20_Tesouro_Direto_com_Python.ipynb

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  "metadata": {
    "colab": {
      "name": "20 - Tesouro Direto com Python",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyNbGs/1fQ6dRBUpY+MLyZ6h",
      "include_colab_link": true
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    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/ricospeloacaso/python_para_investimentos/blob/master/20_Tesouro_Direto_com_Python.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q9eCjHMJoX_l",
        "colab_type": "text"
      },
      "source": [
        "###Python para Investimentos - Tesouro Direto"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rSq3QWFToqf-",
        "colab_type": "text"
      },
      "source": [
        "**Python para Investimentos** é um conjunto de códigos e vídeos em que mostro como utilizar a linguagem de programação PYTHON através da ferramenta online Google Colab para fazer estudos no mercado financeiro."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WNVn7q76os1p",
        "colab_type": "text"
      },
      "source": [
        "**Canal no Youtube:** https://www.youtube.com/ricospeloacaso?sub_confirmation=1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KXP7vhJroyKK",
        "colab_type": "text"
      },
      "source": [
        "---\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T5-qfr8RWggk",
        "colab_type": "code",
        "cellView": "form",
        "outputId": "4445b3fc-a066-4ef9-ece1-9040d0d6ec90",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 501
        }
      },
      "source": [
        "#@title Vídeo\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('U3zuklVH6k4', width=854, height=480)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"854\"\n",
              "            height=\"480\"\n",
              "            src=\"https://www.youtube.com/embed/U3zuklVH6k4\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7fa36b7be9e8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 54
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MMSB_xB51av1",
        "colab_type": "text"
      },
      "source": [
        "##Base de Dados: https://www.tesourotransparente.gov.br/ckan/dataset"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sW9B8WZkpAMS",
        "colab_type": "text"
      },
      "source": [
        "##Importações e Configurações Iniciais"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PS36vQlK4bBg",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "pd.set_option(\"display.max_colwidth\", 150)\n",
        "pd.set_option(\"display.min_rows\", 20)\n",
        "\n",
        "import matplotlib\n",
        "matplotlib.style.use('seaborn-darkgrid')\n",
        "matplotlib.rcParams['figure.figsize'] = (18,8)\n",
        "\n",
        "import plotly.graph_objects as go\n",
        "import plotly.express as px"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wi7BbglxMChO",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!pip install yfinance\n",
        "import yfinance as yf"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5x_nO4F_zSBS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import ssl\n",
        "ssl._create_default_https_context = ssl._create_unverified_context"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9Owdsrfdi0yS",
        "colab_type": "text"
      },
      "source": [
        "##1. Funções para Busca e Tratamento de  Dados do Tesouro Direto"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4KAzrb_a416b",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def busca_titulos_tesouro_direto():\n",
        "  url = 'https://www.tesourotransparente.gov.br/ckan/dataset/df56aa42-484a-4a59-8184-7676580c81e3/resource/796d2059-14e9-44e3-80c9-2d9e30b405c1/download/PrecoTaxaTesouroDireto.csv'\n",
        "  df  = pd.read_csv(url, sep=';', decimal=',')\n",
        "  df['Data Vencimento'] = pd.to_datetime(df['Data Vencimento'], dayfirst=True)\n",
        "  df['Data Base']       = pd.to_datetime(df['Data Base'], dayfirst=True)\n",
        "  multi_indice = pd.MultiIndex.from_frame(df.iloc[:, :3])\n",
        "  df = df.set_index(multi_indice).iloc[: , 3:]  \n",
        "  return df"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XJVV3Jb0ti-m",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def busca_vendas_tesouro():\n",
        "  url = \"https://www.tesourotransparente.gov.br/ckan/dataset/f0468ecc-ae97-4287-89c2-6d8139fb4343/resource/e5f90e3a-8f8d-4895-9c56-4bb2f7877920/download/VendasTesouroDireto.csv\"\n",
        "  df  = pd.read_csv(url, sep=';', decimal=',')\n",
        "  df['Vencimento do Titulo'] = pd.to_datetime(df['Vencimento do Titulo'], dayfirst=True)\n",
        "  df['Data Venda']       = pd.to_datetime(df['Data Venda'], dayfirst=True)\n",
        "  multi_indice = pd.MultiIndex.from_frame(df.iloc[:, :3])\n",
        "  df = df.set_index(multi_indice).iloc[: , 3:]  \n",
        "  return df"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ILnM7B4FxQrt",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def busca_recompras_tesouro():\n",
        "  url = \"https://www.tesourotransparente.gov.br/ckan/dataset/f30db6e4-6123-416c-b094-be8dfc823601/resource/30c2b3f5-6edd-499a-8514-062bfda0f61a/download/RecomprasTesouroDireto.csv\"\n",
        "  df  = pd.read_csv(url, sep=';', decimal=',')\n",
        "  df['Vencimento do Titulo'] = pd.to_datetime(df['Vencimento do Titulo'], dayfirst=True)\n",
        "  df['Data Resgate']       = pd.to_datetime(df['Data Resgate'], dayfirst=True)\n",
        "  multi_indice = pd.MultiIndex.from_frame(df.iloc[:, :3])\n",
        "  df = df.set_index(multi_indice).iloc[: , 3:]  \n",
        "  return df"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0qtErNrkIxCC",
        "colab_type": "text"
      },
      "source": [
        "##2.Preços e Taxas Históricas dos Títulos Negociados\n",
        "\n",
        "Essa conjunto de dados contém as taxas e preços dos títulos ofertados pelo Tesouro Direto. Refletem o mercado secundário de títulos públicos federais. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "11f9GSu3oLEQ",
        "colab_type": "text"
      },
      "source": [
        "###2.1 Buscando dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "G0QXEIKV419C",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "titulos = busca_titulos_tesouro_direto()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8_KFgYvs5WjB",
        "colab_type": "code",
        "outputId": "cf0da748-3ce3-4aee-c54e-a7aca84d79c7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "titulos.sort_index(inplace=True)\n",
        "titulos"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    .dataframe thead th {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tipo Titulo</th>\n",
              "      <th>Data Vencimento</th>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"10\" valign=\"top\">Tesouro IGPM+ com Juros Semestrais</th>\n",
              "      <th rowspan=\"10\" valign=\"top\">2005-07-01</th>\n",
              "      <th>2004-12-31</th>\n",
              "      <td>9.23</td>\n",
              "      <td>9.25</td>\n",
              "      <td>1776.67</td>\n",
              "      <td>1776.51</td>\n",
              "      <td>1827.87</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-03</th>\n",
              "      <td>9.23</td>\n",
              "      <td>9.25</td>\n",
              "      <td>1777.71</td>\n",
              "      <td>1777.55</td>\n",
              "      <td>1776.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-04</th>\n",
              "      <td>9.26</td>\n",
              "      <td>9.28</td>\n",
              "      <td>1778.52</td>\n",
              "      <td>1778.36</td>\n",
              "      <td>1777.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-05</th>\n",
              "      <td>9.28</td>\n",
              "      <td>9.30</td>\n",
              "      <td>1779.40</td>\n",
              "      <td>1779.25</td>\n",
              "      <td>1778.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-06</th>\n",
              "      <td>9.31</td>\n",
              "      <td>9.33</td>\n",
              "      <td>1780.21</td>\n",
              "      <td>1780.06</td>\n",
              "      <td>1779.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-07</th>\n",
              "      <td>9.87</td>\n",
              "      <td>9.89</td>\n",
              "      <td>1777.80</td>\n",
              "      <td>1777.65</td>\n",
              "      <td>1775.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-10</th>\n",
              "      <td>10.14</td>\n",
              "      <td>10.16</td>\n",
              "      <td>1776.84</td>\n",
              "      <td>1776.69</td>\n",
              "      <td>1775.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-11</th>\n",
              "      <td>10.26</td>\n",
              "      <td>10.28</td>\n",
              "      <td>1777.04</td>\n",
              "      <td>1776.89</td>\n",
              "      <td>1775.79</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-12</th>\n",
              "      <td>10.89</td>\n",
              "      <td>10.91</td>\n",
              "      <td>1772.67</td>\n",
              "      <td>1772.52</td>\n",
              "      <td>1771.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-13</th>\n",
              "      <td>10.89</td>\n",
              "      <td>10.91</td>\n",
              "      <td>1773.75</td>\n",
              "      <td>1773.60</td>\n",
              "      <td>1772.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"10\" valign=\"top\">Tesouro Selic</th>\n",
              "      <th rowspan=\"10\" valign=\"top\">2025-03-01</th>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10599.69</td>\n",
              "      <td>10594.61</td>\n",
              "      <td>10593.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10600.91</td>\n",
              "      <td>10595.82</td>\n",
              "      <td>10594.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10602.12</td>\n",
              "      <td>10597.04</td>\n",
              "      <td>10595.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10603.34</td>\n",
              "      <td>10598.26</td>\n",
              "      <td>10597.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10604.56</td>\n",
              "      <td>10599.48</td>\n",
              "      <td>10598.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10605.77</td>\n",
              "      <td>10600.69</td>\n",
              "      <td>10599.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10606.98</td>\n",
              "      <td>10601.92</td>\n",
              "      <td>10600.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10608.20</td>\n",
              "      <td>10603.14</td>\n",
              "      <td>10601.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10609.42</td>\n",
              "      <td>10604.36</td>\n",
              "      <td>10603.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10610.64</td>\n",
              "      <td>10605.58</td>\n",
              "      <td>10604.31</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>108759 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                               Taxa Compra Manha  ...  PU Base Manha\n",
              "Tipo Titulo                        Data Vencimento Data Base                      ...               \n",
              "Tesouro IGPM+ com Juros Semestrais 2005-07-01      2004-12-31               9.23  ...        1827.87\n",
              "                                                   2005-01-03               9.23  ...        1776.51\n",
              "                                                   2005-01-04               9.26  ...        1777.32\n",
              "                                                   2005-01-05               9.28  ...        1778.20\n",
              "                                                   2005-01-06               9.31  ...        1779.01\n",
              "                                                   2005-01-07               9.87  ...        1775.73\n",
              "                                                   2005-01-10              10.14  ...        1775.59\n",
              "                                                   2005-01-11              10.26  ...        1775.79\n",
              "                                                   2005-01-12              10.89  ...        1771.45\n",
              "                                                   2005-01-13              10.89  ...        1772.52\n",
              "...                                                                          ...  ...            ...\n",
              "Tesouro Selic                      2025-03-01      2020-05-08               0.03  ...       10593.34\n",
              "                                                   2020-05-11               0.03  ...       10594.57\n",
              "                                                   2020-05-12               0.03  ...       10595.78\n",
              "                                                   2020-05-13               0.03  ...       10597.00\n",
              "                                                   2020-05-14               0.03  ...       10598.22\n",
              "                                                   2020-05-15               0.03  ...       10599.44\n",
              "                                                   2020-05-18               0.03  ...       10600.65\n",
              "                                                   2020-05-19               0.03  ...       10601.88\n",
              "                                                   2020-05-20               0.03  ...       10603.10\n",
              "                                                   2020-05-21               0.03  ...       10604.31\n",
              "\n",
              "[108759 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4lfFLimYnWPo",
        "colab_type": "code",
        "outputId": "50017c5f-ad9e-4c24-f76c-4472e62ad926",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 119
        }
      },
      "source": [
        "tipos_titulos = titulos.index.droplevel(level=1).droplevel(level=1).drop_duplicates().to_list()\n",
        "tipos_titulos"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['Tesouro IGPM+ com Juros Semestrais',\n",
              " 'Tesouro IPCA+',\n",
              " 'Tesouro IPCA+ com Juros Semestrais',\n",
              " 'Tesouro Prefixado',\n",
              " 'Tesouro Prefixado com Juros Semestrais',\n",
              " 'Tesouro Selic']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mhdHl66wjFwt",
        "colab_type": "text"
      },
      "source": [
        "###2.2 Tesouro Selic"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SMwUgbT2-QXM",
        "colab_type": "code",
        "outputId": "ee080e52-2575-4c7d-bad3-4860dcb3b1f0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "selic2025 = titulos.loc[('Tesouro Selic', '2025-03-01')]\n",
        "selic2025"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-02-01</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9926.99</td>\n",
              "      <td>9902.94</td>\n",
              "      <td>9900.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-04</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9929.43</td>\n",
              "      <td>9905.40</td>\n",
              "      <td>9902.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-05</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9931.88</td>\n",
              "      <td>9907.87</td>\n",
              "      <td>9905.36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-06</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9934.34</td>\n",
              "      <td>9910.33</td>\n",
              "      <td>9907.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-07</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9936.79</td>\n",
              "      <td>9912.80</td>\n",
              "      <td>9910.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-08</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9939.25</td>\n",
              "      <td>9915.26</td>\n",
              "      <td>9912.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-11</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9941.70</td>\n",
              "      <td>9917.72</td>\n",
              "      <td>9915.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-12</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9944.16</td>\n",
              "      <td>9920.19</td>\n",
              "      <td>9917.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-13</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9946.61</td>\n",
              "      <td>9922.65</td>\n",
              "      <td>9920.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-02-14</th>\n",
              "      <td>0.02</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9949.07</td>\n",
              "      <td>9925.12</td>\n",
              "      <td>9922.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10599.69</td>\n",
              "      <td>10594.61</td>\n",
              "      <td>10593.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10600.91</td>\n",
              "      <td>10595.82</td>\n",
              "      <td>10594.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10602.12</td>\n",
              "      <td>10597.04</td>\n",
              "      <td>10595.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10603.34</td>\n",
              "      <td>10598.26</td>\n",
              "      <td>10597.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10604.56</td>\n",
              "      <td>10599.48</td>\n",
              "      <td>10598.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10605.77</td>\n",
              "      <td>10600.69</td>\n",
              "      <td>10599.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10606.98</td>\n",
              "      <td>10601.92</td>\n",
              "      <td>10600.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10608.20</td>\n",
              "      <td>10603.14</td>\n",
              "      <td>10601.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10609.42</td>\n",
              "      <td>10604.36</td>\n",
              "      <td>10603.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>0.03</td>\n",
              "      <td>0.04</td>\n",
              "      <td>10610.64</td>\n",
              "      <td>10605.58</td>\n",
              "      <td>10604.31</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>324 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2019-02-01               0.02              0.06  ...         9902.94        9900.45\n",
              "2019-02-04               0.02              0.06  ...         9905.40        9902.91\n",
              "2019-02-05               0.02              0.06  ...         9907.87        9905.36\n",
              "2019-02-06               0.02              0.06  ...         9910.33        9907.83\n",
              "2019-02-07               0.02              0.06  ...         9912.80        9910.29\n",
              "2019-02-08               0.02              0.06  ...         9915.26        9912.76\n",
              "2019-02-11               0.02              0.06  ...         9917.72        9915.22\n",
              "2019-02-12               0.02              0.06  ...         9920.19        9917.68\n",
              "2019-02-13               0.02              0.06  ...         9922.65        9920.15\n",
              "2019-02-14               0.02              0.06  ...         9925.12        9922.62\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               0.03              0.04  ...        10594.61       10593.34\n",
              "2020-05-11               0.03              0.04  ...        10595.82       10594.57\n",
              "2020-05-12               0.03              0.04  ...        10597.04       10595.78\n",
              "2020-05-13               0.03              0.04  ...        10598.26       10597.00\n",
              "2020-05-14               0.03              0.04  ...        10599.48       10598.22\n",
              "2020-05-15               0.03              0.04  ...        10600.69       10599.44\n",
              "2020-05-18               0.03              0.04  ...        10601.92       10600.65\n",
              "2020-05-19               0.03              0.04  ...        10603.14       10601.88\n",
              "2020-05-20               0.03              0.04  ...        10604.36       10603.10\n",
              "2020-05-21               0.03              0.04  ...        10605.58       10604.31\n",
              "\n",
              "[324 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m4dh6Sdb0P29",
        "colab_type": "code",
        "outputId": "32ba20c2-c61e-45ba-d731-b2a70206edf1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "selic2025['PU Base Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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Vl0Z6EMa0FDUhh/W7Snjpo108uvozsjPbcM+0HPp3tonNzPFLcBwn1hmOqrCwLObhrF8wMn7OBv7Ml19SyexFG9laeAiA8YM6c/N5g0hv7Z/7I/34utWybF/IympX53VR//wkGRPH1u0u4cZFnxAMOcy5cBgndU23rhsTdVbwjYmRYMhhyeYCVuQd5M3c/XRr15q/XjiMk07o7NszVdO8WcE3JgbKA0H+56VNvLu9iE5pKZw/pCs/HNuPzDatYh3NtGBW8I1pYntLK/npPzeSt/8Qv5w4kAtzutk0CKZJWME3pom8vGkfL6zbw/r8UlJbJXH3RTmc3rdDrGOZOGIF35hGFnIc5i3/lMc/2MUJndpyxahefHOoTVlsmp4VfGMaieM47Cg6zL0rtvPG1v1MG9Gdn507gORE674xsWEF35hG8NGuEm5bsoWdRYdJAJuf3viCFXxjouzlTfu47dUtdG+fys/HD2B0v470yEiNdSxjrOAbEw3VNSHW7iph2Zb9PL9+DyN7ZfDHKUPIsGGWxkes4BtznPaUVnLDCx+zbX8FrZISuGh4d2af259WSZHOTWhM47CCb8xx2Li3jJ++8DFVNSFunzyYsf070TYltov2GHM0VvCN+YpqQg5LtIC3tx1k+bYDdGrbivsuHs4JnWxGS+NvVvCN+QoOV9dw8782u4U+LYVvDO7CtWP70rGtTXRm/M8KvjENtK8swOx/bmRLYTmzz+nP9JN7kGjDLE0zYgXfmHq8poX834e7+XhPKanJSdx5wVDGnNCp/i80xmcaVPBFZBiwCLhLVeeLSC/gMSAJd33ay1U1ICK/ASbhrlv7kqre7q1juxDoA9QAM1U1T0RGAPcBDrBeVWdF+diMOS6O4/DY+7uY9/annNCpLTNP783kIV3pbVMimGaq3nFjIpIGzAOWhTXfCtyjqmOBXOAqEekL5KjqmcBo4AoR6QHMAIpVdQxwBzDH28dc4DpVHQ1kiMikKB2TMcftcHUNc9/KY97bnzJRsnj88lO4ZnRfK/amWWvIGX4AmAzcFNY2DrjGe7wYmK2q9/HFYuUdgBBQCowHHvXalwILRCQF6Keq74ftYwLwcmSHYUx07C8P8Mdluby7vYhAMMTFJ/XgZ+f2t7560yLUW/BVNQgERSS8OU1VA97jAqB77RMicjfwHeBnqlouIt2AQm9fIRFxgG5AUdj+vrSPWunprUlOju2Y5qSkRDIz28Y0w9FYtsjVlW/nwQp+8PR6Dhyq4pJTe3HekK6M6tuhyee/8fNrZ9ki45ds0bho+6V3g6peJyK/A94UkZX1bX+MNsrLA3U1NylbGDkyfs4GX87nOA4b9pRx04ufUF0T4t5pOQzt3h6AkpLDMc3mN5YtMjFYxLzO9kjv/S4XkdrOzGwgX0R6icipAKpaBKwETgPycc/o8S7gJuBe6A0f5pDtbWdMk3p+XT4XPLSa7z/5EQkJ8MAlIz4v9sa0NJEW/KXAVO/xVOAVIAu4T0SSRSQJGAlsAZbwRd/+FOANVa0GNovIGK/9Im8fxjQJx3G4f+V25izNpUu71vxq4kCe+N5I+ne2u2VNy1Vvl46IjATuBPoC1SIyDbgUWCgiVwM7gEdUtVpEnsc9s08A/qWqH4nIBmCiiKzAvQB8pbfr64EHRCQRWKWqS6N7aMbUrbSymrlvb+d/V+/k28O68YuJA21REhMXEhzHiXWGoyosLIt5OOsXjIwfsxWUBbh9yRZW7yymJuRw2ak9+cnX+vluURI/vna1LFtkYtCHX+cPtd1pa+LCjoMV/Pi5DZRWBrns1J5MOTmbPuk2/42JL1bwTYtWE3JY81kxv/73ZhwH7r94OIO7tvP12aAxjcUKvmmxnlizi0dWf8bBimq6tWvNvGk59O0Y+7HQxsSKFXzT4jiOw7zln/LYB7s4vU8mU4Z2Y0z/jqSl2I+7iW/2DjAtSkFZgPtXbmfxxn1MG9GdG8cPsGkRjPFYwTctQn5JJb/592bW5ZcCcNUZvbnmrD6+G4FjTCxZwTfNXu7+Q/zkuQ0EgiGuHdOXcQM606+T9dUbcyQr+KbZqgqGWPnpQW5fsoWUpEQeuGQEA+xOWWOOygq+aXYcx2HBqp08unoXFdU19MpMZd60HLIzbK56Y47FCr5pVkKOw5+X5fLsuj2MG9CJC4Z357RemaQkRzotlDHxwwq+aRYcxyHvQAUPvbuDpVv2c/mpPfmxD6dFMMbPrOAb3/us6DCzF20k70AFCcCPxvbjilG9Yh3LmGbHCr7xte0HK5j19HqCIYebxg/ga/070aVd61jHMqZZsoJvfMlxHNbnl/LzFz8B4L6Lh9sIHGOOkxV84ztLNhdwz4rt5JdU0jkthXunD7dx9cZEgRV84ysvbdzLra9sYXDXdL5/xiDOGdCZdqn2Y2pMNDTonSQiw4BFwF2qOl9EegGPAUm469NerqoBEbkE+BkQApap6q+8dWwXAn2AGmCmquaJyAjgPsAB1qvqrCgfm2lGHMfhpY37uO3VLZzWO5M7LxhKaqukWMcypkWpd/CyiKQB84BlYc23Aveo6lggF7hKRNoCfwTGA2cCE0RkCDADKFbVMcAdwBxvH3OB61R1NJAhIpOidEymGakJOSxctZOLF37ArVbsjWlUDblbJQBMBvLD2sYBL3qPFwMTVLUCyFHVMlV1gANAJ9xfAC942y4FRotICtBPVd8P38fxHIhpfmpCDre8otyzYjsd26Zw0/gB/PXCYVbsjWkk9XbpqGoQCIpIeHOaqga8xwVAd2/bMgARycFd9Pw94NdAofd8SEQcoBtQFLa/z/cRLj29NcnJsX3zJyUlkpnpzwuGzTlbTcjh58+t5+VNBfx0wkBmnd2/CdM179culixbZPySLRpXw750q6OIDASeAGaoavURvyj+Y/tjtFFeHqiruUn5eSm85pituKKaFzbsYcnmQnL3H+LaMX357ojuTX4czfG18wPLFpkYLGJeZ3ukE5CUi0jtTFXZeN09ItIT+Cdwhap+5D2fj3tGj3cBNwH3Qm+nsP19vg/TchWWB/j+/33EvSu206ZVErdMEmae3jvWsYyJG5EW/KXAVO/xVOAV7/HDwCxV/TBs2yXAdO/xFOANVa0GNovIGK/9orB9mBaooCzANU+vZ395FX+/ZAQLZpzE5CFdYx3LmLhSb5eOiIwE7sTtk68WkWnApcBCEbka2AE8IiKDgLHArWHdOH8FngImisgK3AvAV3rPXQ88ICKJwCpVXRqtgzL+sbe0kqVb9vPM2t2UVAb529RhjMjOiHUsY+JSQy7arsEdlXOkiUf8ewtwtKsSM+vY7ye4vyBMC/Xu9oPcuOgTAsEQg7ukc/v5J5LTo32sYxkTt+wWRtMo3tpSyOx/bqRvx7b8YcoQenWwxUmMiTUr+CaqCsoCLNFC7l3xKSd0SuOeaTlktGkV61jGGKzgmyhxHIf5b2/n0fc/A+C0vh2YM3mwFXtjfMQKvjlujuMw9608nlizm28O7coVp/XipP6dfTsm2ph4ZQXfHJcDh6p46N0dPLtuD5ec3IOfndPflh00xqes4JuIfLCzmIWrd/L+zmJCDswYmc31Z59gxd4YH7OCb74Sx3H4+7s7+Pu7O8lKT2Hm6b2ZMCiLAVm2GpUxfmcF3zRIIBhiqRayRAt459Mipgztyk0TBtI6OdKbtY0xTc0KvqlXRVUN1z+/gbW7S+narjU/OLMP3z+zN4nWfWNMs2IF3xzToaog1z33MR/vKeWWScKkE7tYP70xzZQVfFOn8kCQt/MO8MQHu9laWM7t55/IBMmKdSxjzHGwgm/+g+4r50fPbaD4cDVZ6SnMmTKEcwZ2jnUsY8xxsoJvvmTTvjJ+9OwG2rZK4sFLRjAiu7311RvTQljBN4DbV/9W7gH+8vo20lsncf/FI+iRkRrrWMaYKLKCb3h67W7+tvxTAsEQfTq0Yd60HLq3t2JvTEtjBT/OPf7BLu5+K4/R/Tpy5aheDLcuHGNaLCv4cepQVZAnPtjNg+/uYMKgztw2eTDJSXYTlTEtWYMKvogMAxYBd6nqfBHpBTwGJOEuSH65qgZEpAPwJFCuqtO8r20FLAT6ADXATFXNE5ERwH2AA6xX1VnRPTRTl8rqGv64LJfXtJBAMMR5ksUtkweTnGhn9ca0dPWe0olIGjAPWBbWfCtwj6qOBXKBq7z2+4EVR+xiBlCsqmOAO4A5Xvtc4DpVHQ1kiMikiI/CNEhldQ2zF23kXxv38c2hXXnwkhHcfr4Ve2PiRUM+wweAyUB+WNs44EXv8WJggvf4v/jPgj8eeMF7vBQYLSIpQD9Vfb+OfZhGUB4IcsM/N7J6RzG/+cYgfjFhICf3zLC7Zo2JIw1ZxDwIBEUkvDlNVQPe4wKgu7dt2RHbAXQDCr3nQyLieG1FYdt8vo9w6emtSU5OatiRNJKkpEQyM4+2NntsNSTbtsJy7nxtC29t3U+wJsSfpw7n2yf18EW2WPJzPssWGctWv2hctP2qp4h1bV/nPsrLA3U1N6nMzLa+Xbmpvmy5hYe49pn1hByHC3O6MWlIV4Z2a9ckx+Pn1w38nc+yRcayfSErq12d7ZEW/HIRaaOqh4Fsvtzdc6R83DP6dd4F3ATcC72dwrapbx/mK9pSUM61z6yndXIi904fQZ+OsT+7MMbEVqTj8JYCU73HU4FXjrHtEmC693gK8IaqVgObRWSM135RPfswDbQi7wCz/7mRmU+sJbVVEg9cYsXeGOOq9wxfREYCdwJ9gWoRmQZcCiwUkauBHcAjIpKEO5InE8gWkTdxR/M8BUwUkRW4F4Cv9HZ9PfCAiCQCq1R1aRSPKy49vTafP7+eS5f0FC4c3p3LTu1JN7tj1hjjachF2zW4o3KONLGOtrq2A5hZx34/AcbW9/+bhnlizS7uejOPs/t3Ys6UE2llN1EZY45gd9o2Y1XBEP/+ZB+vaSEr8g5y7sDO3HG+3TFrjKmbFfxmavvBCu56YSPv5B2ga7vWzDy9Fz84s48Ve2PMUVnBb2Yqqmp4bl0+89/+lJTkRH45cSAX5HSzCc+MMfWygt9MVNeE+NOyXF7eVEAgGGLMCR35y/QRJAVrYh3NGNNMWMFvBqqCIX6x+BPezjvIBTnd+MaJXTi5ZwYd01v79kYTY4z/WMH3ueLD1fz25c2882kRN40fwLQmmBbBGNMyWcH3oWBNiAff3cHybQfYtr+CBOBXEwdywfD/mG7IGGMazAq+z1TXhPiflzbxZu4BRvXO5OtjunBm3w4M7lr33BjGGNNQVvB94nB1DSvyDvLMR/ms3VXC7HP6c8kp2bGOZYxpQazg+8BnRYe59pn17C0L0LFtK24+byDfzrHuG2NMdFnBj7HtByu49pn1VNc4zJs6jNN6dyDJVqAyxjQCK/gxUh4IsnzbAe5+Kw+A+y4ezoDOaTFOZYxpyazgx8DHe0q5+ql1VNU4ZGekcteFw+jXyaYwNsY0Liv4MbBhTxlVNQ73TMvh1N6ZNi2CMaZJWMGPgfySStq0SuS03pm2iLgxpsnY1IoxsKekku7tU63YG2OaVIPO8EVkGLAIuEtV54tIL+AxIAl3fdrLVTUgIpfirmQVAh5U1Ye9dWwXAn2AGmCmquaJyAjgPsAB1qvqrCgfm2/ll1bSI8NWojLGNK16z/BFJA2Yh7t8Ya1bgXtUdSyQC1zlbfcbYALuylc3iEhHYAZQrKpjgDuAOd4+5gLXqepoIENEJkXnkPztYEUVu4vdM3xjjGlKDenSCQCTgfywtnHAi97jxbhF/nTgfVUtUdXDwEpgNDAeeMHbdikwWkRSgH6q+v4R+2jRDhyq4pqn11PjOEw6sUus4xhj4kxD1rQNAkERCW9OU9WA97gA6A50AwrDtvmPdlUNiYjjtRXVse2XpKe3Jjk5qcEH0xiSkhLJzDy+IZOb95bxzJpd/PvjPRwK1PDQ5SM544ROvsjWWPycDfydz7JFxrLVLxqjdI525fGrtNe5bXl5oK7mJpWZ2fa45px/d/tBblz0CY7jcFa/jlwxqheDO7aJyjz2x5utMfk5G/g7n2WLjGX7QlZW3ZMtRlrwy0Wkjdd1k43b3ZOPe+ZeKxt4L6x9nXcBNwH3Qm+nI4m1VGIAABDjSURBVLYN7zJqEVbmHeTGFzfSr2Nb5k/LoUPblFhHMsbEsUiHZS4FpnqPpwKvAKuA00QkU0TScfvv3waWANO9bacAb6hqNbBZRMZ47Rd5+2j2HMfhg53F/GHpVmYv2siAzmncO324FXtjTMzVe4YvIiOBO4G+QLWITAMuBRaKyNXADuARVa0WkV8Ar+IOtbxFVUtE5ClgooiswL0AfKW36+uBB0QkEVilqkuje2hNL+Q4/OX1bTzzUT6pyYmMH9SZm8YPpF2q3d9mjIm9BMdxYp3hqAoLy2IerqF9byHH4Q9Lt/LC+r3MGJnNrNF9SW3VuBecrc8ycn7OZ9kiY9m+kJXVrs7ronbqeZyqa0Ks3lnM8+v2sHzbAWae3otZo/vaXbTGGN+xgn8c9pcH+OGzG8g7UEFaShI/HNOXK0b1smJvjPElK/gRKigLMOuZ9RSWB7jj/MGMG9CZlGSbmsgY419W8L+iQDDEe9uLmPvWNooqqpk3NYcR2RmxjmWMMfWygv8VvJV7gN++vJlDVTV0bNuK+dNyGNa9faxjGWNMg1jBP4aakMPWfWW8v20/G/eU8dz6PUiXdGaN7sOpvTJJTrIuHGNM82EF/yiKKqr4yXMfs7mgHIDU5ETGntCR335DSG9tL5sxpvmxylWHA4equPaZ9ewuqeR3U4ZwYqc29OnQlqREG31jjGm+rOCHqQqGWLWjiL8tz2NvaYC7LhzKxOHZvr2Zwxhjvgor+J53Pj3Izf/aTFkgSEZqMn+bmsPJPW30jTGm5bCCDyzfdoBfLP6Evh3bctvYwYzqnUkruyBrjGlh4rrgV1TV8MrmAv60LBfpks68qcNon9oq1rGMMaZRxGXBDzkOd7+Vx3Pr9hAIhhjRoz1zLxpmo2+MMS1a3FW4mpDDbUu28K+N+5g8pAvfGtaNk7IzbASOMabFi6uCX1pZzZ+W5fLq5kKuPqsP/3Vmn1hHMsaYJhMXBX9vaSV/WJrLezuKqAk5/GhsP64Y1SvWsYwxpklFVPC9VaruB4YBVcA13lMP4q52tQWYpapBEbkUd3WrEPCgqj7srW27EOgD1AAzVTXveA7kaHYVH+baZ9ZTWhnk0pHZTJAsTuxa9wK/xhjTkkU69vDbQIaqngV8H/gL8EdgjqqeDewELhaRNOA3wARgHHCDiHQEZgDFqjoGuAOYc1xHcRTbD1Rw9VPrqKiq4b6Lh/Pjr51gxd4YE7ci7dIZCKwGUNVtItLH29dq7/lXgWuBvcD7qloCICIrcRc3Hw886m27FFgQYY46fbirmHvf3s76/FIy27Ti3unDGdQlPZr/hTHGNDuRFvwNuGfrc4EBwAm4xf583EL+daAr0A0oDPu6AqB7eLuqhkTEEZEUVa0K/0/S01uTnPzV14X9dOM+aoAfnzuAqSdn0yOzzVfeR62kpEQyM9tG/PWNybJFzs/5LFtkLFv9Iir4qvqyiIwGlgPrgU3A94D7RORK4C2grnGORxv7WGd7eXkgknhMHdqVqUO7ev9yjmsuHFsYOTJ+zgb+zmfZImPZvpCVVXfXdcSjdFT15trHIrIN2K2q3/T+/XXcM/l83LP5WtnAe2Ht67wLuAlHnt0bY4yJrogu2orICBFZ4D3+BvAh8FsROd/bZCawGFgFnCYimSKSjtt//zawBJjubTsFeCPyQzDGGNMQx9OHnygiq4FK4FKgLfCYiPwOeFtV/wUgIr/AvYjrALeoaomIPAVMFJEVQAC48riOwhhjTL0i7cMPUXeRHlXHts8Czx7RVoP7KcAYY0wTsTmAjTEmTljBN8aYOGEF3xhj4kSC4zixzmCMMaYJ2Bm+McbECSv4xhgTJ6zgG2NMnLCCb4wxcSLuC76I+HaCfBHpLiJd698yNkQk25taw3dEJDXWGY5FRHy7iLJfs9l79fjFxRKHdfEmbfs5cLaIPAEsVdVdMY4FgIgk42abAvwY2BfbRF/m5bsJd/Gbp4FXRCRBVWM+5Mv7vv4CyBaRZ4FVqlrmh3zeSnG/Bhaq6g4RSfLuOo85n2ez92qUxOUZvoikAHcD7YE/ARcAfWOZqZaInI47o2hnYLKqfhDjSF8iIhOBd3CXrLwB6AgQ62IaZg7uTKzP4K6ydrWItPJJvtHALGAefD7FiF/4Mpu9V6Mrrgq+iNRO1ZwGDFbVm1R1KVCKW8BiRkS6ew+Lvb/vUNUiETlJRIZ5Z2Ax+7gdlm8LcI2qzgHeBPaJSFosuwFqv68i0hYYCvyPqi7DnbTvTOBb3vNNnjHs+5YEnII7B9VQEZkS1h4TYe8HgJH4M5u9V6MoLm68EpFOwO3AENzFWe4HUnDX3r0edznGlcAa4ElVLTzKrpoi233AxcBJuKuCjQQO4hba+aq6p6my1ZHvTeAFVf3Ie+4U4DeqekFTZjpKtrdwz05vAZJV9QciMgT4GRAEfq2qBU2YLRWYD7wI/FtVgyKSo6obRGQacJuqnuht26TdTXV8Tx8FylS1wGfZ7L0aZfFyhn89UIG7mPpB4HlV3e7N+vmaqg4AHsDtCpgWw2xFwOPAPbiLxVSq6njcheAd4JImznZkvgO4b0AAVPVDoCKGF27DsxUD/4tb4IeKyEPAw7gfufcBPZo4W1fgXNyz+hMAVHWD9/ezwEFv6vBYdIf9x89c7S9Dn2Wz92qUteiCX/vRCigBNqpqtarOBYIi8iPvuW0AqvoO7sfFSu9rG/Xj2FGy3YX7EXY67sfrv3vZNnnblTVFtmPk+xvua/dDb5tU3IKa1ZQfX4+S7a+4/bwXqepo4C7gW6r6d+BUoFVT5fMMxJ0WvDcwSkTaeNlrc/wYqH0dR4hIz8YOdIz3Q03t99SH2ey9GkUtsuDXvsjeWQFAa6C9iKR5/74JmO39+zIRmeT9UJ+D+9u50c5sGpBtNvB73I+IQRHJEZFsL1ugMbM1MN9NwI3ehdBK3P7UIUCHxsr0FbLNBu7wLvQdAPqJyHCg2vvT6NnCrFLVn+Ou/DYGEC97tff3h8AmESnGLa6NfpG0Id9Tn2aLyXu1Adli+l6NRIsp+CLSQURmi4jg/uYNP5t6GfgG0FdEElV1JbAauBzIxV2A/RngUVVdGONsK4D3gauBnsAvgReA/1XVx6OdLYJ8K3GXrrzJe/5V3FETjXIGHcFrtxr3tWuH+5F/AbCo9rpDE2SrvdBZu2L1ItxrCOPEG0cuIq1E5Ke4w6KvV9UfRLu/18v2SxE5RUQyav9f7+mjfU9/7m3nt2xN/V5taLYmf68erxZR8EVkPO4bqxvuR6w7vacc7xvzIfAR8B2gn/fcYiCoqq/j/jCNVtX/9VG2SlWt/WE6szGyHWe+vQCquhWYoapRH398HNkOe7l+AYxS1QVNmA1whzV6FzxDuAVqIJAjItfgXoR8DzivkYrW13ALT1fc16b2ukt9r1vt9/AjH2ZrivdqpNma5L0aDS1ilI6IXAaIqv7a+/dG3NEjz3n/Pgn3wsq5uGvvvoc75vh2VX3Jp9nuUNXFjZntOPP5+bXzQ7YxQLWqrvL+/QIwAveMcJaqHmyETKmqWinuSJuzVPWnXvvHwK2q+rT376O9br9X1RejnStK2RrtexqFbE3yXo2GZnmGLyL9vTdcrU5Audd/BrAC9+MVIvJX3CvpH+HelLMEOAt3rHbUf4CimK1RfoDi5LXzQ7bfAyUikiwiVwAZwH+p6iXRLvYiMlRE7gVu9/q32wIFItLR2+RXuHfR1ve6Rb3YRzFbY3xPo5WtWRR7aEZn+BI2HljcW+Z7A79S1ddEZBTulfIk3KFclbgXTh7B7b+N+tlUc8nm93zxkE1EeqvqzsbIJiJ9vP/zfuB03OsF7wCXATepaq63/WvAP4HHVLU0mlksW/PRnM7wWwGIyCDcEReP4l61T1DV1bi3Xa8EilT1FuC3QA7e3XDSuHcN+jmb3/O15GzJANEu9p4U7++xwCFV/T/gd7i/dFYCO4DviEimt93vvW0rvGyN+bpZNp/y/eRpInIO8CMgX0SeUtUVIvIb3GFPw4GrgIdVdTuwXbwr68AoYFvtkCpthLlB/JzN7/niJFuwEbPtEXcisWeBjeJeVCwRkVxv0weAW4GpuDeg9QXW1mZq5NfNsvmUr8/wxZ2z4g7gIdyPW1eIyExvBMZ+4N/AJBHp4W3fB7hORN4BJgEfxmM2v+ezbFHJthKYCXxHVdfijiTpBAwAalRVgXuB/iLyKm5XxbuWzV/ZmprvzvC9j0y/xn1zObhzt7ws7l2d+bg31ixW1f0ishY4A3e89d9wP4LfDryj7kRLcZPN7/ksW6Nme8nL9k1gjaoeEPdGsEJV/R8RGeV1QVk2H2SLJV+d4XtnTU/jjmg4jDsZ1mUi0lbduzprb3S4EUBVd3jbXy3usLjTVTXUSG8832bzez7L1ujZam+CSwSeE5ELgbdxfzHRSAXVsjVDfjvDzwI6qupUABEZxxc3tczytnkc9yN0D9zf3Hfhzk53u6quidNsfs9n2Ro32/Xi3g06Bnf2xqeAn6h7o5Bl81e2mPJbwd+HOyY2Efe37jbcftFHReQhVV0jIqW4v7ULcH+Dz1XVF+I8m9/zWbbGzRbAndPoIWCJqj5l2XybLaZ8Ow5f3CFtrwPfBi4Fvgn8GfduxbHA5apabtmaVz7L1mjZLlXViqPvwbL5LVss+O0MP1wOgKoWAfNF5BDuLc3dcG9Nj1lB9Xk28Hc+yxb9bNfGuGhZtmbCzwU/G3jSG1J1P+6MeTerP6Yb9XM28Hc+yxYZyxYZP2drcn4u+J2AucCFwEJVfSLGecL5ORv4O59li4xli4yfszU5Pxf87bjDpu5V1aoYZznSdvybDfydbzuWLRLbsWyR2I5/szU5P1+0bdLFk78KP2cDf+ezbJGxbJHxc7ZY8G3BN8YYE12+utPWGGNM47GCb4wxccIKvjHGxAkr+MYYEyf8PCzTmOMiIn2BDcAaIAF3Gbvfq+qyY3xNb6BbQ2ZK9CblegbY6DUlAf+tqpuPL7kxjcPO8E1Lp6o6TlXPBn4AzBOR4cfY/lzclasa6i1v/+OAvwM3RB7VmMZlZ/gmbqjqNhG5A/gh7nz2f8Ut7qm4t90vwl3ftFpEduKuY3obUAUUARfXc/NOV2A3gIhMOPJrgTa487S39v78UFU/9DKNxf2EMF9Vn4zmcRtTy87wTbz5ABjirXy0XVXH4BbbW1W1EFgI3K2qLwIdgBnep4NS4Ot17O9sEXlTRNYA3wce9Nrr+trxwC7v08ClQBcRGQv0UdWv4X66uFlE2jTGgRtjBd/Em3a4a5dWAh3FXYv2ZdxFM45UCDwkIm8B5+DOy3Kk2i6dkbhdRk8f42vfBc4UkfuBAar6CnAWcIaIvAm8ivue7B6dQzXmy6xLx8SbU4G1InI27hn12apaLSJ1TX28ADhfVTeJyPz6dqyqy0VkkLjrqf7H16rqHhEZgfsLYJaInAGUAQ+r6pwoHZ8xR2Vn+CZuiEh/4Ke4SxR2Bj7ziv23gCQRScFdAan2RCgD2CkimbhFOqUB+y9W1Zq6vtbr15+gqkuAH+P+8lkFTBGRRBFJFZF5UT5sYz5nc+mYFuuIYZmtcS+K/kpVXxORDOA13KUL/4nbtVIK/B/wCO6i5QJ8C3f92n/hXtA9S1X3ePsfx5eHZbYCfq6qK0Xk1jq+dgbuaktB3F8sv1XVt72LthNwh47eq6oLG+P1MMYKvjHGxAnr0jHGmDhhBd8YY+KEFXxjjIkTVvCNMSZOWME3xpg4YQXfGGPihBV8Y4yJE/8PD1bNXeQAoFQAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OR4tdcehkjgQ",
        "colab_type": "text"
      },
      "source": [
        "###2.3 Pré-fixado 2023"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jSnWgtSrknVp",
        "colab_type": "code",
        "outputId": "89cd4f60-2978-4a67-ac52-64cb57b748a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "pre2023 = titulos.loc[('Tesouro Prefixado', '2023-01-01')]\n",
        "pre2023"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2016-01-26</th>\n",
              "      <td>16.59</td>\n",
              "      <td>16.65</td>\n",
              "      <td>346.72</td>\n",
              "      <td>345.49</td>\n",
              "      <td>345.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-27</th>\n",
              "      <td>16.32</td>\n",
              "      <td>16.38</td>\n",
              "      <td>352.52</td>\n",
              "      <td>351.27</td>\n",
              "      <td>351.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-28</th>\n",
              "      <td>16.42</td>\n",
              "      <td>16.48</td>\n",
              "      <td>350.65</td>\n",
              "      <td>349.41</td>\n",
              "      <td>349.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-29</th>\n",
              "      <td>15.93</td>\n",
              "      <td>15.99</td>\n",
              "      <td>361.21</td>\n",
              "      <td>359.92</td>\n",
              "      <td>359.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-01</th>\n",
              "      <td>15.89</td>\n",
              "      <td>15.95</td>\n",
              "      <td>362.28</td>\n",
              "      <td>360.99</td>\n",
              "      <td>360.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-02</th>\n",
              "      <td>15.62</td>\n",
              "      <td>15.68</td>\n",
              "      <td>368.36</td>\n",
              "      <td>367.04</td>\n",
              "      <td>366.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-03</th>\n",
              "      <td>15.90</td>\n",
              "      <td>15.96</td>\n",
              "      <td>362.49</td>\n",
              "      <td>361.20</td>\n",
              "      <td>360.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-04</th>\n",
              "      <td>15.73</td>\n",
              "      <td>15.79</td>\n",
              "      <td>366.38</td>\n",
              "      <td>365.07</td>\n",
              "      <td>364.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-05</th>\n",
              "      <td>15.99</td>\n",
              "      <td>16.05</td>\n",
              "      <td>360.98</td>\n",
              "      <td>359.70</td>\n",
              "      <td>359.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-02-10</th>\n",
              "      <td>15.97</td>\n",
              "      <td>16.03</td>\n",
              "      <td>361.62</td>\n",
              "      <td>360.34</td>\n",
              "      <td>360.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>4.56</td>\n",
              "      <td>4.68</td>\n",
              "      <td>888.83</td>\n",
              "      <td>886.14</td>\n",
              "      <td>885.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>4.55</td>\n",
              "      <td>4.67</td>\n",
              "      <td>889.21</td>\n",
              "      <td>886.52</td>\n",
              "      <td>886.36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>4.41</td>\n",
              "      <td>4.53</td>\n",
              "      <td>892.51</td>\n",
              "      <td>889.81</td>\n",
              "      <td>889.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>4.62</td>\n",
              "      <td>4.74</td>\n",
              "      <td>887.96</td>\n",
              "      <td>885.28</td>\n",
              "      <td>885.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>4.99</td>\n",
              "      <td>5.11</td>\n",
              "      <td>879.92</td>\n",
              "      <td>877.28</td>\n",
              "      <td>877.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>4.79</td>\n",
              "      <td>4.91</td>\n",
              "      <td>884.50</td>\n",
              "      <td>881.85</td>\n",
              "      <td>881.68</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>4.66</td>\n",
              "      <td>4.78</td>\n",
              "      <td>887.55</td>\n",
              "      <td>884.89</td>\n",
              "      <td>884.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>4.56</td>\n",
              "      <td>4.68</td>\n",
              "      <td>889.93</td>\n",
              "      <td>887.26</td>\n",
              "      <td>887.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>4.54</td>\n",
              "      <td>4.66</td>\n",
              "      <td>890.53</td>\n",
              "      <td>887.87</td>\n",
              "      <td>887.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>4.62</td>\n",
              "      <td>4.74</td>\n",
              "      <td>888.91</td>\n",
              "      <td>886.26</td>\n",
              "      <td>886.10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1074 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2016-01-26              16.59             16.65  ...          345.49         345.28\n",
              "2016-01-27              16.32             16.38  ...          351.27         351.06\n",
              "2016-01-28              16.42             16.48  ...          349.41         349.20\n",
              "2016-01-29              15.93             15.99  ...          359.92         359.71\n",
              "2016-02-01              15.89             15.95  ...          360.99         360.78\n",
              "2016-02-02              15.62             15.68  ...          367.04         366.83\n",
              "2016-02-03              15.90             15.96  ...          361.20         360.99\n",
              "2016-02-04              15.73             15.79  ...          365.07         364.86\n",
              "2016-02-05              15.99             16.05  ...          359.70         359.49\n",
              "2016-02-10              15.97             16.03  ...          360.34         360.13\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               4.56              4.68  ...          886.14         885.98\n",
              "2020-05-11               4.55              4.67  ...          886.52         886.36\n",
              "2020-05-12               4.41              4.53  ...          889.81         889.66\n",
              "2020-05-13               4.62              4.74  ...          885.28         885.12\n",
              "2020-05-14               4.99              5.11  ...          877.28         877.11\n",
              "2020-05-15               4.79              4.91  ...          881.85         881.68\n",
              "2020-05-18               4.66              4.78  ...          884.89         884.72\n",
              "2020-05-19               4.56              4.68  ...          887.26         887.10\n",
              "2020-05-20               4.54              4.66  ...          887.87         887.71\n",
              "2020-05-21               4.62              4.74  ...          886.26         886.10\n",
              "\n",
              "[1074 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ry13P316k1ge",
        "colab_type": "code",
        "outputId": "5e030c96-828c-42d5-db00-a9d7102bc63f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "pre2023['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uzCzj07dlXAp",
        "colab_type": "code",
        "outputId": "b38d2857-8523-4c50-90f6-71e860a539db",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "pre2023['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0QsjNJxDlc0w",
        "colab_type": "code",
        "outputId": "8c646df4-230d-4469-d81f-455077ee7957",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "(pre2023['Taxa Compra Manha'] / pre2023['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(pre2023['PU Compra Manha'] / pre2023['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "Fg7BqufZpaNA"
      },
      "source": [
        "###2.4 Pré-fixado 2026"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "f953fabd-f9a7-4034-f151-6cc5b8cdfcf4",
        "id": "Gv0U9UQApaND",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "pre2026 = titulos.loc[('Tesouro Prefixado', '2026-01-01')]\n",
        "pre2026"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-02-10</th>\n",
              "      <td>6.36</td>\n",
              "      <td>6.48</td>\n",
              "      <td>696.02</td>\n",
              "      <td>691.42</td>\n",
              "      <td>691.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-11</th>\n",
              "      <td>6.26</td>\n",
              "      <td>6.38</td>\n",
              "      <td>700.05</td>\n",
              "      <td>695.42</td>\n",
              "      <td>695.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-12</th>\n",
              "      <td>6.22</td>\n",
              "      <td>6.34</td>\n",
              "      <td>701.76</td>\n",
              "      <td>697.13</td>\n",
              "      <td>696.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-13</th>\n",
              "      <td>6.28</td>\n",
              "      <td>6.40</td>\n",
              "      <td>699.61</td>\n",
              "      <td>695.00</td>\n",
              "      <td>694.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-14</th>\n",
              "      <td>6.23</td>\n",
              "      <td>6.35</td>\n",
              "      <td>701.71</td>\n",
              "      <td>697.08</td>\n",
              "      <td>696.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-17</th>\n",
              "      <td>6.19</td>\n",
              "      <td>6.31</td>\n",
              "      <td>703.43</td>\n",
              "      <td>698.79</td>\n",
              "      <td>698.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-18</th>\n",
              "      <td>6.21</td>\n",
              "      <td>6.33</td>\n",
              "      <td>702.82</td>\n",
              "      <td>698.19</td>\n",
              "      <td>698.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-19</th>\n",
              "      <td>6.24</td>\n",
              "      <td>6.36</td>\n",
              "      <td>701.83</td>\n",
              "      <td>697.21</td>\n",
              "      <td>697.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-20</th>\n",
              "      <td>6.21</td>\n",
              "      <td>6.33</td>\n",
              "      <td>703.16</td>\n",
              "      <td>698.53</td>\n",
              "      <td>698.36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-21</th>\n",
              "      <td>6.28</td>\n",
              "      <td>6.40</td>\n",
              "      <td>700.63</td>\n",
              "      <td>696.02</td>\n",
              "      <td>695.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>7.09</td>\n",
              "      <td>7.21</td>\n",
              "      <td>679.40</td>\n",
              "      <td>675.12</td>\n",
              "      <td>674.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>7.14</td>\n",
              "      <td>7.26</td>\n",
              "      <td>677.80</td>\n",
              "      <td>673.54</td>\n",
              "      <td>673.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>6.93</td>\n",
              "      <td>7.05</td>\n",
              "      <td>685.52</td>\n",
              "      <td>681.21</td>\n",
              "      <td>681.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>7.23</td>\n",
              "      <td>7.35</td>\n",
              "      <td>674.97</td>\n",
              "      <td>670.74</td>\n",
              "      <td>670.55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>7.57</td>\n",
              "      <td>7.69</td>\n",
              "      <td>663.24</td>\n",
              "      <td>659.09</td>\n",
              "      <td>658.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>7.36</td>\n",
              "      <td>7.48</td>\n",
              "      <td>670.76</td>\n",
              "      <td>666.56</td>\n",
              "      <td>666.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>7.26</td>\n",
              "      <td>7.38</td>\n",
              "      <td>674.47</td>\n",
              "      <td>670.25</td>\n",
              "      <td>670.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>7.17</td>\n",
              "      <td>7.29</td>\n",
              "      <td>677.85</td>\n",
              "      <td>673.60</td>\n",
              "      <td>673.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>7.14</td>\n",
              "      <td>7.26</td>\n",
              "      <td>679.10</td>\n",
              "      <td>674.85</td>\n",
              "      <td>674.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>7.19</td>\n",
              "      <td>7.31</td>\n",
              "      <td>677.51</td>\n",
              "      <td>673.28</td>\n",
              "      <td>673.09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>69 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2020-02-10               6.36              6.48  ...          691.42         691.25\n",
              "2020-02-11               6.26              6.38  ...          695.42         695.25\n",
              "2020-02-12               6.22              6.34  ...          697.13         696.96\n",
              "2020-02-13               6.28              6.40  ...          695.00         694.82\n",
              "2020-02-14               6.23              6.35  ...          697.08         696.91\n",
              "2020-02-17               6.19              6.31  ...          698.79         698.62\n",
              "2020-02-18               6.21              6.33  ...          698.19         698.02\n",
              "2020-02-19               6.24              6.36  ...          697.21         697.04\n",
              "2020-02-20               6.21              6.33  ...          698.53         698.36\n",
              "2020-02-21               6.28              6.40  ...          696.02         695.85\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               7.09              7.21  ...          675.12         674.94\n",
              "2020-05-11               7.14              7.26  ...          673.54         673.35\n",
              "2020-05-12               6.93              7.05  ...          681.21         681.02\n",
              "2020-05-13               7.23              7.35  ...          670.74         670.55\n",
              "2020-05-14               7.57              7.69  ...          659.09         658.90\n",
              "2020-05-15               7.36              7.48  ...          666.56         666.37\n",
              "2020-05-18               7.26              7.38  ...          670.25         670.06\n",
              "2020-05-19               7.17              7.29  ...          673.60         673.42\n",
              "2020-05-20               7.14              7.26  ...          674.85         674.66\n",
              "2020-05-21               7.19              7.31  ...          673.28         673.09\n",
              "\n",
              "[69 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "7af84b26-d90f-4a12-a711-c9b8abce85f8",
        "id": "CVUnVNlppaNL",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "pre2026['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "f7a83e91-3ed7-4091-adb3-fe089412b6e5",
        "id": "ZNKFAikepaNQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "pre2026['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "3c3b655e-30f7-497d-ec8f-e04f24be6601",
        "id": "_keYUBW5paNW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "(pre2026['Taxa Compra Manha'] / pre2026['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(pre2026['PU Compra Manha'] / pre2026['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "RXjAU-kBp9WE"
      },
      "source": [
        "###2.5 Pré-fixado 2031 com Juros Semestrais"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "dMMGhHQkp9WG",
        "outputId": "3fea6358-15fa-4837-cb09-ef9d77e37c22",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "pre2031 = titulos.loc[('Tesouro Prefixado com Juros Semestrais', '2031-01-01')]\n",
        "pre2031"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-02-10</th>\n",
              "      <td>6.69</td>\n",
              "      <td>6.81</td>\n",
              "      <td>1257.57</td>\n",
              "      <td>1247.33</td>\n",
              "      <td>1247.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-11</th>\n",
              "      <td>6.57</td>\n",
              "      <td>6.69</td>\n",
              "      <td>1268.26</td>\n",
              "      <td>1257.90</td>\n",
              "      <td>1257.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-12</th>\n",
              "      <td>6.56</td>\n",
              "      <td>6.68</td>\n",
              "      <td>1269.45</td>\n",
              "      <td>1259.08</td>\n",
              "      <td>1258.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-13</th>\n",
              "      <td>6.64</td>\n",
              "      <td>6.76</td>\n",
              "      <td>1262.85</td>\n",
              "      <td>1252.56</td>\n",
              "      <td>1252.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-14</th>\n",
              "      <td>6.56</td>\n",
              "      <td>6.68</td>\n",
              "      <td>1270.09</td>\n",
              "      <td>1259.73</td>\n",
              "      <td>1259.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-17</th>\n",
              "      <td>6.54</td>\n",
              "      <td>6.66</td>\n",
              "      <td>1272.15</td>\n",
              "      <td>1261.77</td>\n",
              "      <td>1261.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-18</th>\n",
              "      <td>6.59</td>\n",
              "      <td>6.71</td>\n",
              "      <td>1268.13</td>\n",
              "      <td>1257.80</td>\n",
              "      <td>1257.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-19</th>\n",
              "      <td>6.63</td>\n",
              "      <td>6.75</td>\n",
              "      <td>1265.00</td>\n",
              "      <td>1254.71</td>\n",
              "      <td>1254.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-20</th>\n",
              "      <td>6.62</td>\n",
              "      <td>6.74</td>\n",
              "      <td>1266.18</td>\n",
              "      <td>1255.89</td>\n",
              "      <td>1255.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-21</th>\n",
              "      <td>6.74</td>\n",
              "      <td>6.86</td>\n",
              "      <td>1256.21</td>\n",
              "      <td>1246.04</td>\n",
              "      <td>1245.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>8.00</td>\n",
              "      <td>8.12</td>\n",
              "      <td>1172.74</td>\n",
              "      <td>1163.82</td>\n",
              "      <td>1163.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>8.08</td>\n",
              "      <td>8.20</td>\n",
              "      <td>1167.14</td>\n",
              "      <td>1158.30</td>\n",
              "      <td>1157.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>7.95</td>\n",
              "      <td>8.07</td>\n",
              "      <td>1177.19</td>\n",
              "      <td>1168.24</td>\n",
              "      <td>1167.88</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>8.25</td>\n",
              "      <td>8.37</td>\n",
              "      <td>1155.37</td>\n",
              "      <td>1146.67</td>\n",
              "      <td>1146.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>8.54</td>\n",
              "      <td>8.66</td>\n",
              "      <td>1134.87</td>\n",
              "      <td>1126.40</td>\n",
              "      <td>1126.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>8.27</td>\n",
              "      <td>8.39</td>\n",
              "      <td>1154.64</td>\n",
              "      <td>1145.96</td>\n",
              "      <td>1145.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>8.17</td>\n",
              "      <td>8.29</td>\n",
              "      <td>1162.31</td>\n",
              "      <td>1153.55</td>\n",
              "      <td>1153.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>8.05</td>\n",
              "      <td>8.17</td>\n",
              "      <td>1171.53</td>\n",
              "      <td>1162.67</td>\n",
              "      <td>1162.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>7.99</td>\n",
              "      <td>8.11</td>\n",
              "      <td>1176.35</td>\n",
              "      <td>1167.45</td>\n",
              "      <td>1167.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>7.91</td>\n",
              "      <td>8.03</td>\n",
              "      <td>1182.70</td>\n",
              "      <td>1173.73</td>\n",
              "      <td>1173.37</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>69 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2020-02-10               6.69              6.81  ...         1247.33        1247.00\n",
              "2020-02-11               6.57              6.69  ...         1257.90        1257.57\n",
              "2020-02-12               6.56              6.68  ...         1259.08        1258.76\n",
              "2020-02-13               6.64              6.76  ...         1252.56        1252.23\n",
              "2020-02-14               6.56              6.68  ...         1259.73        1259.40\n",
              "2020-02-17               6.54              6.66  ...         1261.77        1261.45\n",
              "2020-02-18               6.59              6.71  ...         1257.80        1257.48\n",
              "2020-02-19               6.63              6.75  ...         1254.71        1254.39\n",
              "2020-02-20               6.62              6.74  ...         1255.89        1255.56\n",
              "2020-02-21               6.74              6.86  ...         1246.04        1245.71\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               8.00              8.12  ...         1163.82        1163.46\n",
              "2020-05-11               8.08              8.20  ...         1158.30        1157.94\n",
              "2020-05-12               7.95              8.07  ...         1168.24        1167.88\n",
              "2020-05-13               8.25              8.37  ...         1146.67        1146.30\n",
              "2020-05-14               8.54              8.66  ...         1126.40        1126.02\n",
              "2020-05-15               8.27              8.39  ...         1145.96        1145.59\n",
              "2020-05-18               8.17              8.29  ...         1153.55        1153.19\n",
              "2020-05-19               8.05              8.17  ...         1162.67        1162.31\n",
              "2020-05-20               7.99              8.11  ...         1167.45        1167.09\n",
              "2020-05-21               7.91              8.03  ...         1173.73        1173.37\n",
              "\n",
              "[69 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "RmhBMONap9WQ",
        "outputId": "fefcf783-4bba-40d8-9135-310b59b44bd5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "pre2031['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "n0uGuOnLp9WY",
        "outputId": "e869f470-c50a-4ff8-8b0b-562149383132",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "pre2031['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "JRBBwh7Up9Wh",
        "outputId": "018b2763-764e-400a-d848-800566746581",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "(pre2031['Taxa Compra Manha'] / pre2031['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(pre2031['PU Compra Manha'] / pre2031['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "eiv2w-LEqXwF"
      },
      "source": [
        "###2.6 Tesouro IPCA+ 2026"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "YjVUP7NHqXwY",
        "outputId": "b20a50ca-b223-4d27-a3c5-a5440dcc0ff2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "ipca2026 = titulos.loc[('Tesouro IPCA+', '2026-08-15')]\n",
        "ipca2026"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-02-10</th>\n",
              "      <td>2.65</td>\n",
              "      <td>2.77</td>\n",
              "      <td>2785.55</td>\n",
              "      <td>2764.50</td>\n",
              "      <td>2764.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-11</th>\n",
              "      <td>2.58</td>\n",
              "      <td>2.70</td>\n",
              "      <td>2798.39</td>\n",
              "      <td>2777.24</td>\n",
              "      <td>2776.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-12</th>\n",
              "      <td>2.56</td>\n",
              "      <td>2.68</td>\n",
              "      <td>2802.40</td>\n",
              "      <td>2781.23</td>\n",
              "      <td>2780.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-13</th>\n",
              "      <td>2.58</td>\n",
              "      <td>2.70</td>\n",
              "      <td>2799.33</td>\n",
              "      <td>2778.20</td>\n",
              "      <td>2777.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-14</th>\n",
              "      <td>2.54</td>\n",
              "      <td>2.66</td>\n",
              "      <td>2807.15</td>\n",
              "      <td>2785.97</td>\n",
              "      <td>2785.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-17</th>\n",
              "      <td>2.49</td>\n",
              "      <td>2.61</td>\n",
              "      <td>2816.44</td>\n",
              "      <td>2795.20</td>\n",
              "      <td>2794.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-18</th>\n",
              "      <td>2.53</td>\n",
              "      <td>2.65</td>\n",
              "      <td>2809.76</td>\n",
              "      <td>2788.58</td>\n",
              "      <td>2788.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-19</th>\n",
              "      <td>2.56</td>\n",
              "      <td>2.68</td>\n",
              "      <td>2804.86</td>\n",
              "      <td>2783.74</td>\n",
              "      <td>2783.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-20</th>\n",
              "      <td>2.50</td>\n",
              "      <td>2.62</td>\n",
              "      <td>2815.90</td>\n",
              "      <td>2794.70</td>\n",
              "      <td>2794.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-21</th>\n",
              "      <td>2.55</td>\n",
              "      <td>2.67</td>\n",
              "      <td>2808.11</td>\n",
              "      <td>2786.99</td>\n",
              "      <td>2785.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>3.53</td>\n",
              "      <td>3.65</td>\n",
              "      <td>2658.94</td>\n",
              "      <td>2639.73</td>\n",
              "      <td>2640.17</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>3.53</td>\n",
              "      <td>3.65</td>\n",
              "      <td>2659.02</td>\n",
              "      <td>2639.83</td>\n",
              "      <td>2639.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>3.42</td>\n",
              "      <td>3.54</td>\n",
              "      <td>2676.84</td>\n",
              "      <td>2657.51</td>\n",
              "      <td>2657.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>3.56</td>\n",
              "      <td>3.68</td>\n",
              "      <td>2654.40</td>\n",
              "      <td>2635.27</td>\n",
              "      <td>2635.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>3.69</td>\n",
              "      <td>3.81</td>\n",
              "      <td>2633.79</td>\n",
              "      <td>2614.84</td>\n",
              "      <td>2614.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>3.53</td>\n",
              "      <td>3.65</td>\n",
              "      <td>2658.71</td>\n",
              "      <td>2639.57</td>\n",
              "      <td>2640.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>3.43</td>\n",
              "      <td>3.55</td>\n",
              "      <td>2674.82</td>\n",
              "      <td>2655.56</td>\n",
              "      <td>2655.51</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>3.35</td>\n",
              "      <td>3.47</td>\n",
              "      <td>2687.79</td>\n",
              "      <td>2668.43</td>\n",
              "      <td>2668.39</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>3.31</td>\n",
              "      <td>3.43</td>\n",
              "      <td>2694.30</td>\n",
              "      <td>2674.90</td>\n",
              "      <td>2674.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>3.25</td>\n",
              "      <td>3.37</td>\n",
              "      <td>2704.09</td>\n",
              "      <td>2684.62</td>\n",
              "      <td>2684.58</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>69 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2020-02-10               2.65              2.77  ...         2764.50        2764.01\n",
              "2020-02-11               2.58              2.70  ...         2777.24        2776.76\n",
              "2020-02-12               2.56              2.68  ...         2781.23        2780.75\n",
              "2020-02-13               2.58              2.70  ...         2778.20        2777.72\n",
              "2020-02-14               2.54              2.66  ...         2785.97        2785.22\n",
              "2020-02-17               2.49              2.61  ...         2795.20        2794.77\n",
              "2020-02-18               2.53              2.65  ...         2788.58        2788.15\n",
              "2020-02-19               2.56              2.68  ...         2783.74        2783.31\n",
              "2020-02-20               2.50              2.62  ...         2794.70        2794.28\n",
              "2020-02-21               2.55              2.67  ...         2786.99        2785.97\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               3.53              3.65  ...         2639.73        2640.17\n",
              "2020-05-11               3.53              3.65  ...         2639.83        2639.73\n",
              "2020-05-12               3.42              3.54  ...         2657.51        2657.42\n",
              "2020-05-13               3.56              3.68  ...         2635.27        2635.16\n",
              "2020-05-14               3.69              3.81  ...         2614.84        2614.72\n",
              "2020-05-15               3.53              3.65  ...         2639.57        2640.14\n",
              "2020-05-18               3.43              3.55  ...         2655.56        2655.51\n",
              "2020-05-19               3.35              3.47  ...         2668.43        2668.39\n",
              "2020-05-20               3.31              3.43  ...         2674.90        2674.86\n",
              "2020-05-21               3.25              3.37  ...         2684.62        2684.58\n",
              "\n",
              "[69 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "aMi_NTxuqXwg",
        "outputId": "7a5ea394-c91d-4f2a-910b-1aebe63bc984",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "ipca2026['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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xPy+dlHgnXp9OjRwurNlfQUVDK5fPzOXUsR4ANmjv3VJo464JCZfDTqtfx92HCy9uPUZOipsF4zM4KTuJ1HgnG3Xc3VJo464JCZfdRqv23IcFR6sb+bigkktn5OKw27DbbMwZncaGI9pztxIhVYUUkfuBxebx9wH/AQQLf2cA64B7gW3ABnN7qVLqShFJA54G0oA64BqllA7eWgyXw06rT3vuw4GXtxVhs8El048v73jK2DTe21dOUU0TuanxUVSnCZVejbuILAWmK6UWiEgmsEkpNa7d/j8BfzQ/KqXUkk6XuBV4Vyn1gIh8HbjD/KexEC6HTa+1OgwwBlKLWTghg5wUd9v2uWbcfeORai6cqo27FQglLLMGuNL8uQpIEhEHgIgI4FFKre/h/HOAF82fXwHO7adWTRRx2rXnPhx4f38FZfUtXD5zZIftk8y4ux5UtQ69eu5KKR9Qb368EXjd3AbwLeDhdofnisg/gFHA/ymlngJygVJzfwnQ8anRWAKXQ8fcrUpVQyurPytlcX4m2cnuHo99cesxRiTHsWBCRoftdpuNU8ak6clMFiLklZhE5FIM477M/BwHLFJK3WweUg78EHgSI76+XkRWd7pMl6tYJye7cTodfZQ+cBwOOx5PYsTvO1CioTvB7aShxden+1q1f7vCKm3pSuefP/2M3723j/tX72PJydlcNXcMZ56UjcPe8c/xSGUD6w5WcsuSfLIyTly7d9HJ2by7t5xGm52RaYMXmrFyX8cSoQ6ong/cBSxXSgW/us8C2sIxSqla4M/mxzIR+RSYDBRieO/VwGjzcwfqorQwhMeTSFVVQ1TuPRCiodsWCNDU4u3Tfa3av11hlbZ0pfPDvaXkZyWyaGImr2wv4t+7S8hJcXPJ9BwumZ7bNkD61w8LsAHLJmV22dbxqYbXv2FfKYsmZka0DbFILOjMzu5+Wc5eY+5mtssDwIpOWS7zgC3tjlsqIg+aPycBs4E9wFscj9lfAbzRR/2aGMBpt9GiY+6Wo6nVx46iWs4Yn8Etiyfw6tfn8/8unsKEzET++NEhLvnDem59YTvvfFbGy9uKOGNCRrfZMPlZhje/t7S+y/2a2CIUz/0qIAt4zhg/BeBLGLHzfe2Oex/4soh8BDiA+5RSR0XkN8CTIvI+xoDsdeESr4kcRiqkjrlbjW3Hamj1BThlbBpg/B7PPjmbs0/OprC6iX9uL+KV7UV87+WdAFw2o/shsWS3k5wUN/vKY9+r1oQ2oLoSWNnFrv/qdJwXuL6L8+uAy/qpTxMjuBw2vNpztxwbD1djt8Hs0Wkn7BuVFs9NC8fztQV5fHiggn1l9SyamNHFVY6Tn5XIvjLtuVuBkAdUNcMbl91Oq85ztxwbj1QjI5JJdnf/p+602zgzP5Mz83uPo0/KSuKTQ1V4fX6cDj3BPZbRvx1NSOhUSOvR7PWz/VgNc8ac6LX3l/ysJFp9AQ5X6UVcYh1t3DUhocsPWI8dRTW0+AKcMsYTtmvmZxqDqjo0E/to464JCV1+wHpsOFyNDZgzJjVs1xyfmYjdpo27FdDGXRMSTu25W46NR6rNcr2usF3T7bQz1pPAXm3cYx5t3DUh4bLb8AfAp713S9Dq87OtsIZTxoYvJBMkPyuJ/TodMubRxl0TEi4zM0J779ZgZ1EtzV4/p4RxMDXIpKwkDlc20tTq6/1gTdTQxl0TEi6HUYdEx92tQbDA15wu8tsHSn5WIgHgQIX23mMZbdw1IeG0a8/dSmw8UsWkrCQ8ieGLtweZmKUzZqyANu6akAh67jrXPfbx+vxsOVrDqWPD77UDjPEkEOewsa9Me+6xjDbumpAIGnddPCz22VlcR9MgxdvBmNE6ITNJe+4xjjbumpBwmWEZr/bcY57gaknhnJnaGV1jJvbRxl0TEm1hGb/23GOdjUeqmZiZSHpi3KDdIz8ziZK6FmqaWgftHpqBoY27JiSOp0Jqzz2WafX52XK0mlMHIb+9PVNykwHYfLRmUO+j6T/auGtC4viAqvbcY5nthTU0tvoHbTA1yOzRaSTFOVizr3xQ76PpP9q4a0Ii6LnrPPfYZv0BY7G0wYy3g/E8LBifwfv7yvEH9DMRi2jjrgkJp1177lZgfUEFEzITyRjEeHuQMydlUNHQys6i2kG/l6bvaOOuCQkdc499vP4AGw5WDloKZGfOGJ+Bw4YOzcQoIa3EJCL3A4vN4+8D/gPINndnAOuUUl8Xke9iLIYdAO5RSr1uLrD9NJAG1AHXdFpoW2MBjmfLaOMeq6jiWupbfIM+mBokLcHF7DFpvL+vgpsXTYjIPTWh06vnLiJLgelKqQXAcuAhpdSVSqklSqklwKfAH0VkAnA1sAhYATwoIg7gVuBdpdQi4AXgjsFpimYwOZ7nrsMyscrHBwc/v70zZ+ZnsresnqPVjRG751DBHwjwi9V72XK0elCuH0pYZg2GNw5QBSSZRhsREcCjlFoPLAVWKaValFKlwEFgKnAO8KJ5/ivAuWHUr4kQTl1+IKYJBAK8sauEuXnpZCUNfrw9yOKJxrqr7+/TL+N9ZdXOEp7dVEh5w+DMFejVuCulfEqp4FS0G4HXlVLBWp/fAh42f84FStudWgKM7LQ9uE1jMXTJ39hmT0k9ByoauGRWZP+8xqYnMCEjUcfd+0hTq4/ffXCAKTnJLJnU+8Lk/SGkmDuAiFyKYdyXmZ/jgEVKqZu7OcUW4jaSk904nY5QpYQNh8OOx5MY8fsOlGjo9pm/H6fbGfK9rdq/XRHrbVn90SFcDhsrZo4ixR3yn3VYOG9aDn9aW4Aj3kVKGFZ9CrWvW7x+Hn5nL19ZOH5QZ+N2x0CeiUfe20dJXQsPfmE2GelJYVZmEOqA6vnAXcBypVQwQHQWsL7dYYWAtPs82txWiOG9V7fb1oG6uuY+Cw8HHk8iVVXWq2wXDd0NTV4AauqaQ763Vfu3K2K5LT5/gH9uKWThhAxS3M6I6zxtdCor/QFWbT7KsskjBny9UPv6k0OVPLpmP6kuO1fOHjXg+/aV/j4T5fUtPPrefs7Kz0TS4wf0+8rOTul2XygDqmnAA8CKTlku84At7T6vBi4SkTgRGYVhyHcCb3E8Zn8F8Eaf1GtiAl3yN3b59FAV5fUtXDBl4Ia1P0wfmUp6givioZkD5cYg7g6L5dn/4aODNPv83HLm4GYYheK5XwVkAc8Z46cAfAkjdr4vuEEpdUhE/oAxABsAblJK+UXkN8CTIvI+xoDsdWHUr4kQOuYeu6zaVUyy28HCiYMTu+0Nh93GwokZvLe3HK/Pj9MRmekzBeZKUDuPWce4r9lXzgtbjnHl7FGMzxjcMF+vxl0ptRJY2cWu/+ri2Ic5PsAa3FYHXNZfgZrYwGG3YbfpPPdYo7HVxzuflXOeZON2Rm9O4pn5mby6o5jNR2uYOy4yefZB415Q0UBds5fkCI819JXPSuv44Wu7mZyTzH8NstcOeoaqpg+4HHad5x5jvLu3jIZWHxdMjU5IJsj8vHTiHLaIhmYKKhrISoojAOwurovYfftDeX0Lt724gyS3g19eNo141+AnkGjjrgkZp92mY+4xhM8f4M/rDjM+IyGiE5e6IjHOwbxx6by/v5xABAqJ1TV7Ka1rYbk5zhDLcfdAIMD3X9lJZWMrv7xsGtnJ7ojcVxt3Tci4HHYdc48hXt9ZzIGKBm5aOB67rcss44hyZn4GR6qaOFAx+Nk6B817zB6dyhhPfEwb9/WHqth8tIbbluYzJaf77JZwo427JmRcDpuOuccILV4/Kz88yJScZJaelBVtOQAsMgd01+wd/NBM8AskLyORqTkpMV2Z8u+bCklPcHHR1JyI3lcbd03IuOw2HXOPEZ7feoyi2mZuWTwBWwx47QAjUtxMyUlmTQRKERRUNOK02xiTFs+0kSkU1zZTFqX5Mj1RVNPE+/vLuXRGbsQHvLVx14SM02HXMfcYoL7Fy5/WHeK0cR5Oy0uPtpwOLM7PZPuxGioaWgb1PgXlDYz1JOB02JmWa4Q6dhTF3qDq81uOAXBFhMtCgDbumj6gwzKxwcoPD1LV2MrNi2OvzO6Z+ZkEgA/2h+a97y6u5fdrCzhc2beqkgUVDYzPNPLEZUQyDhvsLIqt9VybvX5e2lbE4omZ5KbGR/z+2rhrQsZl1wOq0ebDAxU8veEoV8wa2eaxxhInZyeRk+Lm/V5SIgvKG7jzlZ188clN/HHdIf7jiQ08veEIvhCch1afnyNVjYzPSAAg3uUgPyspLIOqXn+Ah9fs50jVwEsY/3tPKVWNrVw5J/KlEUAbd00fcDls2rhHkbK6Zn6ySpGflcitZ02MtpwusdlsLJ6YwbqCSppafV0es7+8nquf2MCHByr56unjeO76ucwb5+FX7+7n689uYX9pz+GVw1WN+AJ0mOE5NTeFnUV1BAIBmlp9bDlaHdIXRWc2HaniiU+O8OLWY30+tz3+QIBnNxWSl57AaRGa1NUZbdw1IaNj7tHDHwjw41WKhlYf966YEpFJMP3lzEmZNHn9fHq4qsv9Gw8bhveJ6+bwjYXjmZCZyIOXTeOeC4SCigYu+d2H/PWTw90a54IKw6uekHncuE/LTaG22ct3XtrB+Y+s46t/28LL24v6rD04GLzpSP8X0PD5A/z0zT3sLKrlS/PGRm3AWxt3TcjEOfQkpmjxxPrDrD9Uxe1L85mYOTglYsPFqWM8JLoc3S7gsa+snqQ4B+PSE9q22Ww2Lpyaw7NfPpXFk7L4zZoDfPVvmzlQfmLOfIG5LS/9uHGfPSYNuw22Hatl2eRsRqfFs2pncZ90BwKBthm2O4vraOzmzaMnfP4A97yheG1HMV8/I49LZuT2+RrhQht3Tci4HHa8fh2WiTRbC2t4dG0B556czaVRNBahEue0s2CCMVvV38Vs1f3lDeRnJXXp0WYlu/ndNXP42YWTOVzZyHV/3cBf1h/G286LL6hoICfFTWLc8beX8RmJvPy1+az6z9O5a9nJXDw9h01HayiqaQpZ977yBgqrm1gyKROfP8C2wr4N0Hr9AX68ajerdpVw86LxfG1BXp/ODzfauGtCRpcfiDy1TV7ufm0XOSlu7lp2UszktPfGmfmZlNa1nFDzJRAIsK+snomZ3VdEtNlsnD9lBM9eP5eFEzP57fsHuPGZzewtMxaEK6hoaBtMbU9Oihun3eif88268m/uLj3huO4IDgJ/c/EE7La+hWa8Pj8/fG03b+4u5ZbFE7hh/riQzx0stHHXhEw4yg/8z5uKJz89EiZFQ5tAIMC9/9pDSV0LP7toSsxXPWzPGRMysNs4oZBYRUMr1U1e8rN6Dy1lJsXx/y6ewr0rplBY3cQX/7qRP607ZBr3nsvljvEkMGNkCm/uLglZ85p95UzNTWF8RiIyIplNIS5c7fX5ueu13by9p5RvnTWRL582NuR7DibauGtCJhx57u/tLWftAb2Ycii8tK2It/eUcdPC8cwYlRptOX3Ck+Bi1qjUE4z7PtP7zs8KrZa5zWbjPMnmuetPZcmkLB5ZW0Bjqz+kWujnTx7BZ6X1bR5/T5TVNbP9WC1n5RslFOaMSWP7sVpavD07M60+P3e+uovVn5Xx7SUTuW7umJDaFQm0cdeEjMs+sJK/Ta0+qpu8FPchDjpc2VdWzy/f2cf8PA9fnBc7BqMvLM7P5LPS+g5x733mYGhfB4XTE+O47+Ip/L+LpzBnTBoLJvQ+M/dcycZhgzd39e69v29OujozaNxHp9Hs9bOruPvc+Wavn++/sot395Zz+9J8rjk1tn5P2rhrQsY5wGyZ0jpjSnpxbXNEysJalaZWHz94dRdJcQ5+csHkmKj42B8Wm4XE2r+p7S+rx5PgIiOxfwtpn31yNiuvmsXotBNj7p3JTIpjXl46b+4u6fV5W7OvnFGp7rY3itmjjRLKG7uJuzd7/dzyzCbW7Cvne+dM4qpTRvexJYOPdYJ4mqjjcthpHUC2TIlZ2KnFF6CysZWMKKxYbwV+9e5+9pc38PAV08lKsm4f5WUkMCrVzYcHKrliljFLc19ZAxMzEyM2MLx88gh+8obi+qc347DZgAABIBCgLZMnEIC9ZfVcMWtkmy5PoouJmYlsOlLNDfM7XjNYn/2D/RXcee4kPm1YemkAACAASURBVDcrOjNQe0Mbd03IuAaYLRP03AGKapq1ce+C1XtKeWHrMb40bwynj8+ItpwBYbPZOGNCBq/tLKbF68flsLG/vJ4LI1j69uyTs3h/fznVTV5sgN0GNmyY/2Gzgd1mIzfVzec7Gek5Y9JYtbMErz/QloUDcLCykQ/2V3DrOSfxuSgUBAuVkIy7iNwPLDaPvw94BfgLMAmoBT6vlKoUkVZgbbtTz8EI/TwO5AE+4Aal1P5wNUATOQZafqCk9nhJ1qLaZqbGYG2UaFJY3cT/vLWHabkp3LRwfLTlhIUzJmTwjy3H2HS0mrz0BOpbfD2mQYabBJeD/714ar/OPWVMGs9vOcaekroOz+r2Y0b++7II12fvK73G3EVkKTBdKbUAWA48BHwNKFVKnQY8i2H4AaqVUkva/fMB1wBVSqlFwM8xvhw0FsTpsOMP0K+aHWCEZRymB1RcG3u1t6OJ1+fn7td2EwjAzy6ajNMxNIbD5o7z4HLY+PBABfvNwdRQ0iBjgWDcfUOnMgrbj9WSFOeI+XaE8gStAa40f64CkoCLgacAlFIrlVIv93D+OcCL5s9vAwv7J1UTbVymYe6v915a18JYTzzxTnufZg4OB1Z+dJBtx2r4wXknMcbT+2ChVUhwOTh1jIcPD1S0pUFG0nMfCCNS3OSlJ5xQI2dbYQ3TclOw22N7oLtX466U8imlgomiNwKvA+OBC0TkXRH5m4gEg4PxIvK0iKwVkdvMbblAqXktPxAQER1stSAu05v09tNzL61rZkSym9xUt/bc27HhcBWPf3yYS2fkssycWTmUWDAhnYIKI06dlRRHWkL/MmWiwWl56Ww8XN3m0DS2+thXVs90C8w7CHlAVUQuxTDuy4CPAaWUukdE7gbuBL4L3A48CQSANSKypotLnfB1l5zsxumMfJU7h8OOx2MNL6I90dKdlmKs2p6QHI8nhCyOzjpL61tZkJ+Cy+WgrKHVUn0/mH2+6u29pCfF8dPLppMYN7Ach1h8ppfPHMWv3t3PxiPVnJGf2au+WGrDkik5/H1zIQW1Lcwbn8Geggp8ATh9UlZM6eyKUAdUzwfuApYrpapFpBh4z9z9JnAPgFLq0Xbn/BuYARRieO9bRMQF2JRSHdbgqovS2oceTyJVVYO/Unu4iZbu1mYvAOUV9Thavb0e316nzx+gtLYJT5wDf4ILVVRrqb4fzD7/pKCC2aNSaWlooWWAy9PF4jOd7rQxOi2eo9VN5KXF96ovltowOSMeuw1W7yjiJE886/YYtWompLjx+fxR15md3X1SQigDqmnAA8AKpVRwNsIqjMFVgFMBJQZPi4hNRJwYsfUdwFscj9lfDLzTr1Zooo7LYcbc+5HrXtnQgi8AI5Ld5KS6Katv6XVq93CgrK6ZwuomZlrgNb+/BFMiIfSyA7FCaryLyTkpfHLIiLtvO1bDWE88nn5OwookoQyoXgVkAc+ZMfZ3gaeBC0XkA+Ay4H+VUgo4DKzHSId8XSm1HiObxmEe+02MEI7GgrjsxuPSn1z3YjPHPTvZTY4Z3imJwdXqe+Mv6w9z92u7wna9rceM6e2zRg9d4w5w9klZ2G0wbaT12nnaOA/bi2qpb/Gy7Vgt0y3Shl7DMkqplcDKLnZd2cWxd3SxzQfc0C91mpgi6Ll7+2HcS80B1BEpcSS4jC+J4trmmMoMqWv20uz1k9nNeEJ1YyuPrTtIY6uf7yzNJz0Mk7C2Hq0hzmFDRiQP+FqxzNxxHt78zwWW8Hg7M2+ch8fXH2bVzhLK61uYPtIa8zOGRjKtJiIEc6/7E5Ypaee5B1eCj6WMGa/Pz03PbeXyx9az+rOyLo95fssxGluNtgdf0wfK1sIapuamtGUiDWWsaNgBZo1Ow+2088QnhwEs47kP/SdKEzbaYu798NyDE5gyEl2MSDY83qKa2DHuf/nkMLtL6shKiuOOl3fy6NqCDqsINbX6eHbTUebneUhxO1l/cODGvdnrZ3dJ7ZCOtw8F3E47s0alcqymGbfTzknZsT15KYg27pqQOR5z77vnXlrXTHZSHHabjXiXg/QEF0W1sTGRaW9ZPX/86BDnSTbPfHkuF0/L4bF1h7j9pR3UmRlCL24+SkVDK9efNo654zx8fLBywJUtdxfX0uoLaONuAeaN8wAweUSyZd6yrKFSExMc99z7F5bJTna3fY6ViUxef4CfvqFIcTv57tn5uJ12fnj+yXz37Hw+LKjk+qc2sb+8nsc+KGBqbgqnjk1jfp6HotpmDlU2DujeW801Oq22EMdw5LQ8o368VUIyoI27pg+0xdz7E5apbSYn5fgAZE6KOybCMk9+cphdxXV875xJbQOkNpuNL8wZzf99fgbVTV6ufWIjBysa+NK8MdhsNuabf+jr+xh3X1dQwWPrDraFe7YWGml1ujpm7DM5J5mvzB/L5TNjf4HyINq4a0KmrbZMH8sPBAIBIyzTwXOPj7rnvr+8npUfHeTsk7I4V7JP2H/qWA9/vW4OJ2UnMTknhSWTsgAYnRbPqFQ36w9Whnyvt1Upt764g0fXHuSXq/cRCATYWljDTLM4lSa2sdts3LRoAnkhLO8XK+h67pqQaast08ewTH2Lj8ZWP9nJHT33+hYfdc3eqCz8bIRj9pDocvC9cyZ1e1xuajx/uXYOSSkJNNQZYwQ2m43T8tL5lyo9odZ3V7yxq4Qfr9rNjJGpTM5J5tlNhTR7/VQ0tOp4u2bQ0MZdEzL9zZYJeujByUsAuebPRTXNTMqO/GP4zIYj7Ciq5ecXTe42rz2IzWYjzmmn/UTz+XnpvLStiF1FtSfEzAOBAEeqmth2rIaNR6p5eVsRp4xN48HLphPvslPX7OWf24sAtHHXDBrauGtCxuXoX7ZMqTkTtfOAKkBRbROTIpxaVlDewKNrC1gyKZPzugjHhMLccR5swMcHKzkpO4ndxXVsLaxp+1fZ2ApAUpyD5VNG8IPzTiLeZRTHu3vZydQ0edlVXGeZ8rca66GNuyZkjteW6ZvnfnwCU8ewDEQ+193nD/DTN/cQ73Jwx7kn9XstT0+Ci8k5yTzxyWEeW3eorQzyuPQEzpiYwcxRqcwcmcqEzMS2BUqCOB12fnHZNBpbfZZd/FoT+2jjrgmZ/ua5d+W5ZybF4bTbIj6o+uymo2w7VsM9F8iAF5+++pTRvLKjmGm5KcwclcqMkSkhlySw22wkDbC8r0bTE/rp0oRMf2vLlNS24Elw4XYeT86y22yMSI6jKILG/VBlI7/7oIDFEzO4YMrAF8W4cGpORBd71mj6gk6F1IRMf2vLlNQ1dwjJBElLcFHb1Htd+HDgDwT4nzcVcQ47d57X/3CMRmMVtHHXhIzDZiyj1ZdsmbL6Fg6UNzCiXUgmSJLbSX1LZIz7PzYfY/PRGm5bOrFDeEijGarosIwmZGw2Gy6HLSTjXt3Yyh/WK/7y0UG8/gBfW5B3wjHJcQ6OVrcOhtQTeHtPKTIimYt0GEUzTNDGXdMnXA57jwOq9S1e/rbxKH/95AgNrT6WTx7B18/I67Jue1Kcg/rmyHjuZXXNTMlJ0eEYzbBBG3dNn3DabV0a92avn+e3FPLnjw9T1djKkkmZfHf5ZEa4u1/4PCnOSX2LbzDlAsHyBy0sztc1XDTDB23cNX3C5bB3yHP3+vy8sqOYP350kJK6Fk4b5+HmReOZNjK114WOk9wO6lp8BAKBQfWo65p9NHn9OtauGVZo467pEy6HrUNtmdte2sFHBZXMGJnCPRdMZq5Z9zoUkuOc+PwBmr3+ttmbg0FpvbnEXxcZOxrNUCUk4y4i9wOLzePvA14B/gJMAmqBzyulKkXkWuBWwA+sVEo9JiIu4HEgD/ABNyil9oe7IZrIYMTcj3vuG49Uc8n0HO5ednKfve8kM2RT3+IbXONuzpDN0sZdM4zoNRVSRJYC05VSC4DlwEPA14BSpdRpwLPAYhFJAn4EnAssAb4tIhnANUCVUmoR8HOMLweNRXE5bG1hmaZWH81eP2M8Cf0KqwRnaNYN8qBqWbD8QZIOy2iGD6F47muA9ebPVUAScDHwYwCl1EoAETkb+EQpVW1+XgssBM4BnjDPfxv4U7jEayKPy348W6banICUltC/hY+T4o577oNJSVv5A+25a4YPvRp3pZQPqDc/3gi8DswFLjDDNUXAzUAuUNru1BJgZPvtSim/iAREJE4p1RK2VmgihhFzNzz3arPyoae/xr0tLDP4nnuK2zmooR+NJtYIeUBVRC7FMO7LgI8BpZS6R0TuBu4ENnU6pbv39BO2Jye7cToj/4fncNjxeKxXcjWauuPdTgI2Gx5PIt5yYw3R0VnJXerpTWduo2nUnc5BbU9Vi4+c1PgB3cMqz4pVdPaEVdoQ6zpDHVA9H7gLWK6UqhaRYuA9c/ebwD3AaxheepDRwDqg0Ny+xRxctXX22uvqorPcWm+perFKNHXb/AEavT6qqho4WlYHgMPn61JPbzr9zYbnX1LZMKjtKaxsICPBOaB7WOVZsYrOnrBKG2JBZ3Z2Srf7QhlQTQMeAFYopSrMzaswBlcBTgUUhjc/T0Q8IpKMEW9/H3gLuNI89mLgnX60QRMjtJ+h2haWie9fRm2yOaA62GGZ0roWslP0YKpmeBHKX+VVQBbwnIgEt30J+KWI3AjUAV9WSjWKyPcxPPkAcI/p5T8LnCciHwDNwPVhboMmgrgctraFKapM497fAdXECAyo+gMByupbyB5g7XaNxmqEMqC6EljZxa4ruzj2H8A/Om3zATf0V6AmtnDa7bR4j2fLJMU52pbf6ytxTjtxDht1zYNn3KsaW/H5AzpTRjPs0CV/NX2ifZ57dWMraf0MyQQx6ssMXlimtDY4gUmHZTTDC23cNX2iffmBqsbWfodkgiS5HYMaltGlBzTDFW3cNX2iffmB6ibvwI17nHNQy/62lR7QMXfNMEMbd02fMKpCHs+WGXhYZnA99zJt3DXDFG3cNX3CZbe189xb+z07NUiye3BrupfUNZOR6Gpb/1WjGS7oJ17TJ4Ixd6/PT12zLwxhGcegFg4rq2/Rddw1wxJt3DV9wumw4wu0y3GPH7hxH9QB1boWnQapGZZo467pEy67URqorN6IZXsSBhhzd5+YCvnIBwf46yeHB3TdIKV1zTrerhmW6JWYNH0iOGEpmIUSjrBMqy9Ai9dPnNO49hu7SihvaOXi6bkDiul7fX4qGlq1564ZlmjPXdMnXI5OnvuAwzId68sEzHIBzV4/L209NqBrBzXqmLtmOKKNu6ZPBLNOgoYzbYBhmWR3x/oytc1eWnwBbMDfNxd2WK+1rxw37tpz1ww/tHHX9IlgzL28PnxhGYB6s75MMNyzfMoISupa+Peesn5fu0Qvr6cZxmjjrukT7WPubqedeOfAHqG2dVTNsEzQ275kei7j0hN4euNRAoFAt+f3RFlweb0U7blrhh/auGv6RDDmXlrXTFq8s18LY7cnqVNYJvhGMCLFzdWnjGZnUS1bC2v6de3SuhYcdtuAJ1ppNFZEG3dNn3DajUemvL5lwCEZOHFAtX25gIum5pDidvLMxqP9unYwDdI+wC8gjcaKaOOu6RNBzz18xr1jzL2svoVEl4PEOOPf5TNzeeezMgqrm/p87eK6Fl0NUjNs0cZd0yfizJi7L9D/5fXak9RpNabSuhay2hnkK2ePwgY8t6mwz9c+VNHAuPSEAWvUaKyINu6aPhH03GHgmTIAbqcdp93WFpYpr28ms92M0tzUeM4+OZuXth3r06Ie9S1eSupayMuI3dXpNZrBJCTXS0TuBxabx98HXIKxMHa5ecgDSqnXRKQVWNvu1HMwvkAeB/IAH3CDUmp/WNRrIk776ooDLfcLYLPZjPoy7cIyk3M6ruh+zamj+Zcq5dXtxVx1yuiQrnuwohGA8dq4a4Ypvf51ishSYLpSaoGIZAKbgNXAnUqpVzsdXq2UWtLp/OuAKqXUtSKyDOPL4aqwqNdEnGCeO4THcwejvkz7VMjOk46mj0xlxsgU/rbpKJ+fPQqHvfcB0oKKBkAbd83wJZSwzBqOL4ZdBSQBjj7c4xzgRfPnt4GFfThXE2O0Xww7XCmGQc+9vsVLY6u/y0Jf/3HqGI5UNfHB/oqQrnmwogGHDcZ44sOiUaOxGr0ad6WUTylVb368EXgdI7xyi4isFpG/iUiWuT9eRJ4WkbUicpu5LRcoNa/lBwIiolMYLEqHmPsA68oESY5zUN/ibZudmtmFcV96UhY5KW6e2XgkpGsWVDQy2pPQ4ctIoxlOhBw0FZFLMYz7MmAuUK6U2iwi3wd+AtwC3A48CQSANSKypotLnfBOnZzsxunsy8tAeHA47Hg81nttj6buxnY542NGJPeoI1SdaUluyuqaaTavPT4ntcvzvnzGeO5/U1HY6GXqyNQer3moqomTc1LC1k9WeVasorMnrNKGWNcZ6oDq+cBdwHKlVDXw73a7XwYeAVBKPdrunH8DM4BCDO99i4i4AJtSqqX99evMaeKRxuNJpKqqISr3HgjR1N1Qf/xX5/D6etQRqk63HWoaWykoqgUgHn+X550/KYOHV9tZ+d4+frJcur2e1x+goLyeM8anh62frPKsWEVnT1ilDbGgMzs7pdt9vb6zikga8ACwQilVYW57XkQmmocsAbaLwdMiYhMRJ0ZsfQfwFsdj9hcD7/S3IZroMxhhmaQ4J3XN3ra6Mt0trpEa72LFtFze2l3SdmxXFFY34fUHGJ+hc9w1w5dQApJXAVnAcyLyroi8i+GtPysi7wEXAfcopRRwGFiPkQ75ulJqPfAs4BCRD4BvAneGvxmaSBGMYTtsx8v1DpTgUntl9UYxshR39y+UV58ymlZfgOc3dz+pSWfKaDQhhGWUUiuBlV3s+ksXx97RxTYfcEO/1GlijmAqZFqCa8BFw4IkuR00e/0U1RgTmHq67rj0BBZNzOD5Lce4fv443F1UpTxoGvc87blrhjE6lUDTJ4I55uEKycDx4mEHKxtCWu/0mlNHU9nYypu7SrrcX1DRQEaii9QwatRorIY27po+YbPZiHPYBrwCU3uC9WUOVTaGZNznjvWQn5XIKzuKutxfUNGoQzKaYY827po+43LYw1ojPcmMsTd7u57A1Bmbzcb8vHR2FtXS2mkZvkAgQEFFgzbummGPNu6aPuN2htm4xx0fmM0KsUTvzFGptPgCqJK6DturGlupafLqeLtm2BO+d2vNsOHHy4UxnvAZz+R22TGheO5gGHeArYU1TG83oemAzpTRaABt3DX94IwJGWG9Xn889+xkN7kpbrYV1hj1SU0KzGqQEzK1cdcMb3RYRhN1ktsb9xA9dzC8987rqx6saMDttJOT4g6bPo3Gimjjrok6Sf0IywDMGJVKSV0LRTXHl+DbU1rPuPQEvW6qZtijjbsm6sQ77dhtRg59X2rEB+Pu244ZNWmOVDWy4VAVi/MzB0WnRmMltHHXRB1jNSYnmYmuPnncJ2cn4Xba20Iz/9h8DLvdxhUzRw6WVI3GMugBVU1MkBTn6LKOe084HXam5qawrbCGplYfL28vYumkLEboeLtGoz13TWyQlRzXr1WTZoxMZXdJHf/cVkRts5cvzBk1COo0GuuhPXdNTPC/F0/F3Y9Vk2aOSuWJTwI8sraAk7KTmD2650U8NJrhgjbumpigv6mLM0YZixXUt/j4wuxRYatUqdFYHR2W0ViajMQ4xnriSY13snzKiGjL0WhiBu25ayzPt5fk4w9AvCvy6/BqNLGKNu4ay6Pz2jWaE9FhGY1GoxmCaOOu0Wg0Q5CQwjIicj+w2Dz+PuASjFp85eYhDyilXhORa4FbAT+wUin1mIi4gMeBPMAH3KCU2h/WVmg0Go2mA70adxFZCkxXSi0QkUxgE7AauFMp9Wq745KAHwGnAS3AJyLyInAxUKWUulZElmF8OVwV/qZoNBqNJkgoYZk1wJXmz1VAEtBVWsJ84BOlVLVSqhFYCywEzgFeNI9529ym0Wg0mkGkV89dKeUD6s2PNwKvY4RXbhGR24AS4BYgFyhtd2oJMLL9dqWUX0QCIhKnlGoJWys0Go1G04GQUyFF5FIM474MmAuUK6U2i8j3gZ8AH3Y6pbupgidsT05243RGPkfZ4bDj8VhvxR6r6LaKzlCwSlusorMnrNKGWNcZ6oDq+cBdwHKlVDXw73a7XwYeAf6B4aUHGQ2sAwrN7VvMwVVbZ689ISEuanPG7XZrTnyxim6r6AwFq7TFKjp7wiptiGWdvcbcRSQNeABYoZSqMLc9LyITzUOWANuBj4F5IuIRkWSM2Pr7wFscj9lfDLwT1hZoNBqN5gRC8dyvArKA50QkuO3PwLMi0gDUYaQ3NpohmjeBAHCPUqpaRJ4FzhORD4Bm4Powt0Gj0Wg0nbAFAoFoa4gIImJTSg2PxkYB3b+RR/d5ZLBqPw/p2jJmXv6XgV+bWT8xj4i4lVLN0dYRClbs3+6wSr9bvc91P0eOIVt+QET+G3gKSAX8IhLzhb5F5BrgGRGZZ36OWc1W7N/usEq/W73PdT9HliHpuYvIj4DvArlKqfrejo8h5mHMCbhQRDYopfzRFtQVFu7f7oj5fh8ifa77OYIMGc9dRNovef8E8CngEZHRInKXmacfU4jIJBG5sN2mROA9IB1YYR4TE16DFfu3O6zS71bvc93P0WVIDKiKyBXAM8BipdTH5rb/Am7DyLX/EGMC1p+Ax5VSNdHSamqzAT8FlmLM5N0J/E0ptd2cC/BVYBJwr1KqPNoDOlbr3+6wUr9buc91P8cGlvbc233rp2CURXig3e4nMGrZ/FYp9TDwnxh59nERFdk1CRjppcuAL2JM9PqWiGQppVoxPAc/cDlAFB98q/Zvd8R8vw+RPtf9HANY2rgrpQIikgrEA58DUkTkRnNfNXCbUmqt+Xkd4AXGRktvO1KAs4BkM663CqMo243m/u0YhdcmicjXROTLIhLxB8vC/dsdMd/vQ6TPdT/HAJYy7uYvo/1nm/ma9Jg5OPNd4MftDmkVkWtE5DYRWYkx4epA5BSDiKR0+uxQShVjlHD4ibn5MMbkr5NEJM+sqlmP4S18HTgSiUJrXWiN+f7tDhEZ0emzPRb7vbNOACv1uYiMFJGcdp9jtZ876ARr9XN/sIRxFxGniNwFvCQiN4ocnyprPkyt5v/fxqhhE3zFcgE7gHxgk1LqSqVUVYQ0u0zNz5ueyRhzV/AV9BfAHBGZo5TyAkXmPreI5GI8bCuVUvOUUv8+4QYR0Gp6NzHZvz0hIlOArWKsRYCIOIjNfu9KZ8w+0520O0XkB8ALwJh2u2Kqn3vQaYl+HgiWMO4Y36i5wJ3ABOBzpgccCKZTtUuruhq4ToxyxHcB+4FblFKPREqs+Yr5a4w82fsxYovj2x+jlDqIsULVw+bn7cAowK+UKgIuUUr9OppazYc+5vo3BNIwqo/eCW1lq23mzzHR793ptEKfi8h8jMHGLOBCpdSGdrtjpp970mm+lcZ0Pw+UmDXu5rc7IpIInA78rzmafRQYEZw1JiILReTpdiGFdAwP4ULgr0qp2kgN2AQ1YyxoMlkpdYfpEdRgDCAFa9ovFpGnlFK/BypE5Jcishrj9bXMfPCaYkhrTPRvd7RrSxAv8E3AJyK3Q1tbFkWz3/uoM+b6XI6nDAY92J8rpSpFZJaITA8aTBE5M8r9HIrOgBWe7YEQc6mQYkz7/RkwFSMn9lEMr3Kf+Qq1DLhIKfUtEZkG/DewRin1lPlL/THwhlLqpShrjgMOYawpezPGANKnGK96FwE7lbHGbDrG6+I4pdRrMap1i1LqiWj1b3d0ass7wEvKWGPg60AO8Ji5/XwMr/HzwDal1J8j2e/91LlRKfVkLPR5F8/MI8AXgNkYk5JOBSqAPeb+ZcCuSD/f/dS5NRaf7XAQizNUbwUagHMxvJrnlVIL2u2/FNgKoJTaAXwjuEMpdQwjbSnSdNb8glLqdAAR+ZdS6kERWYjxMM1WSn2n3blVSqlKYFusa41i/3ZH+7bcBKzEWMN3O1CqlCoUkVrgA+A64PZ2r+CR7Pd+64yRPm+v/xbgSYwvoteBw0qpc0RkKsaX0qlKqdvbnRutfu6Tzhjp57ASM2EZEQlqqQZ2KKValVIPYbyy3mwek4Ix+eEl8/NZIjIuKoLpUbNXRG4x9+0DUEZaVSNQaZ7rNLdHKmQ0YK2xQjdt+Q1GhsO1GKl4PxWRV4HNGKWm95shg4j1ezh0RpNu9P8KI5R3JUb57j8AKKV2Yjwzpea50e7nPukcisSMcW/nUbmBVBFJMj/fAXxPjHVXazFmu50iIn8FvsLx0fmI04vm283P14nIBWJkoCzF1KuMDAKttR/00JbvA/dgzIpcAzyglPoq8Hvge+a5EWuLVXR2Rw/6bwfuxTCQXhGZISKjMZ6ZJvPcWOjnmNIZaaISczfjcP+Jkfu6TxmLerjMmPopGL+Q72DE7fwi8hxGDPgJjDjwJ8BflFLPxLjm1Rjxva9hZKD8Vin1lNYaOv1oyzOAUkr9ROsMnX4+M2swVmD7NsYb9a8H+5mxis5YIOKeu4icCbyIMZB0NcaAHkAwp3ojxivq1RhpjwCvABXKSKH6HsaSf5E07P3V7FVKrcaYgr0wQobdMlp7o59teQ04Yp4fzBsf1OJUVtHZHQN4ZpqUUp9gjHstiIBht4TOWCFinruIxCulmkTk88AZSqnbzO3bgZ8qpZ4zP8/GWFz7bIwqcuswBqHuU0r9MyJiw6f5Z0qpV7XWvmGVtlhFZ3eEQf/PlVKvaJ2xyaAbdzHSFb+JMYr9EEbHj8KYnVYhRjnNnymlZojIg8B8jPSlZmAxsBx41vQqI4KVNFtJa29YpS1W0Wl1/VbRGasMinGX45ME8oC/YLw+zceYtPEhRrrXHUqpvebx/8LIgPmrilJJTStptpLW3rBKW6yiszusot8qOq3AYMXcnCjQYgAABWdJREFUgxXeFgP1Sqm/YRQRWooxQeYgcLWIeMzj7jWPbYDjMcgIYyXNVtLaG1Zpi1V0dodV9FtFZ8wTVuMuIktF5HnglyJyBvAP4G5zsKMa2Gse+ntgBnCF+Xk8RnEeL7TVAokIVtJsJa29YZW2WEVnd1hFv1V0WomwGXcxpu/+HPgjxjfsDcDVSqlNGKPZmRhpSD6llAJ+B+SLyJsYr1ofhUvLUNRsJa29YZW2WEVnd1hFv1V0Wo0BxdzNV6AfAmUYE14SlVIPiEg8Rpzs58BlSqkyEfkyxkj3N8RI+ZqilNopIqcppdYPvClDT7OVtPaGVdpiFZ1W128VnVam3567iIwCnsMoW9qIUdrzOhFJVEbFtw8wJhvd0e5ez4vI5cD7GJUeibBht4xmK2ntDau0xSo6u8Mq+q2i0+oMJCyTDWQopb6tlHoMeAoQ4JftjnkSyBVjUdxFwPMYVQb/Wyn1pwHcu79YSbOVtPaGVdpiFZ3dYRX9VtFpaQZSNKcY+JkYRXvsGEWnLgCeEJE/KqU2iEgNRs6pHyOe9pZS6tmBih4AVtJsJa29YZW2WEVnd1hFv1V0Wpqw5LmLUVltNUY53muBFRiric/CSFO6VinVMOAbhRErabaS1t6wSlusorM7rKLfKjqtSLjKXc4AUEbd5t+KSD3GbLJc4OYY/eVYSbOVtPaGVdpiFZ3dYRX9VtFpOcJl3EcDz5gpTY8C64G7VWwvUWUlzVbS2htWaYtVdHaHVfRbRaflCJdxz8So/XA58LhS6ukwXXcwsZJmK2ntDau0xSo6u8Mq+q2i03KEy7gXYKQt/U4p1RKmaw42BVhHcwHW0dobBVijLQVYQ2d3FGAN/QVYQ6flCNeAqs1qr1FW0mwlrb1hlbZYRWd3WEW/VXRakaisxKTRaDSawSVm1lDVaDQaTfjQxl2j0WiGINq4azQazRBEG3eNRqMZgoQrFVKjiRoiMh7YBmwAbBhLst2rlPp3D+eMA3JDqSwoIkuAvwM7zE0O4GtKqd0DU67RDB7ac9cMFZRSaolS6izg68DDIjKzh+PPBk7rw/XfM6+/BPgD8O3+S9VoBh/tuWuGHEqpfSLyc+CbwDdE5EEMQx6PMcX9nxjrcraKyCGM9Tf/B2gBKoEv9DKhJgc4CiAi53Y+F0jAqFfuNv99Uym10dS0GMPz/61S6plwtlujaY/23DVDlU+BqebKPgVKqUUYhvWnSqlS4HHg10qpl4F04BrT668Bzu/iemeJyLsisgG4EVhpbu/q3HOAI6aXfy0wQkQWA3lKqTMx3hruFpGEwWi4RgPauGuGLikYa242ARki8iGwCmOhiM6UAn8UkfeApRj1TjoTDMucihH2ea6Hcz8CFojIo8AkpdQbwBnA6SLyLvAmxt/eyPA0VaM5ER2W0QxV5gKbROQsDE/5LKVUq4jUdXHsn4CLlFK7ROS3vV1YKbVGRE421wE94Vyl1DERmYVh7G8SkdOBWuAxpdR9YWqfRtMj2nPXDDlEJB+4DfgVkAUcNg37JYBDROIwVvgJOjdpwCER8WAY5LgQrl+llPJ1da4Zhz9XKfUW8F8YXzQfAxeLiF1E4uX/t3eHOAgEMRiFnyFIjjF3QCHQHIB7gEGQcAUSNDgkBrWScIhyATwagSgGggRB8z6/m8yKf5O2mba2/vKxpRfeLaO/9zYK2ScblouI6FprA6AjFzEfyPLIDdgDO2BG7u+cABfgSDZbhxFxfb5/xOsoZA+YR8S5tbb68OyU3CZ0J38iy4g4PRuqY3JccxMR2198DwkMd0kqybKMJBVkuEtSQYa7JBVkuEtSQYa7JBVkuEtSQYa7JBVkuEtSQQ/pRii/HlrT/AAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "l4GdX1IHqXwk",
        "outputId": "aaf3bb8c-ced2-48ec-f6b6-ef51159b2940",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "ipca2026['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "ELGAXRiCqXwo",
        "outputId": "66d05c1a-6bb3-4855-f053-f1fbd3f99562",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "(ipca2026['Taxa Compra Manha'] / ipca2026['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(ipca2026['PU Compra Manha'] / ipca2026['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "TvmMW2f5rUQL"
      },
      "source": [
        "###2.7 Tesouro IPCA+ 2035"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "g6qXY2D7rUQR",
        "outputId": "7afea3fb-5e26-4862-acc5-80466be756a1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "ipca2035 = titulos.loc[('Tesouro IPCA+', '2035-05-15')]\n",
        "ipca2035"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2010-03-08</th>\n",
              "      <td>6.23</td>\n",
              "      <td>6.33</td>\n",
              "      <td>415.52</td>\n",
              "      <td>405.82</td>\n",
              "      <td>405.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-09</th>\n",
              "      <td>6.25</td>\n",
              "      <td>6.35</td>\n",
              "      <td>413.78</td>\n",
              "      <td>404.12</td>\n",
              "      <td>403.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-10</th>\n",
              "      <td>6.25</td>\n",
              "      <td>6.35</td>\n",
              "      <td>413.99</td>\n",
              "      <td>404.33</td>\n",
              "      <td>404.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-11</th>\n",
              "      <td>6.25</td>\n",
              "      <td>6.35</td>\n",
              "      <td>414.20</td>\n",
              "      <td>404.54</td>\n",
              "      <td>404.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-12</th>\n",
              "      <td>6.27</td>\n",
              "      <td>6.37</td>\n",
              "      <td>412.69</td>\n",
              "      <td>403.07</td>\n",
              "      <td>402.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-15</th>\n",
              "      <td>6.28</td>\n",
              "      <td>6.38</td>\n",
              "      <td>411.87</td>\n",
              "      <td>402.27</td>\n",
              "      <td>402.12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-16</th>\n",
              "      <td>6.27</td>\n",
              "      <td>6.37</td>\n",
              "      <td>413.00</td>\n",
              "      <td>403.37</td>\n",
              "      <td>403.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-17</th>\n",
              "      <td>6.26</td>\n",
              "      <td>6.36</td>\n",
              "      <td>414.13</td>\n",
              "      <td>404.47</td>\n",
              "      <td>404.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-18</th>\n",
              "      <td>6.26</td>\n",
              "      <td>6.36</td>\n",
              "      <td>414.28</td>\n",
              "      <td>404.62</td>\n",
              "      <td>404.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2010-03-19</th>\n",
              "      <td>6.22</td>\n",
              "      <td>6.32</td>\n",
              "      <td>418.46</td>\n",
              "      <td>408.71</td>\n",
              "      <td>408.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>4.47</td>\n",
              "      <td>4.59</td>\n",
              "      <td>1717.10</td>\n",
              "      <td>1687.85</td>\n",
              "      <td>1688.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>4.52</td>\n",
              "      <td>4.64</td>\n",
              "      <td>1704.97</td>\n",
              "      <td>1675.95</td>\n",
              "      <td>1675.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>4.43</td>\n",
              "      <td>4.55</td>\n",
              "      <td>1727.20</td>\n",
              "      <td>1697.79</td>\n",
              "      <td>1697.66</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>4.61</td>\n",
              "      <td>4.73</td>\n",
              "      <td>1683.41</td>\n",
              "      <td>1654.80</td>\n",
              "      <td>1654.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>4.77</td>\n",
              "      <td>4.89</td>\n",
              "      <td>1645.51</td>\n",
              "      <td>1617.59</td>\n",
              "      <td>1617.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>4.62</td>\n",
              "      <td>4.74</td>\n",
              "      <td>1680.83</td>\n",
              "      <td>1652.28</td>\n",
              "      <td>1652.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>4.52</td>\n",
              "      <td>4.64</td>\n",
              "      <td>1705.12</td>\n",
              "      <td>1676.14</td>\n",
              "      <td>1676.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>4.47</td>\n",
              "      <td>4.59</td>\n",
              "      <td>1717.45</td>\n",
              "      <td>1688.25</td>\n",
              "      <td>1688.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>4.42</td>\n",
              "      <td>4.54</td>\n",
              "      <td>1729.86</td>\n",
              "      <td>1700.44</td>\n",
              "      <td>1700.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>4.40</td>\n",
              "      <td>4.52</td>\n",
              "      <td>1734.91</td>\n",
              "      <td>1705.40</td>\n",
              "      <td>1705.31</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2548 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2010-03-08               6.23              6.33  ...          405.82         405.61\n",
              "2010-03-09               6.25              6.35  ...          404.12         403.91\n",
              "2010-03-10               6.25              6.35  ...          404.33         404.12\n",
              "2010-03-11               6.25              6.35  ...          404.54         404.33\n",
              "2010-03-12               6.27              6.37  ...          403.07         402.82\n",
              "2010-03-15               6.28              6.38  ...          402.27         402.12\n",
              "2010-03-16               6.27              6.37  ...          403.37         403.22\n",
              "2010-03-17               6.26              6.36  ...          404.47         404.32\n",
              "2010-03-18               6.26              6.36  ...          404.62         404.47\n",
              "2010-03-19               6.22              6.32  ...          408.71         408.46\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               4.47              4.59  ...         1687.85        1688.08\n",
              "2020-05-11               4.52              4.64  ...         1675.95        1675.82\n",
              "2020-05-12               4.43              4.55  ...         1697.79        1697.66\n",
              "2020-05-13               4.61              4.73  ...         1654.80        1654.67\n",
              "2020-05-14               4.77              4.89  ...         1617.59        1617.45\n",
              "2020-05-15               4.62              4.74  ...         1652.28        1652.57\n",
              "2020-05-18               4.52              4.64  ...         1676.14        1676.04\n",
              "2020-05-19               4.47              4.59  ...         1688.25        1688.15\n",
              "2020-05-20               4.42              4.54  ...         1700.44        1700.35\n",
              "2020-05-21               4.40              4.52  ...         1705.40        1705.31\n",
              "\n",
              "[2548 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "AabkQEEfrUQc",
        "outputId": "0eecf086-dce5-47a1-8b4b-ae54fce88056",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        }
      },
      "source": [
        "ipca2035['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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VugDYW1rFDa+u8u6/b7ahf5cMRgZxw1G1/ZpVte7QNDLGaM9dKRV2lTWuJo99vDa4mRuXbDkIwKmSH9TzY5323JVSYVfVTHJ/cfl2Oqcnc3RfR6suiu61pxsYlp/V5vbFIu25K6XarLiimorq2iaP/8Oe/8XjvjOEl68e4338r0Wb+cnLX3svkAYiJclKX6doz92vgHruIjISeBuYaox5TET6As8CKUA1cIUxZreIVAOLfZ46GesDZAbQH6jFWm91Y+hCUEq1h80Hyrjl9VUc2bszc0whAL8/dSjnHdGz0bkfrNkNwKC8TP5xwUh65PhfuPr86cuYf9txZKU2Tk27iyvYcrCcsf1zASiqqAHAkRG/qy01p8Weu4hkYS2I/bHP7geBJ40xJwKzgDvt/UXGmEk+/9UClwFOY8wE4CHg4ZBGoJRqF++u3sPe0ipvYgd4aM66Zp/zwhVHN5nYPW55/Ru/+895aim3vvENd7/zLYD3m0JGSlJrmh03AinLVAJnAjt99t1M3QLZhUBeM8+fjPUBADAXOL6VbVRKRdiDH63lP4s3N3tOSWW13/2eUSweO4vqxranJtdPObNvHAfAMf0c3n1rdpc0es3C0rrpfD1L59W4rFEyiToK0q8WyzLGmBqgRkR89x0CEJEk4BbgAftQuoi8hFWCmWmMeQTogfUBgDHGJSJuEUk1xlR5Xi87O43k5JY/fZOSEnE4Mls8L1bEU7zxFCtEf7xvf2OVUe4+a3ijYxXVtaQlJ1Ja7WJYt2ymXTKa0/+5yHv8/bX7uHr8AO/jjcVWYv7dDw5rFLPDkcm6P50BwNA/zPbu31Vew+H28Mi9JRX8qcE3gpycDFbssKYeyM2Nrguq0fK7DXq0jJ3YXwA+McZ4Sja/BF4E3MACEVng56mNPmdLSyv9nNaYw5GJ01kWXIM7oHiKN55ihY4Tb8M27imp5Ownl/CbU4Yw57u9DM3PoktKIsvuOoGCKdY/98fnb+Dcw7t5nzNrxXYABuSkNRvzBUf05M1VuwBYsXEfPTOSqXG5OX7qwkbnyh8/bLKN7S2Sv9v8/KbvzG3LaJlngXXGmPs9O4wxTxhjSu2e/cfAKKxyTg8AEUkBEnx77UqpjmPNrmIA/jLXGv2yt6Rxx+xAWTXTv9hCaaV1wfOVL3cA0MfRfK39qmP7eLfnmn32+zRfw1dNCyq5i8jlQJUx5o8++0REXhKRBBFJxqqtrwE+Ai62TzsHmNfGNiulQuTT9fs5+bHPOPXxz9l/yOpzud1N3/G5p7R+v+ysEd29229eV+DdfmLxFk567DPOeOILAC4p6Et+dlqzbendOYN5tx4HwOJNB3C53d7yUFNSkrTg3pQWyzIiMgaYAgwAqkXkIqAbUCEi8+3TvjXG3Cwi24ClgAt4xxizVERWAKeKyCKsi7PXhDwKpVSr7Sut5Jdvr/E+PuOJL3jxiqPJ75Tq9/x56/bxiD0LI8D9PxDOHF6X3PvmZvDEj47gxtfqphfwfGCc5lOmaU52Wl1KGvtI43JMQ0fqTJBNCuSC6gpgUiAvZoy528++WuDaVrdMKRVWr3y1s9G+fy7YyM0TB/o937cX/db1BfTunNHonDF9HY32AUwcmh9wHfryMX34r12n9xjcNZMN+6znz/pJAedPXwZAXpb/DyKl0w8oFbeKKxoPZVy61cnh9lDDTmn100NOuvX4xMF5fhO7xwtXHMX6fYe4f/ZaABbe3rrRz2kp9avFi34+gbTkRF7+cgddMlLo48hgxuVHcc1/v+Jnxw1o1WvHE03uSsWhl1ZsZ9aq3eRnp3Ly0K4kJyZ6e8vPLd0GQPdOjWvkvTun8/fzRjT72od178Rh3Ttx9ogeQbWtuLz+h06aPTb+0qN7e/eN6NGJZXedENTrxwudW0apOPTmSmvIYWFpFb88eQh3TBrE0jsn0j+3rkeelVr/3pNDVbWN9oVDrc8F3d+eOjTs7xerNLkrFYc8a1t0y0712ZfAloN1E3c5y6vZXVxBZY2Ll1Zsx1leTVZa+L/sd8msa5MunRc8LcsoFYc887H8+0dH1tvfPzeDLQfLGdI1i/X7DnHOU0vrHT/bZ+hjuFw7th/VtS66ZqcxOK/97/TsqDS5KxVnXG433+0ppY8jnX659S+MTr90NNuc5Vz70td+nxuJtUrTkhO57YRBYX+fWKfJXak48uBHa71DGo/tl9voeOeMFDo3M4Vur87N32WqoofW3JWKI75j1S/wM+96c44bmMu4AV1C3SQVJtpzVypO5WUFvsjFI+eNYOLg5mb2VtFGe+5KxanczMDv7tTE3vFoz12pOPHU51sAmDysK2cN705SAKtcnDm8W6vLNyo6aM9dqRjz78WbueiZZY1md3zyMyu5Z6clB9wT/8Npwziyd+eQt1GFn/bclYoxz3yxFbAWkPa3eHRhgIvjACQnaf+vo9LfnFIx5PqX68anH6qq8W779uIHdNEbg+KBJnelOrBZq3bx/R5rQekV25ys3FnsPXbv+4bKGmux6gNl1mRc547swS0T/E/pq2KLJnelOqivtxfx5znruPLFrwAoraytd3zVzmIWbNgPwJaD1lzoJw3tSmpyy//sj+nnf1521XFocleqg1q4cX+9x1/vKAJgip8pead/btXh++Y2PQ+7r8cvGsWSOye2sYWqPWlyV6qD2rTf6o0nYNXXV2xzAnDcgFymnm8l+OpaF9W1LpZutY41nEumKQkJCSQm6PqkHVlAo2VEZCTwNjDVGPOYiPQFXgCSgF3AlcaYSnvh7Duw1lB90hgzXURSgBlAf6AWuNYYszH0oSgVP0oqali48QAAbmDStM8AOFXySU5KZKA9m2Kty808e2UlFV9a7LmLSBYwDfjYZ/cDwL+MMROB9cB19nn3Aqdgrbn6CxHpAlwGOI0xE4CHgIdDGoFScabW5ea5ZdZqSalJ9XvXx/S1xqQn2b3uBz5cy+/f+z6yDVRRIZCyTCVwJuC7mu4k4B17+12shD4WWGaMKTLGlAOLgeOBycAs+9y59j6lVJAenrPOuxTeBzeO4zafBa2z7cU0/N19eu3YvpFpoIoKLZZljDE1QI2I+O7OMsZ47oTYC/QEegCFPuc02m+McYmIW0RSjTFVnhOzs9NITm55+a6kpEQcjvgZoxtP8cZTrNC2eN9eXTezY78enbm9R2emLdwEQEpaCg5HJjV+/j3dfebwgKYcCId4+v1GS6yhuEO1qb+WgPeXBnjHnMORidNZFmCzOr54ijeeYoXA491RVE5JRQ2Hde+E2+3mzVW7yElPpriihrOGd/O+xszrCpg6fwNH98jG6SzjUINFpg/vnk1Jcbm/t4iIePr9RjLW/PymF08JdrRMqYh4Lrv3xirZ7MTqpdPUfvviaoJvr10p5Z/b7ea8p5d5x7Fvd1bwl7nrKa6o4YzDu/GH0+u+TffLzWDq+SO9C210Sq/fb/tuT2nkGq6iQrDJfS5wob19ITAbWAIUiIhDRLKxausLgY+Ai+1zzwHmBd9cFQnLth7k3KeXsnl/fPS0otX6fYfqPT5QVtcnGpSX2WyJJTEhgc4+Cf76cf1C30AV1QIZLTNGROYD1wA/t7fvB64WkYVAF+A5+yLqb4APsZL//caYIuBVIElEFgG3AL8NQxwqhG5+/Rt2FlUwY+nW9m5KXHtkft2IYbO3lHvfrxv10juA5e7euv5Ybjp+AACThnYNeftUdEtoOC1oeygsLAmoEfFUt4P2ifebncVc5zP51NI7J3Lz66s4RfK58MheYXtf/d02VjBlQZPHHrtoFGP7N14DtSGX280OZ0XAd6aGSzz9fiNcc2/y65tO+avqmb++/i3txRU1LN9WxPJtRWFN7qq+jfsP+d1/VUEfUpMSOaZvYHO/JCYktHtiV+1Dpx9Q9Xy1vYghXbN48MzDAPjL3PXeY6WVNU09TYVQrcvNj2es8HvsZ8cN4IbjB7TbkEbVcWhyj1O+5bjqWhevfbWT6loX3+4pYfyAXHrZNd25a+tuXbh95jcRb2c8Ouhz4dR3ibuXrx5DWgAzOioFWpaJW9e/spKc9GSmnj+St7/Zzd8+WY+zvIpal5vczBTvkDpf3+wqaYeWxh/fOdkL+jm4/cSBrNxRzJCuWe3YKtXRaDcgDrncblbtLGbRxgP8de46alxWL/5Tu96enZbs7bkD/P3cETgyUhhkT0blLKumYMoC/vC+zlkSatW1Lmpq675V9cxJIys1meMGdmnHVqmOSJN7HPr12996t99YuYuZK61pg9YWWhfxxvbPJTkxgfzsVACOH9SFs0d0Z+P+MrYcKOPL7db0sbO/28veksDX41TNO1BWxXGPLuIvH6/z7tOLoSpYmtzj0Kf26jw3TxgAwOYD9W9L9/TaX7pqDLN+UkByYgIF9so8Czce4O53v/Oee+7TSyPQ4uhQXevCFcahw7uKrQ9Kz4pKc24aT0564/KYUoHQ5B5nquw1NQEmD8v3br91fQE3HT+Axy8e5d3nyEihj8PqOY4fkEuntGT+8Wn9qfg9JZ1Y53K7Oe7RRdz3gQnbezS858SRqYldBU+Te5zx9NoButllF4DenTO4blw/Cvr5vzEmISGBqtq6D4bzRvWwn9fynZKxYGdRBQAffLc3bO9RVlXb8klKBUiTe5zxJKnrx/UjPSWJ208YyAtXHBXQcyt9ev13Tx7CVQV92VNSSW2U9d6/3O7kwmeWUV4dumT563fqrlMUTFnApGmLQ/r6AOvsax7HDczl/344PKSvreKPJvcO7u1vdnHfB9/z/Z7mhyl+vvkAn67fx7NLrPlirizo6/3/Yd2bnjbUn7+fO4LkpET6OtKpcbn5eG1hy0+KoH8t3MzWg+V818LPpDU8idfjUFUtCzfsb+Ls4Dxql7weOW8kJ+lcMKqNNLl3cA9+tI73vt3rnRbWH7OnlNtnruaXb3/LoapajuyVQ2Zqy4ujNGXcAKt00yMnDSDqlnHrZK9GtN1ZEbLXzPLz85phr4YUCqt8xrbr3acqFDS5x4EV9tBFj/EDW55wyp/RvXMAvHdJepJotBmab93ss3l/GW63m/fW7KGkIripExZvPMDSLQc5ZNfD5916HHNuHg9YvfmKEJVm/v7J+pZPUqoVovNfpwqK2+0mwV4Y+UBZFS+v2FGvd/nBDWP5yBQGPQHYtAtH1au7pyTV9Q1qXe6o6XF6SijVLjebDpRx32xrhMuyu05o1euUV9dyx6zV9fZ51ig9tp+DpVudvLlqFxcc0ZP0lOC/CYEupqFCT3vuMeSQz2iL22eublQ26JqdxmVj+gQ9P0l6SlK9aQkSfZJ5tc9Imva2zWmN29/uLKewtP6iXwfLqnhpxfaALgIXN+jtP/XjI73bN9jzpE+dv5FpCza1scVKhZ4m9xhy7Ut1dff0Bgn8gxvHhfz9kn2Su7PBmp3tyTN75aKNB/jv8u31jj352Ramzt/Ioo11F0P/8elGCqYsaJTwN/ishHTbxIGM7tPZ+/iwbtne7aKK6IldKQ9N7jHE905TzwXT8QNymXPTeLpmpTb1tKAN6FK3wvsn6/aF/PWD5fsN5vPNB73bLrfb+yF0sKwuIb9ofwA8v2wbLyzbxuOLrJ74z9+0SjLv/vRYrjq2b733SE1O5OWrxgBQUR0931qU8giq5i4iPwGu9Nl1DLAcyAI83Z27jDErRORXWGuourGW3nu/De1VAdrmLGfCoC783w+H16uNh9odJw7i0U834rDLNWt2FbNqVwmXHt07bO/ZnN3FFfWuC/iqrnV7Sy1V9uRc73+7x3u8osbFM19YQ0VvnjCQI3vlsHJnMT1y/N+oNaCLdffupxv2U1xR3aapAgbmZbJJ16xVIRRUcjfGTAemA4jIicCPgBHAtcYY7xUoERkIXAKMBzoDC0XkQ2OM3ooXJrUuN4WllWx3VnDy0PywJnaAEwbnecdnA1zzkrVEX6ST+/vf7iEvK9Xb2/anorrWm/hf+XI7PzqqF3/0mU6g0GcStJKKmnpT7/rjewF5ze4Sxg9oeubGzfvL6JObUa+U5auvPc3D85cHdkOZUi0JxWiZe4HLgVf8HDsJ+MAYUwUUisgWYDigqz6ESFpyIhcc0ZPundJ49NONnPTYYsrtMutC224AABeESURBVEEk7hy1B+fQcD6tPSWVdO+UFvb39/hjAHO+nPL45/SzZ1nc5qzggM+iGMN7dKp38XWrfVHW3/h2D8/IJLAuYP/3yqMZ5lOL9/jZK1/z1Y5izh3Vg3tOG+b3tVxuN2lJiW0edaOUR5u6dSJSAGwzxuy2dz0gIgtE5D8ikgH0AHxvX9wL9Gz4Oio41bUuKmtcdM5IJiPF+lWW+9R/rx/fL+xtSLQT3P++3cPzPqNzzn5yCfPbsQ7/J3uZwIa2Hqy7LrHaXnzk1okD6ZWTzpaDdWWRu+3pBqaeP7LZ9xnZs+7u3stf+LLR8ZKKGr7aYX0D2FXU9E1VbnfdB6VSodDWnvv1wAx7+x/AKmPMBhH5N3CLn/P9/vlmZ6eRnNxyjyUpKRGHI7PF82JFS/EuXG8lz/T0VFL83FDUp3tO2Nrmccj+lS7f6mT51vo3S726chfnFQT2ARPM79blcpOYmNBoNkXpns0l4we0uJjIXW+tAWDyiB5scm7yTrkL1jcPgB55Wc22a9bNxzP0D7O9jxue+8g7a7zbWRkp3uMN401KTiQlJSlm/77j6d9utMTa1uQ+CbgNwBgzy2f/u8CPgXmA+OzvDexs+CKlpYEt+OBwZOJ0xs9Fp5bifXL+BgByUxPZcaDuvDMO78YdJw6KyM+qpLjp3mh/RzpOZxlmbyl5WanNjthp7e92u7Oc86cv46ShXbn39PqljsKSSpzOMm48vj9PLN7CqJ45fLOrrn4+uGsmG/ZZ7zW8Ryf6ZKXQp4kSUk4SrWpXw3NLfUo/80wh3209QM+c9EbxVlbV4K51xezfdzz9241krPn5Tc8LFXRZRkR6AaXGmCoRSRCRuSLisA9PAlYDnwBniUiqfX5v4Fv/r6haKy05EUdGCj84vBs56XWf04PzMskLw9BHfxKbqSXMXLmL55du44oXvuQHT3wRsvc8VFXD+dOXATBv3T5+9faaescP2MMcc+0RPN/sKuayMXUXeHv5jH6ZdqFVdrmyoC/njerBm9cV1DuWlRp4/8dzb8H8dftYssUagpmbmUJKUoJ3euVbXl+F2+1mzc4iwKq1F0xZwJItTl2jVoVUW2ruPbFq6Bhj3MCTwMcisgDoC/zLGLMVeApYAMwEbjLG6KDgEHC53WzYf4jDumeTkJDARaN7cfmYPiQAR/ncbBNu/nL7X8453Ls9bWHd3ZuhWsXozZW76j1evq2o3mPPxGYVPkMifzFpsHf72P51c+t4hi+mJSfy+9OGeZe1S09OZFwzo198nTOiu/f9yqpq+dU733LrG9aYgcWbDlBd6+Znx/UHrAu5jy3czHn//pwvtzuj6uYvFVuCLssYY1YAP/B5/Brwmp/zpgHTgn0f5d/Oogq2Oyu45CirR5qUmMAdkwZx68QBJId5+KMvf/m6qQnFDpRV40hPpriyhi6ZwX+z+GcLt/t7PlwmDspj6vyNPGlPG3BU7xy+2lHsXUYwO83/dZ65N49v1Tw595w+jG3Ocr7eUcyFzyzz7i+vrvWWf84d1ZM9JZU89flWnl9mXXi+4dVV9V7no5tCfxexil86cVgH5Sk99GqwElIkEztArU92H907h13FlQzMy2TKeSO8Fyw97v/A8IVdrlj88wmkBjHHTVOzMC69c2K9oYlgLS7tO1nYVcf2JWfVbsb2z+WVq8c0WbrynT8nEIkJCVw/rj+3zvyGnPRk9h2y6uwn/HMxYC2+AXD8oDye+nyr39f49eQh5LbhA0+phjS5d1DrCq1ZBAd1bd+r8r5j6a8q6MvEwXkA5GenseyuE/jd/75jjrFGw3oSO8Cu4gr6d2ld22tdbibaCTMzJYnfnzaU0w7rFvDzJwzKY8Igq32Du2a16r1bMnZALsf2c7DDz3DHH9vfrjzDVQEePHcE99jXCoZ0zeLi0cHN1KlUU3RumQ5qw74yslKT6l0cbA8On16uv4r6n88+3O9Uu2Zv66e4LfaZoGv6paNbldgjIT0lyW9y94yF72n/rm46fgAje9UNU/3vVUdHpoEqrmjPvQNavauYD7/fy8C8zEaliEjLTktmzk3j+e+K7Rw/sOkLkM9cOpr0lET6ODI44Z+L640pD1RpZV1JZkh+aHveobD/UJXf/Z6LthkpSd4PuhKfT8LmRhwpFSxN7h2Is6yaU//9ufdxf3tkR3tzZKZwy8SBzZ4zyu6pem44emzhJpZvdTLtolEBv89Be2TJI+eNCLKl4bVmd+OhjDdPGOD33G7ZaQzKywx64RSlWqLJvQO56fX6oyuO6B25IY+h4vtNw7cGH4houc7QlD+eMYz7Z6/1Pv74lvFNzhSZlpLEq9ccE6mmqTikyb0DcLnd3P3Ot6y3F494+eoxpCUl0sfRvvX2thrSiouaLrebv8y11hlt7+sMTTlreHcKS6t4fNFmgDZNAaxUW+kF1SjmdrtZv+8Qn206wPz11spBl43pzZCuWfTNzWj3enuwrjimD2CtdOQs838TT63LTZXPTUjf+ZQ8ojXuhIQErh0b/snalAqE9tyj2CvLt3HvO3WzNbx81ZiovJDYWj8/cRDH9ndw+8zV/H3eej78vpAZ1xzDiLy6csudb63ms00H+eIXE/l+T4l3nvjnOsB853lZqZw0JK+9m6HinCb3KLNmdwkvr9jOh98X1ts/pm/nmEjsHoPyrFg8cV4zYzk/PqoXvzx5CACfbbLq8U9/voWn7dWRLh7di+E9mp4oKVrMDsN6tUq1lib3KFHjcvPaVzuYOn+j3+OD82InsQPeibR8vfrVTk6VfI70uVD8ylc7AGuqgF9PHhKx9inV0WnNPQq43W5++daaRon91kmDmX3jOC48sieXHdM+a5KGi2/dfOr5Ixhsfyu5/pWVFPpMAe0Z2z7npvGRbaBSHZz23CPsoY/WMnlYV8YN6EKNy82m/Yf469z13vU6j+qdw71nCCWVNYyX7jidZfzmlKHt3OrwGtkzh1euH0vBw58AcNWLX9U7np6cGPE5c5Tq6DS5h9Cekkq2HSznmH4Ov8fLq2t565vdvPXNbt796bFMmbfBOwoGrCGOrRke2NH97tShrN5VjCMjBUdmKt2yU9lbWuWdeOusEd15b82eelP3KqUCo8k9hO6bbVi+1cltEwdy6ZjepDTobb67erd3+5ynltY7dkSvnLhK7ADnH9GT84+oW1J3r88C1QO7ZPKbyUN4b82eJu/yVEo1Tb/rhkhRebV3DdFpCzcx8Z+L+X5P/dvR/c1hPm5ALueO6sH0S0dHpJ3RzDPvOsAzl40mPSWJJXdO5Jpj+7Zjq5TqmDS5N8PtdvPIvA31etwN1dS6cLvdXPuSVSf2LLVW63Jz97vfUVNbV1LYdKCMBOCuk+pWBZpy7gjuOa3+GqDx6qg+nVl21wksu+sEsu0FPxITEqL2piWlopmWZZrxn8+28PKX1lC8Bz605gx55LwRrNxZzPDu2TjLq3nYviUeICkBPrhxHIs3HmCbs5z/fLaF7UUVDLDnLZ/zfSGDumYy2J4bZdKQvKAWrFBKqZYEldxFZBLwOuBZaucb4P+AF4AkYBdwpTGmUkQuB+4AXMCTxpjpbW10OB0sqyIjxVp+7Y2vdzY6fmeD1YU8euWk8co1x5CRksTph3djza5i/vPZFi5+djlL7pxIWVUtmw6UceUxfRjT18HjF49iVM8cv6+llFJt1Zae+6fGmIs8D0TkWaxFsV8XkT8D14nI88C9wLFAFbBMRGYZYw60qdVhUl3r4rR/f8HAvEx+d8pQiipquPDInsy0F2ROTADPwkNnj+jO/9bs4YMbx9HVz3Jt0i3bu33Jcyu864qO6esgMSGBgn65jZ6jlFKhEsqyzCTgRnv7XeCXgAGWGWOKAERkMXC8fTyq7C6u4Gl7fctN+8u8c3NfNLoXM1fu4g+nDeOHo3pQWeMizS6l3Hv6sCbrwclJiSy8/Xh++spKvvdZdUi6Z/s9XymlQqktyX24iLwDdAHuB7KMMZ5bC/cCPYEegO8kKZ799WRnp5Gc7H8lel9JSYk4HKGfy3tXUUWjoYmPfmrdLXrMkHzWPnB60Bf13r1tAgD3vrMGR0YKQ3r7HwPvT7jijUbxFCtovLEsWmINNrmvw0rorwGDgHkNXqupTOh3f2lpYEuuORyZOJ1lgbcyQJ+vrfv8GZSXycb91nukJyeG7P3uPMFaqag1rxeueKNRPMUKGm8si2Ss+flNT6QX1FANY8wOY8yrxhi3MWYDsBvIFRHPum+9gZ32fz18nurZ366c5dXc8voqVu4oAuDPc9Z5j/1i0iDv9hvXFUS8bUopFQrBjpa5HOhpjPm7iPQAugPPAhcCL9r/nw0sAZ4WEQdQg1VvvyMUDW+Lhz5ay9KtTpbaNx0BJCUmsPD240lJSuTjW8bTKS1Zx1crpTqsYAdZvwOcKCILgbeBm4DfA1fb+7oAzxljyoHfAB8Cc4H7PRdXw+XCZ5Zxz3vfNXl8/6GqevO5AAzumskiO7GDtTyaJnalVEcWVM/dGFMCnOPn0Kl+zn0DeCOY92lVm/aW8tX2IrYeLGfrwXIePOvwRufsLq5gyrwNAPz93BGM6tWJLzYf5OShXXXWQaVUTImZO1TvnLW63sRTD360lntOG0ZFdS2rdhaTnJTADa+u8h4/uk9nOqUnc+bw7u3RXKWUCquYSO7PLtlaL7EDvP3Nboorapi3bl+j8y84oied0mMidKWU8qtDZzhnWTU3vLbSO3TxmH4OisqrWVd4CKBRYk9NSmDxHRMj3k6llIq0Dp3cD1XXeBP7nJvG48hMocblZtqCjcwxheRlpvLUJUeSnpLEXFPoncBLKaViXYLb7W7vNlBYWBJQI/zdHLCvtJLkxEQcmSn19te63CQm0KFHveiNH7FL441dEb6JqckE16F77gBds9P87k9K7LhJXSml2krH/ymlVAzS5K6UUjFIk7tSSsUgTe5KKRWDNLkrpVQM0uSulFIxKCrGuSullAot7bkrpVQM0uSulFIxSJO7UkrFIE3uSikVgzS5q4gREZ3wR6kIiZrRMiKSC9yItd7qBmNMkYgkGGOio4EhZsd7J7AM+MIYszcW4/VJ6I9hLZr+v1iLsSERycNaCH4BsMwY42zhKR2aiDiA24HPgS+NMftj8W8ZOlaeioqeu4icAMwCugOXAE8AROMPLBRE5DhgJtbPfwLwIsRsvJ4//AnAWUD/dm5PWIlIf+BlrEXiBRjVvi0KLxE5F3gbyAJOAaZAbP4td7Q8FRXJHegKrDDG3GGM+TVwhIhcDDH7VX4gsNoY83s73gwRGdnejQo1EUk0xrjs3s4+IAc4VkRiedWUXgDGmFuMMY8ZYxZ6DsTo33Jf4HljzN3Ac8B6z4FYiVdE0u3NbljfTDpEnmqX5C4ig0XkCp9dnYD9dhIA+B3wB4jeT8XW8BPvQWCGfawXsBnYEvmWhZ5vrHZiTwQqsEsywMlAZxFJaeZlOgw/v9t9wGYRmSQi/xWR50TkbxCzf8u9gcEich7wNDBGRK6Hjh+viIwQkceBB0WkD5AJ7BWRLvYpUZ2nIpbcG3yy/RW4XUROsR9vAsYAeQDGmLeBXSLyW/u50fINI2AtxDvbGPOlvd0Z62teQjR++geiiVhPBivBY8U42RjzElAGvAHcGWPxTrYfJwM1wMXAR8AvgLEicq/93Fj5Wz7VfjwdmAc8DLwG/Aq4uKP+2/XEapfX/oV13SQJ+DlQAhRgldyiPk9FsjEpACIyDKgGngeutC9GLAD2A5fYF2cA/gwcKSLJdoLoaJqL1yUinlWwxgLrjDHFxhi3z1fAjsRfrFf7JAUXsFhEbgImYZVnlkVjbydA/uK9yv7dfodVmvCU3g4APwUuFJH0GPpbvsKOdz3wBTAXeMF+/FvgdBFJ64Dxptr/nwgcMsa8AtwHnAQsxvqGfWlHyFNhT+4icpKIzASmiMgEY8xa4F7gHaAS6w8f4BGsi08X2o8HAV8ZY2rC3cZQCiDea+1TPX8IfYEXRWSkiCwALo94o4MUQKzX2admA5difZCdi1WSOllEuka+1cELIN7r7VNfA77Dur6QhvU7nmuf02G04m85D+vD7HD78SBgkTGmw8TbINbjsL5d3mNfNyqi7lrCf4CRdIA8FdahkCLSE2tUyJ8AB1a99TNjzLP2RbXTgCuAO4wx2+2vtpOxSjTJwP12r75DaEW8txtjdtrPmQb8EFgFPG6M+aBdGt9KrYj1F8aYbSIyzE4OiEgPoJdPaSrqBfG3fDhwBjAe6yLrA8aYj9qn9a0XRLx3AEOxknwi8FdjzLz2aX3rNBHrYmPMDPvbZxesoY+n28M8TwROJ8rzVMgXyBaRJKyLDPsANzDLGPOBXW7YCTwkIu8aY/aJyFfAOOAi4FFgszHmdyIy1hizJNRtC4c2xPtPERFgL9YfxzPtFELAgoz1AuAfWHVoRCTJGLMb2N0uQbRCkPFeiBVvpTFmqoi8b4wx7RVDa7Tx3+4HWKNlxnWEDkqAsf7PjvVsrNF8++1kX2jnqWONMUvbL4rmhbQsI9bIj9ewLqCVA9OwanOZxpgKYBHWTTu/AjDGbLHP/6mIrMH6Y6EDJfZg471BRL4DDsPq4XSExB5srD+zf7cFdo22tl0CaKUQxOv5W+4oib2t/3bHGGMOdpDEHmisd9tPSQRmisj5wELqfrdRm9gh9D33fKCLMeZCABGZhDVqYApwk33Oi8DP7R+wG5gKrAUeNMasCHF7wq0t8T5kjFke8RYHL55iBf1bnkTsxhtorHeINWR3AvAj4FWskmqHKCeGOrnvwRoTmoj1abcB+AHwvIg8bYxZISLFWJ+We7E+OR81xswKcTsiJZ7ijadYQeON5XgDjbUSa+DD08BHxphX263FQQjbBVWxhvp9gjU64nLgbOBvwJFYw4yuNMaUhuXN20E8xRtPsYLGSwzHG0CslxtjytqvhcEL+QVVH6MAjDEHgcdE5BDWVegewE2x8sfhI57ijadYQeON5Xibi/XmjprYIbzJvTfwsj3M6AlgKXBPB75xpSXxFG88xQoabyzHG7OxhjO552ENkTofmGGsW89jWTzFG0+xgsYby/HGbKzhTO6bsYYSPW6MqQrj+0SLzcRPvJuJn1hB441lm4nRWMN5QTUqJ7APl3iKN55iBY03lsVyrFGzEpNSSqnQiaopKpVSSoWGJnellIpBmtyVUioGhXO0jFIRISIDgG+AFUAC1gyUfzbGfNzMc/oBPQKZ/Mmee+R1YI29Kwn4qTHm+7a1XKnw0Z67ihXGGDPJGHMi8DNgmogc0cz5JwPHtuL1P7VffxLwFNbyeUpFLe25q5hjjNkgIg8Bt2BNr/wIViJPx7oL8W2spdOqRWQr1rqufwKqsBYv/1ELY567AzsAxFoXt95zgQysKWXT7P9uMcZ8abdpIlbP/zFjzMuhjFspX9pzV7FqOTDcXnxhszFmAlZifcAYU4i11N8/jDHvALnAZXavvxhrlZ2GThSR+SKyAvgJ8KS9399zJwPb7V7+5UA3EZkI9DfGnID1reEeEckIR+BKgSZ3Fbs6AbX24gtdROQzrNWC8v2cWwg8LSKfYi2EnOfnHE9ZZgxW2ee1Zp77OTBeRJ4AhhhjZgPHAeNEZD7Wkm2JQM/QhKpUY1qWUbHqGOArsda7PBk40RhTLSL+ZjR8BjjLGPOdiDzW0gsbYxaIyDB7qbZGzzXG7BKRI7GS/U0iMg4oAaYbYx4OUXxKNUt77irmiMhg4E6slYK6AtvsxP5DIElEUrEWYfB0bjoDW0XEgZWQUwN4fae9ZGCj59p1+FOMtSD2bVgfNEuAc0QkUUTSxVoYXamw0ekHVIfXYChkGtYFy98bY+aISGdgDtYKQm9hlUeKgVewFnT+FSDAD7GWjHsP62LrccaYXfbrT6L+UMgU4NfGmMUi8oCf516GteBDDdaHyB+NMQvtC6qnYA3XfNwYMyMcPw+lQJO7UkrFJC3LKKVUDNLkrpRSMUiTu1JKxSBN7kopFYM0uSulVAzS5K6UUjFIk7tSSsUgTe5KKRWD/h+fWKV02zQM/wAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "lej_7QE1rUQl",
        "outputId": "5a1b5174-8197-4534-df9f-0338878a894c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 267
        }
      },
      "source": [
        "ipca2035['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "73ofcAx1rUQs",
        "outputId": "2a4fe58e-0dfd-4466-9bf6-f8e6472fdff5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 264
        }
      },
      "source": [
        "(ipca2035['Taxa Compra Manha'] / ipca2035['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(ipca2035['PU Compra Manha'] / ipca2035['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tnBoxOI1jLbd",
        "colab_type": "text"
      },
      "source": [
        "###2.8 Tesouro IPCA+ 2045"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P0nkysgBc6TU",
        "colab_type": "code",
        "outputId": "40362ecb-d415-4ac0-9b76-24d0ee41a7f3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "ipca2045 = titulos.loc[('Tesouro IPCA+', '2045-05-15')]\n",
        "ipca2045"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2017-02-08</th>\n",
              "      <td>5.34</td>\n",
              "      <td>5.46</td>\n",
              "      <td>685.78</td>\n",
              "      <td>664.14</td>\n",
              "      <td>663.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-09</th>\n",
              "      <td>5.27</td>\n",
              "      <td>5.39</td>\n",
              "      <td>698.96</td>\n",
              "      <td>676.90</td>\n",
              "      <td>676.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-10</th>\n",
              "      <td>5.21</td>\n",
              "      <td>5.33</td>\n",
              "      <td>710.67</td>\n",
              "      <td>688.23</td>\n",
              "      <td>687.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-13</th>\n",
              "      <td>5.21</td>\n",
              "      <td>5.33</td>\n",
              "      <td>710.90</td>\n",
              "      <td>688.46</td>\n",
              "      <td>688.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-14</th>\n",
              "      <td>5.22</td>\n",
              "      <td>5.34</td>\n",
              "      <td>709.23</td>\n",
              "      <td>686.85</td>\n",
              "      <td>686.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-15</th>\n",
              "      <td>5.22</td>\n",
              "      <td>5.34</td>\n",
              "      <td>709.49</td>\n",
              "      <td>687.10</td>\n",
              "      <td>686.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-16</th>\n",
              "      <td>5.25</td>\n",
              "      <td>5.37</td>\n",
              "      <td>704.09</td>\n",
              "      <td>681.88</td>\n",
              "      <td>681.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-17</th>\n",
              "      <td>5.32</td>\n",
              "      <td>5.44</td>\n",
              "      <td>691.53</td>\n",
              "      <td>669.73</td>\n",
              "      <td>669.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-20</th>\n",
              "      <td>5.27</td>\n",
              "      <td>5.39</td>\n",
              "      <td>701.09</td>\n",
              "      <td>678.98</td>\n",
              "      <td>678.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-02-21</th>\n",
              "      <td>5.25</td>\n",
              "      <td>5.37</td>\n",
              "      <td>705.11</td>\n",
              "      <td>682.87</td>\n",
              "      <td>682.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>4.47</td>\n",
              "      <td>4.59</td>\n",
              "      <td>1110.21</td>\n",
              "      <td>1078.88</td>\n",
              "      <td>1079.02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>4.52</td>\n",
              "      <td>4.64</td>\n",
              "      <td>1097.12</td>\n",
              "      <td>1066.18</td>\n",
              "      <td>1066.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>4.43</td>\n",
              "      <td>4.55</td>\n",
              "      <td>1121.02</td>\n",
              "      <td>1089.38</td>\n",
              "      <td>1089.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>4.61</td>\n",
              "      <td>4.73</td>\n",
              "      <td>1073.99</td>\n",
              "      <td>1043.74</td>\n",
              "      <td>1043.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>4.77</td>\n",
              "      <td>4.89</td>\n",
              "      <td>1033.93</td>\n",
              "      <td>1004.86</td>\n",
              "      <td>1004.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>4.62</td>\n",
              "      <td>4.74</td>\n",
              "      <td>1071.32</td>\n",
              "      <td>1041.16</td>\n",
              "      <td>1041.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>4.52</td>\n",
              "      <td>4.64</td>\n",
              "      <td>1097.22</td>\n",
              "      <td>1066.30</td>\n",
              "      <td>1066.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>4.47</td>\n",
              "      <td>4.59</td>\n",
              "      <td>1110.44</td>\n",
              "      <td>1079.13</td>\n",
              "      <td>1079.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>4.42</td>\n",
              "      <td>4.54</td>\n",
              "      <td>1123.82</td>\n",
              "      <td>1092.12</td>\n",
              "      <td>1092.06</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>4.40</td>\n",
              "      <td>4.52</td>\n",
              "      <td>1129.25</td>\n",
              "      <td>1097.40</td>\n",
              "      <td>1097.34</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>813 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2017-02-08               5.34              5.46  ...          664.14         663.92\n",
              "2017-02-09               5.27              5.39  ...          676.90         676.67\n",
              "2017-02-10               5.21              5.33  ...          688.23         687.84\n",
              "2017-02-13               5.21              5.33  ...          688.46         688.23\n",
              "2017-02-14               5.22              5.34  ...          686.85         686.62\n",
              "2017-02-15               5.22              5.34  ...          687.10         686.85\n",
              "2017-02-16               5.25              5.37  ...          681.88         681.62\n",
              "2017-02-17               5.32              5.44  ...          669.73         669.25\n",
              "2017-02-20               5.27              5.39  ...          678.98         678.73\n",
              "2017-02-21               5.25              5.37  ...          682.87         682.62\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               4.47              4.59  ...         1078.88        1079.02\n",
              "2020-05-11               4.52              4.64  ...         1066.18        1066.10\n",
              "2020-05-12               4.43              4.55  ...         1089.38        1089.30\n",
              "2020-05-13               4.61              4.73  ...         1043.74        1043.65\n",
              "2020-05-14               4.77              4.89  ...         1004.86        1004.77\n",
              "2020-05-15               4.62              4.74  ...         1041.16        1041.34\n",
              "2020-05-18               4.52              4.64  ...         1066.30        1066.23\n",
              "2020-05-19               4.47              4.59  ...         1079.13        1079.07\n",
              "2020-05-20               4.42              4.54  ...         1092.12        1092.06\n",
              "2020-05-21               4.40              4.52  ...         1097.40        1097.34\n",
              "\n",
              "[813 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "67ygtxYhdF27",
        "colab_type": "code",
        "outputId": "9f9c2546-88d5-44f7-aa36-71076e6878c8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        }
      },
      "source": [
        "ipca2045['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WPMXy7qRdW5E",
        "colab_type": "code",
        "outputId": "73709ded-3090-4e50-8756-a77c3e1d3d3e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "ipca2045['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OwbZ74W0gswp",
        "colab_type": "code",
        "outputId": "5039bcb2-56fa-431c-c49d-2dce08e64881",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 271
        }
      },
      "source": [
        "(ipca2045['Taxa Compra Manha'] / ipca2045['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(ipca2045['PU Compra Manha'] / ipca2045['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "colab_type": "text",
        "id": "kbgBrJR7rsVf"
      },
      "source": [
        "###2.9 Tesouro IPCA+ 2055 com Juros Semestrais"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "RRqyc89hrsVj",
        "outputId": "90011dfc-0387-45fe-ad9c-f1eb8b689f1a",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "ipca2055 = titulos.loc[('Tesouro IPCA+ com Juros Semestrais', '2055-05-15')]\n",
        "ipca2055"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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>Taxa Compra Manha</th>\n",
              "      <th>Taxa Venda Manha</th>\n",
              "      <th>PU Compra Manha</th>\n",
              "      <th>PU Venda Manha</th>\n",
              "      <th>PU Base Manha</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Data Base</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-02-10</th>\n",
              "      <td>3.42</td>\n",
              "      <td>3.54</td>\n",
              "      <td>5063.37</td>\n",
              "      <td>4956.73</td>\n",
              "      <td>4955.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-11</th>\n",
              "      <td>3.36</td>\n",
              "      <td>3.48</td>\n",
              "      <td>5119.00</td>\n",
              "      <td>5010.64</td>\n",
              "      <td>5009.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-12</th>\n",
              "      <td>3.36</td>\n",
              "      <td>3.48</td>\n",
              "      <td>5120.02</td>\n",
              "      <td>5011.66</td>\n",
              "      <td>5010.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-13</th>\n",
              "      <td>3.40</td>\n",
              "      <td>3.52</td>\n",
              "      <td>5084.54</td>\n",
              "      <td>4977.32</td>\n",
              "      <td>4976.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-14</th>\n",
              "      <td>3.37</td>\n",
              "      <td>3.49</td>\n",
              "      <td>5113.38</td>\n",
              "      <td>5005.31</td>\n",
              "      <td>5003.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-17</th>\n",
              "      <td>3.34</td>\n",
              "      <td>3.46</td>\n",
              "      <td>5141.86</td>\n",
              "      <td>5032.93</td>\n",
              "      <td>5032.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-18</th>\n",
              "      <td>3.37</td>\n",
              "      <td>3.49</td>\n",
              "      <td>5115.22</td>\n",
              "      <td>5007.16</td>\n",
              "      <td>5006.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-19</th>\n",
              "      <td>3.37</td>\n",
              "      <td>3.49</td>\n",
              "      <td>5116.14</td>\n",
              "      <td>5008.08</td>\n",
              "      <td>5007.16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-20</th>\n",
              "      <td>3.34</td>\n",
              "      <td>3.46</td>\n",
              "      <td>5144.62</td>\n",
              "      <td>5035.70</td>\n",
              "      <td>5034.77</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-02-21</th>\n",
              "      <td>3.43</td>\n",
              "      <td>3.55</td>\n",
              "      <td>5064.69</td>\n",
              "      <td>4958.31</td>\n",
              "      <td>4956.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>4.50</td>\n",
              "      <td>4.62</td>\n",
              "      <td>4260.68</td>\n",
              "      <td>4180.23</td>\n",
              "      <td>4180.78</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>4.52</td>\n",
              "      <td>4.64</td>\n",
              "      <td>4247.41</td>\n",
              "      <td>4167.37</td>\n",
              "      <td>4167.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>4.42</td>\n",
              "      <td>4.54</td>\n",
              "      <td>4316.27</td>\n",
              "      <td>4234.21</td>\n",
              "      <td>4233.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>4.50</td>\n",
              "      <td>4.62</td>\n",
              "      <td>4261.59</td>\n",
              "      <td>4181.18</td>\n",
              "      <td>4180.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>4.67</td>\n",
              "      <td>4.79</td>\n",
              "      <td>4051.08</td>\n",
              "      <td>3974.03</td>\n",
              "      <td>4071.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>4.55</td>\n",
              "      <td>4.67</td>\n",
              "      <td>4129.72</td>\n",
              "      <td>4050.36</td>\n",
              "      <td>4051.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>4.48</td>\n",
              "      <td>4.60</td>\n",
              "      <td>4177.36</td>\n",
              "      <td>4096.61</td>\n",
              "      <td>4096.36</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>4.45</td>\n",
              "      <td>4.57</td>\n",
              "      <td>4198.16</td>\n",
              "      <td>4116.80</td>\n",
              "      <td>4116.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>4.44</td>\n",
              "      <td>4.56</td>\n",
              "      <td>4205.27</td>\n",
              "      <td>4123.73</td>\n",
              "      <td>4123.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>4.43</td>\n",
              "      <td>4.55</td>\n",
              "      <td>4212.40</td>\n",
              "      <td>4130.66</td>\n",
              "      <td>4130.43</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>69 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            Taxa Compra Manha  Taxa Venda Manha  ...  PU Venda Manha  PU Base Manha\n",
              "Data Base                                        ...                               \n",
              "2020-02-10               3.42              3.54  ...         4956.73        4955.71\n",
              "2020-02-11               3.36              3.48  ...         5010.64        5009.63\n",
              "2020-02-12               3.36              3.48  ...         5011.66        5010.64\n",
              "2020-02-13               3.40              3.52  ...         4977.32        4976.30\n",
              "2020-02-14               3.37              3.49  ...         5005.31        5003.81\n",
              "2020-02-17               3.34              3.46  ...         5032.93        5032.01\n",
              "2020-02-18               3.37              3.49  ...         5007.16        5006.23\n",
              "2020-02-19               3.37              3.49  ...         5008.08        5007.16\n",
              "2020-02-20               3.34              3.46  ...         5035.70        5034.77\n",
              "2020-02-21               3.43              3.55  ...         4958.31        4956.35\n",
              "...                       ...               ...  ...             ...            ...\n",
              "2020-05-08               4.50              4.62  ...         4180.23        4180.78\n",
              "2020-05-11               4.52              4.64  ...         4167.37        4167.05\n",
              "2020-05-12               4.42              4.54  ...         4234.21        4233.90\n",
              "2020-05-13               4.50              4.62  ...         4181.18        4180.86\n",
              "2020-05-14               4.67              4.79  ...         3974.03        4071.31\n",
              "2020-05-15               4.55              4.67  ...         4050.36        4051.08\n",
              "2020-05-18               4.48              4.60  ...         4096.61        4096.36\n",
              "2020-05-19               4.45              4.57  ...         4116.80        4116.57\n",
              "2020-05-20               4.44              4.56  ...         4123.73        4123.49\n",
              "2020-05-21               4.43              4.55  ...         4130.66        4130.43\n",
              "\n",
              "[69 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "H_GEk93hrsVr",
        "outputId": "e9f01440-d2fd-4fa3-9c9a-75c8b2a3d95e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 281
        }
      },
      "source": [
        "ipca2055['PU Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "SFZUM-5_rsVw",
        "outputId": "a4a90500-ba9a-4dd4-b153-6178d4c3855b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        }
      },
      "source": [
        "ipca2055['Taxa Compra Manha'].plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "dwYEUEjVrsV1",
        "outputId": "9e24b1c2-fe0e-4ba9-cc05-007f3c613bb2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 279
        }
      },
      "source": [
        "(ipca2055['Taxa Compra Manha'] / ipca2055['Taxa Compra Manha'].iloc[0]).plot();\n",
        "(ipca2055['PU Compra Manha'] / ipca2055['PU Compra Manha'].iloc[0]).plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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ul68z6HWMzE1jR6WTykYPOiAvrf8TOISSrY7QHNyR2FvdxOrSWq44rQhT+KpjzrBslt5+Ol8am5h34x270nGeYM/YkJVO7n1rB8NyUvn1QgHAjsrEmiXS6w+yt7qp02GY/kCQ9QfrW5tPWnxz1mB+fuFo9hxt5oYXNvLDN7exrzr+c4O3pW7kUTrw+DWspmO/7aPy7fzzq6f16LWj8tN4c8thijOtZKWaozac7kTy7BamFTtYsv0It8zq/AqhMy+vL8di1HPphMJ2z/fXzUfRMDTbhtmoZ0dlY9yvEnZXNXHHa1tITzHy10vHtS76sa2ikVklse0/0DSNo01e9te42F/b3Pr3QK2L8no3QQ3SLAbeumVGu3/fHZVOmn2BDgncaNDz9ZmDmT80kxfXlfHc54e4+pnPu118JNYS9yxV4sYbCJJh7d2pMTrfzssbylmzv7bfbqHvyoVj8/nFu5IX15e1m0iqK3XNPt7ZXskFo/Nw2BKvrbsrRoOeUQX2uNfAdx5xcturm7EY9fztignkhq+2SrKsbD8c2xr4a5vKeWj5PprbDK+0GPUUZ1oZlWfnvFF5pFmMPLh8L4u3HuaaKQNb9/s03CE8ZaCjw3EBUs1Gbp41mMsnFvGvNQd4dWM57+04wuWnFXHDjGIc1vidOxF9S4UQ44A3gQeklI8ct+0W4CYgAGwCbpdSJm7rv9Kl40ehRKLl8v6I09t6k02szB+Zy7s7jvDAsr2sLq3lZwtGktfNj8gL6w/h9QfbfZmTxfiiDBZtLCOoaegjuGU/WmSlk9v/E0rej105sXX6BIAxBXZWl9aiaVpE0wm0tamsHn9Qa+1U7E6D28fDH+9jaI6NC0bnMzjTyuAsK3l2S4eyWb77KC9vKOeqSQMw6HXUu3y8tL6c04dknvBHvGXxka9OHsATq/bz0voy3txymG9MH8R1Uwe2NsHFUiQr8qQCDwMfdrLNBlwNnCmlnA2MAmZFK0gltjzHjUKJREmWjZRw8o/FEMK2LEY9D106jh/NH86GQ/Vc/cw63ttxpNNRBA1uH69sKGf+yByGZCfuorVdGVuUTpM3Ph2ZOyobue0/m7GaDDx+VfvkDTC2wE5Ns691JFIk/EGNv6/Yxy0vbeLet3b0aATIyxvKafIG+Mm5I7hyUhEzSjIpSE/p9Iftq5MHUF7v5pM91QD867ODOD1+7jxzaI9jbFl85MVvTGFasYO/ryjlhhc2svtoU88/aJRE8i31AAuB8uM3SCmbpZTzpZS+cDLPAA5HKUYlxrzHjUKJhEGva128NxYjUI6n0+m44rQinv/6FEqybPx8yRfc+/aODnOlvLw+9KW/cWZxzGOMhnFFoaubWDejbDvcyO2vbiHVHErenc3YN6YgNLVvpM0ohxvc3PryJv712UGG56ZS6/JRWtP9D5TT4+el9WXMGZbdoxkb5wzPoTDdwovryyird/HKxjK+NDaf4bmRTxLWsvjIfV8eQ5XTw9efW8+Tq/YjK0M3s8VCj7+lUkq/lLLb0hRC/BjYA7wipVS3iiUpbyCIpQ+Xgy3TqMa6Dbyt4kwrT149kTvOHMLHe6q56pnP+Thc63J6/Ly0oYy5PfzSJ6Lh4TVBYznaY2tFA3f8ZzP2FCOPXzWRoozOO/FG5KZh1OvYdrjnPy4f76nmumfXs6uqid8sHMUfLhoDwIbj5rhZKqv404e7W++6/c/Gchrcfm7q4Q+xUa/jykkDWH+onp+98wV6nY5vzS7pcZydOWtEDi99YwpnDs3miU/3c91z65n/yCpue3Uzj68s5dPSGpye3q0peyJR7cSUUv5BCPEgsEQIsUJKubLt9rQ0C0Zj7CeoNxj0OBzJdZkcz5i9gSD2VHOP3r+zOKcNzeHlDeWIgY64l/tdCwTnTyji7tc284NF27hs8gDy0iw0uP3cde7IDvEly7liMOgZVZjO7urmmMS74UAtd762lUybmedunE7RCebKHlVgZ+fRpi5jaylnrz/Ife9Lnv50P2MK03nwqomUZKeiaRp5dgtbKpu4sc0x/vHZAfZUNbF8TzU/v3A0L24oZ86IHE4fld/jz/L12UN48tP9bK1o5NtzhiIGdT1ZWU/PB4fDxuNfn0pZnYv1B2pZf6COdftreeqzAwQ1KMxIYfkP5va6T6ArUUngQogsYJyU8mMppUsI8S4wG2iXwJ3OyNvEosHhsFFXl1jjN08kXjFrmobHF0QLBHv0/p3FOXtQOn++eAxFVmNClHt+ioGnrp7Ik5/u55k1BwlqMKskk0Gppg7xJcu54nDYGJFt470dR6ipberXjsxNZfXc9fpWsmwmHr1iAja0E5aRyE3tNjaHw8bW0mp+8vYOdlQ6uWpSEd+ZMxSzQdd67IlF6azZV01tbRM6nY7Smmb2VDVx2cRCNpbVc2d4MrWvTxkQ8b/ZZRMKee+LI1w5oaDb10Z6PqQCZxY7OLPYAWeU0OT1s62iMbSaUx+mAs7N7XzFqWh1m5qAp4UQLdej0wEZpWMrMeQPamjQpyYUo0HP3OE5Ua9t9IXJoOe2M4bwj6tP44yhWdw5Z0i8Q+qz0flpNHkDvbr7tKc2ldXznde2kp1q5rErJ/a4X2NMgT3UydpFG/aSLRVc9+x6DtW5+dOXx3D32cM79LtMHpjBEaeXsvrQ2qrLd4eawK6fPoh/XzuZG2cWc82UAUwckBHx57pjzhDeuGl6v4/3TzUbmT44s9/GxPc4eiHEFOB+oATwCSEuBxYD+6SUbwghfg38TwjhJzSMcHE/xKv0s5bZ12J1A06sjS9K54FLxsU7jKgYFV4H9ItKJ4Oz+qcZ5f/e30V2qonHr5xATgR31Y4Nd2RuO9xISZtRPm5fgAeW7eX1zRWML7Tz2wtHd9mWPmlgKDGvP1TPQIeV5buPMjo/rfUGmm/3oe1ar9NhMSZOBaO3epzApZTrgLO62f408HSfI1LiyhsIJ/A4jGlVIjMs24bZoGNTeQPn9cMdmUebvOyraeY7c4ZElLwhNJzUatKz4VA9F4zJQ6/TUVrdzL1v72D30SZuOWMIN04dgLGb82xIto2MFCMbDtVzekkmWyoauXV24i9zFkvqTkylnWMLGid/7eRkZzToOWt4Du9sq+Rbpw9ut6B0NGw8FFoeb/LAyJsoDHod4wvTeXPrYT7cVcXYAjubyhpIMRn466XjuHDSwBO2Let1OiYNzGhdHxTgrOE5kX+Qk5iqZintnOxNKCebG2YU0+wL8NL6sqgfe8OheqwmPSKvd0Mtf3vhKH55vmCByKO6ycfUYgcvfH1yRHOsTxqYQXm9m/9sqmCQI4WhSXjTVX9SNXClnZYmlL50YiqxMzw3lbOGZ/PyhnKunTowqp1y6w/VM6Eovdtmju5k2sxcODafC8f2fIjf8VrmJ9lV1cR1UwcmVMd4IlDfUqUdr6qBJ50bZxbT6PHz6sYON0n3Wr3Lx+6jTUzuYoKnWBmem0qqOXTvyFkJtLxdolDfUqUdj+rETDqj8+3MHpLF858fotkbncWON5aFFjCY1Iv272gy6HVMHphBdqo55pOjJQP1LVXaOdaJqU6NZHLjzGLq3X7ueWs7/9lYzq4qJ4E+zMex/lAdZoOudV6TeLr33BE8dsUEDHrVfHI81QautOPxh770qgkluUwoSuf66YNYvPUwq0trAUg1GxhXaGdiUQYTitIZW2jvcRv5hkP1jCtMT4gf8tw0C0k6ZU2/UwlcaUeNA09et585hNvOKKGs3s3m8obW/578dD8aoNfBsJxUbpxRzDmi66Xxmrx+5BEnN8xIzpkaTyUqgSvtqCaU5KbT6RjosDLQYWXhmNDoD6fHz9aKUDL/cOdRfvmeZGReGsWZnU9ItamsgaAW//Zv5cTUt1RpR3VinnzSLEZmlmTxzdNLeOTy8ZgNen71nuyyjXzDoXoMeh0TilSnYaJT31KlHTWM8OSWm2bh7rOHsbm8gRfWHep0n8/21zI6P611gWIlcalvqdKOakI5+V0wOo+5w7J5bGUpe6vbLwO27mAdOyqdnD8qvqvdKz2jvqVKOy1NKPFYoFWJDZ1Ox73njsBqMvCr93a2W/7rn6sPkGUzcfH4gjhGqPSU+pYq7Xj9QQx6HUY15vaklp1q5p5zRrD9cCPPrj0IwObyBtYeqONr0waRoppPkkJEo1CEEOOAN4EHpJSPHLdtHvB7IEBoMYebpZTBaAWqxEZf18NUkse5IpePdh7liVX7OWNoFk+tPkBGipFLJxTGOzSlh3r8TRVCpAIPAx92scsTwOVSytmAHTi/7+Epsebpw4r0SvK5Z/5w0lOM3P3mdlbuq+HaqQOxmVXtO1lE8k31AAuBrmbMmSKlbOnWrgLUzDNJyBcIYjao5pNThcNm4t5zRlBe78ZuMXLFaUXxDkmJQCQr8vgBvxCiq+0NAEKIQmAB8PNoBKjElqqBn3rOGpHDd+YMoSgjpd/XiFSiK6r/WkKIPOAt4DYpZfXx29PSLBiNsb88Mxj0OBzJNRF8vGLW9HqsZmOP3zsZy7Y7yfJ5oh3nned2XjHrL6dqOUdb1BK4ECIdeBf4qZTy/c72cTo90Xq7iDgcthMu35Ro4hVzk8uHUUeP3zsZy7Y7yfJ5kiXOriRL/IkSZ25u57NCRvNa+X5Co1Pei+IxlRjzBILqNnpFSRI9roELIaYQStIlgE8IcTmwGNgH/Bf4OjBCCHFz+CUvSCmfiG64Sn/z+oPqLkxFSRKRdGKuA87qZhdLn6NR4s7rD5KeojqyFCUZqKqW0o5qQlGU5KG+qUo7XjWMUFGShvqmKu2oW+kVJXmob6rSjqqBK0ryUN9UpR2PX7WBK0qyUN9UpZWmaaEmFKOaC0VRkoFK4EqrQFAjqKnl1BQlWahvqtJKLWisKMlFfVOVVmo9TEVJLuqbqrTy+FUNXFGSifqmKq28gdDitqoNXFGSg/qmKq1UE4qiJBf1TVVaqU5MRUku6pt6ittS3sCdr22hwe1rrYGrJhRFSQ7qm3qKe2NzBatLa/nbJ6XHmlBUDVxRkkJEEz8LIcYBbxJaeeeR47alAI8DY6WUU6MXotJfgprGyn01WIx6Xt9cgT08D7iqgStKcujxN1UIkQo8DHzYxS73ARujEZQSG19UOqlp9vHduUMpsFt4bu1BQCVwRUkWkXxTPcBCoLyL7T8B3uhzRErMrNxXgw6YPzKHH80fTngUoWpCUZQk0eNvqpTSL6V0dbO9MTohKbGycm8NYwvtZNrMnDksm7NH5ABgNakErijJIKaLH6alWTAaDbF8SwAMBj0Ohy3m79sX/R1ztdPD9spGvjNveOv7/OmKiazYfZThAzN7fJxkLNvuJMvnSZY4u5Is8Sd6nDFN4E6nJ5Zv18rhsFFX1xyX9+6t/o753W2H0TSYWmRv9z6zB2VE9L7JWLbdSZbPkyxxdiVZ4k+UOHNz7Z0+r66VT1Er99aQk2pG5KXFOxRFUXqpxzVwIcQU4H6gBPAJIS4HFgP7pJRvCCFeBQaFdhXLgCeklC9EP2Slr/yBIKv31zJ/RC46nVq8QVGSVY8TuJRyHXBWN9uviEZASvT4AkHq3X7qXD7qw//Vuf3sq27G6Qlw+tCseIeoKEofxLQNXOl/n+2v5Q9Ld1Hb7KPJG+hyv8J0CzMGO2IYmaIo0aYS+Enm3R1HqG32cdG4AjJSjDisJjKsJhxWIxkpptbHasZBRUl+KoGfZDaX1TN1kIMfzBsW71AURelnqhp2Eqlu8nKwzs3EAenxDkVRlBhQCfwksrm8AYAJRSqBK8qpQDWhxIkvEGTnESdGvR6RH52x2JvKGjAbdIzO73zQv6IoJxeVwGNsU1k9f1tRyvbDja2LCH97dgk3zBjU5zHZm8vrGZ1vV7MJKsopQiXwGAoENX793524fAEunVDIxAHpLN9dzaMrS9lX08zPFozs9egQty/Ajkon10wZEOWoFUVJVCqBx9BSWcWBWhd/vGg0Z4/MBeDsETkMybbx9xWlHKpzcd/FY8lJNUd87B2VTvxBjQlFGdEOW1GUBKWutWMkqGk89dkBhmTbOCs8bSuATqfjhhnF/PHLY9hd1cT1z29g5xFnxMffVFYPwETVgakopwyVwGNk2e5q9lY3c+OMYvSdtKSgqUcAACAASURBVHWfPSKHf1x9GpqmcfNLG1m6ozKi428qb6Aky4rDZopWyIqiJDiVwGNA0zSeWn2A4kwr54rcLvcT+Wk8c+0khmanctuLG3hmzUE0TTvh8YOaxubyBiaq5hNFOaWoBN7PGtw+Xlxfhjzi5PrpgzDoux9pkpNm4bErJ7BwXAGPfLKPX70n8fqDHHV6+HBnFYu3Hqb5uDlOSmuaaXD7maBu4FGUU8qp14mpaeiaqzDW7yVocRDIHtXlfqby1Wg6A/6i6T0+vD+osa2igdWltXy2v5ZthxsJajAiN5ULRuf16BgpJgMPXDGRgXYLj6/az7Ld1e0mpvrrsr1cNrGQOcOy2Vnl5H+7jgKq/VtRTjURJXAhxDjgTeABKeUjx207B/gdEACWSCl/E7Uo29A1V2Gs2QlBP7qgH3+WIJg+sON+7loMdfsw1O9F7z6E/fBODPX7MNTtQ+871knoy5+Ma/zX8Q6aG0ruQT+mQyuwbfoHxurtaHoTdV95BX/htC5jOlTn4rP9tawurWXtgTqavAH0OhhbYOfGGcXMLMlkbIEdYwSLBet0Om6eNZhhOaks230UkZfGxKJ0/EGNF9aV8cyagzy9JrSKfJbNxMXjCyjOtEZQkoqiJLtIFnRIBR4GPuxil4eA84AyYLkQ4jUp5fa+h3iM6dBK0t/7JnpPfetzmt6Ea9zXaJ56F5rJRop8HevmpzDWyGP76PSY7IMIOEpwF0wl4BhCIGMIxtrdpGx7lvSl3+3wXv4sQePc32Pd+DgZ736T2ivfIZhWBIDT4+fzA3Ws3h+qZR+qcwOhKVoXjMpl5uBMphY7SE/pe4fivBE5zGszagVg4oAMDta6kEecjMpPY0BGilqYQVFOQZHUwD3AQuCe4zcIIYYCNVLKg+HHS4D5QNQSuGXHy9iX3UMgYygNC/6OZkoFIOWLV7FueZqUHa+AwYzeXYMvZyzOWT8lkDmMgGMo9kGCOmfHubF9g+fhmngzprJVGGp2gt4IOj2BjBJ8A04HnQ5f0Qwc/7kI29s38fCgB1l5oJmtFQ0ENLCZDEwZlMFXJw9gxuBMijOtMUukgzKtDFI1bkU5pUWyIo8f8AshOttcAFS1eXwEiNp8pqXvP8i0XffhHTSHhvMeQ7Mca+t1Fk7FNfFmbGsfQBf04ZpwA76iWdA2kRotQBcLk+p0+AbOxjdwdqebA1kjaTjnIRzv3sT8qm8xyDoZywhBwdAJlAyfgMmSuCtWK4pycuuvTsxOq6FpaRaMRkPEB6tuqOeJwJeYctZfmJCf03EHx0Qqsh8DoDAjpcNmg0GPw9H7RPuJ/Qw+8t3ADzM+YrLrVXQHgnAAtGU6cAxGyxmJliPQcgTkjETLGQmWvnUodhuzpsFRia56N6QXoWUMAltO+x+tGOlr2SaaZPk8yRJnV5Il/kSPM1oJvJxQLbzFgPBz7Tidnl4dfPiF9/KLZ9fzzCtbee5rk0mztA97w6F6vr9oK/6Axp1zhnL5aYXtbpZxOGzU1XVRAz8BTdN4cOkuKqwX8u2v/Qqvzoehbh/Gml0YandiqN2NsWYnhr3L0AW9ra8LpBYQyBqJP3M4gcyR+AbMIpDZ84sSh8NGw6E92Nb/DWPFWoKpBaHO2mAA84FlGBoPtdvfnyWovfxtMMW2WaUvZZuIkuXzJEucXUmW+BMlztzczmcYjUoCl1KWCiHShRAlwCHgS8C10Tg2QIbVxG8XjuJbr2ziD0t38ZuFo1rbmpfvruan7+ygwG6hMCOF+z7azfLdR7n77OGUZPWsTbrB7WNf9bF/pAEOa+t8JOsO1rOpvIEfnj0sPMufhUD2qI7DD4N+DA0HMNTswlC7C2PtLgw1u7BufwmdvxnNYKHuktfw5592wnj0zgr0nz1B1vpngCC+olnomw5jOvw5BP34Bp5B85Q78OeMQ99UibFqM6mfP4hlzzt4Rl3e43JVFCW5RTIKZQpwP1AC+IQQlwOLgX1SyjeAbwMvhnd/WUq5M5qBnjYwg1tmDebxVfsxGvRkWk24fAEWba5gVL6dv14yjgyrkTc2V/DX5Xu58unPybKZmFCUzoxhOYzITOl0qtUPd1bx+w92Ue/2tz6XYtTznblDuXxiIf9cvZ/sVDNfHldwfEjt6Y0EHEMJOIYSGowTpgUx1JeSsfha0pfcRN0VbxNMK+z8EM4KbOv/Rsq2F4Ag7lFX0jzlToLpg9ocT+vQVOIdsgDL7rewbn9eJXBFOYXoenKrdrRUVTX26c0CQY2fvL2DVftqWp+bWZLJry4Yhc18rG39cIObVftq2FTewObyhtZhfqbwYgcTitIZX5TORzur+O8XVYzOT+PmWYOxGPQENI0X15Wxen8tYwvsbDvcyHfnDuXaqR3HmkfCUP0FjtcuJuAYRt0lr7Vr6ugscRvn/Yg6Omnv74J1w+OkrfoNNVd/SCC7047mfpEol5jRkiyfJ1ni7EqyxJ8ocebm2jttSkiqBN5bfqOBT3ZUsjmc0HdUNuILaBj0Om6aUcwNMwa1u8lG0zRe21TBg8v3YjUZePOW6VhNkXe+Hs9cupT0d27AXzAFX9EMAmmFGGt3kbLtRY6vcUd64uhcNWQ/PRXXuK/RdOav+hxrTyXKCR4tyfJ5kiXOriRL/IkS5ymdwI//R/D6g3xxxElGipHBWV33MFc2evAFggx0RK9jMGXbc9jW/Q1902F0QR+a3thpU0lvThz7f2/DfHA51dd/DsbYdGYmygkeLcnyeZIlzq4kS/yJEmdXCfzUmwsFMBv1PVr4N99uifp7u8deh3vsdaAF0TUfBb0BzZodpWNfS8ruxVj2LMEjLovKMRVFSVynZAJPCDo9WmrPJrfqKd+AWfgzSrBufBIAzWhFM1rBFPqrGVLQWv7fkg6G6P9AKYoSOyqBn0x0etzjrydtxS8xLb2r212D1tx287soipJ8VAI/ybgm3IRn+EXofE3gd6Pzu9C1/PW5IOBG72kgddVvsa39K855f4p3yIqi9JJK4CcbnY5gav4Jd9PXl2Ld+m9ck24Nj10Hgn70jYcIZpT0b4yKokSFWpHnFNU89TtgsGD77M+hJ/xu0t+9hazn56Bz1XT/YkVREoJK4KcozZZL88SbSdm9GGPFWjKW3Iil9AN0WhB985F4h6coSg+oBH4Kc036FkFLBo5FV2I6tAL3qCsA2i2YoShK4lIJ/BSmWTJonvY9QKPx3Idxjb8BAJ1K4IqSFFQn5inONfFm3KOvRjOnoa/fD6gErijJQtXAFTRzWuivJQNQTSiKkixUAldaaZZ0NHTo3HXxDkVRlB5QCVw5RqdHs6SrJhRFSRIRtYELIR4AZgIacJeUcm2bbRcDPyO0ev1LUspHohmoEhuaJUM1oShKkuhxDVwIMRcYIaWcBdwEPNRmmx54BFgIzAEuEkL0bQUEJS6ClgxVA1eUJBFJE8p8YBGAlHIHkCmEaJmTNQeok1JWSSmDwIfAOVGNVIkJVQNXlOQRSQIvAKraPK7i2Er0VYBdCDFCCGEC5gEnnpBDSTiaqoGfknSeBvC74x2GEqG+jANvXSFCSqkJIb4BPAXUA/vabm+RlmbBaOz70mSRMhj0OBxdr7yTiOIVs8Geje5wQ4/fOxnLtjvJ8nmiGadOvoPh7TvAXoj/2sWQ2vO1WHvrVCzn/hBJAi/nWI0boAioaHkgpVwOnAkghPg9UHr8AZxOT6+C7KtEWRYpEvGKOVWXitVd1+P3Tsay7U6yfJ6oxBnwkLrq/7Btfgp/9mgMNXvRPXsxdV95BS0lMzqBduGUKucoyM21d/p8JE0o7wOXAwghJgPlUsrGlo1CiHeFEHlCiFTgImBp78NV4iVoyUAX8IDfFe9QlH6kr9+P47VLsG1+iuYJN1F7xdvUL3wKQ91eMhZfo+4FSBI9TuBSylXAOiHEKkIjUG4XQlwvhLgkvMuThJL8CuD3UsqjUY9W6XeaxQGouzFPZubdb5P5yvkYGvZTf8E/aDrzV2Cw4CueS8P5T2Csltg//H68w1R6IKI2cCnlj497alObba8Dr0cjKCV+Wm6n17nrIbXgBHsrCUvT0LlrMTjL0TvL0TeWYXCWY6jdhaV0Kb78STQs+DvB9EHtXuYtmU/ztO+S+tmfMFZuwJ8/KT7xKz2iJrNS2gmmhBO4qoEnFy2Ibd0jmMo+Re8MJWvdcaNKNL2ZYFohzZNvp2n6D8Bg7vRQrgk3Yt30JLY1f6HhomdjEf2JaRroOoyLOOWpBK60oya0SkJakLRl92Dd/iK+3PEEskfjHXwOQXsRgbQigmmhv5otB3QnbjXVzGk0n/Yt0lb/AePhdfgLpsTgQ3Qt9eOfY6raQt1XXgaDJa6xJBqVwJV2ghZVA08qbZJ309S7aJ5+d1Rqqq7xN2Db+ASpa/9C/UXP9zI2DZ3rKIamSvRNlQRTMkNNMhHEZ6jZiXXL0+jQsK19kOaZP+pdLCcplcCVdo7VwNUohGSQ9vHPo568ATCn0jzpVtI+/V2va+H2pXeRsrN9t1jAPhDPiC/D5KvBPOSE8drW/AXNZMM76Exs6/+Gd9gF+HPHRxzLyUrNRqi0o5lDsyOoGnjiM9Tuwbr1GVzjr49u8g5zjb+eoDWbjHeux7bmfnSu6p7HVr2DlJ2v4xaXUX/Bk9Re9iYN8/9KIHM41g2PY/rHHDJfPBvb2gcw1O3t/BhHt5Oy521cE2+mcd6fCVpzsH/4PQh4we/GvO99zPs/itbHTUqqBq60pzcQNJ+EU8oG/ZjKVmPZuwTj4fW4Jt2KZ+RX4h1Vn1i3/AtNb6Zp6l3908FnslF30QukrvkzqWsfwLbhUdyjrqR54i0EHUO6faltw+NoRhvOM37ZelOQv2AKnlGXo3NVk1m+lODmV0hdcz+pa+7HlzsBz4iL8Qy/iKC9CIDUz/5M0JyOa+ItaCkOnGf9gYwlN+B4/RIMtbvR+5oAaDzrj7jHXtvzz6VppK74BeaDn9Bw3qMEskf1rnwSgErgSgd9ndDKUC1J++RnNJz3OJo1K4qRRSjgwXxwBea9S7Dsex+9uxbNaCWQmo/9gzvReRtxj/ta/OLrC08Dli9exTPiIjRbbr+9TSB3LA0X/gtDzS6sGx8nZftLpGx9Fu+whTRPurXTYYb6xnIsuxbhGveNTu/o1KzZBKfcQP2wq9A7y7HsegvLrjdJW/Ub0lb9Bm/hDHwDZmEpfZ+mGT9ESwndm+Adci6uMV/Fsu/9ULIfegHWLf/Cvuwe0Blwj7n6xB9I00j9NHT3qWa04njtKzQu+Bvekvl9Laq4UAlc6aCvU8ra1j2EuexTzAc+wiMuj2JkPeBzYT64DMueJZhLl6L3NhI02/GWnINn2EK8g84CHaS/dyv25fei8zbimnxbbGOMAv3mF9H7mloXou5vgawROM/+M80zfoh181OkbH2WzD3v4C2agWvSt/EOPrt1hIt18z9B03BNvOWExw2mFeGa9C1ck76FoW4vll2Lsex6k9TP/0owJRPXhJva7e+cdx/Oefe1PvYNmEXGuzeR9r8fom+qwJ8l0FIcBC0ONIsj1ClvsrVeodjWPYxtw2O4xn2D5im3k/7OjaQvuQHnmb/BPf4bUSyx2NBpmhazN6uqaozdm7WRKPMZRCKeMWcsugpd0EvdpW+ccN/j49Q7K8h6dha6oB/3qCtpnP+X/gy1HWPlRjIWX4Pe20AwJRPPkAV4hy7EO+iMjsPPAr5QJ9vuxTRNv5vmad/t9PMkJC1Izkvz8JsyqLt8cVxC0HmdpGx/EeumJzE4y/FnCZqm/wDfgNPJ+vcMvCXn0rig6zVdui1nTcNQvQMMFgKZw04cjN9Fxrs3Yz6wvPPD6U1olgyCZjvG+n24xWU0zn8g9IPjayb9vW9hPvgx1Tdu7HDFkCjnQ26uvdM2MlUDVzrQUjLQ1+w+9kQwgKFGEsgSoO9+NsmUrc9CMIAvbyKmQytjdgOGrvko6e/dgmZJp+78J/ANmAn6bk5vg4nGcx8Gg4nUNX9GM5hba+L6pspQ88TIS1vbYxOJ+cAydDV7cJ0bv0WvNHMartNuwTX+eiy7F2P7/CEy3vsmwZQs9L4mmid9u/cH1+kI5Izp+f5GK/Vfeg69sxydpx69uzb011OHzh3+66lH567DO+wCmmb86Nh4eJON5unfx3Lgf5j3f4RHXNb7uDujBdG5akBvbG0KiiaVwJUOgpYMjG2aUCy7F5P+wZ0EUvPxjLwU96grCGSN7PhCvxvrtufwDlmAt3gu9uU/Qd+wn2BGST8H7Cf9/W+jd9VQd9ming8z0xtoPPsvEPST9unvQAui13vIWvMoOr8by773qbv09e5/CGJM567Ftu4RtLQCPMMWxjscMJjwiMvwjLgYy65F2NY+iK9oBoHcsbGNQ6cjaB8A9gEEInypP28iAVt+qG29twk83N9iqvgMfWM5+qYKDM4K9M7D6IJegpYMqm/e1rtjdyNxzkwlYYQ6MY+NAzdWbUUzWPDnTsC68QlsGx7FlzcR96grYMrVQAoAKTsXoXfX4JpwI8HwPCrmQytw93MCT131O8xln9Iw/6+RjxHWG2ic/1d0QR9pq/+Ahg7PiIvx500kbeWvsH3+IM3Tf9A/gUdA53Vi3fxPrBseQ+d1Ejz/vi5vhY8LvRGPuDz2fR7RoNPjLTkHy65FEPD07G5PTUPfcABT+WeYDy7HXPohep+zdbqCQFoBvvxJBIcVEUgrxJ93Wr+ErhK40kHQ4ghPKesGYwqGmp34M4fTcOG/0DVXkbJzESlfvIL945+hrfgV6UPOxS2uwLr5n/izR+MbcDoAgdR8TIdW4R57Xb/FaipfjW3TE7jGX49nVC+Th8FEw7mPYC38N5ZRZ9NoGQqA8eg2bJ8/iHfQXPyFU098nIAPU/lqzAeX4xaXEcgeHXksLXcvNhzA0HAA45EtmI5swFi1BZ3fjWfIeTTNuBv7sCmQAG2zJwvvkAVYtz+P+dDKUIfs8TQNQ91eTOWfYipbjaniMwzO0HIIQWs2nhFfxjP0AnwDZ8f0h1UlcKWDtvOhBI0pGGt34SsIJTDNlhtq+zztFgxV28gofQPTllex7FkCQOO8+1rbvH0DZmM+uLxf28Fta/5CwJaH8/Sf9u1ABjOuiTdjcdhaE6Nzzm8wVawhfel3aJrxo9DkUH4XOr8Lnd8d/usCvwu9pz40kVS46cmy+21qr3y302F0Ok8D+oaDGBoPYGg4iKHhQOhxw0EMjQdDxwwLXfmMwzX2OjzDv4y/YHLfPqfSKe/A2WhGG+Z977cmcJ2nHv3a57Hv+QRz+WfoXaEVJYPWXLwDZtJcNDPUXJQ1skdzzPSHiBK4EOIBYCagAXdJKde22XY7cB0QAD6XUn43moEqsaO1nQ/FlIah8RDuMdd02C+QO5bgiGnUTb4H84H/Yazagltc2rrdO/AMUna+HuoA7cXNErrmKgwNB/HnTey089RUvhpz2SqcZ/wSjNaIj38imtlOwzkP4Vh0Bekf3NFxu8GCZrSiGVNCt3uXnItn6PloKZlkvPlV0j+4g/oL/w16A4aanaR98guMVZs7jLEPmu0E7YMIOIbgLZ5LIH0QwfRiAuHnEqqp5GRlTME7+CzM+z6Aub+DgJeMxddiOLIR0orwDjoTX1FofHog48RTAMRKjxO4EGIuMEJKOUsIMZrQ+pezwtvSgR8Cw6WUfiHE+0KImVLK1f0StdKv2k5oZQzXBv1ZI7p+gcEU6rgcsqDd0y1NKeZDK3GdKIFrGob6fZjK12CsWIupYg3G+n0AuEdeGhqOeFxnom3NAwRsebgiuQsvQv7CqVR//TP03oZwsg4lbIwp3da6nHN+g33ZPdjW3I9mzSL109+jmWx4RlwcSswtSTp9UGgRjQRJCKcyz5AFWPYswXhkE9bN/8J0ZCP+S5+ituDchP33iaQGPh9YBCCl3CGEyBRCpEspGwBv+L80IYQTsAE1UY9WiYm2TSgtS2sFMjsZdXICwfSBBNIHYypbhWviTR22G6q2YS5bhaliDaaKtehdoUWcgimZ+Aqn4x57LXp3Lbb1f4Ogj8ZzHgKDCWipfa/EOfsX/VL7bktLzSOQmhfRa9xjrsFYuZ7UdQ8B4Ck5l8az/ogW4XGU2PEOno+mM2D/4DsY6/fRNP1uzKO/ktB9DZEk8AJgXZvHVeHnGqSUbiHEr4C9gAt4SUq5M3phKrF0rAZeh7F2J5reRCBjcK+O5R04G8vutyHob1eDtux4mfSPQqM7AunFeIvn4iucjq9weujmjTa122BKFmmrfoPO78Y95hqC1ixsa+4naM3F1Y8dpH2i0+Gc81sA/AXTcI++KmFrcUqIlpKJr2g65rJPcQ//Ms1T7yLRG6/60onZejaGm1B+AowEGoCPhBATpZSb2r4gLc2C0dj9jSD9wWDQ43DYYv6+fRHXmM2FAKTqXega90L2cBxZ6Z3ueqI4dWI++u0vkLXvPwSn3Bh6su4AxhW/IFg8m8DFj0N6EQbAQMuAxOPM+x6BtFTM79+LpfSD1qcD5/wGR252rz5iV6Jb7ja49FGMdPG5+iAZz+m2EjV+3ZwfENz6KoYL7sdhsiVsnC0iSeDlhGrcLYqAivD/jwb2tixkLIT4BJhCmzUzAZxOT+8j7YNEuR02EnGNOWgiF3DXVpFSuQNv3gQau4jlhHEWzCd98NmY//sjnIZcvIPnkbHoVjQNaufeTzDo6Nkl6ojr0BUtCK3x6KoGvwvvkPOifnmbLOdKssTZlYSNP2smzJkJTQDNCRNnbq690+cjGfvyPnA5gBBiMlAupWwMbysFRgshWhojpwK7ehWpEn96A0GzHX1TJfqGAwQyu+nAPOGxjDQseBR/zjjS/3sract/grl8NU1n/JJg+sCIDqWl5uHPPw1vyXy8w7/U2h6uKKeqHidwKeUqYJ0QYhXwEHC7EOJ6IcQlUspK4D7gf0KIFcAGKeUn/ROyEguaJQNT5Xp0aPg7u20+EuZU6i98mqA1G+u25/CUnBNqE1YUpU8iagOXUv74uKc2tdn2OPB4NIJS4i9oycB4dDtA32rgYVpqHvUXPYd1w2PhyYRUh56i9JW6E1PplGbJQIeGpjOEbiaJgkDmcJxn/zkqx1IURa2JqXShZSx4IKNE3QmoKAlKJXClUy1jwQPd3YGpKEpcqQSudKqlBu7vxR2YiqLEhkrgSqc0S2j1EFUDV5TEpRK40qlgePmnaIxAURSlf6hRKEqnPEPPR+dtwB/J2oSKosSUSuBKpzRbLq7Jt8c7DEVRuqGaUBRFUZKUSuCKoihJSiVwRVGUJKUSuKIoSpJSCVxRFCVJqQSuKIqSpFQCVxRFSVI6TdPiHYOiKIrSC6oGriiKkqRUAlcURUlSJ10CF0Kotbr6iSrb+FDlHhvJWM4nxVwoQohs4BvAg1LKQLzj6QkhhEVK6Yl3HCeSjGXblWQpc0j+ck+Wsk72ck76GrgQ4jvA80A6EEyGX1EhxDXAi0KIaeHHCRlzMpZtV5KlzCH5yz1ZyjrZyxmSvAYuhPh/wA+BAillU7zjicA0oApYKIRYJ6UMxjug4yVx2XYl4cscTppyT/iyPknKOflq4EKIwjYP/w18DjiEEAOEED8VQlwcp9C6JIQYLoRY2OYpG7AcyAS+FN4n7r/+yVi2XUmWMofkL/dkKetkL+fOJNU4cCHEZcCLwJlSys/Cz90JfB9YDawCbgKeAp6WUjbEK9ZwbDrg18A84AiwHXhJSrlVCGECbgaGA7+TUlYLIXRSyrj8gyRb2XYlmco8HG/SlnsylXUyl3N3kqIG3ubX2w4sAe5rs/nfwFLgESnlw8CtwEWAOaZBds4K5AALgK8B5cBdQogcKaWPUA0gCFwCEI+TO4nLtisJX+Zw0pR7wpf1SVLOXUqKBC6l1IQQ6UAKcClgF0LcFN5WD3xfSrky/Hg14AcGxSveNuzAXCAt3M72LlBH6JceYCuwEhguhLhFCPENIURMT54kLtuuJHyZw0lT7glf1idJOXcpIRN4uMDbPtaFL2n+Ge4Q+SHwiza7+IQQ1wghvi+EeAJwAvtiFzEIIezHPTZIKSuBD4Ffhp8+CPwXGCGEGCyldAFNhH71vwkcklJ6YxxnwpdtV4QQecc91idimXcWK0AylbsQolAIkd/mcUKW9fFxQnKVc6QSKoELIYxCiJ8Ci4QQNwkhRJtteimlL/x3KbBJCNFyOWQCtgHDgA1SyiuklHUxitkUjvm1cA1jYHhTy+Xin4FJQohJUko/cDi8zSKEKCB0Qj0hpZwmpfww1nGGaygJWbbdEUKMBjYLIeaFHxtIsDI/QawJe04fF7tRCPET4HVgYJtNCVXW3cSZFOXcWwmVwAn9MhYA9wJDgEvDNVmtZShSmyFJVwPXCSG+D/wU2AvcIaV8NFbBhi8HHyQ0jvRPhNr6StruI6XcDzwNPBx+vBUoAoJSysPAl6WUD8YrzvBJnXBl2wMZgI7QuUL4Jgxd+P/jXuYnijUZyl0IMYNQB18OsFBKua7N5oQp6+7iDF9hJnQ590XcE3j4VxohhA2YCfwh3EtcBuS13B0lhJgthHihTRNAJqFf+oXAs1LKxlh1krTEDKQCo6SU94R/2RsIddogpQwKIc4UQjwvpXwcqBFC3C+E+IjQpebR8MnlTpA4E6Jsu9Lms7TwA7cDASHE3dD6Wc6IZ5n3ItaEK3dxbLhdS030/6SUtUKIiUKIcS1JUQgxJ87nd0/i1JLh/O6tuA0jFKFbWH8LjCE0ZvQxQjXEPeHLnQXAhVLKu4QQY4HvAB9LKZ8P/8P9AnhPSrkozjGbgQPAd4HbCHXafE7osuxCYLuU8p9CiExCl3bFUsp3EjDOTVLKf8erbLty3Gf5H7BISrlRCPFNIB/4Z/j58wjV/C4Htkgp/xXLMu9DrOullM8lQrl3ct48ClwJnEboxpwpQA2wM7x9AbAjAc7vnsS5xzFreQAACGhJREFUORHP776K552Y3wWagXMI1U5ek1LOarP9YmAzgJRyG/Ctlg1SygpCQ35i7fiYX5dSzgQQQnwgpfyLEGI2oRPmNCnlD9q8tk5KWQtsSeQ441i2XWn7Wb4NPAFMJzTCoUpKWS6EaARWANcBd7e5VI5lmfcp1gQp97bx3wE8R+jHZglwUEo5XwgxhtAPzxQp5d1tXhuv8zuiOBOknKMm5k0oQoiW96wHtkkpfVLKvxK6vLwtvI+d0A0Ai8KP5wohimMda4tuYvYLIe4Ib9sDIENDklxAbfi1xvDz/X6pE404E0UXn+UhQqMGriU0hO3XQoi3gY2AB9gbvrSPWZlHK9Z46iL+Bwg1vV0BXA88CSCl3E7ovKkKvzbe53dEcZ5sYp7A29SOLEC6ECI1/Pge4EdCCLOUspHQXV2ThRDPAjdyrNc75k4Q893hx9cJIS4QodEd8wjHK0M98yrOCHXzWX4M/IrQnX8fA/dJKW8GHgd+FH5tTD9LMsXamW7ivxv4HaEk6BdCjBdCDCB03rjDr02E8zuh4oylfm0DD7eL3UpobOgeKWW9EMIUbuOeTKjQf0CoHS0ohHiFULvsvwm1za4FnpFSvthvQUYn5o8ItbfdQmh0xyNSyudVnD3Ti8/yIiCllL9UsUaml+fNx8BnwPcIXRk/mKDnd8zjjLd+q4ELIeYAbxDqvLmaUEcaQMu44/WELievJjRkEOAtoEaGhh/9CPhSjJN3b2P2Syk/InQ78ewYnNxJEWdP9PKzvAMcCr++ZUx1v0+WlEyxdqYP541bSrmWUD/UrAQ+v2MaZyKIeg1cCJEipXQLIS4HTpdSfj/8/Fbg11L+//bOPWTPOYzjH4RZyWEOQ6Em36ihaGaZDSvkECnJlCSEKAp/mBQbf8gpazmMNmdj5ZjDIudTxh9y+Ip6nVracpjzMX9c9xzmtt3P9jzv3kvXp94/3qf7vvtcz9t7Pb/nd7guL2h+3wvYATiIqF72CrHwc4XtB/sqNXjnmbYfKc/uZIolk2sbffCfZfvh8hx59C2BK7b6nUWsDl9LvLnbE6ewvlCUapxpe7ykq4F9ia0/PwGTgUOBe5sR4rCQxTmLZxcyxZLJNbN/Fs+RyFolcP21UX4nYD7xVWdf4uDCS8RWqQttf9Bcv4jYWXK711G5xizOWTy7kCmWTK5tZPHP4jnSWds58BWVxSYD39m+hyhscyBxUOQj4HhJmzfXXd5c+z38NSc4zGRxzuLZhUyxZHJtI4t/Fs8RzRolcEkHSloIXCVpEnA/MKNZYPga+KC59EZgPHBs8/vORMGYX+HP+hXDQhbnLJ5dyBRLJtc2svhn8cxCzwlccRR1FjCX+KQ8GTje9pvEKvEYYgvPb7YNzAHGSXqC+Fr0cr/k/2/OWTy7kCmWTK5tZPHP4pmJTnPgzdeVi4FlxMGP0bavlDSKmLeaBRxte5mkk4gV5NMV26V2s/2OpAm2XxtcKDmds3h2IVMsmVwz+2fxzMpqR+CStgcWECUxfyDKRp4oabSj0tgLxIGbC//2zIWSjgGeJyoMMszJO4VzFs8uZIolk2sbWfyzeGamyxTK1sCWts+1fQtwJyDgqr9dcwcwVtHIdH9gIVHh7hzbt/bZuQtZnLN4diFTLJlc28jin8UzLV0KvHwOzFQUklmfKIZ0GHCbpLm2F0taTuzJ/J2Y33rS9r2Dku5AFucsnl3IFEsm1zay+GfxTEtP+8AVFb2eJkq9TgeOILo870ls8Zlu+/sBeK4xWZyzeHYhUyyZXNvI4p/FMxu9llgcD+Co+ztb0nfEqamxwJkj9A+QxTmLZxcyxZLJtY0s/lk8U9FrAt8BuLvZDnQD8BowwyO7HVEW5yyeXcgUSybXNrL4Z/FMRa8JfAxRq+AYYJ7tu/qv1HeyOGfx7EKmWDK5tpHFP4tnKnpN4EPElp85tn/uv85AGCKH8xA5PLswRJ5Yhsjj2sYQOfyHyOGZil4XMdfL9pUni3MWzy5kiiWTaxtZ/LN4ZmOddaUviqIo1o5h74lZFEVR9IdK4EVRFEmpBF4URZGUSuBFURRJ6XUbYVGsMyTtDLwFLAbWI9pvXW77qVXcsyMwtktFO0lTgfuAt5uXNgBOtf3e2pkXxWCoEXiRDdueansKcBpwvaQ9VnH9QcCEHp7/bPP8qcDNwLlrrloUg6VG4EVabH8oaRbR0fx0RcfyCcAo4rj2g0SfxV8kfUz0U7wM+Bn4EjhuNYdKtgU+A5A0beV7gU2IetcbNz9n2X6jcZpMjOBn2767n3EXxQpqBF5k53Vg96bDy5Dt/YnkeantpcA84DrbDwFbACc0o/flwCEtz5si6RlJi4FTgJua19vuPRj4tBmtTwe2kTQZ2Mn2AcTof4akTQYReFFUAi+ysynRQ/FHYEtJLwGPEc0EVmYpMFfSs0T38zEt16yYQtmbmKJZsIp7Xwb2k3QDsIvtx4FJwERJzwBPEP9j2/Un1KL4JzWFUmRnH+BNSVOIEe8U279I+rbl2luBw22/K2n26h5s+zlJuzZ9Hf91r+0lkvYkEvoZkiYC3wC32L6iT/EVxX9SI/AiLZLGAecB1wBbAZ80yfsoYANJGxGdXlYMVDYDPpa0OZF0N+rw/K9s/9Z2bzMvPs32k8DZxIfJq8CRktaXNErS9X0Ouyj+pGqhFGlYaRvhxsQi4UW2F0naDFhENM99gJjKWA7cA8wHzif6MR4FvA88SixwTrK9pHn+VP65jXBD4ALbL0q6tOXeE4iuMr8SHxSX2H6+WcScRmx1nGN73iDej6KoBF4URZGUmkIpiqJISiXwoiiKpFQCL4qiSEol8KIoiqRUAi+KokhKJfCiKIqkVAIviqJISiXwoiiKpPwBay8T5g7+zloAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XHnHI2ArtaEC",
        "colab_type": "text"
      },
      "source": [
        "##3. Vendas Tesouro Direto\n",
        "\n",
        "Este conjunto de dados traz o volume de vendas diário do programa Tesouro Direto."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wzHdH5bxoTTQ",
        "colab_type": "text"
      },
      "source": [
        "###3.1 Buscando Dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8wAaC_3Et2n-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "vendas = busca_vendas_tesouro()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aaGprNVXt6rF",
        "colab_type": "code",
        "outputId": "526c3c9f-d4b1-4fcb-c126-d024eb6f6f2e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "vendas.sort_index(inplace=True)\n",
        "vendas"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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></th>\n",
              "      <th></th>\n",
              "      <th>PU</th>\n",
              "      <th>Quantidade</th>\n",
              "      <th>Valor</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tipo Titulo</th>\n",
              "      <th>Vencimento do Titulo</th>\n",
              "      <th>Data Venda</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"10\" valign=\"top\">Tesouro IGPM+ com Juros Semestrais</th>\n",
              "      <th rowspan=\"10\" valign=\"top\">2005-07-01</th>\n",
              "      <th>2002-01-07</th>\n",
              "      <td>1038.150000</td>\n",
              "      <td>7.40</td>\n",
              "      <td>7682.31</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-08</th>\n",
              "      <td>1035.590000</td>\n",
              "      <td>6.00</td>\n",
              "      <td>6213.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-09</th>\n",
              "      <td>1035.400000</td>\n",
              "      <td>0.20</td>\n",
              "      <td>207.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-14</th>\n",
              "      <td>1038.166666</td>\n",
              "      <td>0.60</td>\n",
              "      <td>622.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-15</th>\n",
              "      <td>1038.640000</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1038.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-16</th>\n",
              "      <td>1039.052173</td>\n",
              "      <td>18.40</td>\n",
              "      <td>19118.55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-17</th>\n",
              "      <td>1039.269911</td>\n",
              "      <td>22.60</td>\n",
              "      <td>23487.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-18</th>\n",
              "      <td>1039.259574</td>\n",
              "      <td>9.40</td>\n",
              "      <td>9769.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-21</th>\n",
              "      <td>1039.720000</td>\n",
              "      <td>12.00</td>\n",
              "      <td>12476.64</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-22</th>\n",
              "      <td>1040.189743</td>\n",
              "      <td>7.80</td>\n",
              "      <td>8113.47</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"10\" valign=\"top\">Tesouro Selic</th>\n",
              "      <th rowspan=\"10\" valign=\"top\">2025-03-01</th>\n",
              "      <th>2020-05-07</th>\n",
              "      <td>10597.262817</td>\n",
              "      <td>5544.77</td>\n",
              "      <td>58759384.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>10598.471191</td>\n",
              "      <td>4642.46</td>\n",
              "      <td>49202978.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>10599.681197</td>\n",
              "      <td>4303.73</td>\n",
              "      <td>45618165.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>10600.899691</td>\n",
              "      <td>5355.18</td>\n",
              "      <td>56769726.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>10602.114034</td>\n",
              "      <td>4422.34</td>\n",
              "      <td>46886152.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>10603.334453</td>\n",
              "      <td>4769.10</td>\n",
              "      <td>50568362.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>10604.553721</td>\n",
              "      <td>4353.36</td>\n",
              "      <td>46165439.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>10605.760877</td>\n",
              "      <td>4507.56</td>\n",
              "      <td>47806103.49</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>10606.969027</td>\n",
              "      <td>5349.63</td>\n",
              "      <td>56743359.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>10608.194896</td>\n",
              "      <td>3050.69</td>\n",
              "      <td>32362314.08</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>63020 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                                              PU  ...        Valor\n",
              "Tipo Titulo                        Vencimento do Titulo Data Venda                ...             \n",
              "Tesouro IGPM+ com Juros Semestrais 2005-07-01           2002-01-07   1038.150000  ...      7682.31\n",
              "                                                        2002-01-08   1035.590000  ...      6213.54\n",
              "                                                        2002-01-09   1035.400000  ...       207.08\n",
              "                                                        2002-01-14   1038.166666  ...       622.89\n",
              "                                                        2002-01-15   1038.640000  ...      1038.64\n",
              "                                                        2002-01-16   1039.052173  ...     19118.55\n",
              "                                                        2002-01-17   1039.269911  ...     23487.49\n",
              "                                                        2002-01-18   1039.259574  ...      9769.03\n",
              "                                                        2002-01-21   1039.720000  ...     12476.64\n",
              "                                                        2002-01-22   1040.189743  ...      8113.47\n",
              "...                                                                          ...  ...          ...\n",
              "Tesouro Selic                      2025-03-01           2020-05-07  10597.262817  ...  58759384.94\n",
              "                                                        2020-05-08  10598.471191  ...  49202978.56\n",
              "                                                        2020-05-11  10599.681197  ...  45618165.95\n",
              "                                                        2020-05-12  10600.899691  ...  56769726.00\n",
              "                                                        2020-05-13  10602.114034  ...  46886152.97\n",
              "                                                        2020-05-14  10603.334453  ...  50568362.33\n",
              "                                                        2020-05-15  10604.553721  ...  46165439.98\n",
              "                                                        2020-05-18  10605.760877  ...  47806103.49\n",
              "                                                        2020-05-19  10606.969027  ...  56743359.71\n",
              "                                                        2020-05-20  10608.194896  ...  32362314.08\n",
              "\n",
              "[63020 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DZkHLaBtodA6",
        "colab_type": "text"
      },
      "source": [
        "###3.2 Gráficos"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NnbR_3U_ui3h",
        "colab_type": "code",
        "outputId": "8bfdbf79-8668-40c6-fe97-b4cc816cba4b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        }
      },
      "source": [
        "vendas['Valor'].groupby('Data Venda').sum().plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WvfZik9mxOa-",
        "colab_type": "text"
      },
      "source": [
        "##4. Recompras Tesouro Direto\n",
        "\n",
        "Esse conjunto da dados contém listagem dos títulos que foram entregues pelo investidor antes do vencimento. Estão listados por dia e por título. Frequência: Atualização diária com dados até dois dias antes à data do arquivo."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qpaG-7Ksoi56",
        "colab_type": "text"
      },
      "source": [
        "###4.1 Buscando Dados"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c5H1IsTsxbN1",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "recompras = busca_recompras_tesouro()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "d1k4NoVOxfwd",
        "colab_type": "code",
        "outputId": "236903c0-19a1-46b4-efc2-3b11a4395626",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "recompras.sort_index(inplace=True)\n",
        "recompras"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<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></th>\n",
              "      <th></th>\n",
              "      <th>Quantidade</th>\n",
              "      <th>Valor</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Tipo Titulo</th>\n",
              "      <th>Vencimento do Titulo</th>\n",
              "      <th>Data Resgate</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th rowspan=\"10\" valign=\"top\">Tesouro IGPM+ com Juros Semestrais</th>\n",
              "      <th rowspan=\"9\" valign=\"top\">2005-07-01</th>\n",
              "      <th>2005-01-13</th>\n",
              "      <td>2.00</td>\n",
              "      <td>3545.04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-02-03</th>\n",
              "      <td>1.00</td>\n",
              "      <td>1783.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-03-03</th>\n",
              "      <td>2.00</td>\n",
              "      <td>3595.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-03-10</th>\n",
              "      <td>1.00</td>\n",
              "      <td>1803.81</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-03-24</th>\n",
              "      <td>0.20</td>\n",
              "      <td>364.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-03-31</th>\n",
              "      <td>0.60</td>\n",
              "      <td>1098.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-04-14</th>\n",
              "      <td>3.60</td>\n",
              "      <td>6666.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-04-22</th>\n",
              "      <td>36.00</td>\n",
              "      <td>66912.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-06-02</th>\n",
              "      <td>6.40</td>\n",
              "      <td>11999.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-12-01</th>\n",
              "      <th>2005-01-06</th>\n",
              "      <td>141.20</td>\n",
              "      <td>249321.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th rowspan=\"10\" valign=\"top\">Tesouro Selic</th>\n",
              "      <th rowspan=\"10\" valign=\"top\">2025-03-01</th>\n",
              "      <th>2020-05-07</th>\n",
              "      <td>1875.96</td>\n",
              "      <td>19870459.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>3606.82</td>\n",
              "      <td>38208433.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-11</th>\n",
              "      <td>2565.44</td>\n",
              "      <td>27179823.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-12</th>\n",
              "      <td>2773.17</td>\n",
              "      <td>29383990.44</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-13</th>\n",
              "      <td>2430.07</td>\n",
              "      <td>25751540.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-14</th>\n",
              "      <td>2637.12</td>\n",
              "      <td>27948871.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>2684.45</td>\n",
              "      <td>28453761.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>1762.51</td>\n",
              "      <td>18683812.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>2994.47</td>\n",
              "      <td>31747112.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>1989.45</td>\n",
              "      <td>21094409.64</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>38490 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                                      Quantidade        Valor\n",
              "Tipo Titulo                        Vencimento do Titulo Data Resgate                         \n",
              "Tesouro IGPM+ com Juros Semestrais 2005-07-01           2005-01-13          2.00      3545.04\n",
              "                                                        2005-02-03          1.00      1783.97\n",
              "                                                        2005-03-03          2.00      3595.96\n",
              "                                                        2005-03-10          1.00      1803.81\n",
              "                                                        2005-03-24          0.20       364.14\n",
              "                                                        2005-03-31          0.60      1098.15\n",
              "                                                        2005-04-14          3.60      6666.62\n",
              "                                                        2005-04-22         36.00     66912.84\n",
              "                                                        2005-06-02          6.40     11999.94\n",
              "                                   2005-12-01           2005-01-06        141.20    249321.07\n",
              "...                                                                          ...          ...\n",
              "Tesouro Selic                      2025-03-01           2020-05-07       1875.96  19870459.40\n",
              "                                                        2020-05-08       3606.82  38208433.41\n",
              "                                                        2020-05-11       2565.44  27179823.15\n",
              "                                                        2020-05-12       2773.17  29383990.44\n",
              "                                                        2020-05-13       2430.07  25751540.34\n",
              "                                                        2020-05-14       2637.12  27948871.86\n",
              "                                                        2020-05-15       2684.45  28453761.34\n",
              "                                                        2020-05-18       1762.51  18683812.71\n",
              "                                                        2020-05-19       2994.47  31747112.61\n",
              "                                                        2020-05-20       1989.45  21094409.64\n",
              "\n",
              "[38490 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rRpLchY9E-B3",
        "colab_type": "code",
        "outputId": "9c236356-0408-4d90-e0b6-e6d7f5591ecb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 275
        }
      },
      "source": [
        "recompras['Valor'].groupby('Data Resgate').sum().plot();"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fcgaKryLLI1s",
        "colab_type": "text"
      },
      "source": [
        "###4.2 Recompras diárias Tesouro Selic 2025"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uUuoEmQgxiS9",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "recompras_selic = recompras.loc[('Tesouro Selic', '2025-03-01')]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2jf4dUINCjSX",
        "colab_type": "code",
        "outputId": "6fc991dc-09b8-4fe5-e38c-5571fb1ac22c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        }
      },
      "source": [
        "fig = px.bar(data_frame=recompras_selic,  x=recompras_selic.index, y='Valor', labels={'x':'Data'})\n",
        "fig.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CcAMSj_AMO-W",
        "colab_type": "text"
      },
      "source": [
        "###4.3 Resgastes Tesouro Selic vs Índice Bovespa"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ny5jvgtYExuu",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "ibov = yf.download('^BVSP')['Adj Close'].resample('W').last().pct_change()[1:]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fVokkmByHMl0",
        "colab_type": "code",
        "outputId": "07915628-428d-4cd3-ccef-41b9d54de33f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 760
        }
      },
      "source": [
        "selic_ibov = pd.concat([recompras_selic_semanal['Valor'].pct_change()[1:], ibov], axis=1).dropna()[1:]\n",
        "selic_ibov.columns = ['Recompra(%)', 'IBOV(%)']\n",
        "selic_ibov"
      ],
      "execution_count": 0,
      "outputs": [
        {
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          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Recompra(%)</th>\n",
              "      <th>IBOV(%)</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2019-02-24</th>\n",
              "      <td>0.236251</td>\n",
              "      <td>0.003691</td>\n",
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              "    <tr>\n",
              "      <th>2019-03-03</th>\n",
              "      <td>0.423072</td>\n",
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              "      <th>2019-03-10</th>\n",
              "      <td>-0.219953</td>\n",
              "      <td>0.008044</td>\n",
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              "    <tr>\n",
              "      <th>2019-03-17</th>\n",
              "      <td>1.231367</td>\n",
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              "    <tr>\n",
              "      <th>2019-03-24</th>\n",
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              "      <td>-0.054490</td>\n",
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              "    <tr>\n",
              "      <th>2019-03-31</th>\n",
              "      <td>0.579274</td>\n",
              "      <td>0.017923</td>\n",
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              "    <tr>\n",
              "      <th>2019-04-07</th>\n",
              "      <td>-0.185600</td>\n",
              "      <td>0.017744</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-04-14</th>\n",
              "      <td>0.124599</td>\n",
              "      <td>-0.043591</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-04-21</th>\n",
              "      <td>0.030708</td>\n",
              "      <td>0.018336</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-04-28</th>\n",
              "      <td>0.232518</td>\n",
              "      <td>0.017531</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>2020-03-22</th>\n",
              "      <td>0.848841</td>\n",
              "      <td>-0.188793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-29</th>\n",
              "      <td>-0.552286</td>\n",
              "      <td>0.094828</td>\n",
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              "    <tr>\n",
              "      <th>2020-04-05</th>\n",
              "      <td>-0.503418</td>\n",
              "      <td>-0.052990</td>\n",
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              "    <tr>\n",
              "      <th>2020-04-12</th>\n",
              "      <td>-0.106493</td>\n",
              "      <td>0.117116</td>\n",
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              "    <tr>\n",
              "      <th>2020-04-19</th>\n",
              "      <td>0.079916</td>\n",
              "      <td>0.016838</td>\n",
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              "    <tr>\n",
              "      <th>2020-04-26</th>\n",
              "      <td>-0.088002</td>\n",
              "      <td>-0.046322</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-03</th>\n",
              "      <td>0.263718</td>\n",
              "      <td>0.068697</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-10</th>\n",
              "      <td>-0.048104</td>\n",
              "      <td>-0.003018</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-17</th>\n",
              "      <td>0.095632</td>\n",
              "      <td>-0.033714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-24</th>\n",
              "      <td>-0.484383</td>\n",
              "      <td>0.059518</td>\n",
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              "            Recompra(%)   IBOV(%)\n",
              "Date                             \n",
              "2019-02-24     0.236251  0.003691\n",
              "2019-03-03     0.423072 -0.033529\n",
              "2019-03-10    -0.219953  0.008044\n",
              "2019-03-17     1.231367  0.039553\n",
              "2019-03-24     0.179772 -0.054490\n",
              "2019-03-31     0.579274  0.017923\n",
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              "2019-04-21     0.030708  0.018336\n",
              "2019-04-28     0.232518  0.017531\n",
              "...                 ...       ...\n",
              "2020-03-22     0.848841 -0.188793\n",
              "2020-03-29    -0.552286  0.094828\n",
              "2020-04-05    -0.503418 -0.052990\n",
              "2020-04-12    -0.106493  0.117116\n",
              "2020-04-19     0.079916  0.016838\n",
              "2020-04-26    -0.088002 -0.046322\n",
              "2020-05-03     0.263718  0.068697\n",
              "2020-05-10    -0.048104 -0.003018\n",
              "2020-05-17     0.095632 -0.033714\n",
              "2020-05-24    -0.484383  0.059518\n",
              "\n",
              "[66 rows x 2 columns]"
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          "metadata": {
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          "execution_count": 51
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        "colab": {
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      "source": [
        "fig = go.Figure(data=[\n",
        "    go.Bar(name='Recompras Selic(%)', x=selic_ibov.index,  y=selic_ibov['Recompra(%)']),\n",
        "    go.Bar(name='IBOV(%)', x=selic_ibov.index,  y=selic_ibov['IBOV(%)']),\n",
        "])\n",
        "fig.update_layout(barmode='group')\n",
        "fig.show()"
      ],
      "execution_count": 0,
      "outputs": [
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              "             Recompra(%)   IBOV(%)\n",
              "Recompra(%)     1.000000 -0.309419\n",
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