LSTM_BNIjk.ipynb

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      "metadata": {
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        "#Authors"
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      "source": [
        "# Zaky Syihab Hatmoko\n",
        "# 18/425535/PA/18427\n",
        "# Co-author: Ivan L. Ihwani\n",
        "# Last Update: 9/30/2024\n",
        "\n",
        "# Data Saham Bank BNI dari 1 Mei 2016 s.d. 13 Mei 2024"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
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        "id": "tnEsVV9ffU3L"
      },
      "source": [
        "#Importing Library"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1wOLd5qifMrX"
      },
      "source": [
        "import math\n",
        "import pandas_datareader as web\n",
        "import numpy as np\n",
        "import yfinance as yf\n",
        "import pandas as pd\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense, LSTM\n",
        "import matplotlib.pyplot as plt\n",
        "plt.style.use('fivethirtyeight')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mxT70E-Af0Ck"
      },
      "source": [
        "#Importing Dataset"
      ]
    },
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          "height": 472
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        "outputId": "367e016a-d01a-4dce-cfa9-be8b48d2cc09"
      },
      "source": [
        "df = yf.download('BBNI.JK', start='2016-05-01', end=None)\n",
        "df"
      ],
      "execution_count": 5,
      "outputs": [
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          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
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              "              Open    High     Low   Close    Adj Close     Volume\n",
              "Date                                                              \n",
              "2016-05-02  2290.0  2290.0  2235.0  2245.0  1787.617798   66135200\n",
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              "2016-05-10  2250.0  2285.0  2225.0  2280.0  1815.487305   66174200\n",
              "...            ...     ...     ...     ...          ...        ...\n",
              "2024-09-24  5800.0  5825.0  5750.0  5800.0  5800.000000   39900400\n",
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              "2024-09-27  5600.0  5600.0  5400.0  5450.0  5450.000000   79718100\n",
              "2024-09-30  5400.0  5450.0  5350.0  5350.0  5350.000000   22405700\n",
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 2086,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2016-05-02 00:00:00\",\n        \"max\": \"2024-09-30 00:00:00\",\n        \"num_unique_values\": 2086,\n        \"samples\": [\n          \"2019-09-18 00:00:00\",\n          \"2019-07-16 00:00:00\",\n          \"2017-11-10 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 936.4395199614736,\n        \"min\": 1580.0,\n        \"max\": 6225.0,\n        \"num_unique_values\": 360,\n        \"samples\": [\n          1765.0,\n          2650.0,\n          4987.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"High\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 941.28370237851,\n        \"min\": 1705.0,\n        \"max\": 6250.0,\n        \"num_unique_values\": 363,\n        \"samples\": [\n          4700.0,\n          2725.0,\n          2400.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 931.0320853747864,\n        \"min\": 1485.0,\n        \"max\": 6100.0,\n        \"num_unique_values\": 375,\n        \"samples\": [\n          4750.0,\n          2675.0,\n          2325.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 936.5548353950992,\n        \"min\": 1580.0,\n        \"max\": 6225.0,\n        \"num_unique_values\": 373,\n        \"samples\": [\n          5550.0,\n          2650.0,\n          2275.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Adj Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 968.718628073802,\n        \"min\": 1408.58154296875,\n        \"max\": 5950.0,\n        \"num_unique_values\": 848,\n        \"samples\": [\n          3636.852294921875,\n          3039.486572265625,\n          2875.620849609375\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 45559863,\n        \"min\": 0,\n        \"max\": 444085400,\n        \"num_unique_values\": 2026,\n        \"samples\": [\n          48409200,\n          311447600,\n          77318600\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ymehY9aQgjdu",
        "outputId": "e7cf7209-9060-46e2-d71f-7bfacc13a030"
      },
      "source": [
        "df.shape"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2086, 6)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vCnGC7Cdg1Ju"
      },
      "source": [
        "#Data Visualization"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "R6_ovFbYg_HY"
      },
      "source": [
        "##Close Price History"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 274
        },
        "id": "Ts42HRz-glRr",
        "outputId": "f774c6c0-f743-437d-9cfd-bba625e9542a"
      },
      "source": [
        "plt.figure(figsize=(30,8))\n",
        "plt.title('Close Price History')\n",
        "plt.plot(df['Close'])\n",
        "plt.xlabel('Data', fontsize=18)\n",
        "plt.ylabel('Close Price in IDR', fontsize=18)\n",
        "plt.show()"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 3000x800 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bowvf5Mght1l"
      },
      "source": [
        "#Data Preprocessing"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KJwZMJL6ipCN"
      },
      "source": [
        "##Only use the 'Close' column"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AJpuKcnnhsbi",
        "outputId": "39e11909-f019-4987-c906-60ab28566e89"
      },
      "source": [
        "# Create a new dataframe with only the 'Close' column\n",
        "data = df.filter(['Close'])\n",
        "\n",
        "# Convert the dataframe to numpy array\n",
        "dataset = data.values\n",
        "\n",
        "# Get the number of rows to train the model (train = 80%, test = 20%)\n",
        "training_data_len = math.ceil(len(dataset)*.8)\n",
        "\n",
        "training_data_len"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1669"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iD3sYxsCivte"
      },
      "source": [
        "##Scale the data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "36bDHubEiypk",
        "outputId": "a1c75bc7-ed9f-49e0-d925-2e1040d443f3"
      },
      "source": [
        "scaler = MinMaxScaler(feature_range=(0,1))\n",
        "scaled_data = scaler.fit_transform(dataset)\n",
        "\n",
        "scaled_data"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0.14316469],\n",
              "       [0.15823466],\n",
              "       [0.15715823],\n",
              "       ...,\n",
              "       [0.86544672],\n",
              "       [0.83315393],\n",
              "       [0.8116254 ]])"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CoOZB1yvjHdN"
      },
      "source": [
        "##Create Training Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ETVArwdYjLvT",
        "outputId": "f3ce8c3f-658b-4a60-8217-52eaa3b00d0c"
      },
      "source": [
        "train_data = scaled_data[0:training_data_len, :]\n",
        "\n",
        "# Spit the data into x_train and y_train\n",
        "x_train = []\n",
        "y_train = []\n",
        "\n",
        "for i in range(60, len(train_data)):\n",
        "  x_train.append(train_data[i-60 : i, 0])\n",
        "  y_train.append(train_data[i, 0])\n",
        "\n",
        "  if i <= 61:\n",
        "    print(x_train)\n",
        "    print(y_train)\n",
        "    print()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[array([0.14316469, 0.15823466, 0.15715823, 0.14316469, 0.15069968,\n",
            "       0.16361679, 0.15392896, 0.14208827, 0.13455328, 0.12378902,\n",
            "       0.13347686, 0.12917115, 0.131324  , 0.13670614, 0.13778256,\n",
            "       0.14531755, 0.14962325, 0.15823466, 0.1679225 , 0.17653391,\n",
            "       0.17330463, 0.16469322, 0.16576964, 0.17330463, 0.17868676,\n",
            "       0.17868676, 0.17330463, 0.1722282 , 0.16469322, 0.16146394,\n",
            "       0.16899892, 0.16254037, 0.16146394, 0.1679225 , 0.18191604,\n",
            "       0.18945102, 0.18622174, 0.18622174, 0.18083961, 0.1926803 ,\n",
            "       0.21959096, 0.21959096, 0.21420883, 0.23035522, 0.24381055,\n",
            "       0.24111948, 0.23035522, 0.24650161, 0.24919268, 0.26264801,\n",
            "       0.26803014, 0.25995694, 0.23035522, 0.21689989, 0.22228202,\n",
            "       0.23842842, 0.24111948, 0.23573735, 0.25457481, 0.24919268])]\n",
            "[0.24381054897739507]\n",
            "\n",
            "[array([0.14316469, 0.15823466, 0.15715823, 0.14316469, 0.15069968,\n",
            "       0.16361679, 0.15392896, 0.14208827, 0.13455328, 0.12378902,\n",
            "       0.13347686, 0.12917115, 0.131324  , 0.13670614, 0.13778256,\n",
            "       0.14531755, 0.14962325, 0.15823466, 0.1679225 , 0.17653391,\n",
            "       0.17330463, 0.16469322, 0.16576964, 0.17330463, 0.17868676,\n",
            "       0.17868676, 0.17330463, 0.1722282 , 0.16469322, 0.16146394,\n",
            "       0.16899892, 0.16254037, 0.16146394, 0.1679225 , 0.18191604,\n",
            "       0.18945102, 0.18622174, 0.18622174, 0.18083961, 0.1926803 ,\n",
            "       0.21959096, 0.21959096, 0.21420883, 0.23035522, 0.24381055,\n",
            "       0.24111948, 0.23035522, 0.24650161, 0.24919268, 0.26264801,\n",
            "       0.26803014, 0.25995694, 0.23035522, 0.21689989, 0.22228202,\n",
            "       0.23842842, 0.24111948, 0.23573735, 0.25457481, 0.24919268]), array([0.15823466, 0.15715823, 0.14316469, 0.15069968, 0.16361679,\n",
            "       0.15392896, 0.14208827, 0.13455328, 0.12378902, 0.13347686,\n",
            "       0.12917115, 0.131324  , 0.13670614, 0.13778256, 0.14531755,\n",
            "       0.14962325, 0.15823466, 0.1679225 , 0.17653391, 0.17330463,\n",
            "       0.16469322, 0.16576964, 0.17330463, 0.17868676, 0.17868676,\n",
            "       0.17330463, 0.1722282 , 0.16469322, 0.16146394, 0.16899892,\n",
            "       0.16254037, 0.16146394, 0.1679225 , 0.18191604, 0.18945102,\n",
            "       0.18622174, 0.18622174, 0.18083961, 0.1926803 , 0.21959096,\n",
            "       0.21959096, 0.21420883, 0.23035522, 0.24381055, 0.24111948,\n",
            "       0.23035522, 0.24650161, 0.24919268, 0.26264801, 0.26803014,\n",
            "       0.25995694, 0.23035522, 0.21689989, 0.22228202, 0.23842842,\n",
            "       0.24111948, 0.23573735, 0.25457481, 0.24919268, 0.24381055])]\n",
            "[0.24381054897739507, 0.24650161463939724]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nL9faFVvkSmA",
        "outputId": "4daecdec-3385-4129-c816-02a19158745e"
      },
      "source": [
        "# Convert x_train and y_train into numpy arrays\n",
        "x_train, y_train = np.array(x_train), np.array(y_train)\n",
        "\n",
        "#Reshape the data\n",
        "x_train = np.reshape(x_train, (x_train.shape[0], x_train.shape[1], 1))\n",
        "x_train.shape"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1609, 60, 1)"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-7C8A2awkvVl"
      },
      "source": [
        "#Build The LSTM Model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NvAIvQrxl4Wv"
      },
      "source": [
        "##Training Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FIONEvW6kyIT",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "18a6a853-e0a2-45a6-a046-fe34f9d50dcc"
      },
      "source": [
        "model = Sequential()\n",
        "model.add(LSTM(50, return_sequences=True, input_shape=(x_train.shape[1], 1)))\n",
        "model.add(LSTM(50, return_sequences=False))\n",
        "model.add(Dense(25))\n",
        "model.add(Dense(1))"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/keras/src/layers/rnn/rnn.py:204: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n",
            "  super().__init__(**kwargs)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zy_5VUhLlcBN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0e1a911a-8b13-4c31-c043-68a058c5b8b6"
      },
      "source": [
        "# Compile the model\n",
        "model.compile(optimizer='adam', loss='mean_squared_error')\n",
        "\n",
        "# Train the model\n",
        "model.fit(x_train, y_train, batch_size=5, epochs=30, verbose=2)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/30\n",
            "322/322 - 18s - 55ms/step - loss: 0.0041\n",
            "Epoch 2/30\n",
            "322/322 - 14s - 44ms/step - loss: 0.0012\n",
            "Epoch 3/30\n",
            "322/322 - 15s - 46ms/step - loss: 9.4798e-04\n",
            "Epoch 4/30\n",
            "322/322 - 14s - 44ms/step - loss: 6.5594e-04\n",
            "Epoch 5/30\n",
            "322/322 - 14s - 44ms/step - loss: 5.3122e-04\n",
            "Epoch 6/30\n",
            "322/322 - 14s - 45ms/step - loss: 4.7725e-04\n",
            "Epoch 7/30\n",
            "322/322 - 21s - 64ms/step - loss: 4.3382e-04\n",
            "Epoch 8/30\n",
            "322/322 - 20s - 62ms/step - loss: 3.8919e-04\n",
            "Epoch 9/30\n",
            "322/322 - 22s - 68ms/step - loss: 3.8984e-04\n",
            "Epoch 10/30\n",
            "322/322 - 19s - 60ms/step - loss: 3.5894e-04\n",
            "Epoch 11/30\n",
            "322/322 - 14s - 45ms/step - loss: 3.1976e-04\n",
            "Epoch 12/30\n",
            "322/322 - 21s - 65ms/step - loss: 3.0632e-04\n",
            "Epoch 13/30\n",
            "322/322 - 20s - 61ms/step - loss: 3.2901e-04\n",
            "Epoch 14/30\n",
            "322/322 - 21s - 64ms/step - loss: 3.3587e-04\n",
            "Epoch 15/30\n",
            "322/322 - 20s - 63ms/step - loss: 3.5632e-04\n",
            "Epoch 16/30\n",
            "322/322 - 14s - 45ms/step - loss: 3.0960e-04\n",
            "Epoch 17/30\n",
            "322/322 - 14s - 44ms/step - loss: 3.2246e-04\n",
            "Epoch 18/30\n",
            "322/322 - 14s - 43ms/step - loss: 2.9329e-04\n",
            "Epoch 19/30\n",
            "322/322 - 14s - 43ms/step - loss: 3.2400e-04\n",
            "Epoch 20/30\n",
            "322/322 - 23s - 72ms/step - loss: 3.3441e-04\n",
            "Epoch 21/30\n",
            "322/322 - 18s - 56ms/step - loss: 3.0449e-04\n",
            "Epoch 22/30\n",
            "322/322 - 21s - 64ms/step - loss: 3.3534e-04\n",
            "Epoch 23/30\n",
            "322/322 - 20s - 63ms/step - loss: 2.9174e-04\n",
            "Epoch 24/30\n",
            "322/322 - 20s - 63ms/step - loss: 2.9206e-04\n",
            "Epoch 25/30\n",
            "322/322 - 14s - 44ms/step - loss: 3.0671e-04\n",
            "Epoch 26/30\n",
            "322/322 - 20s - 63ms/step - loss: 2.8244e-04\n",
            "Epoch 27/30\n",
            "322/322 - 14s - 44ms/step - loss: 3.1023e-04\n",
            "Epoch 28/30\n",
            "322/322 - 20s - 64ms/step - loss: 2.8628e-04\n",
            "Epoch 29/30\n",
            "322/322 - 14s - 44ms/step - loss: 2.9769e-04\n",
            "Epoch 30/30\n",
            "322/322 - 14s - 44ms/step - loss: 2.9919e-04\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.history.History at 0x7e545c0bcd30>"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VpfU7Dcdl6o2"
      },
      "source": [
        "##Testing Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "c3BTf3NWl9sW"
      },
      "source": [
        "# Create Testing Data\n",
        "test_data = scaled_data[training_data_len - 60: len(dataset)]\n",
        "\n",
        "# Create x_test and y_test\n",
        "x_test = []\n",
        "y_test = dataset[training_data_len:, :]\n",
        "\n",
        "for i in range(60, len(test_data)):\n",
        "  x_test.append(test_data[i-60: i, 0])"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rA4gklltm1sc"
      },
      "source": [
        "# Convert the data into numpy array\n",
        "x_test = np.array(x_test)\n",
        "\n",
        "# Reshape the data\n",
        "x_test = np.reshape(x_test, (x_test.shape[0], x_test.shape[1], 1))"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "36X5UD9Sm9ex",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0e770fb7-73a0-4bbd-8484-64882c521f00"
      },
      "source": [
        "# Get the models predicted price values\n",
        "predictions = model.predict(x_test)\n",
        "predictions = scaler.inverse_transform(predictions)"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m14/14\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 47ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6tFqvrvVnVin",
        "outputId": "c1b3379f-c1d1-4d9c-a45a-5ae72c3c7454"
      },
      "source": [
        "# Get the RMSE\n",
        "rmse = np.sqrt(np.mean(predictions - y_test)**2)\n",
        "rmse"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "75.36624723658574"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3lohF1UCqoY7"
      },
      "source": [
        "#Visualization"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        },
        "id": "54DYtRIGqqzu",
        "outputId": "da792355-8f81-47e1-b971-a5d5b884169d"
      },
      "source": [
        "# Plot\n",
        "train = data[: training_data_len]\n",
        "valid = data[training_data_len:]\n",
        "valid['Predictions'] = predictions\n",
        "\n",
        "# Visualize the data\n",
        "plt.figure(figsize=(30,8))\n",
        "plt.title('Model')\n",
        "plt.xlabel('Data', fontsize=18)\n",
        "plt.ylabel('IDR', fontsize=18)\n",
        "plt.plot(train['Close'])\n",
        "plt.plot(valid[['Close', 'Predictions']])\n",
        "plt.legend(['Train', 'Val', 'Predictions'], loc='lower right')\n",
        "plt.show()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-19-70216de76af1>:4: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  valid['Predictions'] = predictions\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 3000x800 with 1 Axes>"
            ],
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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "G5Zlx2wb2zGh"
      },
      "source": [
        "#Prediction Result and Actual Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "4SGscMvg2upC",
        "outputId": "8f375379-1a29-4fb0-a304-5652608dab22"
      },
      "source": [
        "valid"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "             Close  Predictions\n",
              "Date                           \n",
              "2022-12-28  4612.5  4603.687012\n",
              "2022-12-29  4612.5  4566.280762\n",
              "2022-12-30  4612.5  4569.503418\n",
              "2023-01-02  4612.5  4569.411621\n",
              "2023-01-03  4637.5  4569.894043\n",
              "...            ...          ...\n",
              "2024-09-24  5800.0  5649.351074\n",
              "2024-09-25  5600.0  5637.052246\n",
              "2024-09-26  5600.0  5440.724609\n",
              "2024-09-27  5450.0  5472.727539\n",
              "2024-09-30  5350.0  5313.659180\n",
              "\n",
              "[417 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-7abc3481-1ca8-4245-9e2f-76764faf9cbc\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "    }\n",
              "\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>Close</th>\n",
              "      <th>Predictions</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2022-12-28</th>\n",
              "      <td>4612.5</td>\n",
              "      <td>4603.687012</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-12-29</th>\n",
              "      <td>4612.5</td>\n",
              "      <td>4566.280762</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-12-30</th>\n",
              "      <td>4612.5</td>\n",
              "      <td>4569.503418</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-01-02</th>\n",
              "      <td>4612.5</td>\n",
              "      <td>4569.411621</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2023-01-03</th>\n",
              "      <td>4637.5</td>\n",
              "      <td>4569.894043</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-09-24</th>\n",
              "      <td>5800.0</td>\n",
              "      <td>5649.351074</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-09-25</th>\n",
              "      <td>5600.0</td>\n",
              "      <td>5637.052246</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-09-26</th>\n",
              "      <td>5600.0</td>\n",
              "      <td>5440.724609</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-09-27</th>\n",
              "      <td>5450.0</td>\n",
              "      <td>5472.727539</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2024-09-30</th>\n",
              "      <td>5350.0</td>\n",
              "      <td>5313.659180</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>417 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-7abc3481-1ca8-4245-9e2f-76764faf9cbc')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-7abc3481-1ca8-4245-9e2f-76764faf9cbc 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-7abc3481-1ca8-4245-9e2f-76764faf9cbc');\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",
              "\n",
              "\n",
              "<div id=\"df-3fafff11-a177-416f-8301-d0aa0bcbe265\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3fafff11-a177-416f-8301-d0aa0bcbe265')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    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",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-3fafff11-a177-416f-8301-d0aa0bcbe265 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "  <div id=\"id_c1279b9b-1495-4761-951f-96bede319162\">\n",
              "    <style>\n",
              "      .colab-df-generate {\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-generate: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-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate: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",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('valid')\"\n",
              "            title=\"Generate code using this dataframe.\"\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=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_c1279b9b-1495-4761-951f-96bede319162 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('valid');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "valid",
              "summary": "{\n  \"name\": \"valid\",\n  \"rows\": 417,\n  \"fields\": [\n    {\n      \"column\": \"Date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2022-12-28 00:00:00\",\n        \"max\": \"2024-09-30 00:00:00\",\n        \"num_unique_values\": 417,\n        \"samples\": [\n          \"2023-08-23 00:00:00\",\n          \"2024-09-02 00:00:00\",\n          \"2024-09-23 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 470.18647756327596,\n        \"min\": 4250.0,\n        \"max\": 6225.0,\n        \"num_unique_values\": 123,\n        \"samples\": [\n          4650.0,\n          5150.0,\n          5187.5\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Predictions\",\n      \"properties\": {\n        \"dtype\": \"float32\",\n        \"num_unique_values\": 417,\n        \"samples\": [\n          4508.72216796875,\n          5254.939453125,\n          5583.033203125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "KaK-pWUcY6aO"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}