-34b9445a-b02a-42ab-b126-14306e7ebc74 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-34b9445a-b02a-42ab-b126-14306e7ebc74');\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-3b923163-5df2-48ee-8d5b-fadb586faf68\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3b923163-5df2-48ee-8d5b-fadb586faf68')\"\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-3b923163-5df2-48ee-8d5b-fadb586faf68 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df"
            }
          },
          "metadata": {},
          "execution_count": 631
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['PONTO_VIRADA'].value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uRzs24xpaOGA",
        "outputId": "131b7843-3cda-49a3-9e95-1a0ebfbeeee4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PONTO_VIRADA\n",
              "Não    1932\n",
              "Sim     315\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 632
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.query('PONTO_VIRADA == \"Sim\"').head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "UVBqnikzaSBV",
        "outputId": "2f3f5530-f3cd-4680-e5a1-973a8e48db88"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   INSTITUICAO_ENSINO_ALUNO      NOME  IDADE_ALUNO  ANOS_PM FASE_TURMA  \\\n",
              "4        Rede Decisão/União   ALUNO-8         14.0      3.0         4L   \n",
              "6            Escola Pública  ALUNO-11          8.0      0.0         0A   \n",
              "12       Rede Decisão/União  ALUNO-28         13.0      2.0         3J   \n",
              "28       Rede Decisão/União  ALUNO-55         17.0      3.0         6C   \n",
              "36       Rede Decisão/União  ALUNO-75         11.0      1.0         3L   \n",
              "40           Escola Pública  ALUNO-81         15.0      1.0         4L   \n",
              "42       Rede Decisão/União  ALUNO-83         14.0      4.0         4B   \n",
              "46       Rede Decisão/União  ALUNO-87         14.0      4.0         4L   \n",
              "47       Rede Decisão/União  ALUNO-88         11.0      2.0         2D   \n",
              "53           Escola Pública  ALUNO-96         18.0      1.0         7A   \n",
              "\n",
              "   PONTO_VIRADA      INDE INDE_CONCEITO     PEDRA  \\\n",
              "4           Sim  8.381391             B  Ametista   \n",
              "6           Sim  9.712504             A   Topázio   \n",
              "12          Sim  9.354726             A   Topázio   \n",
              "28          Sim  6.878125             C     Ágata   \n",
              "36          Sim  9.687504             A   Topázio   \n",
              "40          Sim  7.386391             B  Ametista   \n",
              "42          Sim  8.155003             B  Ametista   \n",
              "46          Sim  8.188613             B  Ametista   \n",
              "47          Sim  9.040420             A   Topázio   \n",
              "53          Sim  6.432501             C     Ágata   \n",
              "\n",
              "                                         DESTAQUE_IEG  \\\n",
              "4   Seu destaque em 2020: A sua boa entrega das li...   \n",
              "6   Seu destaque em 2020: A sua boa entrega das li...   \n",
              "12  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "28  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "36  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "40  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "42  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "46  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "47  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "53  Ponto a melhorar em 2021: Melhorar a sua entre...   \n",
              "\n",
              "                                         DESTAQUE_IDA  \\\n",
              "4   Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "6   Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "12  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "28  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "36  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "40  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "42  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "46  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "47  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "53  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "\n",
              "                                         DESTAQUE_IPV       IAA   IEG     IPS  \\\n",
              "4   Seu destaque em 2020: A sua boa integração aos...   8.33334   9.9   4.375   \n",
              "6   Seu destaque em 2020: A sua boa integração aos...   9.00002  10.0   8.125   \n",
              "12  Seu destaque em 2020: A sua boa integração aos...   9.58335   9.6   6.875   \n",
              "28  Ponto a melhorar em 2021: Integrar-se mais aos...   0.00000   9.0   7.500   \n",
              "36  Seu destaque em 2020: A sua boa integração aos...  10.00002  10.0  10.000   \n",
              "40  Ponto a melhorar em 2021: Integrar-se mais aos...   5.41667   8.8   7.500   \n",
              "42  Seu destaque em 2020: A sua boa integração aos...   9.16668   9.4   5.625   \n",
              "46  Seu destaque em 2020: A sua boa integração aos...   8.33334   9.2   5.625   \n",
              "47  Seu destaque em 2020: A sua boa integração aos...  10.00002   9.4   7.500   \n",
              "53  Ponto a melhorar em 2021: Integrar-se mais aos...   9.16668   6.1   6.875   \n",
              "\n",
              "          IDA        IPP        IPV   IAN   ANO  FASE TURMA  \\\n",
              "4    7.333333   8.750000   8.944450  10.0  2020   NaN   NaN   \n",
              "6   10.000000  10.000000  10.000010  10.0  2020   NaN   NaN   \n",
              "12   9.000000  10.000000   9.944453  10.0  2020   NaN   NaN   \n",
              "28   6.333333   8.281250   8.666667   5.0  2020   NaN   NaN   \n",
              "36   9.000000   9.375000   9.750010  10.0  2020   NaN   NaN   \n",
              "40   6.000000   8.125000   9.111120   5.0  2020   NaN   NaN   \n",
              "42   5.333333   8.958333   9.166677  10.0  2020   NaN   NaN   \n",
              "46   6.666667   8.750000   8.722227  10.0  2020   NaN   NaN   \n",
              "47   9.500000   5.937500   9.583340  10.0  2020   NaN   NaN   \n",
              "53   3.000000   7.500000   8.791665   5.0  2020   NaN   NaN   \n",
              "\n",
              "   SINALIZADOR_INGRESSANTE REC_EQUIPE_1 REC_EQUIPE_2 REC_EQUIPE_3  \\\n",
              "4                      NaN          NaN          NaN          NaN   \n",
              "6                      NaN          NaN          NaN          NaN   \n",
              "12                     NaN          NaN          NaN          NaN   \n",
              "28                     NaN          NaN          NaN          NaN   \n",
              "36                     NaN          NaN          NaN          NaN   \n",
              "40                     NaN          NaN          NaN          NaN   \n",
              "42                     NaN          NaN          NaN          NaN   \n",
              "46                     NaN          NaN          NaN          NaN   \n",
              "47                     NaN          NaN          NaN          NaN   \n",
              "53                     NaN          NaN          NaN          NaN   \n",
              "\n",
              "   REC_EQUIPE_4 NIVEL_IDEAL  DEFASAGEM  ANO_INGRESSO BOLSISTA  CG  CF  CT  \\\n",
              "4           NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "6           NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "12          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "28          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "36          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "40          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "42          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "46          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "47          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "53          NaN         NaN        NaN           NaN      NaN NaN NaN NaN   \n",
              "\n",
              "    NOTA_PORT  NOTA_MAT  NOTA_ING  QTD_AVAL REC_AVA_1 REC_AVA_2 REC_AVA_3  \\\n",
              "4         NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "6         NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "12        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "28        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "36        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "40        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "42        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "46        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "47        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "53        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
              "\n",
              "   REC_AVA_4 INDICADO_BOLSA  \n",
              "4        NaN            NaN  \n",
              "6        NaN            NaN  \n",
              "12       NaN            NaN  \n",
              "28       NaN            NaN  \n",
              "36       NaN            NaN  \n",
              "40       NaN            NaN  \n",
              "42       NaN            NaN  \n",
              "46       NaN            NaN  \n",
              "47       NaN            NaN  \n",
              "53       NaN            NaN  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-26208559-6dac-4e23-9a34-7dc7cdbe0361\" 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>INSTITUICAO_ENSINO_ALUNO</th>\n",
              "      <th>NOME</th>\n",
              "      <th>IDADE_ALUNO</th>\n",
              "      <th>ANOS_PM</th>\n",
              "      <th>FASE_TURMA</th>\n",
              "      <th>PONTO_VIRADA</th>\n",
              "      <th>INDE</th>\n",
              "      <th>INDE_CONCEITO</th>\n",
              "      <th>PEDRA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "      <th>ANO</th>\n",
              "      <th>FASE</th>\n",
              "      <th>TURMA</th>\n",
              "      <th>SINALIZADOR_INGRESSANTE</th>\n",
              "      <th>REC_EQUIPE_1</th>\n",
              "      <th>REC_EQUIPE_2</th>\n",
              "      <th>REC_EQUIPE_3</th>\n",
              "      <th>REC_EQUIPE_4</th>\n",
              "      <th>NIVEL_IDEAL</th>\n",
              "      <th>DEFASAGEM</th>\n",
              "      <th>ANO_INGRESSO</th>\n",
              "      <th>BOLSISTA</th>\n",
              "      <th>CG</th>\n",
              "      <th>CF</th>\n",
              "      <th>CT</th>\n",
              "      <th>NOTA_PORT</th>\n",
              "      <th>NOTA_MAT</th>\n",
              "      <th>NOTA_ING</th>\n",
              "      <th>QTD_AVAL</th>\n",
              "      <th>REC_AVA_1</th>\n",
              "      <th>REC_AVA_2</th>\n",
              "      <th>REC_AVA_3</th>\n",
              "      <th>REC_AVA_4</th>\n",
              "      <th>INDICADO_BOLSA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-8</td>\n",
              "      <td>14.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4L</td>\n",
              "      <td>Sim</td>\n",
              "      <td>8.381391</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>9.9</td>\n",
              "      <td>4.375</td>\n",
              "      <td>7.333333</td>\n",
              "      <td>8.750000</td>\n",
              "      <td>8.944450</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-11</td>\n",
              "      <td>8.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0A</td>\n",
              "      <td>Sim</td>\n",
              "      <td>9.712504</td>\n",
              "      <td>A</td>\n",
              "      <td>Topázio</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.00002</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.125</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000010</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-28</td>\n",
              "      <td>13.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3J</td>\n",
              "      <td>Sim</td>\n",
              "      <td>9.354726</td>\n",
              "      <td>A</td>\n",
              "      <td>Topázio</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.58335</td>\n",
              "      <td>9.6</td>\n",
              "      <td>6.875</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.944453</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-55</td>\n",
              "      <td>17.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6C</td>\n",
              "      <td>Sim</td>\n",
              "      <td>6.878125</td>\n",
              "      <td>C</td>\n",
              "      <td>Ágata</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.500</td>\n",
              "      <td>6.333333</td>\n",
              "      <td>8.281250</td>\n",
              "      <td>8.666667</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-75</td>\n",
              "      <td>11.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3L</td>\n",
              "      <td>Sim</td>\n",
              "      <td>9.687504</td>\n",
              "      <td>A</td>\n",
              "      <td>Topázio</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>10.00002</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>9.375000</td>\n",
              "      <td>9.750010</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-81</td>\n",
              "      <td>15.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4L</td>\n",
              "      <td>Sim</td>\n",
              "      <td>7.386391</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>5.41667</td>\n",
              "      <td>8.8</td>\n",
              "      <td>7.500</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>8.125000</td>\n",
              "      <td>9.111120</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-83</td>\n",
              "      <td>14.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4B</td>\n",
              "      <td>Sim</td>\n",
              "      <td>8.155003</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.16668</td>\n",
              "      <td>9.4</td>\n",
              "      <td>5.625</td>\n",
              "      <td>5.333333</td>\n",
              "      <td>8.958333</td>\n",
              "      <td>9.166677</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-87</td>\n",
              "      <td>14.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4L</td>\n",
              "      <td>Sim</td>\n",
              "      <td>8.188613</td>\n",
              "      <td>B</td>\n",
              "      <td>Ametista</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>9.2</td>\n",
              "      <td>5.625</td>\n",
              "      <td>6.666667</td>\n",
              "      <td>8.750000</td>\n",
              "      <td>8.722227</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>Rede Decisão/União</td>\n",
              "      <td>ALUNO-88</td>\n",
              "      <td>11.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2D</td>\n",
              "      <td>Sim</td>\n",
              "      <td>9.040420</td>\n",
              "      <td>A</td>\n",
              "      <td>Topázio</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>10.00002</td>\n",
              "      <td>9.4</td>\n",
              "      <td>7.500</td>\n",
              "      <td>9.500000</td>\n",
              "      <td>5.937500</td>\n",
              "      <td>9.583340</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>Escola Pública</td>\n",
              "      <td>ALUNO-96</td>\n",
              "      <td>18.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>7A</td>\n",
              "      <td>Sim</td>\n",
              "      <td>6.432501</td>\n",
              "      <td>C</td>\n",
              "      <td>Ágata</td>\n",
              "      <td>Ponto a melhorar em 2021: Melhorar a sua entre...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>9.16668</td>\n",
              "      <td>6.1</td>\n",
              "      <td>6.875</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>7.500000</td>\n",
              "      <td>8.791665</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2020</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</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-26208559-6dac-4e23-9a34-7dc7cdbe0361')\"\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-26208559-6dac-4e23-9a34-7dc7cdbe0361 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-26208559-6dac-4e23-9a34-7dc7cdbe0361');\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-eb518a2a-c62e-4326-8d14-9335f458ee90\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-eb518a2a-c62e-4326-8d14-9335f458ee90')\"\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-eb518a2a-c62e-4326-8d14-9335f458ee90 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe"
            }
          },
          "metadata": {},
          "execution_count": 633
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3.1) Definição das features que serão utilizadas pelo XGB"
      ],
      "metadata": {
        "id": "vvIdT_pauQYe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df_ml = df[['PONTO_VIRADA', 'DESTAQUE_IEG',\t'DESTAQUE_IDA',\t'DESTAQUE_IPV',\t'INDE', 'IAA',\t'IEG',\t'IPS',\t'IDA', \t'IPP',\t'IPV',\t'IAN']]\n",
        "df_ml.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 293
        },
        "id": "dJB_vYEEZwpH",
        "outputId": "2737294f-f8fd-4809-daf8-db0d17efa7e9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  PONTO_VIRADA                                       DESTAQUE_IEG  \\\n",
              "0          Não  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "1          Não  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "2          Não  Ponto a melhorar em 2021: Melhorar a sua entre...   \n",
              "3          Não  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "4          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "\n",
              "                                        DESTAQUE_IDA  \\\n",
              "0  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "1  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "2  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "3  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "4  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "\n",
              "                                        DESTAQUE_IPV      INDE      IAA  IEG  \\\n",
              "0  Seu destaque em 2020: A sua boa integração aos...  7.883752  8.50002  8.7   \n",
              "1  Seu destaque em 2020: A sua boa integração aos...  7.856390  7.91667  8.9   \n",
              "2  Ponto a melhorar em 2021: Integrar-se mais aos...  5.076252  8.00002  4.1   \n",
              "3  Seu destaque em 2020: A sua boa integração aos...  8.077085  7.50002  8.0   \n",
              "4  Seu destaque em 2020: A sua boa integração aos...  8.381391  8.33334  9.9   \n",
              "\n",
              "     IPS       IDA     IPP       IPV   IAN  \n",
              "0  7.500  7.000000  5.9375  7.750000  10.0  \n",
              "1  7.500  5.500000  8.1250  8.111113  10.0  \n",
              "2  6.875  0.000000  7.1875  7.750000   5.0  \n",
              "3  7.500  7.500000  8.4375  8.166665  10.0  \n",
              "4  4.375  7.333333  8.7500  8.944450  10.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9238870e-a15a-4771-a1e3-a1e323de91a9\" 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>PONTO_VIRADA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Não</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>7.883752</td>\n",
              "      <td>8.50002</td>\n",
              "      <td>8.7</td>\n",
              "      <td>7.500</td>\n",
              "      <td>7.000000</td>\n",
              "      <td>5.9375</td>\n",
              "      <td>7.750000</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Não</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>7.856390</td>\n",
              "      <td>7.91667</td>\n",
              "      <td>8.9</td>\n",
              "      <td>7.500</td>\n",
              "      <td>5.500000</td>\n",
              "      <td>8.1250</td>\n",
              "      <td>8.111113</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Não</td>\n",
              "      <td>Ponto a melhorar em 2021: Melhorar a sua entre...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>5.076252</td>\n",
              "      <td>8.00002</td>\n",
              "      <td>4.1</td>\n",
              "      <td>6.875</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>7.1875</td>\n",
              "      <td>7.750000</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Não</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.077085</td>\n",
              "      <td>7.50002</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.500</td>\n",
              "      <td>7.500000</td>\n",
              "      <td>8.4375</td>\n",
              "      <td>8.166665</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.381391</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>9.9</td>\n",
              "      <td>4.375</td>\n",
              "      <td>7.333333</td>\n",
              "      <td>8.7500</td>\n",
              "      <td>8.944450</td>\n",
              "      <td>10.0</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-9238870e-a15a-4771-a1e3-a1e323de91a9')\"\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-9238870e-a15a-4771-a1e3-a1e323de91a9 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-9238870e-a15a-4771-a1e3-a1e323de91a9');\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-d54d17d0-d637-4ae2-ba76-4122d6279dd9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d54d17d0-d637-4ae2-ba76-4122d6279dd9')\"\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-d54d17d0-d637-4ae2-ba76-4122d6279dd9 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df_ml",
              "summary": "{\n  \"name\": \"df_ml\",\n  \"rows\": 2273,\n  \"fields\": [\n    {\n      \"column\": \"PONTO_VIRADA\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Sim\",\n          \"N\\u00e3o\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Seu destaque em 2020: A sua boa entrega das li\\u00e7\\u00f5es de casa.\",\n          \"Ponto a melhorar em 2021: Melhorar a sua entrega de li\\u00e7\\u00f5es de casa.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"Ponto a melhorar em 2021: Empenhar-se mais nas aulas e avalia\\u00e7\\u00f5es.\",\n          \"Seu destaque em 2020: As suas boas notas na Passos M\\u00e1gicos.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Ponto a melhorar em 2021: Integrar-se mais aos Princ\\u00edpios Passos M\\u00e1gicos.\",\n          \"Melhorar: Integrar-se mais aos Princ\\u00edpios Passos M\\u00e1gicos.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.200129469140643,\n        \"min\": 2.468,\n        \"max\": 9.712504,\n        \"num_unique_values\": 2221,\n        \"samples\": [\n          8.257224,\n          6.344244591269144\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.0128173555907583,\n        \"min\": 0.0,\n        \"max\": 10.00002,\n        \"num_unique_values\": 82,\n        \"samples\": [\n          8.33335,\n          8.500020000000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.195622359669798,\n        \"min\": 0.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 843,\n        \"samples\": [\n          5.858788554440729,\n          8.046833064949007\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2958476836171458,\n        \"min\": 0.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 23,\n        \"samples\": [\n          3.8,\n          2.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.4327995389026276,\n        \"min\": 0.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 456,\n        \"samples\": [\n          1.477777777777778,\n          2.333333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.529398999637998,\n        \"min\": 0.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 123,\n        \"samples\": [\n          0.0,\n          6.40625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.4903266325366007,\n        \"min\": 0.0,\n        \"max\": 10.00001,\n        \"num_unique_values\": 720,\n        \"samples\": [\n          7.374995,\n          6.833333333333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.506591486749192,\n        \"min\": 2.5,\n        \"max\": 10.0,\n        \"num_unique_values\": 3,\n        \"samples\": [\n          10.0,\n          5.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 634
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3.2) Recarregamento do SVC e NLP (para análise de sentimentos)"
      ],
      "metadata": {
        "id": "SDtKJCKMuUYG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "modelo = joblib.load('/content/model.pkl')\n",
        "vect = joblib.load(\"/content/vect.pkl\")"
      ],
      "metadata": {
        "id": "mrLfz7GuazAH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3.3) Funções auxiliares para executar o NLP"
      ],
      "metadata": {
        "id": "Sgj03HRguZou"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def normalize_accents(text):\n",
        "    return unicodedata.normalize(\"NFKD\", text).encode(\"ASCII\", \"ignore\").decode(\"utf-8\")\n",
        "\n",
        "def remove_punctuation(text):\n",
        "    punctuations = string.punctuation\n",
        "    table = str.maketrans({key: \" \" for key in punctuations})\n",
        "    text = text.translate(table)\n",
        "    return text\n",
        "\n",
        "def normalize_str(text):\n",
        "    text = text.lower()\n",
        "    text = remove_punctuation(text)\n",
        "    text = normalize_accents(text)\n",
        "    text = re.sub(re.compile(r\" +\"), \" \",text)\n",
        "    return \" \".join([w for w in text.split()])\n",
        "\n",
        "def tokenizer(text):\n",
        "    stop_words = stopwords.words(\"portuguese\")\n",
        "    if isinstance(text, str):\n",
        "        text = normalize_str(text)\n",
        "        text = \"\".join([w for w in text if not w.isdigit()])\n",
        "        text = word_tokenize(text)\n",
        "        text = [x for x in text if x not in stop_words]\n",
        "        text = [y for y in text if len(y) > 2]\n",
        "        return \" \".join([t for t in text])\n",
        "    else:\n",
        "        return None\n",
        "\n",
        "def lemmatize(text):\n",
        "    doc = nlp_spacy_ptbr(text)\n",
        "    return \" \".join([token.lemma_ for token in doc])\n",
        "\n",
        "def predict_sentiment(texto):\n",
        "    texto_teste = tokenizer(texto)\n",
        "    texto_lematizado = lemmatize(texto_teste)\n",
        "    text_vect = vect.transform([texto_lematizado])\n",
        "    return modelo.predict(text_vect)[0]"
      ],
      "metadata": {
        "id": "EZhHK0aZbbAd"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "clone = df_ml.copy()"
      ],
      "metadata": {
        "id": "Rdmn9G04XrXu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "clone['PONTO_VIRADA'].value_counts(dropna=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dtdaVEa-2SA4",
        "outputId": "0e9f5a28-b21d-4f35-f88c-61da76b41e40"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PONTO_VIRADA\n",
              "Não    1932\n",
              "Sim     315\n",
              "NaN      26\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 638
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clone['PONTO_VIRADA'][clone['PONTO_VIRADA'].isna()].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5fmcewRq3TUw",
        "outputId": "180e40e2-74e8-4186-98ec-5897638b2916"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "27     NaN\n",
              "86     NaN\n",
              "94     NaN\n",
              "118    NaN\n",
              "161    NaN\n",
              "Name: PONTO_VIRADA, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 639
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clone.iloc[27].to_frame().T"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 98
        },
        "id": "Wi2tmN6K3Y43",
        "outputId": "1cf9e62a-679c-41b2-9044-d2096018fb03"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   PONTO_VIRADA                                       DESTAQUE_IEG  \\\n",
              "27          NaN  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "\n",
              "                                         DESTAQUE_IDA  \\\n",
              "27  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "\n",
              "                                         DESTAQUE_IPV      INDE      IAA  \\\n",
              "27  Seu destaque em 2020: A sua boa integração aos...  8.696668  9.16668   \n",
              "\n",
              "     IEG  IPS  IDA  IPP  IPV   IAN  \n",
              "27  10.0  7.5  8.2  0.0  0.0  10.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-9f17730a-f6ba-4f00-a6c7-c7e4b7600911\" 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>PONTO_VIRADA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>NaN</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.696668</td>\n",
              "      <td>9.16668</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.5</td>\n",
              "      <td>8.2</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>10.0</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-9f17730a-f6ba-4f00-a6c7-c7e4b7600911')\"\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-9f17730a-f6ba-4f00-a6c7-c7e4b7600911 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-9f17730a-f6ba-4f00-a6c7-c7e4b7600911');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "repr_error": "0"
            }
          },
          "metadata": {},
          "execution_count": 640
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clone = clone.dropna(subset=['PONTO_VIRADA'])"
      ],
      "metadata": {
        "id": "TA-wn1ZO3-LY"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "clone.query('PONTO_VIRADA == \"Sim\"').head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 537
        },
        "id": "_JKmOj9w7a3A",
        "outputId": "203112cf-fbfc-41c9-8c90-9b40a756a713"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   PONTO_VIRADA                                       DESTAQUE_IEG  \\\n",
              "4           Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "6           Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "12          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "28          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "36          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "40          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "42          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "46          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "47          Sim  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "53          Sim  Ponto a melhorar em 2021: Melhorar a sua entre...   \n",
              "\n",
              "                                         DESTAQUE_IDA  \\\n",
              "4   Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "6   Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "12  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "28  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "36  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "40  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "42  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "46  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "47  Seu destaque em 2020: As suas boas notas na Pa...   \n",
              "53  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "\n",
              "                                         DESTAQUE_IPV      INDE       IAA  \\\n",
              "4   Seu destaque em 2020: A sua boa integração aos...  8.381391   8.33334   \n",
              "6   Seu destaque em 2020: A sua boa integração aos...  9.712504   9.00002   \n",
              "12  Seu destaque em 2020: A sua boa integração aos...  9.354726   9.58335   \n",
              "28  Ponto a melhorar em 2021: Integrar-se mais aos...  6.878125   0.00000   \n",
              "36  Seu destaque em 2020: A sua boa integração aos...  9.687504  10.00002   \n",
              "40  Ponto a melhorar em 2021: Integrar-se mais aos...  7.386391   5.41667   \n",
              "42  Seu destaque em 2020: A sua boa integração aos...  8.155003   9.16668   \n",
              "46  Seu destaque em 2020: A sua boa integração aos...  8.188613   8.33334   \n",
              "47  Seu destaque em 2020: A sua boa integração aos...  9.040420  10.00002   \n",
              "53  Ponto a melhorar em 2021: Integrar-se mais aos...  6.432501   9.16668   \n",
              "\n",
              "     IEG     IPS        IDA        IPP        IPV   IAN  \n",
              "4    9.9   4.375   7.333333   8.750000   8.944450  10.0  \n",
              "6   10.0   8.125  10.000000  10.000000  10.000010  10.0  \n",
              "12   9.6   6.875   9.000000  10.000000   9.944453  10.0  \n",
              "28   9.0   7.500   6.333333   8.281250   8.666667   5.0  \n",
              "36  10.0  10.000   9.000000   9.375000   9.750010  10.0  \n",
              "40   8.8   7.500   6.000000   8.125000   9.111120   5.0  \n",
              "42   9.4   5.625   5.333333   8.958333   9.166677  10.0  \n",
              "46   9.2   5.625   6.666667   8.750000   8.722227  10.0  \n",
              "47   9.4   7.500   9.500000   5.937500   9.583340  10.0  \n",
              "53   6.1   6.875   3.000000   7.500000   8.791665   5.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c43119c6-102a-444b-ac81-21d907676fe9\" 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>PONTO_VIRADA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.381391</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>9.9</td>\n",
              "      <td>4.375</td>\n",
              "      <td>7.333333</td>\n",
              "      <td>8.750000</td>\n",
              "      <td>8.944450</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.712504</td>\n",
              "      <td>9.00002</td>\n",
              "      <td>10.0</td>\n",
              "      <td>8.125</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>10.000010</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.354726</td>\n",
              "      <td>9.58335</td>\n",
              "      <td>9.6</td>\n",
              "      <td>6.875</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>10.000000</td>\n",
              "      <td>9.944453</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>6.878125</td>\n",
              "      <td>0.00000</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.500</td>\n",
              "      <td>6.333333</td>\n",
              "      <td>8.281250</td>\n",
              "      <td>8.666667</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.687504</td>\n",
              "      <td>10.00002</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.000</td>\n",
              "      <td>9.000000</td>\n",
              "      <td>9.375000</td>\n",
              "      <td>9.750010</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>7.386391</td>\n",
              "      <td>5.41667</td>\n",
              "      <td>8.8</td>\n",
              "      <td>7.500</td>\n",
              "      <td>6.000000</td>\n",
              "      <td>8.125000</td>\n",
              "      <td>9.111120</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.155003</td>\n",
              "      <td>9.16668</td>\n",
              "      <td>9.4</td>\n",
              "      <td>5.625</td>\n",
              "      <td>5.333333</td>\n",
              "      <td>8.958333</td>\n",
              "      <td>9.166677</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>8.188613</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>9.2</td>\n",
              "      <td>5.625</td>\n",
              "      <td>6.666667</td>\n",
              "      <td>8.750000</td>\n",
              "      <td>8.722227</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Seu destaque em 2020: As suas boas notas na Pa...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>9.040420</td>\n",
              "      <td>10.00002</td>\n",
              "      <td>9.4</td>\n",
              "      <td>7.500</td>\n",
              "      <td>9.500000</td>\n",
              "      <td>5.937500</td>\n",
              "      <td>9.583340</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>53</th>\n",
              "      <td>Sim</td>\n",
              "      <td>Ponto a melhorar em 2021: Melhorar a sua entre...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Ponto a melhorar em 2021: Integrar-se mais aos...</td>\n",
              "      <td>6.432501</td>\n",
              "      <td>9.16668</td>\n",
              "      <td>6.1</td>\n",
              "      <td>6.875</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>7.500000</td>\n",
              "      <td>8.791665</td>\n",
              "      <td>5.0</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-c43119c6-102a-444b-ac81-21d907676fe9')\"\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-c43119c6-102a-444b-ac81-21d907676fe9 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-c43119c6-102a-444b-ac81-21d907676fe9');\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-8e04c82a-3eff-435a-800e-ea8ff64a319d\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-8e04c82a-3eff-435a-800e-ea8ff64a319d')\"\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-8e04c82a-3eff-435a-800e-ea8ff64a319d button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"clone\",\n  \"rows\": 10,\n  \"fields\": [\n    {\n      \"column\": \"PONTO_VIRADA\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Sim\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Ponto a melhorar em 2021: Melhorar a sua entrega de li\\u00e7\\u00f5es de casa.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Seu destaque em 2020: As suas boas notas na Passos M\\u00e1gicos.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"Ponto a melhorar em 2021: Integrar-se mais aos Princ\\u00edpios Passos M\\u00e1gicos.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.1527890755924433,\n        \"min\": 6.432500999999999,\n        \"max\": 9.712504,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          9.04042\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3.073639367755719,\n        \"min\": 0.0,\n        \"max\": 10.00002,\n        \"num_unique_values\": 7,\n        \"samples\": [\n          8.33334\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.144261042478216,\n        \"min\": 6.1,\n        \"max\": 10.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.5534459901922708,\n        \"min\": 4.375,\n        \"max\": 10.0,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          4.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.1915240764768655,\n        \"min\": 3.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 9,\n        \"samples\": [\n          9.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2160835622292054,\n        \"min\": 5.9375,\n        \"max\": 10.0,\n        \"num_unique_values\": 8,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.5111128776805298,\n        \"min\": 8.666667499999999,\n        \"max\": 10.00001,\n        \"num_unique_values\": 10,\n        \"samples\": [\n          9.58334\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 2.41522945769824,\n        \"min\": 5.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          5.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 642
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clone['PONTO_VIRADA'].value_counts(dropna=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3JX7qvw94CgA",
        "outputId": "608e3ea2-ec27-4983-c746-e7b046369c21"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "PONTO_VIRADA\n",
              "Não    1932\n",
              "Sim     315\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 643
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 3.4) Normalizações e padronizações da base de dados"
      ],
      "metadata": {
        "id": "rd0405WMulMP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "onehot_encoder = OneHotEncoder(sparse=False)\n",
        "label_encoder = LabelEncoder()\n",
        "# scaler = StandardScaler() # NOTA: desativado o scaler... ele impactava a previsão final de forma negativa"
      ],
      "metadata": {
        "id": "03gdolDucSra"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def processar_sentimento_nlp_df(df):\n",
        "  df['DESTAQUE_IEG_NLP'] = df['DESTAQUE_IEG'].apply(lambda x: predict_sentiment(x) if pd.notnull(x) else 'NA')\n",
        "  df['DESTAQUE_IDA_NLP'] = df['DESTAQUE_IDA'].apply(lambda x: predict_sentiment(x) if pd.notnull(x) else 'NA')\n",
        "  df['DESTAQUE_IPV_NLP'] = df['DESTAQUE_IPV'].apply(lambda x: predict_sentiment(x) if pd.notnull(x) else 'NA')\n",
        "\n",
        "  return df\n",
        "\n",
        "def aplicar_onehot_encoder(df):\n",
        "  # colunas que vão receber o OneHotEncoder\n",
        "  cols_to_encode = ['DESTAQUE_IDA_NLP', 'DESTAQUE_IEG_NLP', 'DESTAQUE_IPV_NLP']\n",
        "  df[cols_to_encode] = df[cols_to_encode].astype(str)\n",
        "\n",
        "  # dropa as colunas originais que o NLP processou\n",
        "  df.drop(['DESTAQUE_IDA', 'DESTAQUE_IEG', 'DESTAQUE_IPV'], axis=1, inplace=True)\n",
        "\n",
        "  # aplica o OneHotEncoder\n",
        "  codificado = onehot_encoder.fit_transform(df[cols_to_encode])\n",
        "  colunas_codificadas = onehot_encoder.get_feature_names_out(cols_to_encode)\n",
        "  df_codificado = pd.DataFrame(codificado, columns=colunas_codificadas)\n",
        "\n",
        "  # pode ser que um registro não possua todas as colunas finais do OneHotEncoder (p.ex. quando para a coluna IPV não é classificada como neutra),\n",
        "  # entretanto, o NLP ainda pode eventualmente classificar tal feature como neutra, o que quebraria o modelo em tal caso\n",
        "  # o código a seguir, garante que todas as linhas do df possuam as variantes geradas pelo NLP\n",
        "  colunas_necessarias = [\n",
        "      'DESTAQUE_IDA_NLP_NA', 'DESTAQUE_IDA_NLP_negativo', 'DESTAQUE_IDA_NLP_neutro', 'DESTAQUE_IDA_NLP_positivo',\n",
        "      'DESTAQUE_IEG_NLP_NA', 'DESTAQUE_IEG_NLP_negativo', 'DESTAQUE_IEG_NLP_neutro', 'DESTAQUE_IEG_NLP_positivo',\n",
        "      'DESTAQUE_IPV_NLP_NA', 'DESTAQUE_IPV_NLP_negativo', 'DESTAQUE_IPV_NLP_neutro', 'DESTAQUE_IPV_NLP_positivo'\n",
        "  ]\n",
        "\n",
        "  for col in colunas_necessarias:\n",
        "        if col not in df_codificado.columns:\n",
        "            df_codificado[col] = 0\n",
        "\n",
        "  # reseta o index para o concat\n",
        "  df_codificado = df_codificado.reset_index(drop=True)\n",
        "  df = df.reset_index(drop=True)\n",
        "\n",
        "  # concat final das colunas (OneHotEncoder + colunas originais - colunas originais que deveriam ser encodadas)\n",
        "  df_final = pd.concat([df_codificado, df.drop(columns=cols_to_encode)], axis=1)\n",
        "\n",
        "  return df_final\n",
        "\n",
        "def aplicar_scaler(df):\n",
        "  clone = df.copy()\n",
        "  # clone_scaled = scaler.fit_transform(df)\n",
        "  clone_scaled = clone # NOTA: desativado o scaler... ele impactava a previsão final de forma negativa, aqui eu simplesmente retorno o valor enviado por parâmetro, para não quebrar o script\n",
        "\n",
        "  return clone_scaled\n",
        "\n",
        "def preparar_dados(df):\n",
        "  df = processar_sentimento_nlp_df(df)\n",
        "  df = aplicar_onehot_encoder(df)\n",
        "  df = df[sorted(df.columns)] # para garantir que o input sempre será enviado para o scaler na ordem correta\n",
        "\n",
        "  return df"
      ],
      "metadata": {
        "id": "UbPL7TMMcSk3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X = aplicar_scaler(preparar_dados(clone.drop('PONTO_VIRADA', axis=1)))\n",
        "y = pd.Series(label_encoder.fit_transform(clone['PONTO_VIRADA']))"
      ],
      "metadata": {
        "id": "ExCKtlNTgdLM"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "label_encoder.classes_"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_1KmGLbY2FU5",
        "outputId": "883a2923-965a-45d0-8121-5d68f8088187"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Não', 'Sim'], dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 647
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "V4V6Xr342igQ",
        "outputId": "af538261-ab5d-4243-b056-424e4f818117"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1932\n",
              "1     315\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 648
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4) Divisão da base de dados em treinamento e validação"
      ],
      "metadata": {
        "id": "rs4eods6u1Ug"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, stratify=y, random_state=777)"
      ],
      "metadata": {
        "id": "WHB1vPdMkSls"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "smote = SMOTE()\n",
        "X_train_resampled, y_train_resampled = smote.fit_resample(X_train, y_train)"
      ],
      "metadata": {
        "id": "G7NApa3JxmRP"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.1) Utilização do SMOTE para fazer um resample das classes\n",
        "Nesta seção foi utilizado SMOTE para executar um resample de registros para as classes com menos representantes."
      ],
      "metadata": {
        "id": "luCfIfnIu6H1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "y_train_resampled.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Snz42tJB-HM_",
        "outputId": "aee7f568-e875-432a-dd66-201242384816"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    1352\n",
              "1    1352\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 651
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.2) Obtendo os melhores parâmetros do XGB"
      ],
      "metadata": {
        "id": "x3_UF6dZvGKW"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def melhores_hiperparamentros_xgb(X_train, y_train):\n",
        "    param_grid = {\n",
        "      'learning_rate':[0.01, 0.05, 0.2],\n",
        "      'n_estimators':[50, 100, 200, 500],\n",
        "      'max_depth': [1, 2, 5, 8]\n",
        "    }\n",
        "    cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=777)\n",
        "\n",
        "    grid = GridSearchCV(\n",
        "      GradientBoostingClassifier(),\n",
        "      param_grid = param_grid,\n",
        "      scoring = 'f1',\n",
        "      cv = cv,\n",
        "      n_jobs= -1\n",
        "    )\n",
        "\n",
        "    # seleciona os melhores hiperparâmetros com base nos dados de treino\n",
        "    grid.fit(X_train, y_train)\n",
        "    xgb_params = grid.best_params_\n",
        "\n",
        "    print(\"Melhores hiperparâmetros para XGB:\", xgb_params)\n",
        "\n",
        "    return xgb_params"
      ],
      "metadata": {
        "id": "2hljWlf8gz7n"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "%%time\n",
        "# NOTA: desativado pois é muito pesado para rodar\n",
        "# params = melhores_hiperparamentros_xgb(X_train, y_train)\n",
        "# params\n",
        "\n",
        "# Melhores hiperparâmetros para XGB: {'learning_rate': 0.01, 'max_depth': 1, 'n_estimators': 50}\n",
        "# {'learning_rate': 0.01, 'max_depth': 1, 'n_estimators': 50}"
      ],
      "metadata": {
        "id": "YQoqdlX8g1RO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e635ddb4-bed9-491f-e5df-7c6953c84023"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "CPU times: user 4 µs, sys: 0 ns, total: 4 µs\n",
            "Wall time: 7.63 µs\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.3) Treinamento do modelo XGB"
      ],
      "metadata": {
        "id": "9P7pxHxrvM3v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "kfold = KFold(n_splits=5, shuffle=True)\n",
        "xgb = GradientBoostingClassifier(learning_rate=0.01, max_depth=5, n_estimators=300)\n",
        "xgb.fit(X_train, y_train)\n",
        "xgb_result = cross_val_score(xgb, X_train_resampled, y_train_resampled, cv=kfold)"
      ],
      "metadata": {
        "id": "avTDaMTqhy4j"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(f'Média das pontuações de validação cruzada: {xgb_result.mean()}')\n",
        "print(f'Desvio padrão das pontuações: {xgb_result.std()}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C0ycDOWbvEE7",
        "outputId": "fbe8fdb8-796f-4962-b07e-6648f50d80d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Média das pontuações de validação cruzada: 0.9940829739166155\n",
            "Desvio padrão das pontuações: 0.0007383553410132701\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## 4.4) Validação do modelo XGB"
      ],
      "metadata": {
        "id": "1JLN2V7uvQG1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = xgb.predict(X_test)\n",
        "print(classification_report(y_test, y_pred))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Yv_7w196hCxG",
        "outputId": "c853254d-73e0-48d2-cd55-4e0dce76359c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.99      1.00      0.99       580\n",
            "           1       0.99      0.95      0.97        95\n",
            "\n",
            "    accuracy                           0.99       675\n",
            "   macro avg       0.99      0.97      0.98       675\n",
            "weighted avg       0.99      0.99      0.99       675\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "xgb_acuracia = accuracy_score(y_true=y_test, y_pred=y_pred) * 100\n",
        "xgb_acuracia"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G0gyDxJPjFp1",
        "outputId": "37edd035-fbab-405d-e25c-79a0729f008f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "99.11111111111111"
            ]
          },
          "metadata": {},
          "execution_count": 657
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def xgb_predict(aluno):\n",
        "    aluno = preparar_dados(aluno.drop('PONTO_VIRADA', axis=1))\n",
        "    aluno_scaled = aplicar_scaler(aluno)\n",
        "\n",
        "    display('aluno', aluno)\n",
        "    display('aluno scaled', aluno_scaled)\n",
        "\n",
        "    return xgb.predict(aluno_scaled)"
      ],
      "metadata": {
        "id": "PcukGSrSZWwT"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df_ml.iloc[0].to_frame().T"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 98
        },
        "id": "nRaCcTP1m3hA",
        "outputId": "720bae3e-8cf7-4b30-d7ba-0cb11844e2e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  PONTO_VIRADA                                       DESTAQUE_IEG  \\\n",
              "0          Não  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "\n",
              "                                        DESTAQUE_IDA  \\\n",
              "0  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "\n",
              "                                        DESTAQUE_IPV      INDE      IAA  IEG  \\\n",
              "0  Seu destaque em 2020: A sua boa integração aos...  7.883752  8.50002  8.7   \n",
              "\n",
              "   IPS  IDA     IPP   IPV   IAN  \n",
              "0  7.5  7.0  5.9375  7.75  10.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-b9632322-02f1-4825-8bf3-5c1383a055e7\" 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>PONTO_VIRADA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Não</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>7.883752</td>\n",
              "      <td>8.50002</td>\n",
              "      <td>8.7</td>\n",
              "      <td>7.5</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.9375</td>\n",
              "      <td>7.75</td>\n",
              "      <td>10.0</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-b9632322-02f1-4825-8bf3-5c1383a055e7')\"\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-b9632322-02f1-4825-8bf3-5c1383a055e7 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-b9632322-02f1-4825-8bf3-5c1383a055e7');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df_ml\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"PONTO_VIRADA\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"N\\u00e3o\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Seu destaque em 2020: A sua boa entrega das li\\u00e7\\u00f5es de casa.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Ponto a melhorar em 2021: Empenhar-se mais nas aulas e avalia\\u00e7\\u00f5es.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Seu destaque em 2020: A sua boa integra\\u00e7\\u00e3o aos Princ\\u00edpios Passos M\\u00e1gicos.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.883752,\n        \"max\": 7.883752,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.883752\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.500020000000001,\n        \"max\": 8.500020000000001,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.500020000000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.7,\n        \"max\": 8.7,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.5,\n        \"max\": 7.5,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.0,\n        \"max\": 7.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 5.9375,\n        \"max\": 5.9375,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          5.9375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.75,\n        \"max\": 7.75,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 10.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 659
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_ml = df[['PONTO_VIRADA', 'DESTAQUE_IEG', 'DESTAQUE_IDA', 'DESTAQUE_IPV', 'INDE', 'IAA', 'IEG', 'IPS', 'IDA', 'IPP', 'IPV', 'IAN']].query('DESTAQUE_IEG.notna() and DESTAQUE_IDA.notna() and DESTAQUE_IPV.notna()')\n",
        "aluno = df_ml.iloc[0].to_frame().T\n",
        "aluno"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 98
        },
        "id": "2UwjszDbZ7gL",
        "outputId": "00b0685b-af57-48ce-93d3-10a1ecaf8670"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  PONTO_VIRADA                                       DESTAQUE_IEG  \\\n",
              "0          Não  Seu destaque em 2020: A sua boa entrega das li...   \n",
              "\n",
              "                                        DESTAQUE_IDA  \\\n",
              "0  Ponto a melhorar em 2021: Empenhar-se mais nas...   \n",
              "\n",
              "                                        DESTAQUE_IPV      INDE      IAA  IEG  \\\n",
              "0  Seu destaque em 2020: A sua boa integração aos...  7.883752  8.50002  8.7   \n",
              "\n",
              "   IPS  IDA     IPP   IPV   IAN  \n",
              "0  7.5  7.0  5.9375  7.75  10.0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-58c90620-4594-48d7-8c40-523c2ecb393e\" 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>PONTO_VIRADA</th>\n",
              "      <th>DESTAQUE_IEG</th>\n",
              "      <th>DESTAQUE_IDA</th>\n",
              "      <th>DESTAQUE_IPV</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPV</th>\n",
              "      <th>IAN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Não</td>\n",
              "      <td>Seu destaque em 2020: A sua boa entrega das li...</td>\n",
              "      <td>Ponto a melhorar em 2021: Empenhar-se mais nas...</td>\n",
              "      <td>Seu destaque em 2020: A sua boa integração aos...</td>\n",
              "      <td>7.883752</td>\n",
              "      <td>8.50002</td>\n",
              "      <td>8.7</td>\n",
              "      <td>7.5</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.9375</td>\n",
              "      <td>7.75</td>\n",
              "      <td>10.0</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-58c90620-4594-48d7-8c40-523c2ecb393e')\"\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-58c90620-4594-48d7-8c40-523c2ecb393e 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-58c90620-4594-48d7-8c40-523c2ecb393e');\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=\"id_7beba088-e6f7-439c-893d-451fe5a303ea\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('aluno')\"\n",
              "            title=\"Generate code using this dataframe.\"\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",
              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_7beba088-e6f7-439c-893d-451fe5a303ea button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('aluno');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "aluno",
              "summary": "{\n  \"name\": \"aluno\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"PONTO_VIRADA\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"N\\u00e3o\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Seu destaque em 2020: A sua boa entrega das li\\u00e7\\u00f5es de casa.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Ponto a melhorar em 2021: Empenhar-se mais nas aulas e avalia\\u00e7\\u00f5es.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"Seu destaque em 2020: A sua boa integra\\u00e7\\u00e3o aos Princ\\u00edpios Passos M\\u00e1gicos.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.883752,\n        \"max\": 7.883752,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.883752\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.500020000000001,\n        \"max\": 8.500020000000001,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.500020000000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.7,\n        \"max\": 8.7,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.5,\n        \"max\": 7.5,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.0,\n        \"max\": 7.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 5.9375,\n        \"max\": 5.9375,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          5.9375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.75,\n        \"max\": 7.75,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 10.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 660
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "xgb_predict(aluno)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "PhQ5_Okeak9V",
        "outputId": "f09f2261-db30-47f9-97c0-7dc3fcc0a4e8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                        1.0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo      IAA   IAN  IDA  IEG      INDE     IPP  IPS  \\\n",
              "0                        1.0  8.50002  10.0  7.0  8.7  7.883752  5.9375  7.5   \n",
              "\n",
              "    IPV  \n",
              "0  7.75  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ad7700da-553b-4416-9f9f-4a1f848261bc\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>8.50002</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.7</td>\n",
              "      <td>7.883752</td>\n",
              "      <td>5.9375</td>\n",
              "      <td>7.5</td>\n",
              "      <td>7.75</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-ad7700da-553b-4416-9f9f-4a1f848261bc')\"\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-ad7700da-553b-4416-9f9f-4a1f848261bc 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-ad7700da-553b-4416-9f9f-4a1f848261bc');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.500020000000001,\n        \"max\": 8.500020000000001,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.500020000000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 10.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.0,\n        \"max\": 7.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.7,\n        \"max\": 8.7,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.883752,\n        \"max\": 7.883752,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.883752\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 5.9375,\n        \"max\": 5.9375,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          5.9375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.5,\n        \"max\": 7.5,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.75,\n        \"max\": 7.75,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno scaled'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                        1.0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo      IAA   IAN  IDA  IEG      INDE     IPP  IPS  \\\n",
              "0                        1.0  8.50002  10.0  7.0  8.7  7.883752  5.9375  7.5   \n",
              "\n",
              "    IPV  \n",
              "0  7.75  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7a13012a-488b-4b8a-b4c0-36259acd3d58\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>8.50002</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.7</td>\n",
              "      <td>7.883752</td>\n",
              "      <td>5.9375</td>\n",
              "      <td>7.5</td>\n",
              "      <td>7.75</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-7a13012a-488b-4b8a-b4c0-36259acd3d58')\"\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-7a13012a-488b-4b8a-b4c0-36259acd3d58 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-7a13012a-488b-4b8a-b4c0-36259acd3d58');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.500020000000001,\n        \"max\": 8.500020000000001,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.500020000000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 10.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.0,\n        \"max\": 7.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 8.7,\n        \"max\": 8.7,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.883752,\n        \"max\": 7.883752,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.883752\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 5.9375,\n        \"max\": 5.9375,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          5.9375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.5,\n        \"max\": 7.5,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 7.75,\n        \"max\": 7.75,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0])"
            ]
          },
          "metadata": {},
          "execution_count": 661
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aluno = pd.DataFrame({\n",
        "  'PONTO_VIRADA': 'Sim',\n",
        "  'DESTAQUE_IEG': 'Ótimo aluno! Muito bom, continue assim! Você está indo muito bem',\n",
        "  'DESTAQUE_IDA': 'Horrivel, muito ruim, tem que melhorar muito ainda.',\n",
        "  'DESTAQUE_IPV': 'Bem mediano, mas poderia melhorar as notas e se esforçar mais do que fez',\n",
        "  'INDE': 10,\n",
        "  'IAA': 10,\n",
        "  'IEG': 10,\n",
        "  'IPS': 10,\n",
        "  'IDA': 10,\n",
        "  'IPP': 10,\n",
        "  'IPV': 10,\n",
        "  'IAN': 10\n",
        "}, index=[0])\n",
        "\n",
        "xgb_predict(aluno)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "lJV6QCUQthk4",
        "outputId": "2359d49a-815a-47b8-9419-116e67dc94ae"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                        1.0   10   10   10   10    10   10   10   10  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a44af279-3654-4d42-91f9-f1d8fdac52ac\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</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-a44af279-3654-4d42-91f9-f1d8fdac52ac')\"\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-a44af279-3654-4d42-91f9-f1d8fdac52ac 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-a44af279-3654-4d42-91f9-f1d8fdac52ac');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno scaled'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                        1.0   10   10   10   10    10   10   10   10  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-8b4260ef-74ee-460c-8164-0ed26b4ae755\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</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-8b4260ef-74ee-460c-8164-0ed26b4ae755')\"\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-8b4260ef-74ee-460c-8164-0ed26b4ae755 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-8b4260ef-74ee-460c-8164-0ed26b4ae755');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1])"
            ]
          },
          "metadata": {},
          "execution_count": 662
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clone.iloc[4].to_frame().T['DESTAQUE_IPV'].values"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Is09II8R7qDm",
        "outputId": "d12a61e0-b914-4bc3-e8be-60808d1322eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array(['Seu destaque em 2020: A sua boa integração aos Princípios Passos Mágicos.'],\n",
              "      dtype=object)"
            ]
          },
          "metadata": {},
          "execution_count": 663
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aluno = pd.DataFrame({\n",
        "  'PONTO_VIRADA': 'Sim',\n",
        "  'DESTAQUE_IEG': 'Seu destaque em 2020: A sua boa entrega das lições de casa.',\n",
        "  'DESTAQUE_IDA': 'Ponto a melhorar em 2021: Empenhar-se mais nas aulas e avaliações.',\n",
        "  'DESTAQUE_IPV': 'Seu destaque em 2020: A sua boa integração aos Princípios Passos Mágicos.',\n",
        "  'INDE': 8.381391,\n",
        "  'IAA': 8.33334,\n",
        "  'IEG': 9.9,\n",
        "  'IPS': 4.375,\n",
        "  'IDA': 7.333333,\n",
        "  'IPP': 8.750000,\n",
        "  'IPV': 8.944450,\n",
        "  'IAN': 10.0\n",
        "}, index=[0])\n",
        "\n",
        "xgb_predict(aluno)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "3vXDWjXfx2gQ",
        "outputId": "e7f2fd87-91f2-4e6b-d836-d39496a1481b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                        1.0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo      IAA   IAN       IDA  IEG      INDE   IPP  \\\n",
              "0                        1.0  8.33334  10.0  7.333333  9.9  8.381391  8.75   \n",
              "\n",
              "     IPS      IPV  \n",
              "0  4.375  8.94445  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-021fd985-04dd-4759-b95e-1d871b39ea84\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.333333</td>\n",
              "      <td>9.9</td>\n",
              "      <td>8.381391</td>\n",
              "      <td>8.75</td>\n",
              "      <td>4.375</td>\n",
              "      <td>8.94445</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-021fd985-04dd-4759-b95e-1d871b39ea84')\"\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-021fd985-04dd-4759-b95e-1d871b39ea84 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-021fd985-04dd-4759-b95e-1d871b39ea84');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.33334,\n        \"max\": 8.33334,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.33334\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 7.333333,\n        \"max\": 7.333333,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 9.9,\n        \"max\": 9.9,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          9.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.381391,\n        \"max\": 8.381391,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.381391\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.75,\n        \"max\": 8.75,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 4.375,\n        \"max\": 4.375,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          4.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.94445,\n        \"max\": 8.94445,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.94445\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno scaled'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                        1.0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo      IAA   IAN       IDA  IEG      INDE   IPP  \\\n",
              "0                        1.0  8.33334  10.0  7.333333  9.9  8.381391  8.75   \n",
              "\n",
              "     IPS      IPV  \n",
              "0  4.375  8.94445  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7cdf4083-1cf8-426b-89d1-685744ae9648\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>8.33334</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.333333</td>\n",
              "      <td>9.9</td>\n",
              "      <td>8.381391</td>\n",
              "      <td>8.75</td>\n",
              "      <td>4.375</td>\n",
              "      <td>8.94445</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-7cdf4083-1cf8-426b-89d1-685744ae9648')\"\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-7cdf4083-1cf8-426b-89d1-685744ae9648 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-7cdf4083-1cf8-426b-89d1-685744ae9648');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.33334,\n        \"max\": 8.33334,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.33334\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10.0,\n        \"max\": 10.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 7.333333,\n        \"max\": 7.333333,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          7.333333\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 9.9,\n        \"max\": 9.9,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          9.9\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.381391,\n        \"max\": 8.381391,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.381391\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.75,\n        \"max\": 8.75,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 4.375,\n        \"max\": 4.375,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          4.375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 8.94445,\n        \"max\": 8.94445,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          8.94445\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1])"
            ]
          },
          "metadata": {},
          "execution_count": 664
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aluno = pd.DataFrame({\n",
        "  'PONTO_VIRADA': 'Não',\n",
        "  'DESTAQUE_IEG': 'Péssimo aluno, muito ruim, horrivel',\n",
        "  'DESTAQUE_IDA': 'Péssimo aluno, muito ruim, horrivel',\n",
        "  'DESTAQUE_IPV': 'Péssimo aluno, muito ruim, horrivel',\n",
        "  'INDE': 0,\n",
        "  'IAA': 0,\n",
        "  'IEG': 0,\n",
        "  'IPS': 0,\n",
        "  'IDA': 0,\n",
        "  'IPP': 0,\n",
        "  'IPV': 0,\n",
        "  'IAN': 0\n",
        "}, index=[0])\n",
        "\n",
        "xgb_predict(aluno)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "z9MrS_N_8D4h",
        "outputId": "0ea2d8e0-28c0-4132-b279-c478aaa7588b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                        1.0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                          0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                          0    0    0    0    0     0    0    0    0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-e64b6104-dea1-423c-89da-4ce4333ca5b9\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <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-e64b6104-dea1-423c-89da-4ce4333ca5b9')\"\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-e64b6104-dea1-423c-89da-4ce4333ca5b9 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-e64b6104-dea1-423c-89da-4ce4333ca5b9');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno scaled'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                        1.0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                          0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                          0    0    0    0    0     0    0    0    0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-ba5caf06-f779-4f67-90f3-c52a782971e1\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <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-ba5caf06-f779-4f67-90f3-c52a782971e1')\"\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-ba5caf06-f779-4f67-90f3-c52a782971e1 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-ba5caf06-f779-4f67-90f3-c52a782971e1');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0])"
            ]
          },
          "metadata": {},
          "execution_count": 665
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 5) Exportação do XGB e encoders auxiliares para uso no Streamlit"
      ],
      "metadata": {
        "id": "6AKn3JjeAkfB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "xgb_file = 'xgb.pkl'\n",
        "labelencoder_file = 'labelencoder.pkl'\n",
        "onehotencoder_file = 'onehotencoder.pkl'"
      ],
      "metadata": {
        "id": "X1915KI3BPiW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "joblib.dump(xgb, xgb_file)\n",
        "joblib.dump(label_encoder, labelencoder_file)\n",
        "joblib.dump(onehot_encoder, onehotencoder_file)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f7Jb-VwX_3A2",
        "outputId": "14b90686-a402-45b9-f9bc-c91f00841ba7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['onehotencoder.pkl']"
            ]
          },
          "metadata": {},
          "execution_count": 667
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 6) Reimportação do XGB e encoders auxiliares para teste"
      ],
      "metadata": {
        "id": "PeOFKMY1Al7_"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "xgb = joblib.load(xgb_file)\n",
        "label_encoder = joblib.load(labelencoder_file)\n",
        "onehot_encoder = joblib.load(onehotencoder_file)"
      ],
      "metadata": {
        "id": "dhNo1L_cAn4Y"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "aluno = pd.DataFrame({\n",
        "  'PONTO_VIRADA': 'Não',\n",
        "  'DESTAQUE_IEG': 'Péssimo aluno, muito ruim, horrivel',\n",
        "  'DESTAQUE_IDA': 'Péssimo aluno, muito ruim, horrivel',\n",
        "  'DESTAQUE_IPV': 'Péssimo aluno, muito ruim, horrivel',\n",
        "  'INDE': 0,\n",
        "  'IAA': 0,\n",
        "  'IEG': 0,\n",
        "  'IPS': 0,\n",
        "  'IDA': 0,\n",
        "  'IPP': 0,\n",
        "  'IPV': 0,\n",
        "  'IAN': 0\n",
        "}, index=[0])\n",
        "\n",
        "xgb_predict(aluno)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "7jEQ-J4sBUSe",
        "outputId": "718e6750-14bd-4243-95df-3e8fde4617d2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                        1.0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                          0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                          0    0    0    0    0     0    0    0    0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7556d1e8-06b8-4399-b7ef-50ec3a918447\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <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-7556d1e8-06b8-4399-b7ef-50ec3a918447')\"\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-7556d1e8-06b8-4399-b7ef-50ec3a918447 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-7556d1e8-06b8-4399-b7ef-50ec3a918447');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno scaled'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                        1.0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                          0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                          0    0    0    0    0     0    0    0    0  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-bb21150c-356c-43ac-9e43-815f8444e087\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <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-bb21150c-356c-43ac-9e43-815f8444e087')\"\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-bb21150c-356c-43ac-9e43-815f8444e087 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-bb21150c-356c-43ac-9e43-815f8444e087');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([0])"
            ]
          },
          "metadata": {},
          "execution_count": 670
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aluno = pd.DataFrame({\n",
        "  'PONTO_VIRADA': 'Sim',\n",
        "  'DESTAQUE_IEG': 'Ótimo aluno! Muito bom, continue assim! Você está indo muito bem',\n",
        "  'DESTAQUE_IDA': 'Horrivel, muito ruim, tem que melhorar muito ainda.',\n",
        "  'DESTAQUE_IPV': 'Bem mediano, mas poderia melhorar as notas e se esforçar mais do que fez',\n",
        "  'INDE': 10,\n",
        "  'IAA': 10,\n",
        "  'IEG': 10,\n",
        "  'IPS': 10,\n",
        "  'IDA': 10,\n",
        "  'IPP': 10,\n",
        "  'IPV': 10,\n",
        "  'IAN': 10\n",
        "}, index=[0])\n",
        "\n",
        "xgb_predict(aluno)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
        },
        "id": "N1w74r2nDfXQ",
        "outputId": "3190feb7-52ce-4236-9600-67a0d04427cb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                        1.0   10   10   10   10    10   10   10   10  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-2e7f2fc2-3921-467e-b152-20ad45c870fd\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</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-2e7f2fc2-3921-467e-b152-20ad45c870fd')\"\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-2e7f2fc2-3921-467e-b152-20ad45c870fd 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-2e7f2fc2-3921-467e-b152-20ad45c870fd');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "'aluno scaled'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "   DESTAQUE_IDA_NLP_NA  DESTAQUE_IDA_NLP_negativo  DESTAQUE_IDA_NLP_neutro  \\\n",
              "0                    0                        1.0                        0   \n",
              "\n",
              "   DESTAQUE_IDA_NLP_positivo  DESTAQUE_IEG_NLP_NA  DESTAQUE_IEG_NLP_negativo  \\\n",
              "0                          0                    0                          0   \n",
              "\n",
              "   DESTAQUE_IEG_NLP_neutro  DESTAQUE_IEG_NLP_positivo  DESTAQUE_IPV_NLP_NA  \\\n",
              "0                        0                        1.0                    0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_negativo  DESTAQUE_IPV_NLP_neutro  \\\n",
              "0                          0                        0   \n",
              "\n",
              "   DESTAQUE_IPV_NLP_positivo  IAA  IAN  IDA  IEG  INDE  IPP  IPS  IPV  \n",
              "0                        1.0   10   10   10   10    10   10   10   10  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-47394de8-7ba4-4cd8-a92c-b31ac1cefe27\" 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>DESTAQUE_IDA_NLP_NA</th>\n",
              "      <th>DESTAQUE_IDA_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IDA_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IDA_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_NA</th>\n",
              "      <th>DESTAQUE_IEG_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IEG_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IEG_NLP_positivo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_NA</th>\n",
              "      <th>DESTAQUE_IPV_NLP_negativo</th>\n",
              "      <th>DESTAQUE_IPV_NLP_neutro</th>\n",
              "      <th>DESTAQUE_IPV_NLP_positivo</th>\n",
              "      <th>IAA</th>\n",
              "      <th>IAN</th>\n",
              "      <th>IDA</th>\n",
              "      <th>IEG</th>\n",
              "      <th>INDE</th>\n",
              "      <th>IPP</th>\n",
              "      <th>IPS</th>\n",
              "      <th>IPV</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</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-47394de8-7ba4-4cd8-a92c-b31ac1cefe27')\"\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-47394de8-7ba4-4cd8-a92c-b31ac1cefe27 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-47394de8-7ba4-4cd8-a92c-b31ac1cefe27');\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>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"xgb_predict(aluno)\",\n  \"rows\": 1,\n  \"fields\": [\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IDA_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IEG_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_NA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_negativo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_neutro\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 0,\n        \"max\": 0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"DESTAQUE_IPV_NLP_positivo\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 1.0,\n        \"max\": 1.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          1.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IAN\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IDA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IEG\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"INDE\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPP\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPS\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"IPV\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": null,\n        \"min\": 10,\n        \"max\": 10,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          10\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([1])"
            ]
          },
          "metadata": {},
          "execution_count": 671
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "z-OfMs5qDiCo"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}