_ComparacaoCarteiras.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "_ComparacaoCarteiras.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNVEOMVGVWBZk3FHK+HobSZ",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/raulc27/python_testes/blob/master/_ComparacaoCarteiras.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uC9caen1wZPj",
        "outputId": "7e2136e9-6e91-4d8c-91ea-1769958aa913"
      },
      "source": [
        "!pip install yfinance"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting yfinance\n",
            "  Downloading yfinance-0.1.63.tar.gz (26 kB)\n",
            "Requirement already satisfied: pandas>=0.24 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.1.5)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.19.5)\n",
            "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.7/dist-packages (from yfinance) (2.23.0)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.9)\n",
            "Collecting lxml>=4.5.1\n",
            "  Downloading lxml-4.6.3-cp37-cp37m-manylinux2014_x86_64.whl (6.3 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.3 MB 8.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24->yfinance) (2018.9)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24->yfinance) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24->yfinance) (1.15.0)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.20->yfinance) (2021.5.30)\n",
            "Building wheels for collected packages: yfinance\n",
            "  Building wheel for yfinance (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for yfinance: filename=yfinance-0.1.63-py2.py3-none-any.whl size=23918 sha256=30a56c4eeafa4d0528ec3ec551569d5b6a8d22a9c652dacf4ffa4f38c619b365\n",
            "  Stored in directory: /root/.cache/pip/wheels/fe/87/8b/7ec24486e001d3926537f5f7801f57a74d181be25b11157983\n",
            "Successfully built yfinance\n",
            "Installing collected packages: lxml, yfinance\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "Successfully installed lxml-4.6.3 yfinance-0.1.63\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8GQ66S9awyFY"
      },
      "source": [
        "import yfinance as yf\n",
        "import pandas as pd\n",
        "import numpy as np"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TJLpqYyFw6EN"
      },
      "source": [
        "ativos=[\n",
        "        'PETR4.SA',\n",
        "        'VALE3.SA',\n",
        "        'WEGE3.SA',\n",
        "        'RADL3.SA',\n",
        "        'OIBR3.SA',\n",
        "        'KNRI11.SA',\n",
        "        'SMAL11.SA',\n",
        "        'AAPL34.SA',\n",
        "        'IVVB11.SA',\n",
        "        'ETH-USD',\n",
        "        'USDBRL=X'\n",
        "]"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7__RknIjxbsi"
      },
      "source": [
        "inicio = '2020-05-01'\n",
        "fim = '2021-08-15'"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-RLKTHBOxklh",
        "outputId": "113d460f-c528-45c1-875c-57d1919a6233"
      },
      "source": [
        "precos = pd.DataFrame()\n",
        "\n",
        "for i in ativos:\n",
        "  precos[i] = yf.download(i, start=inicio, end=fim)['Adj Close']"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PW7_RAh0x_CM"
      },
      "source": [
        "precos['ETH-BRL'] = precos['ETH-USD']*precos['USDBRL=X']"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lbr1tnLbyMwQ"
      },
      "source": [
        "precos = precos.drop(columns=['ETH-USD'])"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 494
        },
        "id": "hJNoftftyVdn",
        "outputId": "9dcce629-0349-4162-c613-a83bdf6dbdd5"
      },
      "source": [
        "normalizado = precos/precos.iloc[0]\n",
        "normalizado.plot(figsize=(8,8))"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f20c45cff90>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HeZZek-cyvi4"
      },
      "source": [
        "compras = {\n",
        "   'PETR4.SA':1000,\n",
        "        'VALE3.SA':700,\n",
        "        'WEGE3.SA':1500,\n",
        "        'RADL3.SA':700,\n",
        "        'OIBR3.SA':200,\n",
        "        'KNRI11.SA':700,\n",
        "        'SMAL11.SA':1500,\n",
        "        'AAPL34.SA':2000,\n",
        "        'IVVB11.SA':1500,\n",
        "        'ETH-USD':200,\n",
        "\n",
        "}"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LSMBh58HzJ1n"
      },
      "source": [
        "compras_df = pd.Series(data=compras, index=list(compras.keys()))"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2BFme6m6zUIO",
        "outputId": "bd583838-924d-4003-d6b1-a49b4314d66a"
      },
      "source": [
        "sum(compras.values())"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "10000"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0ESD-1mhzbJM"
      },
      "source": [
        "primeiro = precos.iloc[0]"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZcHcd5gPzgQ1"
      },
      "source": [
        "qtd_acoes = compras_df/primeiro"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IqjCPFI_ztOK"
      },
      "source": [
        "PL = precos*qtd_acoes"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "xOkQWt6tz0y2",
        "outputId": "0be6922e-2a5c-4a02-bf38-a104bb541f8f"
      },
      "source": [
        "PL.head(3)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
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              "      <th>KNRI11.SA</th>\n",
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              "      <th>RADL3.SA</th>\n",
              "      <th>SMAL11.SA</th>\n",
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              "      <th>VALE3.SA</th>\n",
              "      <th>WEGE3.SA</th>\n",
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              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "      <td>1000.000000</td>\n",
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              "      <td>700.000000</td>\n",
              "      <td>1500.000000</td>\n",
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              "    <tr>\n",
              "      <th>2020-05-05</th>\n",
              "      <td>2059.369090</td>\n",
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              "      <td>696.335118</td>\n",
              "      <td>1468.750176</td>\n",
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              "    <tr>\n",
              "      <th>2020-05-06</th>\n",
              "      <td>2137.167589</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>706.373761</td>\n",
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              "              AAPL34.SA  ETH-BRL  ETH-USD  ...  USDBRL=X    VALE3.SA     WEGE3.SA\n",
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              "2020-05-04  2000.000000      NaN      NaN  ...       NaN  700.000000  1500.000000\n",
              "2020-05-05  2059.369090      NaN      NaN  ...       NaN  696.335118  1468.750176\n",
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              "\n",
              "[3 rows x 12 columns]"
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          "metadata": {},
          "execution_count": 21
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      "cell_type": "code",
      "metadata": {
        "id": "QLZLVKip0A99"
      },
      "source": [
        "PL['PL Total']=PL.iloc[:].sum(axis=1)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
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        "outputId": "62f8df9c-f09c-4695-eed3-4d4f0d776a5e"
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      "source": [
        "PL.head()"
      ],
      "execution_count": 23,
      "outputs": [
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              "      <th></th>\n",
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              "      <td>1000.000000</td>\n",
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              "      <td>700.000000</td>\n",
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              "    <tr>\n",
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              "      <td>9926.561519</td>\n",
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              "    <tr>\n",
              "      <th>2020-05-07</th>\n",
              "      <td>2199.999886</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1622.340455</td>\n",
              "      <td>716.112560</td>\n",
              "      <td>197.058826</td>\n",
              "      <td>1003.452454</td>\n",
              "      <td>694.175587</td>\n",
              "      <td>1431.655459</td>\n",
              "      <td>NaN</td>\n",
              "      <td>733.780947</td>\n",
              "      <td>1471.762093</td>\n",
              "      <td>10070.338267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>2220.108426</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1602.393646</td>\n",
              "      <td>727.301819</td>\n",
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              "      <td>700.803383</td>\n",
              "      <td>1433.359785</td>\n",
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              "      <td>1439.759181</td>\n",
              "      <td>10168.356020</td>\n",
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            "text/plain": [
              "              AAPL34.SA  ETH-BRL  ...     WEGE3.SA      PL Total\n",
              "Date                              ...                           \n",
              "2020-05-04  2000.000000      NaN  ...  1500.000000   9800.000000\n",
              "2020-05-05  2059.369090      NaN  ...  1468.750176   9868.558335\n",
              "2020-05-06  2137.167589      NaN  ...  1461.973107   9926.561519\n",
              "2020-05-07  2199.999886      NaN  ...  1471.762093  10070.338267\n",
              "2020-05-08  2220.108426      NaN  ...  1439.759181  10168.356020\n",
              "\n",
              "[5 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tk-4CoHo0Uey",
        "outputId": "0b7ea608-aa50-4756-c879-558af50076b5"
      },
      "source": [
        "ibov = yf.download('^BVSP', start = inicio, end = fim)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RSytBiKL0rpC"
      },
      "source": [
        "ibov.rename(columns={'Adj Close':'IBOV'},inplace=True)"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xoWTc2_700S5"
      },
      "source": [
        "ibov = ibov.drop(ibov.columns[[0,1,2,3,5]], axis=1)"
      ],
      "execution_count": 27,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PAZl-ODK0eg7"
      },
      "source": [
        "ibov.index = pd.to_datetime(ibov.index)"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "12pTRiyb1EgO"
      },
      "source": [
        "PL.index = pd.to_datetime(PL.index)"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1jHmuAm01Oar"
      },
      "source": [
        "novo_df = pd.merge(ibov, PL, how = 'inner', on='Date')"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
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        "id": "__xxKmds1WBD",
        "outputId": "79c92e5d-4df1-4233-b8a5-2ef5238a0cd3"
      },
      "source": [
        "novo_df.head()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <td>1000.000000</td>\n",
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              "      <td>1462.333842</td>\n",
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              "      <td>706.373761</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>10070.338267</td>\n",
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              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>80263.0</td>\n",
              "      <td>2220.108426</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1602.393646</td>\n",
              "      <td>727.301819</td>\n",
              "      <td>202.941174</td>\n",
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              "      <td>700.803383</td>\n",
              "      <td>1433.359785</td>\n",
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              "      <td>1439.759181</td>\n",
              "      <td>10168.356020</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               IBOV    AAPL34.SA  ...     WEGE3.SA      PL Total\n",
              "Date                              ...                           \n",
              "2020-05-04  78876.0  2000.000000  ...  1500.000000   9800.000000\n",
              "2020-05-05  79471.0  2059.369090  ...  1468.750176   9868.558335\n",
              "2020-05-06  79064.0  2137.167589  ...  1461.973107   9926.561519\n",
              "2020-05-07  78119.0  2199.999886  ...  1471.762093  10070.338267\n",
              "2020-05-08  80263.0  2220.108426  ...  1439.759181  10168.356020\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yUeQOnbt1xkN"
      },
      "source": [
        "PL_normalizado = novo_df/novo_df.iloc[0]"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "OtMS-kbj12Zp",
        "outputId": "28e04c8c-5ce6-42c7-f437-42c0f2b07625"
      },
      "source": [
        "PL_normalizado.head()"
      ],
      "execution_count": 34,
      "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>IBOV</th>\n",
              "      <th>AAPL34.SA</th>\n",
              "      <th>ETH-BRL</th>\n",
              "      <th>ETH-USD</th>\n",
              "      <th>IVVB11.SA</th>\n",
              "      <th>KNRI11.SA</th>\n",
              "      <th>OIBR3.SA</th>\n",
              "      <th>PETR4.SA</th>\n",
              "      <th>RADL3.SA</th>\n",
              "      <th>SMAL11.SA</th>\n",
              "      <th>USDBRL=X</th>\n",
              "      <th>VALE3.SA</th>\n",
              "      <th>WEGE3.SA</th>\n",
              "      <th>PL Total</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></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>2020-05-04</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-05</th>\n",
              "      <td>1.007543</td>\n",
              "      <td>1.029685</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.017967</td>\n",
              "      <td>1.003836</td>\n",
              "      <td>1.029412</td>\n",
              "      <td>1.032221</td>\n",
              "      <td>0.995696</td>\n",
              "      <td>0.986252</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.994764</td>\n",
              "      <td>0.979167</td>\n",
              "      <td>1.006996</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-06</th>\n",
              "      <td>1.002383</td>\n",
              "      <td>1.068584</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.032210</td>\n",
              "      <td>1.024616</td>\n",
              "      <td>1.029412</td>\n",
              "      <td>0.994246</td>\n",
              "      <td>0.990054</td>\n",
              "      <td>0.974889</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.009105</td>\n",
              "      <td>0.974649</td>\n",
              "      <td>1.012914</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-07</th>\n",
              "      <td>0.990403</td>\n",
              "      <td>1.100000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.081560</td>\n",
              "      <td>1.023018</td>\n",
              "      <td>0.985294</td>\n",
              "      <td>1.003452</td>\n",
              "      <td>0.991679</td>\n",
              "      <td>0.954437</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.048258</td>\n",
              "      <td>0.981175</td>\n",
              "      <td>1.027586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-08</th>\n",
              "      <td>1.017585</td>\n",
              "      <td>1.110054</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.068262</td>\n",
              "      <td>1.039003</td>\n",
              "      <td>1.014706</td>\n",
              "      <td>1.063291</td>\n",
              "      <td>1.001148</td>\n",
              "      <td>0.955573</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.111996</td>\n",
              "      <td>0.959839</td>\n",
              "      <td>1.037587</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                IBOV  AAPL34.SA  ETH-BRL  ...  VALE3.SA  WEGE3.SA  PL Total\n",
              "Date                                      ...                              \n",
              "2020-05-04  1.000000   1.000000      NaN  ...  1.000000  1.000000  1.000000\n",
              "2020-05-05  1.007543   1.029685      NaN  ...  0.994764  0.979167  1.006996\n",
              "2020-05-06  1.002383   1.068584      NaN  ...  1.009105  0.974649  1.012914\n",
              "2020-05-07  0.990403   1.100000      NaN  ...  1.048258  0.981175  1.027586\n",
              "2020-05-08  1.017585   1.110054      NaN  ...  1.111996  0.959839  1.037587\n",
              "\n",
              "[5 rows x 14 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 588
        },
        "id": "A6S7W8MD15AC",
        "outputId": "2494d24f-878a-4231-ac49-7f6bef6aae16"
      },
      "source": [
        "PL_normalizado[['IBOV','PL Total']].plot(figsize=(10,10))"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f20c2ea9850>"
            ]
          },
          "metadata": {},
          "execution_count": 35
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}