Acoes.ipynb

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        "<a href=\"https://colab.research.google.com/github/renannevesr/Trader/blob/main/Acoes.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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        "outputId": "38cf5f54-84ce-452e-b39e-9df860e56947"
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      "outputs": [
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          "name": "stdout",
          "text": [
            "Requirement already satisfied: yfinance in /usr/local/lib/python3.7/dist-packages (0.1.70)\n",
            "Requirement already satisfied: requests>=2.26 in /usr/local/lib/python3.7/dist-packages (from yfinance) (2.27.1)\n",
            "Requirement already satisfied: lxml>=4.5.1 in /usr/local/lib/python3.7/dist-packages (from yfinance) (4.8.0)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.21.6)\n",
            "Requirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.10)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2022.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24.0->yfinance) (1.15.0)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2021.10.8)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.0.12)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (1.24.3)\n",
            "Requirement already satisfied: xlrd in /usr/local/lib/python3.7/dist-packages (2.0.1)\n"
          ]
        }
      ],
      "source": [
        "import pandas_datareader.data as web\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "!pip install yfinance\n",
        "import yfinance as yf\n",
        "!pip install --upgrade xlrd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
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        },
        "id": "X1jVubjxYq4f",
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "empresas =pd.read_excel(\"/content/drive/MyDrive/Python/acoes/empresas.xlsx\")\n",
        "empresas"
      ],
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            "text/plain": [
              "  Empresas\n",
              "0    BBAS3\n",
              "1    BBDC4\n",
              "2   BIDI11\n",
              "3    CASH3\n",
              "4    CIEL3\n",
              "5    MGLU3\n",
              "6    ITSA4\n",
              "7    PETR4\n",
              "8    SEER3\n",
              "9    SHOW3"
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    {
      "cell_type": "code",
      "source": [
        "df = []\n",
        "df = pd.DataFrame(df)\n",
        "cota_final = []\n",
        "cota_final = pd.DataFrame(df)\n",
        "df_emp = [(('Empresa'))]\n",
        "df_emp = pd.DataFrame(df_emp, columns=['Empresa'])"
      ],
      "metadata": {
        "id": "r-E08-daZNcK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "for empresa in empresas['Empresas']:\n",
        "    try:\n",
        "        cotacoes = yf.download(f'{empresa}.SA',start=\"2013-01-01\", end=\"2022-03-30\")\n",
        "        df = df.append(cotacoes)\n",
        "        df['Data'] = df.index\n",
        "        print(df.shape)\n",
        "        balanco = pd.read_excel(f'/content/drive/MyDrive/Python/acoes/{empresa}.xls')\n",
        "        datas = balanco.loc[0]\n",
        "        datas = pd.DataFrame(datas)\n",
        "\n",
        "        datas.columns = ['Data']\n",
        "        datas['Data'] = pd.to_datetime(datas['Data'])\n",
        "        df['Data'] = pd.to_datetime(df['Data'])\n",
        "        cota = pd.concat([df, datas]).sort_values(by='Data').drop_duplicates()\n",
        "        nova_cota = cota.assign(Nome=empresa)\n",
        "        cota_final = cota_final.append(nova_cota)\n",
        "    except:\n",
        "        print(f\"Não foi possível localizar os dados da {empresa}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iCv9aaP-ZTV6",
        "outputId": "ed2d837e-b5dd-4e56-fccd-65a160c82faf"
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      "execution_count": null,
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          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n",
            "(2294, 7)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(4589, 7)\n",
            "WARNING *** file size (67762) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(5196, 7)\n",
            "WARNING *** file size (31789) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(5538, 7)\n",
            "WARNING *** file size (18199) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(7832, 7)\n",
            "WARNING *** file size (63974) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(10126, 7)\n",
            "WARNING *** file size (64202) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(12421, 7)\n",
            "WARNING *** file size (64192) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(14715, 7)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(16803, 7)\n",
            "WARNING *** file size (52804) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n",
            "[*********************100%***********************]  1 of 1 completed\n",
            "(19097, 7)\n",
            "WARNING *** file size (64204) not 512 + multiple of sector size (512)\n",
            "WARNING *** OLE2 inconsistency: SSCS size is 0 but SSAT size is non-zero\n"
          ]
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "high = ['High']\n",
        "cota_final = cota_final.drop(cota_final[cota_final['High'].isin(high)].index)"
      ],
      "metadata": {
        "id": "PXhSG9mRf1dx"
      },
      "execution_count": null,
      "outputs": []
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      "source": [
        "cota_final.shape"
      ],
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        "colab": {
          "base_uri": "https://localhost:8080/"
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        "id": "qKT1yNhxf5Uz",
        "outputId": "a93239b4-20e5-4933-f191-0a9eb615b2f0"
      },
      "execution_count": null,
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(98974, 8)"
            ]
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          "metadata": {},
          "execution_count": 98
        }
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    {
      "cell_type": "code",
      "source": [
        "#inicio da limpeza dos dados\n",
        "cota_final.reset_index(inplace=True, drop=False)\n",
        "cota_final.isna().sum()"
      ],
      "metadata": {
        "colab": {
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        "id": "4IH1mBMeHVeo",
        "outputId": "342c5096-50e6-4328-e206-6f144d0cf588"
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              "index          0\n",
              "Open         386\n",
              "High         386\n",
              "Low          386\n",
              "Close        386\n",
              "Adj Close    386\n",
              "Volume       386\n",
              "Data          10\n",
              "Nome           0\n",
              "dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 99
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    {
      "cell_type": "code",
      "source": [
        "\n",
        "data_erradas = cota_final[cota_final['Data'].isnull()].index.tolist()\n",
        "cota_final[cota_final['Data'].isnull()].index.tolist()"
      ],
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      "source": [
        "filtro = cota_final.Data.isnull()\n",
        "cota_final.loc[filtro]"
      ],
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              "                                                  index  Open  High  Low  \\\n",
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              "98973  XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data   NaN   NaN  NaN   \n",
              "\n",
              "       Close  Adj Close  Volume Data    Nome  \n",
              "2336     NaN        NaN     NaN  NaT   BBAS3  \n",
              "6968     NaN        NaN     NaN  NaT   BBDC4  \n",
              "12182    NaN        NaN     NaN  NaT  BIDI11  \n",
              "17729    NaN        NaN     NaN  NaT   CASH3  \n",
              "25604    NaN        NaN     NaN  NaT   CIEL3  \n",
              "35773    NaN        NaN     NaN  NaT   MGLU3  \n",
              "48237    NaN        NaN     NaN  NaT   ITSA4  \n",
              "62995    NaN        NaN     NaN  NaT   PETR4  \n",
              "79833    NaN        NaN     NaN  NaT   SEER3  \n",
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              "      <th>2336</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>BBAS3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6968</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>BBDC4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12182</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>BIDI11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17729</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>CASH3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25604</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>35773</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>MGLU3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48237</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>ITSA4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62995</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>PETR4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>79833</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>SEER3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>98973</th>\n",
              "      <td>XLSWrite 1.34 Copyright(c) 1999,2000 Axolot Data</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaT</td>\n",
              "      <td>SHOW3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a9d859c9-44e4-4b1c-abf9-8c80bd27a446')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a9d859c9-44e4-4b1c-abf9-8c80bd27a446 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-a9d859c9-44e4-4b1c-abf9-8c80bd27a446');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#excluindo as datas erradas\n",
        "cota_final=cota_final.drop(cota_final.index[data_erradas])\n"
      ],
      "metadata": {
        "id": "Ba2A1wDgqmzs"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "del cota_final['index']\n",
        "cota_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "hGKFTqaDe7ZG",
        "outputId": "bf14abd3-047d-4a0b-bf26-6321ad461b2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Open       High        Low      Close  Adj Close      Volume  \\\n",
              "0            NaN        NaN        NaN        NaN        NaN         NaN   \n",
              "1            NaN        NaN        NaN        NaN        NaN         NaN   \n",
              "2            NaN        NaN        NaN        NaN        NaN         NaN   \n",
              "3            NaN        NaN        NaN        NaN        NaN         NaN   \n",
              "4            NaN        NaN        NaN        NaN        NaN         NaN   \n",
              "...          ...        ...        ...        ...        ...         ...   \n",
              "98968   2.600000   2.670000   2.570000   2.640000   2.640000  35332300.0   \n",
              "98969  29.170000  29.170000  29.170000  29.170000  29.170000         0.0   \n",
              "98970  11.900000  12.300000  11.700000  11.740000  11.740000    408200.0   \n",
              "98971   2.930000   2.960000   2.860000   2.930000   2.930000  32154600.0   \n",
              "98972  35.400002  35.560001  34.759998  35.110001  35.110001   9119800.0   \n",
              "\n",
              "            Data   Nome  \n",
              "0     2011-09-30  BBAS3  \n",
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              "3     2012-06-30  BBAS3  \n",
              "4     2012-09-30  BBAS3  \n",
              "...          ...    ...  \n",
              "98968 2022-03-29  SHOW3  \n",
              "98969 2022-03-29  SHOW3  \n",
              "98970 2022-03-29  SHOW3  \n",
              "98971 2022-03-29  SHOW3  \n",
              "98972 2022-03-29  SHOW3  \n",
              "\n",
              "[98964 rows x 8 columns]"
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              "      <th></th>\n",
              "      <th>Open</th>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>2011-12-31</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>2012-06-30</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2012-09-30</td>\n",
              "      <td>BBAS3</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>98968</th>\n",
              "      <td>2.600000</td>\n",
              "      <td>2.670000</td>\n",
              "      <td>2.570000</td>\n",
              "      <td>2.640000</td>\n",
              "      <td>2.640000</td>\n",
              "      <td>35332300.0</td>\n",
              "      <td>2022-03-29</td>\n",
              "      <td>SHOW3</td>\n",
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              "      <th>98969</th>\n",
              "      <td>29.170000</td>\n",
              "      <td>29.170000</td>\n",
              "      <td>29.170000</td>\n",
              "      <td>29.170000</td>\n",
              "      <td>29.170000</td>\n",
              "      <td>0.0</td>\n",
              "      <td>2022-03-29</td>\n",
              "      <td>SHOW3</td>\n",
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              "    <tr>\n",
              "      <th>98970</th>\n",
              "      <td>11.900000</td>\n",
              "      <td>12.300000</td>\n",
              "      <td>11.700000</td>\n",
              "      <td>11.740000</td>\n",
              "      <td>11.740000</td>\n",
              "      <td>408200.0</td>\n",
              "      <td>2022-03-29</td>\n",
              "      <td>SHOW3</td>\n",
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              "    <tr>\n",
              "      <th>98971</th>\n",
              "      <td>2.930000</td>\n",
              "      <td>2.960000</td>\n",
              "      <td>2.860000</td>\n",
              "      <td>2.930000</td>\n",
              "      <td>2.930000</td>\n",
              "      <td>32154600.0</td>\n",
              "      <td>2022-03-29</td>\n",
              "      <td>SHOW3</td>\n",
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              "      <td>35.400002</td>\n",
              "      <td>35.560001</td>\n",
              "      <td>34.759998</td>\n",
              "      <td>35.110001</td>\n",
              "      <td>35.110001</td>\n",
              "      <td>9119800.0</td>\n",
              "      <td>2022-03-29</td>\n",
              "      <td>SHOW3</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>98964 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6f0f5b91-96a1-4763-90ee-9854f4594e41')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6f0f5b91-96a1-4763-90ee-9854f4594e41 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6f0f5b91-96a1-4763-90ee-9854f4594e41');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 103
        }
      ]
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    {
      "cell_type": "code",
      "source": [
        "filtro = cota_final.Data.isnull()\n",
        "cota_final.loc[filtro]"
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    {
      "cell_type": "code",
      "source": [
        "filtro = cota_final.Volume.isnull()\n",
        "cota_final.loc[filtro]"
      ],
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        "colab": {
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        "id": "_dx3NDvtr_35",
        "outputId": "9a3b0b8c-cd5e-4058-fce1-1b01e3b8f605"
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      "execution_count": null,
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              "       Open  High  Low  Close  Adj Close  Volume       Data   Nome\n",
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              "\n",
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              "          document.querySelector('#df-c95bd472-76fe-4ed8-bf68-eccfb08906be button.colab-df-convert');\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c95bd472-76fe-4ed8-bf68-eccfb08906be');\n",
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              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lista_vazias =cota_final[cota_final['Volume'].isnull()].index.tolist()"
      ],
      "metadata": {
        "id": "DEijXxp8jeqW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "colunas_cota_final = cota_final.loc[0]\n",
        "colunas_cota_final = pd.DataFrame(colunas_cota_final)\n",
        "colunas_cota_final['colunas'] = colunas_cota_final.index\n",
        "colunas_cota_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 300
        },
        "id": "-bgb66G2kWRB",
        "outputId": "ffef4515-1524-4b45-eaf1-f2f62a584609"
      },
      "execution_count": null,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                             0    colunas\n",
              "Open                       NaN       Open\n",
              "High                       NaN       High\n",
              "Low                        NaN        Low\n",
              "Close                      NaN      Close\n",
              "Adj Close                  NaN  Adj Close\n",
              "Volume                     NaN     Volume\n",
              "Data       2011-09-30 00:00:00       Data\n",
              "Nome                     BBAS3       Nome"
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              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-fb9f1209-42e6-408b-abbd-715662d16c19');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "          docLink.innerHTML = docLinkHtml;\n",
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              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del colunas_cota_final[0]\n",
        "colunas_cota_final = colunas_cota_final.drop(colunas_cota_final.index[[6,7]])\n",
        "colunas_cota_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "78CA_lmIlIHr",
        "outputId": "8486d854-2227-437d-832e-dc5c85d57a0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             colunas\n",
              "Open            Open\n",
              "High            High\n",
              "Low              Low\n",
              "Close          Close\n",
              "Adj Close  Adj Close\n",
              "Volume        Volume"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a6dd435b-997d-45a6-8be5-c3dfe66309e0\">\n",
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              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\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>colunas</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Open</th>\n",
              "      <td>Open</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>High</th>\n",
              "      <td>High</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Low</th>\n",
              "      <td>Low</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Close</th>\n",
              "      <td>Close</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Adj Close</th>\n",
              "      <td>Adj Close</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Volume</th>\n",
              "      <td>Volume</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
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              "\n",
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              "      fill: #FFFFFF;\n",
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              "  </style>\n",
              "\n",
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              "          const element = document.querySelector('#df-a6dd435b-997d-45a6-8be5-c3dfe66309e0');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "correcao_linhas = cota_final[cota_final['Open'].isnull()].index.tolist()\n",
        "correcao_linhas"
      ],
      "metadata": {
        "id": "fhoq3qgm9KZF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#cota_final.loc[2337]\n",
        "cota_final.reset_index(drop=True, inplace=True)\n",
        "cota_final.loc[2336]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lQTG1PMzRsBe",
        "outputId": "ddcb85b0-3cd0-4def-898e-7f27f004895b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Open                         NaN\n",
              "High                         NaN\n",
              "Low                          NaN\n",
              "Close                        NaN\n",
              "Adj Close                    NaN\n",
              "Volume                       NaN\n",
              "Data         2011-09-30 00:00:00\n",
              "Nome                       BBDC4\n",
              "Name: 2336, dtype: object"
            ]
          },
          "metadata": {},
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cota_final.loc[2335:2337]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "VLDqwiZeX-jH",
        "outputId": "d38c5fd8-7c65-447f-b653-e63a67a9010f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "           Open       High        Low      Close  Adj Close     Volume  \\\n",
              "2335  35.400002  35.560001  34.759998  35.110001  35.110001  9119800.0   \n",
              "2336        NaN        NaN        NaN        NaN        NaN        NaN   \n",
              "2337        NaN        NaN        NaN        NaN        NaN        NaN   \n",
              "\n",
              "           Data   Nome  \n",
              "2335 2022-03-29  BBAS3  \n",
              "2336 2011-09-30  BBDC4  \n",
              "2337 2011-12-31  BBDC4  "
            ],
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              "\n",
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              "\n",
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              "          const element = document.querySelector('#df-18603e54-bc0d-442c-b501-884c41dd95cc');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 111
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for linha in correcao_linhas:\n",
        "  try:\n",
        "    if cota_final.loc[linha,'Nome'] == cota_final.loc[linha-1,'Nome']:\n",
        "        for coluna in colunas_cota_final['colunas']:\n",
        "            cota_final.loc[linha,f'{coluna}'] = cota_final.loc[linha-1,f'{coluna}']\n",
        "    else:\n",
        "      print(\"else = \", linha)\n",
        "      raise Exception('Empresas diferentes')\n",
        "  except:\n",
        "    cota_final = cota_final.drop(linha,axis=0)\n",
        "    #print(\"except = \", linha)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "P2v1kNVe9j7K",
        "outputId": "0bc1204e-9355-43c2-b52a-45fcacacb0c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "except =  0\n",
            "except =  1\n",
            "except =  2\n",
            "except =  3\n",
            "except =  4\n",
            "except =  5\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#idx = 97180\n",
        "#cota_final.loc[idx,'Volume'] = cota_final.loc[idx-1,'Volume']\n",
        "#print(cota_final.loc[idx])\n",
        "#print(cota_final.loc[idx-1])"
      ],
      "metadata": {
        "id": "jY6VPTDJfk0Q"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "cota_final.loc[22880:22910]\n",
        "#22848"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "lhcQyci_s1fB",
        "outputId": "d8095caf-8904-4a75-df48-a37b572fc69a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Open       High        Low      Close  Adj Close      Volume  \\\n",
              "22880   7.530000   7.810000   7.500000   7.750000   7.085480  16082700.0   \n",
              "22881  25.469570  26.033056  25.401953  25.912848  22.432842  15452510.0   \n",
              "22882  45.240002  45.560001  44.830002  45.000000  38.515919   6863500.0   \n",
              "22883  16.770067  17.919159  16.753414  17.679348  17.503912   5188701.0   \n",
              "22884   7.730000   7.890000   7.680000   7.780000   7.112908  10408000.0   \n",
              "22885  25.927874  26.318558  25.777611  26.123215  22.614952  26255439.0   \n",
              "22886  17.819239  18.548660  16.853334  17.086485  16.916931   5753147.0   \n",
              "22887  44.970001  45.180000  44.270000  44.380001  37.985249  14788500.0   \n",
              "22888   7.780000   7.790000   7.550000   7.580000   6.930057  16910500.0   \n",
              "22889  44.400002  45.360001  43.900002  45.000000  38.515919  15239700.0   \n",
              "22890  26.145756  26.746805  25.890308  26.746805  23.154808  27560617.0   \n",
              "22891   7.600000   7.660000   7.520000   7.650000   6.994054  11643000.0   \n",
              "22892  17.059839  17.282995  16.350401  16.620186  16.455257   4169695.0   \n",
              "22893   7.660000   7.800000   7.580000   7.600000   6.948341  12464900.0   \n",
              "22894  16.653494  17.073160  16.440329  16.686800  16.521215   2300718.0   \n",
              "22895  45.330002  45.700001  44.580002  44.910000  38.438885  24953800.0   \n",
              "22896  26.746805  27.009768  26.243425  26.296019  22.764561  28942595.0   \n",
              "22897  46.000000  46.549999  45.500000  46.060001  39.423191  47116600.0   \n",
              "22898   7.600000   7.690000   7.510000   7.650000   6.994054  13506100.0   \n",
              "22899  16.786720  17.153097  16.570227  16.570227  16.405796    936440.0   \n",
              "22900  25.492111  25.597296  25.251690  25.386927  22.652952  17146208.0   \n",
              "22901  46.299999  46.750000  45.770000  46.400002  39.714191  15751100.0   \n",
              "22902  25.401953  25.642374  25.184072  25.567242  22.813837  16341086.0   \n",
              "22903  16.673477  16.959917  16.570227  16.959917  16.791616    780016.0   \n",
              "22904   7.680000   7.730000   7.600000   7.700000   7.039767   9424400.0   \n",
              "22905  46.500000  47.669998  46.439999  47.400002  40.570095  17097300.0   \n",
              "22906  25.567242  26.296019  25.492111  26.296019  23.464132  38381381.0   \n",
              "22907   7.750000   7.990000   7.710000   7.890000   7.213476  22873000.0   \n",
              "22908  16.953257  17.099808  16.463642  16.503613  16.339842   4510765.0   \n",
              "22909  16.916618  16.986563  16.656824  16.693462  16.527809   2079143.0   \n",
              "22910  26.108189  26.897070  25.995493  26.521412  23.665253  36496419.0   \n",
              "\n",
              "            Data   Nome  \n",
              "22880 2019-10-11  CIEL3  \n",
              "22881 2019-10-14  CIEL3  \n",
              "22882 2019-10-14  CIEL3  \n",
              "22883 2019-10-14  CIEL3  \n",
              "22884 2019-10-14  CIEL3  \n",
              "22885 2019-10-15  CIEL3  \n",
              "22886 2019-10-15  CIEL3  \n",
              "22887 2019-10-15  CIEL3  \n",
              "22888 2019-10-15  CIEL3  \n",
              "22889 2019-10-16  CIEL3  \n",
              "22890 2019-10-16  CIEL3  \n",
              "22891 2019-10-16  CIEL3  \n",
              "22892 2019-10-16  CIEL3  \n",
              "22893 2019-10-17  CIEL3  \n",
              "22894 2019-10-17  CIEL3  \n",
              "22895 2019-10-17  CIEL3  \n",
              "22896 2019-10-17  CIEL3  \n",
              "22897 2019-10-18  CIEL3  \n",
              "22898 2019-10-18  CIEL3  \n",
              "22899 2019-10-18  CIEL3  \n",
              "22900 2019-10-18  CIEL3  \n",
              "22901 2019-10-21  CIEL3  \n",
              "22902 2019-10-21  CIEL3  \n",
              "22903 2019-10-21  CIEL3  \n",
              "22904 2019-10-21  CIEL3  \n",
              "22905 2019-10-22  CIEL3  \n",
              "22906 2019-10-22  CIEL3  \n",
              "22907 2019-10-22  CIEL3  \n",
              "22908 2019-10-22  CIEL3  \n",
              "22909 2019-10-23  CIEL3  \n",
              "22910 2019-10-23  CIEL3  "
            ],
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              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>Data</th>\n",
              "      <th>Nome</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>22880</th>\n",
              "      <td>7.530000</td>\n",
              "      <td>7.810000</td>\n",
              "      <td>7.500000</td>\n",
              "      <td>7.750000</td>\n",
              "      <td>7.085480</td>\n",
              "      <td>16082700.0</td>\n",
              "      <td>2019-10-11</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22881</th>\n",
              "      <td>25.469570</td>\n",
              "      <td>26.033056</td>\n",
              "      <td>25.401953</td>\n",
              "      <td>25.912848</td>\n",
              "      <td>22.432842</td>\n",
              "      <td>15452510.0</td>\n",
              "      <td>2019-10-14</td>\n",
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              "    <tr>\n",
              "      <th>22882</th>\n",
              "      <td>45.240002</td>\n",
              "      <td>45.560001</td>\n",
              "      <td>44.830002</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>38.515919</td>\n",
              "      <td>6863500.0</td>\n",
              "      <td>2019-10-14</td>\n",
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              "    <tr>\n",
              "      <th>22883</th>\n",
              "      <td>16.770067</td>\n",
              "      <td>17.919159</td>\n",
              "      <td>16.753414</td>\n",
              "      <td>17.679348</td>\n",
              "      <td>17.503912</td>\n",
              "      <td>5188701.0</td>\n",
              "      <td>2019-10-14</td>\n",
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              "      <th>22884</th>\n",
              "      <td>7.730000</td>\n",
              "      <td>7.890000</td>\n",
              "      <td>7.680000</td>\n",
              "      <td>7.780000</td>\n",
              "      <td>7.112908</td>\n",
              "      <td>10408000.0</td>\n",
              "      <td>2019-10-14</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22885</th>\n",
              "      <td>25.927874</td>\n",
              "      <td>26.318558</td>\n",
              "      <td>25.777611</td>\n",
              "      <td>26.123215</td>\n",
              "      <td>22.614952</td>\n",
              "      <td>26255439.0</td>\n",
              "      <td>2019-10-15</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22886</th>\n",
              "      <td>17.819239</td>\n",
              "      <td>18.548660</td>\n",
              "      <td>16.853334</td>\n",
              "      <td>17.086485</td>\n",
              "      <td>16.916931</td>\n",
              "      <td>5753147.0</td>\n",
              "      <td>2019-10-15</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22887</th>\n",
              "      <td>44.970001</td>\n",
              "      <td>45.180000</td>\n",
              "      <td>44.270000</td>\n",
              "      <td>44.380001</td>\n",
              "      <td>37.985249</td>\n",
              "      <td>14788500.0</td>\n",
              "      <td>2019-10-15</td>\n",
              "      <td>CIEL3</td>\n",
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              "      <th>22888</th>\n",
              "      <td>7.780000</td>\n",
              "      <td>7.790000</td>\n",
              "      <td>7.550000</td>\n",
              "      <td>7.580000</td>\n",
              "      <td>6.930057</td>\n",
              "      <td>16910500.0</td>\n",
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              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22889</th>\n",
              "      <td>44.400002</td>\n",
              "      <td>45.360001</td>\n",
              "      <td>43.900002</td>\n",
              "      <td>45.000000</td>\n",
              "      <td>38.515919</td>\n",
              "      <td>15239700.0</td>\n",
              "      <td>2019-10-16</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22890</th>\n",
              "      <td>26.145756</td>\n",
              "      <td>26.746805</td>\n",
              "      <td>25.890308</td>\n",
              "      <td>26.746805</td>\n",
              "      <td>23.154808</td>\n",
              "      <td>27560617.0</td>\n",
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              "      <th>22891</th>\n",
              "      <td>7.600000</td>\n",
              "      <td>7.660000</td>\n",
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              "      <td>7.650000</td>\n",
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              "      <th>22892</th>\n",
              "      <td>17.059839</td>\n",
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              "      <td>16.620186</td>\n",
              "      <td>16.455257</td>\n",
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              "      <th>22893</th>\n",
              "      <td>7.660000</td>\n",
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              "      <td>6.948341</td>\n",
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              "      <th>22894</th>\n",
              "      <td>16.653494</td>\n",
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              "      <td>16.686800</td>\n",
              "      <td>16.521215</td>\n",
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              "      <th>22895</th>\n",
              "      <td>45.330002</td>\n",
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              "      <td>44.580002</td>\n",
              "      <td>44.910000</td>\n",
              "      <td>38.438885</td>\n",
              "      <td>24953800.0</td>\n",
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              "      <th>22896</th>\n",
              "      <td>26.746805</td>\n",
              "      <td>27.009768</td>\n",
              "      <td>26.243425</td>\n",
              "      <td>26.296019</td>\n",
              "      <td>22.764561</td>\n",
              "      <td>28942595.0</td>\n",
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              "      <th>22897</th>\n",
              "      <td>46.000000</td>\n",
              "      <td>46.549999</td>\n",
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              "      <td>46.060001</td>\n",
              "      <td>39.423191</td>\n",
              "      <td>47116600.0</td>\n",
              "      <td>2019-10-18</td>\n",
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              "    <tr>\n",
              "      <th>22898</th>\n",
              "      <td>7.600000</td>\n",
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              "      <td>7.510000</td>\n",
              "      <td>7.650000</td>\n",
              "      <td>6.994054</td>\n",
              "      <td>13506100.0</td>\n",
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              "    <tr>\n",
              "      <th>22899</th>\n",
              "      <td>16.786720</td>\n",
              "      <td>17.153097</td>\n",
              "      <td>16.570227</td>\n",
              "      <td>16.570227</td>\n",
              "      <td>16.405796</td>\n",
              "      <td>936440.0</td>\n",
              "      <td>2019-10-18</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22900</th>\n",
              "      <td>25.492111</td>\n",
              "      <td>25.597296</td>\n",
              "      <td>25.251690</td>\n",
              "      <td>25.386927</td>\n",
              "      <td>22.652952</td>\n",
              "      <td>17146208.0</td>\n",
              "      <td>2019-10-18</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22901</th>\n",
              "      <td>46.299999</td>\n",
              "      <td>46.750000</td>\n",
              "      <td>45.770000</td>\n",
              "      <td>46.400002</td>\n",
              "      <td>39.714191</td>\n",
              "      <td>15751100.0</td>\n",
              "      <td>2019-10-21</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22902</th>\n",
              "      <td>25.401953</td>\n",
              "      <td>25.642374</td>\n",
              "      <td>25.184072</td>\n",
              "      <td>25.567242</td>\n",
              "      <td>22.813837</td>\n",
              "      <td>16341086.0</td>\n",
              "      <td>2019-10-21</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22903</th>\n",
              "      <td>16.673477</td>\n",
              "      <td>16.959917</td>\n",
              "      <td>16.570227</td>\n",
              "      <td>16.959917</td>\n",
              "      <td>16.791616</td>\n",
              "      <td>780016.0</td>\n",
              "      <td>2019-10-21</td>\n",
              "      <td>CIEL3</td>\n",
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              "    <tr>\n",
              "      <th>22904</th>\n",
              "      <td>7.680000</td>\n",
              "      <td>7.730000</td>\n",
              "      <td>7.600000</td>\n",
              "      <td>7.700000</td>\n",
              "      <td>7.039767</td>\n",
              "      <td>9424400.0</td>\n",
              "      <td>2019-10-21</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22905</th>\n",
              "      <td>46.500000</td>\n",
              "      <td>47.669998</td>\n",
              "      <td>46.439999</td>\n",
              "      <td>47.400002</td>\n",
              "      <td>40.570095</td>\n",
              "      <td>17097300.0</td>\n",
              "      <td>2019-10-22</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22906</th>\n",
              "      <td>25.567242</td>\n",
              "      <td>26.296019</td>\n",
              "      <td>25.492111</td>\n",
              "      <td>26.296019</td>\n",
              "      <td>23.464132</td>\n",
              "      <td>38381381.0</td>\n",
              "      <td>2019-10-22</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22907</th>\n",
              "      <td>7.750000</td>\n",
              "      <td>7.990000</td>\n",
              "      <td>7.710000</td>\n",
              "      <td>7.890000</td>\n",
              "      <td>7.213476</td>\n",
              "      <td>22873000.0</td>\n",
              "      <td>2019-10-22</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22908</th>\n",
              "      <td>16.953257</td>\n",
              "      <td>17.099808</td>\n",
              "      <td>16.463642</td>\n",
              "      <td>16.503613</td>\n",
              "      <td>16.339842</td>\n",
              "      <td>4510765.0</td>\n",
              "      <td>2019-10-22</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22909</th>\n",
              "      <td>16.916618</td>\n",
              "      <td>16.986563</td>\n",
              "      <td>16.656824</td>\n",
              "      <td>16.693462</td>\n",
              "      <td>16.527809</td>\n",
              "      <td>2079143.0</td>\n",
              "      <td>2019-10-23</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22910</th>\n",
              "      <td>26.108189</td>\n",
              "      <td>26.897070</td>\n",
              "      <td>25.995493</td>\n",
              "      <td>26.521412</td>\n",
              "      <td>23.665253</td>\n",
              "      <td>36496419.0</td>\n",
              "      <td>2019-10-23</td>\n",
              "      <td>CIEL3</td>\n",
              "    </tr>\n",
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              "        \n",
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              "          document.querySelector('#df-518fb958-d5de-4f50-8314-e70ceb093c38 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-518fb958-d5de-4f50-8314-e70ceb093c38');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "colunas_cota_final"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "uFWPHiAkvMfD",
        "outputId": "c66bd8f8-5b1a-4ae4-882b-178f65646475"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             colunas\n",
              "Open            Open\n",
              "High            High\n",
              "Low              Low\n",
              "Close          Close\n",
              "Adj Close  Adj Close\n",
              "Volume        Volume"
            ],
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              "      <th>colunas</th>\n",
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              "  <tbody>\n",
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              "      <th>Open</th>\n",
              "      <td>Open</td>\n",
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              "      <th>Adj Close</th>\n",
              "      <td>Adj Close</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Volume</th>\n",
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              "\n",
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              "        const buttonEl =\n",
              "          document.querySelector('#df-88279cd3-d996-43a4-8df2-0edce1d949f0 button.colab-df-convert');\n",
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              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-88279cd3-d996-43a4-8df2-0edce1d949f0');\n",
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              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "  "
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          "metadata": {},
          "execution_count": 118
        }
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    }
  ]
}