Ações_Analises7.ipynb

{
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  "metadata": {
    "colab": {
      "name": "Ações_Analises7.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyPTvfN5pS5Zmgh1aDOXUdSd",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/fonsecajr/Projects/blob/master/A%C3%A7%C3%B5es_Analises7.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J2x_Fx-eRNxS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 70
        },
        "outputId": "b1bb6a33-67c7-4c1a-99ba-0e48168ab417"
      },
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib; matplotlib.rcParams['figure.figsize'] = (22,8)\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns; sns.set()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "doiStOijTsyN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "outputId": "5232865c-3ff7-4306-c1ed-c05a238ac57a"
      },
      "source": [
        "!pip install alpha_vantage"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: alpha_vantage in /usr/local/lib/python3.6/dist-packages (2.2.0)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.6/dist-packages (from alpha_vantage) (3.6.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.6/dist-packages (from alpha_vantage) (2.23.0)\n",
            "Requirement already satisfied: multidict<5.0,>=4.5 in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (4.7.6)\n",
            "Requirement already satisfied: idna-ssl>=1.0; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (1.1.0)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (19.3.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.5; python_version < \"3.7\" in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (3.6.6)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (1.4.2)\n",
            "Requirement already satisfied: async-timeout<4.0,>=3.0 in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (3.0.1)\n",
            "Requirement already satisfied: chardet<4.0,>=2.0 in /usr/local/lib/python3.6/dist-packages (from aiohttp->alpha_vantage) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->alpha_vantage) (2.9)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests->alpha_vantage) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests->alpha_vantage) (2020.4.5.1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zSb1-GNsUznY",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from alpha_vantage.timeseries import TimeSeries"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ILYv2TkST_9d",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#https://www.alphavantage.co/support/#api-key"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xUC4JCsZVhsJ",
        "colab_type": "code",
        "colab": {},
        "cellView": "both"
      },
      "source": [
        "#@title\n",
        "ALPHAVANTAGE_API_KEY ='**hiden**'"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Lmj9l2OIXO1I",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "ts = TimeSeries(key=ALPHAVANTAGE_API_KEY, output_format='pandas')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tv-iyfoiXYjN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 180
        },
        "outputId": "df9c5ff7-0272-4ec7-f928-f5e93924e4a8"
      },
      "source": [
        "ts.get_symbol_search('bov')"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(                                1. symbol  ... 9. matchScore\n",
              " date                                       ...              \n",
              " 1970-01-01 00:00:00.000000000  BOVA11.SAO  ...        0.7500\n",
              " 1970-01-01 00:00:00.000000001  BOVV11.SAO  ...        0.6667\n",
              " 1970-01-01 00:00:00.000000002     BOV.FRK  ...        0.5000\n",
              " 1970-01-01 00:00:00.000000003  BOVB11.SAO  ...        0.5000\n",
              " 1970-01-01 00:00:00.000000004   S3609.MDR  ...        0.5000\n",
              " 1970-01-01 00:00:00.000000005     BOV.STG  ...        0.2222\n",
              " \n",
              " [6 rows x 9 columns], None)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NjD1FTRVXi0O",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "dados, meta_dados = ts.get_daily(symbol='bova11.sao', outputsize='full')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WQpTerNPcYqC",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 420
        },
        "outputId": "c05d63b6-e3dd-4eb7-d2c0-dc97cf875749"
      },
      "source": [
        "dados"
      ],
      "execution_count": 57,
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\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>1. open</th>\n",
              "      <th>2. high</th>\n",
              "      <th>3. low</th>\n",
              "      <th>4. close</th>\n",
              "      <th>5. volume</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>78.59</td>\n",
              "      <td>80.30</td>\n",
              "      <td>78.46</td>\n",
              "      <td>79.97</td>\n",
              "      <td>12578810.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-20</th>\n",
              "      <td>78.31</td>\n",
              "      <td>79.27</td>\n",
              "      <td>77.85</td>\n",
              "      <td>78.32</td>\n",
              "      <td>13277450.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-19</th>\n",
              "      <td>78.34</td>\n",
              "      <td>79.18</td>\n",
              "      <td>77.62</td>\n",
              "      <td>77.84</td>\n",
              "      <td>13781890.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-18</th>\n",
              "      <td>77.24</td>\n",
              "      <td>78.49</td>\n",
              "      <td>76.91</td>\n",
              "      <td>78.35</td>\n",
              "      <td>13748530.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-15</th>\n",
              "      <td>75.70</td>\n",
              "      <td>76.66</td>\n",
              "      <td>74.48</td>\n",
              "      <td>74.56</td>\n",
              "      <td>13103190.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008-12-08</th>\n",
              "      <td>37.35</td>\n",
              "      <td>38.46</td>\n",
              "      <td>36.95</td>\n",
              "      <td>38.46</td>\n",
              "      <td>103100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008-12-05</th>\n",
              "      <td>34.51</td>\n",
              "      <td>35.35</td>\n",
              "      <td>34.11</td>\n",
              "      <td>35.35</td>\n",
              "      <td>193700.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008-12-04</th>\n",
              "      <td>35.80</td>\n",
              "      <td>36.00</td>\n",
              "      <td>35.15</td>\n",
              "      <td>35.70</td>\n",
              "      <td>128400.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008-12-03</th>\n",
              "      <td>34.73</td>\n",
              "      <td>35.40</td>\n",
              "      <td>33.90</td>\n",
              "      <td>35.31</td>\n",
              "      <td>330100.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2008-12-02</th>\n",
              "      <td>35.11</td>\n",
              "      <td>35.81</td>\n",
              "      <td>34.91</td>\n",
              "      <td>35.39</td>\n",
              "      <td>759900.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2840 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "            1. open  2. high  3. low  4. close   5. volume\n",
              "date                                                      \n",
              "2020-05-21    78.59    80.30   78.46     79.97  12578810.0\n",
              "2020-05-20    78.31    79.27   77.85     78.32  13277450.0\n",
              "2020-05-19    78.34    79.18   77.62     77.84  13781890.0\n",
              "2020-05-18    77.24    78.49   76.91     78.35  13748530.0\n",
              "2020-05-15    75.70    76.66   74.48     74.56  13103190.0\n",
              "...             ...      ...     ...       ...         ...\n",
              "2008-12-08    37.35    38.46   36.95     38.46    103100.0\n",
              "2008-12-05    34.51    35.35   34.11     35.35    193700.0\n",
              "2008-12-04    35.80    36.00   35.15     35.70    128400.0\n",
              "2008-12-03    34.73    35.40   33.90     35.31    330100.0\n",
              "2008-12-02    35.11    35.81   34.91     35.39    759900.0\n",
              "\n",
              "[2840 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 57
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JkEzUaY3cbh7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 98
        },
        "outputId": "d365f1a5-e2e1-4074-8f53-f297a7622b4a"
      },
      "source": [
        "meta_dados"
      ],
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'1. Information': 'Daily Prices (open, high, low, close) and Volumes',\n",
              " '2. Symbol': 'bova11.sao',\n",
              " '3. Last Refreshed': '2020-05-21',\n",
              " '4. Output Size': 'Full size',\n",
              " '5. Time Zone': 'US/Eastern'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1nNtIIYXchLu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 347
        },
        "outputId": "94c59a31-03c3-4e6f-f5f9-b4dc219305b9"
      },
      "source": [
        "dados['4. close'].plot(figsize=(22,8))"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f768fcc02e8>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        },
        {
          "output_type": "display_data",
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\n",
            "text/plain": [
              "<Figure size 1584x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}