StockAnalysis.ipynb

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            "Collecting pandas_ta\n",
            "  Downloading pandas_ta-0.3.14b.tar.gz (115 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.1/115.1 kB\u001b[0m \u001b[31m1.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from pandas_ta) (1.5.3)\n",
            "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->pandas_ta) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->pandas_ta) (2023.4)\n",
            "Requirement already satisfied: numpy>=1.21.0 in /usr/local/lib/python3.10/dist-packages (from pandas->pandas_ta) (1.25.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->pandas_ta) (1.16.0)\n",
            "Building wheels for collected packages: pandas_ta\n",
            "  Building wheel for pandas_ta (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pandas_ta: filename=pandas_ta-0.3.14b0-py3-none-any.whl size=218907 sha256=a6eb3f2cb147a28bf761ea7d03975bda629c55c32dca667775e685fe225b862e\n",
            "  Stored in directory: /root/.cache/pip/wheels/69/00/ac/f7fa862c34b0e2ef320175100c233377b4c558944f12474cf0\n",
            "Successfully built pandas_ta\n",
            "Installing collected packages: pandas_ta\n",
            "Successfully installed pandas_ta-0.3.14b0\n"
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    {
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      "execution_count": null,
      "metadata": {
        "id": "aX_a1FBou2Ek"
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      "source": [
        "import yfinance as yf\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "# import seaborn as sns\n",
        "# import datetime\n",
        "# import plotly.graph_objects as go\n",
        "import pandas_ta as ta"
      ]
    },
    {
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            "\r[*********************100%%**********************]  1 of 1 completed\n"
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2004-08-19    2.490664    2.591785    2.390042    2.499133    2.499133   \n",
              "2004-08-20    2.515820    2.716817    2.503118    2.697639    2.697639   \n",
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              "2004-08-24    2.770615    2.779581    2.579581    2.611960    2.611960   \n",
              "2004-08-25    2.614201    2.689918    2.587302    2.640104    2.640104   \n",
              "...                ...         ...         ...         ...         ...   \n",
              "2024-03-04  136.539993  136.630005  132.860001  134.199997  134.199997   \n",
              "2024-03-05  132.740005  134.020004  131.550003  133.779999  133.779999   \n",
              "2024-03-06  134.240005  134.740005  131.949997  132.559998  132.559998   \n",
              "2024-03-07  133.889999  135.820007  132.660004  135.240005  135.240005   \n",
              "2024-03-08  135.035004  138.985001  134.800003  136.289993  136.289993   \n",
              "\n",
              "               Volume  \n",
              "Date                   \n",
              "2004-08-19  897427216  \n",
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              "2004-08-23  366857939  \n",
              "2004-08-24  306396159  \n",
              "2004-08-25  184645512  \n",
              "...               ...  \n",
              "2024-03-04   43571500  \n",
              "2024-03-05   28447600  \n",
              "2024-03-06   23175200  \n",
              "2024-03-07   24107300  \n",
              "2024-03-08   26472400  \n",
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              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 4922,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2004-08-19 00:00:00\",\n        \"max\": \"2024-03-08 00:00:00\",\n        \"num_unique_values\": 4922,\n        \"samples\": [\n          \"2006-02-10 00:00:00\",\n          \"2024-03-05 00:00:00\",\n          \"2010-10-14 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 39.99498834098069,\n        \"min\": 2.470489978790283,\n        \"max\": 154.00999450683594,\n        \"num_unique_values\": 4770,\n        \"samples\": [\n          12.85880184173584,\n          21.32706069946289,\n          27.523500442504883\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"High\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 40.44490745652211,\n        \"min\": 2.5340020656585693,\n        \"max\": 155.1999969482422,\n        \"num_unique_values\": 4773,\n        \"samples\": [\n          3.4483249187469482,\n          12.413471221923828,\n          130.72999572753906\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 39.592206814646836,\n        \"min\": 2.3900420665740967,\n        \"max\": 152.9199981689453,\n        \"num_unique_values\": 4806,\n        \"samples\": [\n          11.472000122070312,\n          38.849998474121094,\n          16.739505767822266\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 40.02494022431995,\n        \"min\": 2.490912914276123,\n        \"max\": 154.83999633789062,\n        \"num_unique_values\": 4827,\n        \"samples\": [\n          11.646098136901855,\n          21.97538185119629,\n          14.303635597229004\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Adj Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 40.02494022431995,\n        \"min\": 2.490912914276123,\n        \"max\": 154.83999633789062,\n        \"num_unique_values\": 4827,\n        \"samples\": [\n          11.646098136901855,\n          21.97538185119629,\n          14.303635597229004\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 150648552,\n        \"min\": 158434,\n        \"max\": 1650832619,\n        \"num_unique_values\": 4811,\n        \"samples\": [\n          112785168,\n          42590000,\n          241915372\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "\n",
        "data = yf.download(tickers = 'GOOG')\n",
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3O3fIrVCu2En"
      },
      "outputs": [],
      "source": [
        "# fig = go.Figure(data=[go.Candlestick(\n",
        "#                 open=data['Open'],\n",
        "#                 high=data['High'],\n",
        "#                 low=data['Low'],\n",
        "#                 close=data['Close'])])\n",
        "\n",
        "# fig.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 694
        },
        "id": "BodCJAzQu2En",
        "outputId": "d70c325e-915f-4896-f3fe-068db4b6fcd7"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7ba63b83bca0>]"
            ]
          },
          "metadata": {},
          "execution_count": 5
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.figure(figsize=(16,8))\n",
        "plt.plot(data[\"Adj Close\"], color = 'black', label = 'Price')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "nbmWrvabu2Eo",
        "outputId": "59d44dd8-85e1-4a00-96e8-b4058e0a2d92"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2004-08-19    2.490664    2.591785    2.390042    2.499133    2.499133   \n",
              "2004-08-20    2.515820    2.716817    2.503118    2.697639    2.697639   \n",
              "2004-08-23    2.758411    2.826406    2.716070    2.724787    2.724787   \n",
              "2004-08-24    2.770615    2.779581    2.579581    2.611960    2.611960   \n",
              "2004-08-25    2.614201    2.689918    2.587302    2.640104    2.640104   \n",
              "...                ...         ...         ...         ...         ...   \n",
              "2024-03-04  136.539993  136.630005  132.860001  134.199997  134.199997   \n",
              "2024-03-05  132.740005  134.020004  131.550003  133.779999  133.779999   \n",
              "2024-03-06  134.240005  134.740005  131.949997  132.559998  132.559998   \n",
              "2024-03-07  133.889999  135.820007  132.660004  135.240005  135.240005   \n",
              "2024-03-08  135.035004  138.985001  134.800003  136.289993  136.289993   \n",
              "\n",
              "               Volume  \n",
              "Date                   \n",
              "2004-08-19  897427216  \n",
              "2004-08-20  458857488  \n",
              "2004-08-23  366857939  \n",
              "2004-08-24  306396159  \n",
              "2004-08-25  184645512  \n",
              "...               ...  \n",
              "2024-03-04   43571500  \n",
              "2024-03-05   28447600  \n",
              "2024-03-06   23175200  \n",
              "2024-03-07   24107300  \n",
              "2024-03-08   26472400  \n",
              "\n",
              "[4922 rows x 6 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-c3968d20-174f-4f63-898a-0e9502f4b503\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
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              "        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>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>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",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2004-08-19</th>\n",
              "      <td>2.490664</td>\n",
              "      <td>2.591785</td>\n",
              "      <td>2.390042</td>\n",
              "      <td>2.499133</td>\n",
              "      <td>2.499133</td>\n",
              "      <td>897427216</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-20</th>\n",
              "      <td>2.515820</td>\n",
              "      <td>2.716817</td>\n",
              "      <td>2.503118</td>\n",
              "      <td>2.697639</td>\n",
              "      <td>2.697639</td>\n",
              "      <td>458857488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-23</th>\n",
              "      <td>2.758411</td>\n",
              "      <td>2.826406</td>\n",
              "      <td>2.716070</td>\n",
              "      <td>2.724787</td>\n",
              "      <td>2.724787</td>\n",
              "      <td>366857939</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-24</th>\n",
              "      <td>2.770615</td>\n",
              "      <td>2.779581</td>\n",
              "      <td>2.579581</td>\n",
              "      <td>2.611960</td>\n",
              "      <td>2.611960</td>\n",
              "      <td>306396159</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-08-25</th>\n",
              "      <td>2.614201</td>\n",
              "      <td>2.689918</td>\n",
              "      <td>2.587302</td>\n",
              "      <td>2.640104</td>\n",
              "      <td>2.640104</td>\n",
              "      <td>184645512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-03-04</th>\n",
              "      <td>136.539993</td>\n",
              "      <td>136.630005</td>\n",
              "      <td>132.860001</td>\n",
              "      <td>134.199997</td>\n",
              "      <td>134.199997</td>\n",
              "      <td>43571500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-03-05</th>\n",
              "      <td>132.740005</td>\n",
              "      <td>134.020004</td>\n",
              "      <td>131.550003</td>\n",
              "      <td>133.779999</td>\n",
              "      <td>133.779999</td>\n",
              "      <td>28447600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-03-06</th>\n",
              "      <td>134.240005</td>\n",
              "      <td>134.740005</td>\n",
              "      <td>131.949997</td>\n",
              "      <td>132.559998</td>\n",
              "      <td>132.559998</td>\n",
              "      <td>23175200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-03-07</th>\n",
              "      <td>133.889999</td>\n",
              "      <td>135.820007</td>\n",
              "      <td>132.660004</td>\n",
              "      <td>135.240005</td>\n",
              "      <td>135.240005</td>\n",
              "      <td>24107300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-03-08</th>\n",
              "      <td>135.035004</td>\n",
              "      <td>138.985001</td>\n",
              "      <td>134.800003</td>\n",
              "      <td>136.289993</td>\n",
              "      <td>136.289993</td>\n",
              "      <td>26472400</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>4922 rows × 6 columns</p>\n",
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              "  @keyframes spin {\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
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              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "summary": "{\n  \"name\": \"data\",\n  \"rows\": 4922,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2004-08-19 00:00:00\",\n        \"max\": \"2024-03-08 00:00:00\",\n        \"num_unique_values\": 4922,\n        \"samples\": [\n          \"2006-02-10 00:00:00\",\n          \"2024-03-05 00:00:00\",\n          \"2010-10-14 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 39.99498834098069,\n        \"min\": 2.470489978790283,\n        \"max\": 154.00999450683594,\n        \"num_unique_values\": 4770,\n        \"samples\": [\n          12.85880184173584,\n          21.32706069946289,\n          27.523500442504883\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"High\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 40.44490745652211,\n        \"min\": 2.5340020656585693,\n        \"max\": 155.1999969482422,\n        \"num_unique_values\": 4773,\n        \"samples\": [\n          3.4483249187469482,\n          12.413471221923828,\n          130.72999572753906\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 39.592206814646836,\n        \"min\": 2.3900420665740967,\n        \"max\": 152.9199981689453,\n        \"num_unique_values\": 4806,\n        \"samples\": [\n          11.472000122070312,\n          38.849998474121094,\n          16.739505767822266\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 40.02494022431995,\n        \"min\": 2.490912914276123,\n        \"max\": 154.83999633789062,\n        \"num_unique_values\": 4827,\n        \"samples\": [\n          11.646098136901855,\n          21.97538185119629,\n          14.303635597229004\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Adj Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 40.02494022431995,\n        \"min\": 2.490912914276123,\n        \"max\": 154.83999633789062,\n        \"num_unique_values\": 4827,\n        \"samples\": [\n          11.646098136901855,\n          21.97538185119629,\n          14.303635597229004\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 150648552,\n        \"min\": 158434,\n        \"max\": 1650832619,\n        \"num_unique_values\": 4811,\n        \"samples\": [\n          112785168,\n          42590000,\n          241915372\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 676
        },
        "id": "BVTTxPhzu2Eo",
        "outputId": "22e55f45-9a33-4a07-9f58-ca7b2f451405"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ],
      "source": [
        "data['RSI']=ta.rsi(data.Close, length=15)\n",
        "data['EMAF']=ta.ema(data.Close, length=20)\n",
        "data['EMAM']=ta.ema(data.Close, length=100)\n",
        "data['EMAS']=ta.ema(data.Close, length=150)\n",
        "\n",
        "data['Target'] = data['Adj Close']-data.Open\n",
        "data['Target'] = data['Target'].shift(-1)\n",
        "\n",
        "data['TargetClass'] = [1 if data.Target[i]>0 else 0 for i in range(len(data))]\n",
        "\n",
        "data['TargetNextClose'] = data['Adj Close'].shift(-1)\n",
        "\n",
        "data.dropna(inplace=True)\n",
        "data.reset_index(inplace = True)\n",
        "plt.figure(figsize=(16,8))\n",
        "# plt.plot(data[\"Adj Close\"], color = 'black', label = 'Price')\n",
        "# plt.plot(data[\"RSI\"], color = 'black', label = 'Price')\n",
        "plt.plot(data[\"EMAF\"], color = 'black', label = 'Price')\n",
        "plt.plot(data[\"EMAM\"], color = 'green', label = 'Price')\n",
        "plt.plot(data[\"EMAS\"], color = 'blue', label = 'Price')\n",
        "\n",
        "plt.plot(data[\"Adj Close\"], color = 'black', label = 'Price')\n",
        "data.drop(['Volume', 'Close', 'Date'], axis=1, inplace=True)\n",
        "data_set = data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wsSDI55wu2Eo"
      },
      "outputs": [],
      "source": [
        "target_col = \"TargetNextClose\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VQWEFoxIu2Eo",
        "outputId": "2e3f5165-fc97-4354-8b72-6b3f8ba211c1"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(4772, 10)\n",
            "4772\n",
            "[[3.32815299e-06 0.00000000e+00 5.53468672e-05 ... 4.57107723e-01\n",
            "  0.00000000e+00 0.00000000e+00]\n",
            " [4.57914321e-04 1.02466749e-04 2.61658127e-04 ... 4.59194782e-01\n",
            "  0.00000000e+00 3.59411194e-04]\n",
            " [6.21095830e-04 7.53595387e-04 5.55173777e-04 ... 4.57055107e-01\n",
            "  0.00000000e+00 5.29997062e-05]\n",
            " ...\n",
            " [8.57799882e-01 8.59466015e-01 8.56090028e-01 ... 3.41348654e-01\n",
            "  0.00000000e+00 8.51837555e-01]\n",
            " [8.67828104e-01 8.64243384e-01 8.58783669e-01 ... 5.54715067e-01\n",
            "  1.00000000e+00 8.69659662e-01]\n",
            " [8.65488145e-01 8.71409438e-01 8.63565002e-01 ... 5.48024232e-01\n",
            "  1.00000000e+00 8.76642103e-01]]\n"
          ]
        }
      ],
      "source": [
        "from sklearn.preprocessing import MinMaxScaler\n",
        "sc_data = MinMaxScaler(feature_range=(0,1))\n",
        "sc_response = MinMaxScaler(feature_range=(0,1))\n",
        "\n",
        "response_scaled = sc_response.fit_transform(data_set[[target_col]])\n",
        "# print(response_scaled)\n",
        "# print(data_set.loc[:, data_set.columns != target_col])\n",
        "# print(response_scaled)\n",
        "data_set_scaled = sc_data.fit_transform(data_set.loc[:, data_set.columns != target_col])\n",
        "print(data_set_scaled.shape)\n",
        "# print(data_set_scaled)\n",
        "print(len(data_set_scaled))\n",
        "data_set_scaled_new = []\n",
        "for i in range(len(data_set_scaled)):\n",
        "    data_set_scaled_new.append([])\n",
        "    # print(response_scaled[i][0])\n",
        "\n",
        "    # print(data_set_scaled[i])\n",
        "    data_set_scaled_new[i] = np.append(data_set_scaled[i],response_scaled[i])\n",
        "    # print(data_set_scaled_new[i])\n",
        "    # print(\"#\"*80)\n",
        "\n",
        "data_set_scaled_new = np.asarray(data_set_scaled_new)\n",
        "print(data_set_scaled_new)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# multiple feature from data provided to the model\n",
        "X = []\n",
        "#print(data_set_scaled[0].size)\n",
        "#data_set_scaled=data_set.values\n",
        "backcandles = 30\n",
        "print(data_set_scaled_new.shape[0])\n",
        "for j in range(8):#data_set_scaled_new[0].size):#2 columns are target not X\n",
        "    X.append([])\n",
        "    for i in range(backcandles, data_set_scaled_new.shape[0]):#backcandles+2\n",
        "        X[j].append(data_set_scaled_new[i-backcandles:i, j])\n",
        "\n",
        "#move axis from 0 to position 2\n",
        "print(X)\n",
        "X=np.moveaxis(X, [0], [2])\n",
        "print(X)\n",
        "#Erase first elements of y because of backcandles to match X length\n",
        "#del(yi[0:backcandles])\n",
        "#X, yi = np.array(X), np.array(yi)\n",
        "# Choose -1 for last column, classification else -2...\n",
        "X, yi =np.array(X), np.array(data_set_scaled_new[backcandles:,-1])\n",
        "print(yi.shape)\n",
        "y=np.reshape(yi,(len(yi),1))\n",
        "#y=sc.fit_transform(yi)\n",
        "#X_train = np.reshape(X_train, (X_train.shape[0], X_train.shape[1], 1))\n",
        "print(X)\n",
        "print(X.shape)\n",
        "print(y)\n",
        "print(y.shape)"
      ],
      "metadata": {
        "id": "si_7zdlju8Ym",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ece7a66e-e770-415f-9c5c-9f44d60143b5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "4772\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "IOPub data rate exceeded.\n",
            "The notebook server will temporarily stop sending output\n",
            "to the client in order to avoid crashing it.\n",
            "To change this limit, set the config variable\n",
            "`--NotebookApp.iopub_data_rate_limit`.\n",
            "\n",
            "Current values:\n",
            "NotebookApp.iopub_data_rate_limit=1000000.0 (bytes/sec)\n",
            "NotebookApp.rate_limit_window=3.0 (secs)\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# split data into train test sets\n",
        "splitlimit = int(len(X)*0.8)\n",
        "print(splitlimit)\n",
        "X_train, X_test = X[:splitlimit], X[splitlimit:]\n",
        "y_train, y_test = y[:splitlimit], y[splitlimit:]\n",
        "print(X_train.shape)\n",
        "print(X_test.shape)\n",
        "print(y_train.shape)\n",
        "print(y_test.shape)\n",
        "print(y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JZMb3Ng8fG4z",
        "outputId": "c9c64bcd-20cd-4d58-bf57-accf3ad83f8f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "3793\n",
            "(3793, 30, 8)\n",
            "(949, 30, 8)\n",
            "(3793, 1)\n",
            "(949, 1)\n",
            "[[0.00807776]\n",
            " [0.0077465 ]\n",
            " [0.00804132]\n",
            " ...\n",
            " [0.44137506]\n",
            " [0.44542822]\n",
            " [0.4463925 ]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from keras.models import Sequential\n",
        "from keras.layers import LSTM\n",
        "from keras.layers import Dropout\n",
        "from keras.layers import Dense\n",
        "from keras.layers import TimeDistributed\n",
        "\n",
        "import tensorflow as tf\n",
        "import keras\n",
        "from keras import optimizers\n",
        "from keras.callbacks import History\n",
        "from keras.models import Model\n",
        "from keras.layers import Dense, Dropout, LSTM, Input, Activation, concatenate\n",
        "import numpy as np\n",
        "#tf.random.set_seed(20)\n",
        "np.random.seed(10)\n",
        "\n",
        "lstm_input = Input(shape=(backcandles, 8), name='lstm_input')\n",
        "inputs = LSTM(150, name='first_layer')(lstm_input)\n",
        "inputs = Dense(1, name='dense_layer')(inputs)\n",
        "output = Activation('linear', name='output')(inputs)\n",
        "model = Model(inputs=lstm_input, outputs=output)\n",
        "adam = optimizers.Adam()\n",
        "model.compile(optimizer=adam, loss='mse')\n",
        "model.fit(x=X_train, y=y_train, batch_size=15, epochs=30, shuffle=True, validation_split = 0.1)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8lHd0jVlfMwY",
        "outputId": "c4c2a1c7-29f7-49e2-9e2d-d0f7f13ba4c1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/30\n",
            "228/228 [==============================] - 11s 40ms/step - loss: 7.8170e-04 - val_loss: 2.0408e-04\n",
            "Epoch 2/30\n",
            "228/228 [==============================] - 7s 31ms/step - loss: 2.9996e-05 - val_loss: 1.9305e-04\n",
            "Epoch 3/30\n",
            "228/228 [==============================] - 9s 38ms/step - loss: 2.8404e-05 - val_loss: 1.5730e-04\n",
            "Epoch 4/30\n",
            "228/228 [==============================] - 9s 39ms/step - loss: 2.2781e-05 - val_loss: 1.7164e-04\n",
            "Epoch 5/30\n",
            "228/228 [==============================] - 7s 31ms/step - loss: 2.4865e-05 - val_loss: 1.9418e-04\n",
            "Epoch 6/30\n",
            "228/228 [==============================] - 8s 36ms/step - loss: 2.3897e-05 - val_loss: 1.7115e-04\n",
            "Epoch 7/30\n",
            "228/228 [==============================] - 8s 35ms/step - loss: 2.6283e-05 - val_loss: 1.6806e-04\n",
            "Epoch 8/30\n",
            "228/228 [==============================] - 8s 34ms/step - loss: 2.2812e-05 - val_loss: 2.4721e-04\n",
            "Epoch 9/30\n",
            "228/228 [==============================] - 8s 37ms/step - loss: 2.5372e-05 - val_loss: 1.7857e-04\n",
            "Epoch 10/30\n",
            "228/228 [==============================] - 7s 33ms/step - loss: 2.6012e-05 - val_loss: 1.3319e-04\n",
            "Epoch 11/30\n",
            "228/228 [==============================] - 10s 42ms/step - loss: 2.1506e-05 - val_loss: 1.5841e-04\n",
            "Epoch 12/30\n",
            "228/228 [==============================] - 8s 36ms/step - loss: 2.2436e-05 - val_loss: 2.9059e-04\n",
            "Epoch 13/30\n",
            "228/228 [==============================] - 7s 30ms/step - loss: 2.7330e-05 - val_loss: 2.2965e-04\n",
            "Epoch 14/30\n",
            "228/228 [==============================] - 10s 42ms/step - loss: 2.3679e-05 - val_loss: 1.3266e-04\n",
            "Epoch 15/30\n",
            "228/228 [==============================] - 9s 39ms/step - loss: 2.1604e-05 - val_loss: 1.2802e-04\n",
            "Epoch 16/30\n",
            "228/228 [==============================] - 7s 32ms/step - loss: 2.3975e-05 - val_loss: 1.7042e-04\n",
            "Epoch 17/30\n",
            "228/228 [==============================] - 9s 38ms/step - loss: 2.4690e-05 - val_loss: 2.7502e-04\n",
            "Epoch 18/30\n",
            "228/228 [==============================] - 7s 32ms/step - loss: 2.3294e-05 - val_loss: 1.9659e-04\n",
            "Epoch 19/30\n",
            "228/228 [==============================] - 8s 34ms/step - loss: 2.1267e-05 - val_loss: 1.3305e-04\n",
            "Epoch 20/30\n",
            "228/228 [==============================] - 9s 39ms/step - loss: 1.8857e-05 - val_loss: 1.1261e-04\n",
            "Epoch 21/30\n",
            "228/228 [==============================] - 7s 32ms/step - loss: 2.1170e-05 - val_loss: 1.1867e-04\n",
            "Epoch 22/30\n",
            "228/228 [==============================] - 8s 37ms/step - loss: 2.0187e-05 - val_loss: 2.6040e-04\n",
            "Epoch 23/30\n",
            "228/228 [==============================] - 8s 36ms/step - loss: 2.3002e-05 - val_loss: 1.3652e-04\n",
            "Epoch 24/30\n",
            "228/228 [==============================] - 7s 30ms/step - loss: 2.5315e-05 - val_loss: 1.6891e-04\n",
            "Epoch 25/30\n",
            "228/228 [==============================] - 8s 37ms/step - loss: 2.2475e-05 - val_loss: 1.8903e-04\n",
            "Epoch 26/30\n",
            "228/228 [==============================] - 7s 31ms/step - loss: 2.4453e-05 - val_loss: 1.1346e-04\n",
            "Epoch 27/30\n",
            "228/228 [==============================] - 9s 39ms/step - loss: 1.9161e-05 - val_loss: 1.1338e-04\n",
            "Epoch 28/30\n",
            "228/228 [==============================] - 8s 36ms/step - loss: 1.9195e-05 - val_loss: 1.3118e-04\n",
            "Epoch 29/30\n",
            "228/228 [==============================] - 7s 31ms/step - loss: 2.0491e-05 - val_loss: 1.2002e-04\n",
            "Epoch 30/30\n",
            "228/228 [==============================] - 8s 37ms/step - loss: 1.9721e-05 - val_loss: 1.9023e-04\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7ba5dcaefe50>"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y_pred = model.predict(X_test)\n",
        "#y_pred=np.where(y_pred > 0.43, 1,0)\n",
        "for i in range(10):\n",
        "    print(y_pred[i], y_test[i])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bTyOts8WfQZf",
        "outputId": "f4a9f7eb-c3e0-4abe-c66f-f813507e9371"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "30/30 [==============================] - 1s 22ms/step\n",
            "[0.45169312] [0.44885298]\n",
            "[0.45310405] [0.44790869]\n",
            "[0.45532152] [0.43986217]\n",
            "[0.45578387] [0.44857703]\n",
            "[0.4483217] [0.45131016]\n",
            "[0.45405707] [0.45448555]\n",
            "[0.45724156] [0.45770751]\n",
            "[0.46179098] [0.43708911]\n",
            "[0.46542355] [0.44019464]\n",
            "[0.44689173] [0.44241245]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(sc_response.inverse_transform(y_test)[0])\n",
        "print(sc_response.inverse_transform(y_pred)[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-9vjMWSkfSXC",
        "outputId": "ad31854f-40f9-417c-ddd6-e7837af55d50"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[71.96099854]\n",
            "[72.388084]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(16,8))\n",
        "plt.plot(y_test, color = 'black', label = 'Test')\n",
        "plt.plot(y_pred, color = 'green', label = 'pred')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MyZmzVLIfUjO",
        "outputId": "dc69899f-6567-46d9-d294-505c2f07bae5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "iJGP7DI2fYxm"
      },
      "execution_count": null,
      "outputs": []
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "base",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.13"
    },
    "colab": {
      "provenance": []
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}